Cartridge and analyzer for detection and quantification of ammonia and ammonium in fluids

Abstract

To provide systems and methods that enable continuous automatic monitoring of changes in the concentration and / or amount of ammonia (NH3) in a body fluid in consideration of the presence of ammonium (NH4+) in the body fluid.SOLUTION: A system with an analyzer in fluid communication with a sample of a body fluid is configured to chemically or electrochemically convert at least a portion of ammonium (NH4+) contained in the body fluid into ammonia (NH3) and discharge the converted ammonia (NH3) into a gas sensing chamber. An ammonia (NH3) sensor located within the gas sensing chamber in conjunction with a processor can quantify the amount of ammonia (NH3) present in the gas sensing chamber in relation to the total ammonia of the body fluid.SELECTED DRAWING: None

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit of U.S. Provisional Application No. 62 / 617,053, filed January 12, 2018. The disclosure of the prior application is considered part of the disclosure of this application (and is incorporated herein by reference).

[0002] FIELD OF THE INVENTION The present invention relates to "total ammonia" (herein ammonia (NH3) and ammonium (NH4 + The present invention relates to systems and methods for the detection and quantification of . [Background technology]

[0003] Hospital-acquired acute kidney injury (AKI) is a serious medical problem that can affect up to 30% of children and 20% of adults presenting to the hospital. AKI is associated with increased mortality and can lead to chronic kidney disease (CKD), which is strongly correlated with future hospitalizations, cardiovascular events, and reduced life expectancy.

[0004] In most cases, hospital-acquired AKI is very difficult to diagnose quickly (i.e., within minutes or hours) because the symptoms and signs of AKI are generally not apparent when AKI begins to develop. Therefore, medical treatment for AKI has been slow to develop due to delayed recognition of AKI. Furthermore, the diagnostic features of AKI (i.e., elevated serum creatinine levels and decreased urine excretion rate) are actually very poor markers of early kidney tissue distress or early AKI because they do not necessarily change rapidly and may occur well after the initial period of early AKI (hours or days). Furthermore, changes in serum creatinine or urine output are not specific for AKI. In fact, many commonly encountered clinical scenarios (e.g., decreased oral water intake, gastrointestinal water loss, transepidermal water loss) in which blood perfusion to the renal tissue ("effective circulating blood volume") is sufficiently reduced can result in elevated serum creatinine levels and decreased urine output (without actual renal tissue damage). Adaptive responses to a decrease in effective circulating blood volume include increased renal water recovery within the renal collecting duct in response to a decrease in renal glomerular filtration rate (resulting in decreased creatinine clearance and increased serum creatinine) and increased circulating levels of antidiuretic hormone (resulting in the production of more concentrated urine and decreased urine volume). Serum creatinine levels can also be significantly affected by the administration of certain medications without actual renal tissue damage. These medications include cimetidine, trimethoprim, pyrimethamine, salicylates, phenacemide, corticosteroids, and some vitamin D derivatives. The use of angiotensin-converting enzyme inhibitors, angiotensin II receptor blockers, and diuretics also affect creatinine clearance (and therefore serum creatinine levels) without causing AKI. Therefore, improving the diagnostic process for early recognition of AKI in hospitalized patients represents an unmet clinical need.

[0005] There is strong interest in discovering and validating novel methods for detecting AKI. Conventional methods for detecting AKI may include serial testing of lagging blood markers (i.e., creatinine) and monitoring urine flow rate (i.e., hourly urine output). Subjecting patients to serial blood draws to monitor changes in serum creatinine is inherently problematic because each sample taken necessarily involves the removal of that body tissue. In addition to the delay and lack of specificity for AKI, significantly altered serum creatinine values ​​as a result of AKI indicate tissue damage and global organ dysfunction rather than early renal tissue cellular failure. Novel urinary biomarkers of AKI (including neutrophil gelatinase-binding lipocalin (NGAL), kidney injury molecule-1 (KIM-1), insulin-like growth factor-binding protein 7 (IGFBP7), and tissue inhibitor of metalloproteinase 2 (TIMP2)) correlate with AKI (as defined by traditional hallmark markers) and can change more rapidly than serum creatinine, but share the same limitations as creatinine in that they change relatively delayed (i.e., within hours rather than minutes after kidney injury occurs). Furthermore, novel urinary AKI biomarkers perform less well in predicting and / or diagnosing AKI in patients with certain health conditions, including chronic kidney disease (CKD) and sepsis. Furthermore, given the often clinically important nature of determining whether a particular episode of AKI can best be treated by prompt administration of treatment to increase effective circulating blood volume, the inherent inability of each and every standard and novel AKI laboratory test to aid in that determination also limits their overall usefulness in healthcare settings. Therefore, there is a need for an AKI detection system and method that can rapidly detect at-risk kidney tissue, kidney tissue failure, and / or early AKI before significant AKI occurs.

[0006] For this purpose, urinary "total ammonia" (ammonia (NH3) and ammonium (NH4 +) can be used as a novel urinary biomarker for the rapid detection of renal tissue at risk, renal tissue failure, early AKI, and / or AKI. In the fluid, ammonia (NH3) and ammonium (NH4 + ) exist in equilibrium, and the amount of each species depends on environmental conditions (e.g., pH, temperature, and pressure). Renal production of total ammonia (renal ammonia production) primarily depends on glutamine metabolism within renal proximal tubule cells, in addition to other intrarenal conditions. Renal ammonia production normally changes or adapts in response to various systemic conditions, such as systemic acid / base status, potassium status, and fluctuations in dietary protein intake. Changes in systemic total ammonia levels, such as those due to changes in liver function, also lead to changes in urinary total ammonia levels. Reduced effective circulating blood volume and / or AKI rapidly affect renal ammonia production, reducing urinary total ammonia and total ammonia excreted from renal tissue. Therefore, continuous, automatic, and predictive monitoring of dynamic changes in urinary total ammonia concentration and / or content can be used to rapidly detect potential changes in renal blood flow (effective circulating blood volume) at risk for renal tissue, renal cellular failure, early AKI, and / or AKI. Furthermore, continuous automated monitoring of dynamic changes in urinary total ammonia (increasing or decreasing levels) can be used to detect potential changes in any systemic condition that affects renal ammonia production and / or urinary total ammonia, including systemic acid / base status, potassium status, dietary protein intake, and liver function status.

[0007] Therefore, the total ammonia (ammonia (NH3) and ammonium (NH4) in the fluid, including that excreted from the body (i.e., urine), + There is a need for a system and method that allows for continuous, automated monitoring of changes in the amount of ).

[0008] Ammonia (NH3) and ammonium (NH4 +Conventional systems and methods for the measurement of ammonia or ammonium are often inaccurate, difficult to use, cumbersome, and not suitable for bedside urinalysis or continuous monitoring. Conventional systems for the measurement of ammonia or ammonium include (1) colorimetric sensors, (2) spectroscopic-based sensors, (3) nanomaterial-based sensors, (4) non-contact conductive sensors, and (5) reagent sticks.

[0009] The colorimetric sensor detects ammonia (NH3) and / or ammonium (NH4 + ) is used to measure pH. This type of sensor consists of a thin film embedded with an ammonia (NH3)-sensitive pH dye attached to the end of a detection unit (e.g., optical fiber). Although these devices have high sensitivity, further instrumentation is required for use with biological samples.

[0010] For example, the hematology technology in the Roche Cobas Integra® is based on an enzymatic method that requires the use of two reagents and analysis within 30 minutes of blood sample collection. This method, used for hematology, is not directly applicable to urine measurements. When used for urine, the urine (millimolar urinary total ammonia concentration) must be diluted at least 10-1000 times to achieve a concentration within the limits of the hematology technology (micromolar blood total ammonia concentration). Therefore, the hematology technology is not suitable for bedside urine testing.

[0011] In another example, a handheld portable device measures blood ammonium (NH4 + The handheld portable device uses a color-based sensor and a detector to detect the level of ammonium (NH4 + However, handheld devices can be disposable and can be used to convert ammonium (NH4 +) and are not suitable for continuous, automated, or repeated measurements. In addition, the described handheld portable devices may be used with blood, which requires invasive blood sampling, making evaluation more difficult and cumbersome when continuous patient monitoring is desired. Furthermore, because the described handheld portable devices are used with blood, they may not be adaptable for use outside of a medical environment (i.e., in the patient's home). Furthermore, the devices do not provide continuous quantification for at least 24 hours, which is required to monitor clinically important conditions. Furthermore, conventional handheld portable devices have demonstrated poor accuracy and are prone to both false-positive and false-negative test results.

[0012] Ammonium (NH4 + Conventional methods for detecting ammonium (NH) or ammonia (NH) may also include laboratory-based methods involving manual or pump-based handling of liquids and samples, as well as external detection instruments such as scanners or photomultiplier tubes and optical fibers. These conventional systems detect ammonium (NH) in water. + For the analysis of ammonium (NH3) or ammonia (NH3) or pure samples, paper-based extraction membranes or solution mixtures can be used. Laboratory-based methods can extract ammonium (NH4) from complex body fluid samples with highly variable amounts of other dissolved components (i.e., urine). + ) or ammonia (NH3) levels cannot be accurately detected.

[0013] Additionally, ammonium (NH4) is used in water quality monitoring applications using commercial technologies based on amperometric or colorimetric sensors. + Semi-continuous measurement of ammonium (NH3) / ammonia (NH3) is not feasible in a clinical setting. For example, the ANALYTICAL TECHNOLOGY Q45N device weighs 15 pounds and measures ammonium (NH4 +Ammonia (NH3) is converted to stable monochloramine, which is measured with an amperometric sensor. A minimum flow rate of 200 mL / min is required (Note: The minimum or absolute human urine volume is 0.5 mL / kg / hr. For adults, typical urine volumes are 800-2000 mL / day (0.6-1.4 mL / min)). It is reliable over a range of 0-5 ppm NH3 (0-270 micromolar). The Aztec 600 Colorimeter (ABB) is designed for semi-continuous use in wastewater. The Aztec 600 Colorimeter can measure only four samples per hour using indophenol blue chemistry, requiring a continuous flow rate of 200-500 mL / min. The Aztec 600 Colorimeter measures ammonia (NH3) down to 3 ppm. The AWA INSTRUMENTS CX4000 also operates on the colorimetric principle. These large-scale commercially available semi-continuous measurement devices from the water treatment industry are not easily adapted for use in a medical environment, and the sensors they utilize must be periodically calibrated for different concentration ranges. + Batch measurements of ammonium (NH) / ammonia (NH) are commonly performed in water treatment applications via either an ammonium ion probe or a colorimeter coupled to a spectrophotometer.

[0014] Ammonium (NH4 + ) Ion-selective electrodes (either solid-state or membrane-based) detect ammonium (NH4 + It operates on the principle of a membrane with a selective ion exchanger, which compares an unknown solution with a reference solution to produce a different potential across the membrane. Most ammonium (NH4 + ) Colorimetric methods involve adding a reagent to a water sample and evaluating the color of the liquid solution with a special device. +Colorimetric tests involve strips (similar to pH measuring strips) where a reagent is added to a solution, the strip is dipped into the solution, and a color change is observed visually. Commercially available batch measurement products require the use of reagents, enzymes, and / or large analytical equipment. The Roche enzymatic method requires a minimum sample volume of 20 μL and is not designed for urine. Ammonium (NH4 + ) selective electrodes require a minimum sample volume of a few milliliters, and the electrode must be calibrated every 1-2 hours (for continuous measurements). To be accurate, the electrode also needs to detect the ammonium (NH4 + ) must be calibrated with a variety of solutions depending on the expected concentration range.

[0015] Ammonium (NH4 + Most measurement techniques for detecting ammonium (NH3) rely on exhaled breath or blood (plasma). However, conventional techniques are not suitable for continuous monitoring because the ion-selective electrodes require time-consuming calibration between each sample analysis due to limited sensing membrane stability and drift in measurement output. For example, ORION™ high performance ammonium (NH4 + ) The electrodes need to be calibrated before each new measurement to minimize measurement drift due to the limited stability of the sensing membrane.

[0016] Furthermore, given the complexity of biological samples, few methodologies have been approved by the U.S. Food and Drug Administration (FDA) for clinical research. + For detection of HIV-1, enzyme assays are the only technology that meets U.S. Food and Drug Administration standards. Generally, enzyme assays have a limited shelf life, involve multiple incubation steps, require processing times of over an hour, and involve significant operator effort.

[0017] Spectroscopic methods for measuring ammonia gas (NH3) include pulsed quantum cascade laser spectroscopy and optical microring resonators. While large (tabletop) measurement systems exist, they lack the compact size, light weight, and low cost desirable for portable individual monitoring (e.g., at the hospital bedside). For example, ammonia (NH3) can be detected via absorption spectroscopy with instruments such as the NEPHROLUX™, which use a tunable laser and acoustic detector to perform sub-parts-per-billion (ppb) zero-background measurements of ammonia (NH3) in the presence of interfering substances such as carbon dioxide and water vapor (e.g., in exhaled breath). While spectroscopic techniques are highly sensitive, they typically have bulky components, making them inconvenient for personal use. Furthermore, the optical components in absorption spectroscopy are prone to misalignment, making them unsuitable for personal use.

[0018] Gas chromatography-mass spectrometry (GC-MS) and selected ion flow tube mass spectrometry (SIFT-MS) may be accurate for measuring ammonia (NH3), but the equipment is expensive and difficult to maintain. GC-MS can separate ammonia (NH3) and ammonium (NH4 + ) but requires expensive instrumentation (~$300,000) and a pre-concentration step that precludes high reproducibility and real-time implementation. SIFT-MS has been developed for real-time detection of low molecular weight volatiles, including ammonia (NH3), in various biological samples (e.g., skin and urine headspace, breath), but is expensive (~$200,000) and quite difficult to maintain.

[0019] Nanomaterial-based chemiresistors and electrochemical sensors exhibit detection limits consistent with clinically relevant ammonia (NH3) levels (exhaled ammonia (NH3) (ppb)) under well-defined, near-ideal laboratory conditions. However, the use of these sensors to detect ammonia (NH3) in complex samples requires further refinement to achieve the selectivity and lifetime required for continuous monitoring.

[0020] Furthermore, conventional ammonia (NH3) detectors may have contactless conductivity sensors. However, the acidic solution used in conventional contactless conductivity sensors must be replaced after each measurement, making continuous measurements impractical.

[0021] Finally, urine reagent sticks are widely used to determine 10 different urine parameters (including pH, specific gravity, leukocyte esterase, nitrite, urobilinogen, protein, hemoglobin, glucose, ketones, and bilirubin), but commercially available electronic readers for these urine dipsticks only measure ammonia (NH3) or ammonium (NH4 + However, it does not include the measurement of ammonium (NH4 + ) detection reagent sticks are commercially available for use with water samples. + ) The operation of detection reagent sticks is based on irreversible chemical reactions, and therefore they are disposable devices. While these reagent sticks are fast and easy to use, they only provide semi-quantitative assessment of parameters and lack the precision and continuous real-time monitoring capabilities desired in critical applications.

[0022] Furthermore, ammonia (NH3) and ammonium (NH4 + ) are in equilibrium with each other, and each species spontaneously converts to the other depending on changes in local conditions (i.e., pH, temperature, pressure) within the biological sample being tested, so the concentrations of ammonia (NH3) and ammonium (NH4 + ) in biological samples (e.g., body fluids, urine) in the medical field, which also accounts for the presence of both total ammonia (ammonia (NH3) and ammonium (NH4 + There is a need for systems and methods for detecting and quantifying ).

[0023] Therefore, ammonium (NH4 +There is a need for a system and method that enables continuous and automatic monitoring of changes in the concentration and / or amount of ammonia (NH3) in body fluids, taking into account the presence of SUMMARY OF THE INVENTION

[0024] This disclosure describes systems and methods for detecting total ammonia (ammonia (NH3) and ammonium (NH4 + )) in a fluid.

[0025] In some embodiments, the systems and methods described herein can convert ammonium (NH4 + ) to ammonia (NH3). Body samples such as urine can contain varying amounts of ammonia (NH3) and ammonium (NH4 + ) depending on the pH. The systems and methods described herein can extract ammonia (NH3) from body fluids (e.g., urine, sweat, blood, etc.) through an extraction membrane, whereby the total ammonia (NH3) and ammonium (NH4 + ) contained in the biological sample is substantially measured as ammonia (NH3). In some embodiments, this enables continuous samples of a fluid (e.g., when urine is produced) to be measured continuously and almost continuously for total ammonia (ammonia (NH3) and ammonium (NH4 + )) concentration. The extraction membrane can chemically or electrochemically convert substantially all of the ammonium (NH4 + ) in the fluid sample to ammonia (NH3).

[0026] In some embodiments, the system has an analyzer. The analyzer may be in fluid communication with a sample of body fluid. The analyzer has an intelligent controlled sample conditioning and transport system, an extraction membrane (ammonium (NH4 +The sample preparation and delivery system may include a sensing chamber, a sensing chamber, and an ammonia (NH3) sensor. The intelligently controlled sample preparation and delivery system can control the amount of body fluid in contact with the extraction membrane to ensure that sensor performance remains consistent over multiple consecutive uses and over time. The sample preparation and delivery system can be operated by an intelligent programmable valve system based on an intelligent algorithm that includes sample volume, time, and sensor signal change information.

[0027] In some embodiments, the sample preparation and delivery system may have a signal saturation and drift avoidance mechanism with a micro-controlled valve system. The micro-controlled valve system may control the volume of bodily fluid in contact with the analytical device. The micro-controlled valve system may have valves configured to control the delivery of gas from the bodily fluid, headspace gas, and zeroing channel. The sample preparation and delivery system may be formed by at least two inlets: a sampling channel in contact with the bodily fluid, and a purge channel in contact with a zeroing material that allows the system to record a baseline. The baseline may be essential to correct for drift in the sensor signal. An extraction membrane may be disposed between the region in fluid communication with the bodily fluid and the sensing chamber, and may include: 1) an extraction membrane for extracting ammonium (NH4) contained in the bodily fluid; +1) converting at least a portion of the ammonia (NH3) present in the sensing chamber to ammonia (NH3); and 2) expelling the converted ammonia (NH3) into a sensing chamber. The ammonia (NH3) sensor disposed in the sensing chamber may be thermally pre-treated under specific conditions and may have a pre-calibration algorithm to ensure sensor performance over a wide range of temperature, relative humidity, and pressure conditions. The ammonia (NH3) sensor processor may have non-transitory memory that stores instructions that, when executed, cause the processor to quantify the amount of ammonia (NH3) present in the sensing chamber. The analyzer may determine, based on the quantified amount of ammonia (NH3) present in the sensing chamber and how that amount may change over time, changes in organ or tissue function, the occurrence of organ or tissue damage, and the presence of whole-body total ammonia (ammonia (NH3) and ammonium (NH4 + )) changes in physiological functions or total ammonia (ammonia (NH3) and ammonium (NH4 + )) may detect other bodily processes whose levels change. Optionally, the system may also include a user interface device. In some embodiments, the ammonia (NH3) sensor may be further configured to transmit a quantified amount of ammonia (NH3) present in the sensing chamber to the user interface device. In some embodiments, the user interface device may be configured to receive at least the transmission from the analytical device and may include a display having a graphical user interface configured to display the transmission received from the analytical device.

[0028] In some embodiments, the method includes receiving a sample of bodily fluid in an analytical device and extracting ammonium (NH4) contained within the sample of bodily fluid through an extraction membrane located between a region in fluid communication with the sample of bodily fluid and a sensing chamber of the analytical device. +The method converts at least a portion of the ammonia (NH3) present in the sensing chamber to ammonia (NH3), discharges the converted ammonia (NH3) through an extraction membrane into a sensing chamber, and determines the amount of ammonia (NH3) present in the sensing chamber via an ammonia (NH3) sensor located in the sensing chamber. A change in organ or tissue function, organ or tissue damage, a change in physiological function affecting the total ammonia concentration in the body fluid, or other body fluid process in which the total ammonia level in the body fluid changes may be detected if the determined amount of ammonia (NH3) present in the sensing chamber changes or is interpreted as being outside a normal or expected concentration or range for the individual at the time of measurement. Optionally, the method may further include transmitting the amount of ammonia (NH3) present in the sensing chamber to a user interface device, the user interface device further having a display with a graphical user interface. Optionally, the method may also include receiving, at the user interface device, the amount of ammonia (NH3) present in the sensing chamber and displaying the amount of ammonia (NH3) present in the sensing chamber via the graphical user interface.

[0029] In some embodiments, the method for determining renal function includes measuring, in a first analytical device, total ammonia (ammonia (NH) and ammonium (NH + The analyzer then measures the detected total ammonia (ammonia (NH3) and ammonium (NH4) concentrations. + )) levels in the subject sample to the second user interface device. The second user interface device can then transmit the total ammonia (ammonia (NH3) and ammonium (NH4 + )) can be correlated with the diagnosis of altered renal function. This correlation is consistent with the correlation between total ammonia (ammonia (NH3) and ammonium (NH4)) in normal subjects. +)) or the detected levels of total ammonia (ammonia (NH3) and ammonium (NH4 + ) in the subject samples compared to the detection level of total ammonia (ammonia (NH3) and ammonium (NH4 + ))'s detection level can be taken into account.

[0030] In some embodiments, the non-invasive device measures the total ammonia (ammonia (NH3) and ammonium (NH4 + )) concentrations semi-continuously. The non-invasive device can be miniaturized, conveniently deployed, and automatically transmit data to provide near real-time and / or semi-continuous analysis. In some embodiments, the device may be used for automated monitoring and rapid detection of acute kidney injury (AKI) in hospitalized patients with indwelling urinary catheters. Alternatively, the device may measure renal ammonia production and / or urinary total ammonia (ammonia (NH3) and ammonium (NH4)) resulting from: + ) can be used to detect changes in: 1) changes in renal function, 2) acute kidney injury or failure, 3) chronic kidney disease, 4) changes in liver function, 5) acute liver injury or failure, 6) chronic liver disease (e.g., cirrhosis), 7) acute gastrointestinal bleeding, 8) chronic gastrointestinal bleeding, 9) genetic or inherited metabolic disorders involved in or affecting the generation, handling, and / or excretion of ammonia physiology (e.g., urea cycle disorders, organic acidurias, carnitine deficiency due to defective fatty acid oxidation, dibasic amino acidurias, and defects in pyruvate metabolism), 10) changes in normal metabolic processes (e.g., increased ammonia production and excretion after a protein meal), 11) acute or chronic systemic acid / base changes or imbalances due to metabolic processes or disease states, 12) acute or chronic systemic acid / base changes or imbalances due to respiratory processes or disease states, 13) changes in effective circulating blood volume, 14) changes in renal blood flow, or 15) renal plasma flow. [Brief explanation of the drawings]

[0031] [Figure 1-1]FIG. 1 shows a schematic diagram of an analytical device for determining total ammonia in a fluid according to one aspect of the present disclosure. [Figure 1-2] FIG. 1 shows a schematic diagram of an analytical device for determining total ammonia in a fluid according to one aspect of the present disclosure.

[0032] [Figure 2] FIG. 1 shows a schematic diagram of an example of an ammonia sensing chamber according to one aspect of the present disclosure.

[0033] [Figure 3] 1 shows a photograph of a sensor for detecting ammonia (NH3) from a body fluid according to one embodiment of the present disclosure.

[0034] [Figure 4] 1 shows a graph of absorbance change according to one embodiment of the present disclosure.

[0035] [Figure 5] FIG. 1 shows a graph of absorbance change for an ammonia sensor according to one embodiment of the present disclosure (Panel A), an assembly diagram of the ammonia sensor (Panel B), a graph of absorbance change for the sensor before and after exposure to ammonia (Panel C), and a diagram of the sensor assembly (referred to as a hybrid sensor) (Panel D).

[0036] [Figure 6] 1 shows graphs relating to the specificity (Panel A), precision (Panel B), reversibility and time response (Panel C), and sensor lifetime and stability (Panel D) of a sensor for ammonia, according to one embodiment of the present disclosure.

[0037] [Figure 7] 1A and 1B are photographs and a schematic diagram of an ammonia sensor according to one embodiment of the present disclosure.

[0038] [Figure 8] 1 shows a graph of an analysis of urine performed using a sensor for ammonia (called a hybrid sensor) according to one embodiment of the present disclosure and a graph of an analysis of urine performed using a reference method: an ion-selective electrode.

[0039] [Figure 9] 1 shows a graph from an ammonia sensor upon exposure to ammonia. The graph shows the signal of photodiodes operating as sensing and reference photodiodes according to one aspect of the present disclosure.

[0040] [Figure 10] 1A-1D show schematic diagrams and graphs of experimental data related to sensor substrates of the present disclosure.

[0041] [Figure 11] 1 shows a schematic diagram of an integrated analyzer for total ammonia (ammonium (NH4 +) and ammonia (NH3)) according to one embodiment of the present disclosure, not including the light color detector.

[0042] [Figure 12] 1 shows a graph of an ammonia sensor signal according to one aspect of the present disclosure.

[0043] [Figure 13] 1 shows a calibration plot for an ammonia sensor according to one aspect of the present disclosure.

[0044] [Figure 14] 1 shows a graph of experimental data evaluated by a Total Ammonia Analyzer (CODA) according to one embodiment of the present disclosure, demonstrating selectivity and response for sequential sample analysis.

[0045] [Figure 15] 1 shows a graph of experimental data evaluated by a Total Ammonia Analyzer (CODA) according to one embodiment of the present invention, illustrating total ammonia (as ammonia, NH3) production and accuracy of the device.

[0046] [Figure 16] 1 shows a graph of experimental data relating to one embodiment of the present disclosure illustrating the stability of a sensor for ammonia.

[0047] [Figure 17] 1 shows graphs of experimental data related to embodiments of the present disclosure, illustrating actual body fluid analysis (urine) by an analyzer (CODA) and a reference method (ion selective electrode (ISE)).

[0048] [Figure 18-1] 1 illustrates sensor preparation in a diaper and detection of urinary ammonia in the prepared diaper insert according to one aspect of the present disclosure. [Figure 18-2] 1 illustrates sensor preparation in a diaper and detection of urinary ammonia in the prepared diaper insert according to one aspect of the present disclosure.

[0049] [Figure 19] 1 shows exemplary CODA components for continuous monitoring of ammonia in biological samples.

[0050] [Figure 20a] An example of a chemical extraction membrane is presented to demonstrate how different variables such as porosity, boundary conditions, initial NH4 + concentration in the sample, and geometry affect the concentration profile of alkaline substances in the extraction membrane. [Figure 20b] An example of a chemical extraction membrane is presented to demonstrate how different variables such as porosity, boundary conditions, initial NH4 + concentration in the sample, and geometry affect the concentration profile of alkaline substances in the extraction membrane. [Figure 20c] An example of a chemical extraction membrane is presented to demonstrate how different variables such as porosity, boundary conditions, initial NH4 + concentration in the sample, and geometry affect the concentration profile of alkaline substances in the extraction membrane. [Figure 20d] An example of a chemical extraction membrane is presented to demonstrate how different variables such as porosity, boundary conditions, initial NH4 + concentration in the sample, and geometry affect the concentration profile of alkaline substances in the extraction membrane. [Figure 20e]An example of a chemical extraction membrane is presented to demonstrate how different variables such as porosity, boundary conditions, initial NH4 + concentration in the sample, and geometry affect the concentration profile of alkaline substances in the extraction membrane. [Figure 20f] An example of a chemical extraction membrane is presented to demonstrate how different variables such as porosity, boundary conditions, initial NH4 + concentration in the sample, and geometry affect the concentration profile of alkaline substances in the extraction membrane. [Figure 20g] An example of a chemical extraction membrane is presented to demonstrate how different variables such as porosity, boundary conditions, initial NH4 + concentration in the sample, and geometry affect the concentration profile of alkaline substances in the extraction membrane. [Figure 20h] An example of a chemical extraction membrane is presented to demonstrate how different variables such as porosity, boundary conditions, initial NH4 + concentration in the sample, and geometry affect the concentration profile of alkaline substances in the extraction membrane. [Figure 20i] An example of a chemical extraction membrane is presented to demonstrate how different variables such as porosity, boundary conditions, initial NH4 + concentration in the sample, and geometry affect the concentration profile of alkaline substances in the extraction membrane. [Figure 20j] An example of a chemical extraction membrane is presented to demonstrate how different variables such as porosity, boundary conditions, initial NH4 + concentration in the sample, and geometry affect the concentration profile of alkaline substances in the extraction membrane. [Figure 20k] An example of a chemical extraction membrane is presented to demonstrate how different variables such as porosity, boundary conditions, initial NH4 + concentration in the sample, and geometry affect the concentration profile of alkaline substances in the extraction membrane. [Figure 20l] An example of a chemical extraction membrane is presented to demonstrate how different variables such as porosity, boundary conditions, initial NH4 + concentration in the sample, and geometry affect the concentration profile of alkaline substances in the extraction membrane. [Figure 20m] An example of a chemical extraction membrane is presented to demonstrate how different variables such as porosity, boundary conditions, initial NH4 + concentration in the sample, and geometry affect the concentration profile of alkaline substances in the extraction membrane. [Figure 20n] An example of a chemical extraction membrane is presented to demonstrate how different variables such as porosity, boundary conditions, initial NH4 + concentration in the sample, and geometry affect the concentration profile of alkaline substances in the extraction membrane. [Figure 20o] An example of a chemical extraction membrane is presented to demonstrate how different variables such as porosity, boundary conditions, initial NH4 + concentration in the sample, and geometry affect the concentration profile of alkaline substances in the extraction membrane.

[0051] [Figure 21a] 10 is a model result of the cross-sectional concentration profile of alkaline substances in the chemical extraction membrane after the first cycle. [Figure 21b] 10 is a model result of the cross-sectional concentration profile of alkaline substances in a chemical extraction membrane after the 20th cycle.

[0052] [Figure 22a] The analytical performance of the extraction membrane and the entire sensor on complex body fluids is shown. [Figure 22b] The analytical performance of the extraction membrane and the entire sensor on complex body fluids is shown.

[0053] [Figure 23] Shown are the results of ammonia measured by the reference enzymatic method for three samples with interference from amino acids.

[0054] [Figure 24] Demonstration of quantifiable universal sensor sensitivity is presented, enabling a calibration-free approach for the quantification of ammonia.

[0055] [Figure 25] Continuous measurement of NH4 + from 37.6 mM to 3.6 mM is shown. DETAILED DESCRIPTION OF THE INVENTION

[0056] Some embodiments of the systems and methods described herein provide a wireless, solid-state, and portable method for measuring continuous total ammonia (ammonia (NH3) and ammonium (NH4) + In addition to other potential uses, healthcare providers can use the systems, methods, and devices described herein to measure total ammonia (ammonia (NH3) and ammonium (NH4) in biological samples more quickly and more accurately than was possible with conventional systems. + In some embodiments, the systems, methods, and devices described herein can reliably measure total ammonia (ammonia (NH3) and ammonium (NH4)) in a biological sample within 5 seconds. + The system can determine the exact concentration of ammonia (NH3) and wirelessly transmit the data to another device. In some embodiments, wireless transmission may be performed using Bluetooth®. In some embodiments, the systems, methods, and devices described herein may include an ammonia (NH3) sensor composed of an extraction membrane and a hydrophobic material, such as a polytetrafluoroethylene (PTFE) substrate impregnated with a pH indicator, such as bromophenol blue; a light-emitting diode (LED) at the maximum absorption wavelength of the indicator; and a photodiode configured to measure the absorbance change after exposure to ammonia (NH3). Additionally, an LED at a different wavelength where the indicator does not absorb light may be configured with a corresponding photodiode to generate a second reading, allowing for further correction of sensor signal drift. The photodiode converts the sensor's color change into an electronic signal that can be transmitted (wired or wirelessly) to a smart device for readout. The described systems, methods, and devices may exhibit high sensitivity, high specificity, fast reversibility, and fast response time compared to conventional systems.

[0057] As mentioned above, urinary total ammonia (ammonia (NH3) and ammonium (NH4 +) can be used as a biomarker for the early detection of acute kidney injury (AKI) and other physiological conditions and diseases. The systems and methods described herein can measure total ammonia (ammonia (NH3) and ammonium (NH4) in urine or other body fluids. + )) and / or urine headspace or the headspace of other bodily fluids, which may include one or more of whole blood, plasma, serum, intracellular fluid, interstitial fluid, lymphatic fluid (lymph), sweat, urine, pleural fluid, pericardial fluid, peritoneal fluid, biliary fluid (bile), feces, cerebrospinal fluid, synovial fluid, saliva, sputum, nasal fluid, or ocular fluid.

[0058] As discussed further below, the systems and methods described herein can include an analytical device, optionally referred to herein as a colorimetric photoelectrodynamic analyzer (or simply "CODA"), that measures urinary total ammonia (ammonia (NH3) and ammonium (NH4) in real time and continuously using very small volumes of urine or bodily fluid. + The analytical device can provide for the detection and quantification of dissolved ammonium (NH4) in blood or urine. The analytical device can use a sensor embedded with a pH dye-based ammonia (NH3)-sensitive sensing probe. + Unlike conventional detection methods for human body fluids that directly measure ammonium hydroxide (NH4), the sensing chamber of the analyzer detects ammonium hydroxide (NH4) by exposing the body fluid (or body fluid sample) to alkali before measurement. + Ammonia (NH3) gas can be detected and measured in the urine headspace by converting NH3 to gaseous ammonia (NH3).

[0059] Referring now to FIG. 1, total ammonia (ammonia (NH3) and ammonium (NH4 +1, a schematic diagram of a system for detecting ammonium nitrate (Am) is shown. As shown in FIG. 1, the wearable analyzer can have an analytical device 100 in wireless communication with a user interface device 102. In some embodiments, the analytical device 100 can have an extraction membrane 104, an ammonia (NH) sensor 106, a photodiode 108, a light-emitting diode 110, a microcontroller 112, a Bluetooth® transmitter / receiver 114, a flexible printed circuit board 116, and / or a flexible battery 118. The extraction membrane 104 can be configured to be in fluid communication with a bodily fluid sample, such as urine, or the headspace of a bodily fluid sample 120.

[0060] In some embodiments, the extraction membrane 104 may be disposed between the region in fluid communication with the bodily fluid and the sensing chamber (containing the ammonia (NH3) sensor 106). The extraction membrane 104 extracts ammonium (NH4 + ) in the body fluid sample to ammonia (NH3) and discharge the converted ammonia (NH3) into the sensing chamber. As described further below, in some embodiments, the extraction membrane can have a partitioning layer, an alkaline layer, a hydrophobic layer, and an indicator layer. The partitioning layer can be configured to distribute the body fluid sample along the extraction membrane. The alkaline layer can be configured to convert at least a portion of the ammonium (NH4) in the body fluid sample to ammonia (NH3) and discharge the converted ammonia (NH3) into the sensing chamber. + The alkaline layer can be configured to convert at least a portion of the converted ammonia (NH) to ammonia (NH). In some embodiments, the alkaline layer can comprise an organic hydroxide and / or sodium hydroxide. The hydrophobic layer can be configured to filter the converted ammonia (NH) from the body fluid sample and discharge the converted ammonia (NH) to the sensing chamber. In some implementations, the hydrophobic layer can comprise polytetrafluoroethylene, or the like. The indicator layer can comprise bromophenol blue, a plant-derived pH indicator (e.g., anthocyanin), or any other suitable material. The indicator layer converts ammonia (NH) gas from the body fluid and / or the fluid ammonium (NH) upon exposure to and interaction with the alkaline layer. +The device may be configured to change color in response to the amount and / or concentration of ammonia (NH3) gas extracted from the device.

[0061] In some embodiments, the ammonia (NH) sensor 106 may include a colorimetric nanocomposite sensor that evaluates the absorption color change using a composite sensing nanomaterial for the detection of ammonia (NH) on the sensing region 106A and the reference region 106B (without the sensing probe). In some embodiments, the absorbance is calculated as the negative logarithm of the signal from the sensing region divided by the signal from the reference region. The light-emitting diode 110 and the photodiode can be combined to form a detection unit (or hybrid sensor), as described further below. The ammonia (NH) sensor 106 may also include a processor having a non-transitory memory device that stores instructions that, when executed, cause the processor to quantify the amount of ammonia (NH) present in the sensing chamber.

[0062] As described in more detail below, the ammonia (NH3) sensor may have four photodiodes: two sensing photodiodes located in the sensing region 106A and two reference photodiodes located in the reference region 106B. The two light emitting diodes may be configured to illuminate the indicator layer. In some embodiments, the light emitting diodes may emit red light. In some embodiments, the light source and photodetector may be configured to use a CMOS chip (camera).

[0063] The ammonia (NH3) sensor 106 can quantify the amount of ammonia (NH3) present in the sensing chamber by calculating an absorbance metric of the indicator layer based on the signal from the first photodiode and the signal from the second photodiode, and converting the absorbance metric to a quantifiable amount of ammonia (NH3) by comparing the calculated absorbance metric to one or more reference values ​​that indicate the relationship between absorbance and ammonia (NH3) concentration. Additionally, the absorbance signal can be further corrected from an LED and corresponding photodiode designed to record the sensor signal at wavelengths where the indicator has no optical absorption (minimum absorption wavelength), for example, above 675 nm.

[0064] In some embodiments, the user interface 102 is presented on a computing device. The computing device may be built into the detection system or built into an external device. An embedded computing device may be associated with a display. In an external device, the user interface 102 may include one or more software applications capable of acquiring data from the analytical device 100 and generating one or more reports for display on the graphical user interface of the user interface 102. The generated reports may require the performance of one or more analytical calculations on the data acquired from the analytical device 100. The computing device may be a mobile device, such as a tablet computer (e.g., Apple iPad®, Samsung Galaxy Tab, etc.), a smartphone (e.g., Apple iPhone®, Blackberry Phone, Android Phone, etc.), a smartwatch (e.g., Apple Watch, etc.), a personal digital assistant (PDA), a personal computing device (PC; via a web browser and installable software), and / or other similar devices. The computing device may be wired or communicatively connected to the analytical device 100 via a network, such as a local area network (LAN), a wide area network (WAN), a digital subscriber line (DSL), a wireless network (e.g., a 3G or 4G network), or other equivalent connection means. A Bluetooth® communication configuration is shown in FIG.

[0065] A computing device may have a processing unit, memory, data storage, and a communication interface. The components may communicate with each other via data and control buses. The processing unit may include, but is not limited to, a microprocessor, a central processing unit, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), and / or a network processor. The processing unit may be configured to execute processing logic to perform the operations described herein. In general, the processing unit may include any suitable dedicated processing unit specifically programmed with processing logic to perform the operations described herein.

[0066] The memory may include, but is not limited to, at least one of read-only memory, random-access memory, flash memory, dynamic RAM, and static RAM, and stores computer-readable instructions executable by the processing unit. In general, the memory may include any suitable non-transitory computer-readable storage medium that stores computer-readable instructions executable by the processing unit to perform the operations described herein. In some examples, a computing device may include two or more memory units (e.g., dynamic memory and static memory).

[0067] A computing device may have a communication interface device for direct communication with other computers (including wired and / or wireless communication) and / or communication with a network. In some examples, a computing device may have a display device (e.g., a liquid crystal display, a touch-sensitive display, etc.). In some examples, a computing device may have a user interface (e.g., an alphanumeric input device, a cursor control device, etc.).

[0068] In some examples, a computing device may include a data storage device that stores instructions (e.g., software) for performing any one or more of the functions described herein. The data storage device may include any suitable non-transitory computer-readable storage medium, including, but not limited to, solid-state memory, optical media, and magnetic media.

[0069] As illustrated in Figure 1, the analytical device 100 can have a variety of configurations. For example, panel C of Figure 1 shows a tube version of the analytical device 100. In the tube version of the analytical device 100, the wireless flexible printed circuit board 116 is configured with a flexible battery 118 and a flexible display located below the wireless flexible printed circuit board 116. The tube version of the analytical device 100 is configured so that the extraction membrane is in fluid contact with the urine in the tube. In panel C of Figure 1, the analytical device 100 is placed in line with the patient's urine in a catheter tube or collection bag.

[0070] In some embodiments, to reduce fouling of the analyzer, the sensor surface can be oriented parallel to the urine flow to avoid accumulation of urine solids (see Figure 1, panel C).

[0071] In some embodiments, hydrophilic modifications to the connector walls are included to enhance easy wetting of the connector and membrane and reduce sample clogging within the membrane due to insertion of the analyzer into the catheter. Additionally, one embodiment of the system described herein can use Jaco™ leak-proof standard tubing fittings to prevent urine leakage.

[0072] Alternatively, as shown in panel D of FIG. 1, an adhesive version of the analytical device 100 can be used, with the device 100 adhered to the diaper or skin so that the extraction membrane 104 comes into contact with the urine or sweat, respectively.

[0073] In some embodiments, the analytical device 100 detects ammonium (NH4 + The ammonia (NH3) sensor 106 can provide specific, rapid response, and accurate measurements of ammonia (NH3) gas concentrations ranging from 0.1 mmol / L to 50 mmol / L (corresponding to 0.1 mmol / L to 50 mmol / L of NH3). The ammonia (NH3) sensor 106 can be highly selective for ammonia (NH3), particularly considering the large amount of interfering substances in the urine headspace. As described below, sensors 106 constructed in accordance with the methods and systems described herein can exhibit good reusability over long sampling periods, enabling routine use for medical applications. Thus, the analytical device 100 can measure total ammonia (ammonia (NH3)) and ammonium (NH4) in urine and / or ammonia (NH3) gas extracted from urine, as evidenced by comparison with measurements from a commercially available reference method (ISE electrode) described further in the experimental section below. + )) concentrations can be accurately monitored. In some embodiments, the ammonia (NH3) sensor 106 is durable and can last for at least 10 weeks. As described below, the synthesis process of the sensor 106 is simple and easily reproducible. Furthermore, the analytical device 100 can be wirelessly connected to smart devices, thereby providing measurement flexibility for inpatient, outpatient, or personal health monitoring.

[0074] In some embodiments, the analytical device 100 may be particularly well suited for hospital or ambulatory settings. As described above in connection with FIG. 1, the analytical device 100 may have a replaceable cartridge containing an extraction membrane / sensor and optoelectronic combination for ammonia (NH) detection, signal conditioning, and wireless communication with a user interface device. Software for data acquisition, signal processing algorithms, display, transmission, and user interface may be included in the analytical device 100 and / or the user interface 102.

[0075] In some embodiments, a sample of bodily fluid (such as urine or sweat) may be diverted onto an extraction membrane / sensor cartridge (replaceable cartridge) where ammonia (NH3) is extracted. The extracted ammonia (NH3) can then interact with the cartridge's colorimetric sensor, causing it to change color depending on the ammonia (NH3) concentration. Software containing one or more signal processing algorithms can then determine the ammonia (NH3) concentration. In some embodiments, the total ammonia (NH3) and ammonium (NH4) in urine or sweat can be analyzed. + The excretion rate of total ammonia (ammonia (NH3) and ammonium (NH4)) in urine, skin headspace, or sweat can be determined by knowing the extracted ammonia (NH3) concentration and the pH of the fluid, and / or the flow rate of the fluid. In some embodiments, the total ammonia (ammonia (NH3) and ammonium (NH4)) in urine, skin headspace, or sweat can be determined by knowing the extracted ammonia (NH3) concentration and the fluid's density, specific gravity, osmolality, or osmolarity. + )) The excretion rate can also be estimated. In some embodiments, the test can be performed in an automated, continuous manner, with tests being performed every few minutes. The data can then be automatically transmitted from the analyzer 100 to the user interface 102, where it can be processed and displayed graphically.

[0076] For example, the user interface 102 may display the total ammonia (ammonia (NH3) and ammonium (NH4 + )) or ammonia (NH3) concentration, or total ammonia (ammonia (NH3) and ammonium (NH4 + )) or ammonia (NH3) excretion rate. The user interface 102 may be configured to be reviewed periodically by a healthcare provider, patient, etc. In some embodiments, the analytical device 100 or user interface 102 may display changes in urinary total ammonia (ammonia (NH3) and ammonium (NH4 +Sudden or unexpected changes in urinary total ammonia (ammonia (NH3) and ammonium (NH4)) concentrations and / or excretion rates can be identified and an automated alert can be triggered, thereby informing the healthcare provider of the presence or absence of urinary total ammonia (ammonia (NH3) and ammonium (NH4)) concentrations and / or excretion rates. + )) parameters (e.g., either possible acute renal failure or possible acute kidney injury (AKI) events) can be notified as soon as possible about changes in the relevant and related health or metabolic status. + Previous measurements of the concentration and / or excretion rate of )) can be stored in a database and compared.

[0077] As mentioned above, the composite extraction membrane / sensor is based on a colorimetric sensor and an extraction membrane for measuring ammonia (NH), both of which are assembled on the same substrate / unit, making the detection principle scalable and miniaturized (as shown in Figures 1 and 5). Extraction membranes with alkaline buffer extraction capabilities can be scaled down in size from centimeters to millimeters. In some embodiments, the extraction membrane follows Henry's constant partition behavior to extract ammonium (NH) at a pH of 10 or higher. + The colorimetric component may be configured to extract ammonia (NH) from the membrane into the gas phase. The colorimetric component may be configured to detect light absorption per unit area, whereby sensitivity is determined by the binding sites per unit area, independent of the total sensing area. In other words, the systems and methods described herein allow for scalable extraction membrane / sensor size combinations without sacrificing extraction quality, sensitivity, and detection limits. The sensor detection method utilizes high-performance flexible optoelectronic components such as LEDs and photodiodes (PDs) at low cost (see Figure 5, Panel D).

[0078] Referring now to FIG. 2, which shows a schematic diagram of an ammonia (NH3) sensor according to one embodiment of the present invention. As shown, the sensing chamber may include a red light-emitting diode 110 positioned to illuminate a sensing region 106A and a reference region 106B positioned parallel to the flow direction. A photodiode 108 may be positioned below the sensing region 106A and the reference region 106B. A target gas may be directed into the sensing chamber, where it is exposed to the sensor, which then exhibits a color change proportional to the concentration of ammonia (NH3) in the target gas. The photodiode 108 may be mounted on a printed circuit board with a resistor to obtain the photodiode signal sensitivity. Using Beer's Law, the negative logarithmic change in the signal ratio between the sensing region and the reference region can be used to determine the concentration of ammonia (NH3) gas via absorbance.

[0079] FIG. 3 shows a graph of the total ammonia (ammonia (NH3) and ammonium (NH4) of a fluid according to one embodiment of the present invention. + 1 shows an analytical cartridge for ammonia (NH3) detection. As shown in FIG. 1, the analytical device 100 can communicate wirelessly with the user interface 102. Wired communication may also be used. Furthermore, as shown in FIG. 3, the sensing area is sensitive to ammonia (NH3) concentration. In the before and after sections of FIG. 3, a color change in the sensing area 106A is shown after exposure to ammonia (NH3).

[0080] Referring now to FIG. 4, a graph of absorbance change according to one embodiment of the present disclosure is shown. The graph shows the change in the absorption spectrum of a sensor obtained in the sensor chamber of a JAZ spectrophotometer before and after exposure to ammonia (NH3). As shown, the sensor has a maximum absorption range wavelength of 600 nm to 630 nm. The maximum absorbance of the sensor for ammonia (NH3) occurs between 600 and 630 nm, while the minimum absorbance occurs at wavelengths greater than 675 nm.

[0081] FIG. 5 shows a graph of the total ammonia (ammonia (NH3) and ammonium (NH4) of a fluid according to one embodiment of the present invention.+ 5 shows a schematic and assembly diagram of a sensor for the detection of ammonia (NH3). Panel A of Figure 5 shows a nanocomposite sensor of bromophenol blue (BPB) contained in the indicator layer of an extraction membrane. As shown in Panel A of Figure 5, the sensing element can change color after exposure to ammonia (NH3). The sensing element may be fabricated from chemically selective nanocrystals of BPB deposited on a porous hydrophobic substrate, which provides a rapid and reversible response to ammonia (NH3). The sensor fabrication process is shown in Panel B of Figure 5. As shown, the sensor fabrication process may include lamination and laser cutting processes. Panel C of Figure 5 shows the absorption spectrum of the sensor during exposure to ammonia (NH3). The maximum absorption wavelength of 630 nm is shown. Panel D of Figure 5 shows the sensor assembly (referred to as a hybrid sensor) produced by the lamination process shown in Panel B of Figure 5. A schematic diagram of this sensor assembly shows the optoelectronic components for simultaneous detection at the maximum and minimum absorption wavelengths.

[0082] As shown in panels A and C of Figure 5, nanocomposites for an ammonia (NH3) sensor may be fabricated using a pH indicator (e.g., bromophenol blue, BPB) as the molecular probe. Any suitable alternative pH indicator can be used. In some embodiments, the colorimetric sensor substrate may consist of a custom-made or commercially available (e.g., polytetrafluoroethylene (PTFE)) membrane immersed in a BPB (colorimetric detector) solution, which generates nanocrystals when deposited on the substrate. The modified PTFE substrate can then be dried at 25 °C. This process allows the molecular probe (BPB) to generate nanocrystalline structures that form on the PTFE. In some embodiments, this can enable a significant or rapid reaction with the analyte ammonia (NH3). In some embodiments, the molecular probe can be used to rapidly and selectively detect ammonia (NH3) from urine or the headspace of skin. Different combinations of chemicals and substrate preparation methods were screened and studied, as discussed below in connection with the experiments. In some embodiments, the porous hydrophobic substrate for immobilization of BPB (PTFE) can facilitate not only fast ammonia (NH) reactions but also reversible reactions, since the substrate does not retain surrounding water, thereby avoiding permanently solubilizing ammonia (NH). As shown, the resulting nanocomposite exhibited rapid and highly responsive nanocrystals (<200 ms) (see Panel C in Figures 5 and 6) with high specificity in the presence of urine / sweat interfering molecules (see Panel A in Figure 6).

[0083] In Panel D of FIG. 5, a structured sensor is depicted with its main components. The main components have a laminated membrane on a spacer, and the laminated membrane and spacer are disposed on top of the sensor. Alternatively, the extraction membrane may be physically separated from the sensor or sensor chamber. Additionally, the assembly has a feed distributor that directly contacts the body fluid (i.e., urine, sweat). The illustrated components may be integrated into a sensor cartridge using a mask layer via a lamination process as illustrated in Panel B of FIG. 5. The laminated components may form a single assembly that fits into the sensor chamber along with the optoelectronic components, as shown in Panel D of FIG. 5 and Panel A of FIG. 1. The signal generated by the optoelectronic components may be electronically captured and processed with calibration data. The data may then be transmitted wired or wirelessly to the user interface 102. The total ammonia (ammonia (NH3)) and ammonium (NH4) in the body fluid may then be measured. + Data can be graphed over time to show trends in total ammonia (ammonia (NH3) and ammonium (NH4)) concentrations and / or excretion rates in body fluids. In some embodiments, + )) Automatic warning signals about rapid changes in concentration and / or excretion may be sent to the attending clinician to alert them to changes in metabolic state and / or potentially harmful conditions.

[0084] The cartridge is designed with integrated flexible electronics to fit into a tubular system or adhesive strips, allowing the user to easily "plug and play," as illustrated in the two configurations of the analyzer shown in panels C and D of Figure 1. In some embodiments, the LED and PD may be located on a flexible printed circuit board (PCB) as close as possible to the sensor cartridge to eliminate the need for focusing optics, thereby reducing size and cost (see panels A and D of Figure 5).

[0085] The LED and PD may be used in reflective mode. Two LEDs may be used to mitigate sensor drift signals. The analyzer 100 can form an integrated unit adapted to mate with tubing or adhesive strips. In both versions of the wearable analyzer (see panels C and D of FIG. 1 ), the electronics, including the electro-optical components, the microcontroller, power from a small thin-film flexible battery (e.g., Blue Spark Technologies Inc.), a small display, a power switch, and low-energy Bluetooth®, are mounted on a flexible PCB. The flexible PCB houses one microcontroller for controlling and reading the colorimetric sensor signal, the overall functionality of data collection, and minimal data processing (instantaneous total ammonia (ammonia (NH) and ammonium (NH)) for the embedded display). + )) if used as an option for concentration), and transmission via Bluetooth®. In some embodiments, the entire assembly described can be placed in a sleek housing designed to be portable, functional, and ergonomic.

[0086] In some embodiments, to mitigate baseline drift of an ammonia (NH3) sensor during use due to temperature changes, mechanical operation changes, changes in electronic component stability, etc., the sensor may be configured with two identical sensing areas and two identical reference areas. Each pair of sensing and reference areas may be illuminated with an LED. The LEDs may have unique wavelengths. One LED may have a wavelength of 630 nm and be used to capture the maximum absorbance change (Abs max) of the sensing probe. The second LED may have a non-absorbing wavelength (e.g., 700 nm) and be used to capture the baseline minimum absorbance (Abs min) of the sensing probe. The difference in absorbance: Δabsorbance = maximum absorbance - minimum absorbance, can be used as the sensor signal. The use of two wavelengths compensates for additional baseline drift in the sensor system (see panel D of Figure 5).

[0087] Furthermore, to mitigate variations in LED light intensity, in some embodiments, a single LED is used to illuminate the sensing and reference areas, as also shown in panel D of Figure 5. The absorbance reading of the sensing probe can be calculated as follows: absorbance = -log(sensing area reading / reference area reading).

[0088] FIG. 6 shows the specificity analysis (Panel A), ammonia (NH) detection accuracy (Panel B), reversibility and response time (Panel C), and sensor lifetime (Panel D).

[0089] As shown in Figure 6, panel A, the sensor can be configured to be specific for ammonia (NH3) and insensitive to other materials.

[0090] Furthermore, as shown in panel B of Figure 6, the assembly of the extraction membrane and ammonia (NH3) sensor can exhibit high sensitivity ranging from parts per billion (ppb) to parts per million (ppm) of ammonia (NH3) detection, and a high level of accuracy when compared to commercially available methods such as enzymatic reference methods or ion-selective electrodes. For example, as shown in panel B of Figure 6, the correlation coefficient (r2) is 0.998, which is 88% accuracy with a 2% error (95% confidence interval).

[0091] Panel C of Figure 6 demonstrates the reversibility and time response of the sensor. It shows the sensing region potential response over time to cyclic exposure to high and low parts per million of ammonia (NH).

[0092] Panel D of Figure 6 shows the sensor sensitivity (absorbance vs. concentration) after 24 hours of exposure to ammonia (NH3) levels. As shown, the sensor demonstrates reusability after pre-conditioning. Pre-conditioning involves placing the analytical device at 45°C for two weeks, which allows for robust immobilization of the components to the support substrate and allows for rigorous shipping and operational use conditions. In conjunction with this testing, ammonia (NH3) extraction was performed on a polystyrene / PTFE membrane with high glycine buffer at pH 10, cured with an organic hydroxide.

[0093] In some embodiments, the analytical device may further include a temperature sensor 120, as shown in Figure 7. The illustrated analytical device measures total ammonia (ammonia (NH3) and ammonium (NH4 + )). In some embodiments, a temperature sensor 120 may be mounted adjacent to the assembly sensor face to determine the in-situ temperature of the assembly sensor and provide correction of ammonia (NH) level readings due to temperature changes. Additionally, the embodiment of the analyzer shown in FIG. 7 and panel D of FIG. 1 may have an adhesive layer that provides an airtight seal of the skin headspace compartment.

[0094] In some embodiments, the analyzer measures fluid pH, fluid density, fluid specific gravity, fluid osmolality, fluid temperature, oxygen (O2) partial pressure, carbon dioxide (CO2) partial pressure, nitrogen (Na + ) partial pressure, sodium (Na + ), potassium (K + ), chloride (Cl - ), bicarbonate (HCO3 - ), calcium (Ca 2+ ), magnesium (Mg 2+ ), phosphate ions (H2PO4 - , HPO4 2- , PO4 3- The analyzer may include one or more sensors for at least one of the following: urinary tract enzymes (including urinary tract enzymes), creatinine, urea, uric acid, cystatin C, amino acids, renal tubular brush border enzymes, albumin, Tamm-Horsfall protein, insulin, cortisol, cortisone, creatinine, lactate, cyclic adenosine monophosphate, neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), insulin-like growth factor binding protein 7 (IGFBP7), and tissue inhibitor of metalloproteinase 2 (TIMP2). The analyzer may include a flow sensor configured to determine the total volume of fluid and / or the rate of fluid production. In some embodiments, the rate of fluid production may be expressed in units of urine volume per unit time.

[0095] In some embodiments, the analytical device 100 may also include one or more signal processing algorithms configured to process the raw data from the sensor and calibrate for any memory effects in the sensor. In some embodiments, the signal processing algorithms can account for any memory effects in the sensor when the concentration of the feed solution changes rapidly.

[0096] Total ammonia (ammonia (NH3) and ammonium (NH4 + Measurement of urinary total ammonia (ammonia (NH3) and ammonium (NH4 + )) and / or ammonium (NH4 +) concentrations are not commonly measured, and physicians measure total ammonia (ammonia (NH3) and ammonium (NH4 + )) and / or ammonium (NH4 + However, many researchers have been trained to calculate and utilize flawed indirect indicators (i.e., the "urinary anion gap") to estimate the concentrations of total ammonia (ammonia (NH3)) and ammonium (NH4 + A more reliable method for determining blood total ammonia (ammonia (NH3) and ammonium (NH4) levels) would be highly beneficial in certain treatment scenarios. + )) is a critical marker used to inform treatment decisions in patients with urea cycle disorders, organic acidurias, carnitine deficiency due to defective fatty acid oxidation, dibasic amino acidurias, defective pyruvate metabolism, and liver disease (e.g., cirrhosis), although sampling is less convenient than urine. Urinary total ammonia (ammonia (NH3) and ammonium (NH4 + )) levels in UCD patients were significantly higher than those in total ammonia (ammonia (NH3) and ammonium (NH4 + )) in the blood, and therefore, the urinary total ammonia (ammonia (NH3) and ammonium (NH4 + )) levels would be of great help in individualizing treatment for UCD patients without the need for very frequent blood draws. Renal total ammonia (ammonia (NH3) and ammonium (NH4 + Dynamic changes in urinary ammonia production (i.e., renal ammonia production) are stimulated by acid-base balance, potassium balance, and other systemic conditions. Therefore, the urinary total ammonia (ammonia (NH3) and ammonium (NH4)) levels in patients prone to acid-base or potassium disorders (i.e., critically ill hospitalized patients) are + Instantaneous understanding of total ammonia (ammonia (NH3)) and ammonium (NH4) levels can be leveraged to augment immediate clinical knowledge and serve as an early warning signal of rapidly changing (and otherwise under- or unrecognized) systemic conditions.+ Given the complex interplay of renal and hepatic adaptations to homeostasis, impairment of either of these organs can lead to a significant decrease in total ammonia (ammonia (NH3) and ammonium (NH4 + For example, acute liver dysfunction or decompensation can result in rapid changes in plasma total ammonia (ammonia (NH3) and ammonium (NH4 + )) levels, and acute renal dysfunction is associated with elevated urinary total ammonia (ammonia (NH3) and ammonium (NH4 + In outpatients, total ammonia (ammonia (NH3) and ammonium (NH4)) in biological samples (including breath, sweat, blood, and urine) is associated with a rapid decline in ammonia levels. + Continuous monitoring of total ammonia (NH3) and ammonium (NH4 + )) can provide a baseline level of urinary total ammonia (ammonia (NH3) and ammonium (NH4)), deviation from which is a strong predictive signal of unresolved hepatic decompensation in patients with advanced liver disease or of unresolved renal dysfunction. In hospitalized patients, patients with indwelling urinary catheters at high risk of acute kidney injury may report elevated urinary total ammonia (ammonia (NH3) and ammonium (NH4)) as the first sign of renal tissue damage or acute kidney injury. + )) concentrations or excretion rates could be monitored for rapid changes. Utilizing this technology could lead to rapid identification of acute renal failure (minutes to hours or days compared to lagging with traditional markers including serum creatinine). In any of these scenarios, specific treatments to ameliorate the underlying organ failure or dysfunction could be employed in a much more rapid and personalized manner than is currently practiced in modern medical practice. Thus, total ammonia (ammonia (NH3)) and ammonium (NH4 + The systems and methods described herein for detecting )) can be adapted for use in clinical settings.

[0097] In some embodiments, the systems and methods described herein can improve health outcomes and reduce associated medical costs for hospitalized patients who experience an acute kidney injury (AKI) event. In hospitalized patients with indwelling urinary catheters, the systems and methods described herein can continuously monitor AKI and automatically signal medical team members if and when a suspected AKI event begins. Previous studies have shown that patient outcomes improve when AKI events are recognized more quickly.

[0098] In some embodiments, the systems and methods described herein can aid clinical researchers in testing novel therapeutics for AKI in humans. The lack of ability to rapidly diagnose AKI (outside of a controlled laboratory environment in animal models) has significantly hindered most, if not all, past attempts at AKI treatment research in human subjects and continues to severely hinder AKI care in clinical settings. This is, at least in part, because novel therapies being tested in human study populations are almost universally given outside of the ideal therapeutic window, with some studies reporting that the drug was administered several days after an AKI event was known to have begun. Interestingly, many novel therapeutics have shown great promise in animal studies where the timing of AKI was precisely known and the drug was administered rapidly after the AKI event occurred (i.e., within 90 minutes). In clinical settings, the timing of AKI is unknown because: 1) symptoms and signs are almost always absent; 2) markers are present with significant delays (i.e., hours or days); and 3) detection systems have not been developed to identify the earliest moments of acute renal failure and / or early AKI. With appropriate testing, it is possible that one of the novel therapeutic agents that has shown great promise in animal models of AKI could find a place in the readily envisioned future clinical practice where human AKI can be rapidly detected using systems and methods such as those described herein.

[0099] Total ammonia (ammonia (NH3) and ammonium (NH4 + The systems and methods described herein for the detection of renal ammonia production and / or renal total ammonia (ammonia (NH3) and ammonium (NH4) + )) excretion changes rapidly. Furthermore, the systems and methods described herein are useful in conjunction with physiological studies where current diagnostic tools are limited in their ability to measure urinary total ammonia (ammonia (NH3) and ammonium (NH4)). + )) can be used to detect medical conditions in which changes can be correlated with the onset or activity of disease. These conditions include: 1) changes in kidney function, 2) acute kidney injury or failure, 3) chronic kidney disease, 4) changes in liver function, 5) acute liver injury or failure, 6) chronic liver disease (e.g., cirrhosis), 7) acute gastrointestinal bleeding, 8) chronic gastrointestinal bleeding, 9) ammonia (NH3) and / or ammonium (NH4 + 10) genetic or inherited metabolic disorders that involve or affect the physiological function of the development, handling, and / or excretion of ammonia (NH3) and / or ammonium (NH4) after a protein meal (e.g., urea cycle disorders, organic acidurias, carnitine deficiency due to defective fatty acid oxidation, dibasic amino acidurias, and defects in pyruvate metabolism), 11) alterations in normal metabolic processes (e.g., ammonia (NH3) and / or ammonium (NH4) after a protein meal) + 11) acute or chronic systemic acid / base changes or imbalances due to metabolic processes or disease states; 12) acute or chronic systemic acid / base changes or imbalances due to respiratory processes or disease states.

[0100] In some embodiments, the systems and methods described herein may include a "plug-and-play," reversible, continuous-use, and fast-response assembly sensor cartridge having a specific configuration of extraction membrane and colorimetric sensor.

[0101] In some embodiments, the systems and methods described herein may also have signal processing algorithms based on two wavelength specific optoelectronic system designs, and built-in mechanisms for eliminating drift (built-in sensing and reference regions, and temperature sensors).

[0102] Additionally, the systems and methods described herein can be used to detect total ammonia (ammonia (NH3) and ammonium (NH4) in wastewater, such as groundwater discharge, reclaimed water, industrial wastewater, sanitary wastewater, and produced water from oil and gas wells. + )) can be applied to industrial applications such as measurement of [Example]

[0103] The following examples are given to illustrate exemplary embodiments of the present disclosure, but it should be understood that the present disclosure should not be limited to the particular conditions or details set forth in these examples.

[0104] Example 1: Field performance of the analyzer The response of an analytical device constructed according to the systems and methods described herein was tested using actual human urine samples in comparison with an ion-selective electrode method. Urine samples were evaluated from subjects who consumed 1 g of protein / kg body weight in a single meal (shake). After the meal, samples were analyzed hourly for several hours. The ion-selective method required a two-point calibration before each sample was analyzed. For the analytical device, a single sensor assembly was used for analysis of the complete experiment. As shown in Figure 8, both the reference method and the analytical device sensor assembly yielded correlation results close to unity. This example demonstrates that an analytical device using a single sensor can perform similarly to the reference method using actual samples of human urine, and reuse several times a day reassured the sensor's successful performance.

[0105] Example 2: Sensor preparation In one example, an ammonia (NH3) sensor according to the systems and methods described herein was constructed based on bromophenol blue (BpB) from Sigma-Aldrich. The sensor was synthesized by immersing the sensor substrate in a BpB solution. The sensor substrate in the solution was then vortexed for 10 minutes using a Scientific Industries Vortex Genie 2 and allowed to dry at room temperature for 5 minutes. To test the influence of the substrate on detection sensitivity, sensors were constructed on five different sensor substrates, including Omnipore™ polyvinylidene fluoride (PVDF) (pore size: 0.1 μm and porosity: 80%), Sterlitech polytetrafluoroethylene (PTFE) / polyethylene (PE) (pore size: 0.2 or 0.45 μm), Interstate Specialty Products hydrophobic PTFE (pore size: 10 μm), Omnipore™ hydrophilic PTFE (pore size: 0.1 μm and porosity: 70%), and Whatman No. 1 filter paper (pore size: 11 μm). The sensor substrates were cut into rectangular shapes (2.7 cm × 1.2 cm) and stacked so that they fit into the sensing chamber of an analyzer, arbitrarily named a colorimetric photoelectrodynamic analyzer (CODA). Some of the constructed sensors were sealed in black Mylar™ bags and placed in a 45° C. oven for 2 days to test their performance stability.

[0106] Example 3: Preparation of the analytical device An analytical device, a colorimetric photoelectrodynamic analyzer (CODA), was constructed according to the systems and methods described herein. The analyzer had a horizontal flow path through a sensing chamber, which contained a red LED above the sensor and four photodiodes (a sensing / reference pair and a sensing / reference backup pair) below the sensor. Target gas was introduced into the sensing chamber, where it was exposed to the sensor. The sensor exhibited a color change proportional to the concentration of ammonia (NH3) in the target gas. The photodiode (manufactured by Vishay Semiconductor Opto Division) was mounted on a PCB with an integrated Bluetooth unit, along with a 5 MΩ resistor to obtain the photodiode (PD) signal sensitivity, enabling signal transmission to an Android phone. An application was created to provide a user interface for displaying the signal read by the PD within the range of 0 to 3 V. The sensor had a reference region and a sensing region. The background response from the reference and sensing regions when the sensor was in the chamber was measured to be approximately 1.2 V. A pair of PDs simultaneously and continuously read the responses of the reference and sensing regions every 0.2 seconds.

[0107] Figure 9 shows the results of Example 3, specifically the change in sensor signal before and after exposure to ammonia (NH3). The reproducibility of the sensors was determined using (a) four different PVDF sensors to detect 2 ppm ammonia (NH3), and (b) four different PTFE sensors to detect 40 ppm ammonia (NH3) using an analytical instrument. The four different substrates show similar signal responses. The PTFE response signal has higher noise compared to the PVDF substrate.

[0108] The absorbance is calculated by the sensing area (S sens. ) is the signal response from the reference region (S ref. ) was calculated based on Beer's Law by taking the negative logarithm of the signal response from the

number

[0109] The PTFE and PVDF sensors were cut into rectangles using a laser cutter (Universal Laser Systems) and then laminated using a Fellowes Jupiter 125 Laminator. A calibration curve for PTFE was created by plotting the measured absorbance change against known concentrations of ammonia (NH3) in the concentration range 2 to 1000 ppm.

[0110] To ensure there was no interference between the PD readings from the sensor's sensing and reference areas, a crosstalk test was performed. In this test, either the reference or sensing area was individually masked with thick black ink to block light. Measurements were performed for 30 seconds to verify that there was zero response for the blocked area and no effect for the unblocked sensor area. The crosstalk test results are shown in Tables 1 and 2. [Table 1] [Table 2]

[0111] For both masked substrates, crosstalk tests showed small signal changes (<0.1% for the sensing area and <15% for the reference area), which were not significantly significant under the sensing conditions and could be further improved by creating a thicker barrier between the PDs or reducing the sensor-to-detector distance.

[0112] Example 4: Optoelectronic Devices An Ocean Optics JAZ spectrophotometer (JS) was used to perform sensitivity testing and spectral measurements of various sensor materials before and after exposure to ammonia (NH3). Figure 10 shows a schematic diagram of the JS measurement setup. The optical fiber is located at the top of the chamber, while the tungsten light source is located at the bottom. Gas travels through the tube on the left and is released into the ambient environment through the tube on the right. The response of sensors synthesized with various materials after 180 seconds of exposure to 10 ppm ammonia (NH3) was measured by JS, and PVDF showed superior absorbance response compared to the other materials.

[0113] The filter paper was cut into a round shape to fit the JS sensing chamber. An ammonia (NH3) sensor integrated with an ammonia (NH3) extraction membrane was used for the spectral measurements. A schematic diagram of the sensor and sample transport from the liquid fluid to the gas being measured is shown in Figure 11. The extraction membrane / sensor assembly consisted of five components: 1) a distribution layer (e.g., filter paper) that ensures homogeneous distribution of the liquid fluid; 2) an alkalinization membrane layer (e.g., PE membrane impregnated with 40 μL of 2 M NaOH solution) that extracts ammonia (NH3) from the sample; 3) a polytetrafluoroethylene (PTFE) membrane that prevents the liquid fluid from reaching the indicator layer; 4) an indicator layer (filter paper impregnated with bromothymol blue) that reacts with the extracted ammonia (NH3); and 5) a tape mask that protects the sensing probe. The synthetic urine delivery (ammonium (NH4) + A solution containing ammonium chloride (NaCl) and other ions simulating urine (NaCl, KH2PO4, CaCl2, MgSO4) was injected on top of the integrated ammonia (NH3) sensor membrane. JS quantified the ammonia (NH3) levels in the sample. The ammonia (NH3) sensing mechanism is further described below.

[0114] The distributor distributes the sample feed evenly. The alkaline layer is composed of fluid ammonium (NH4 +) into its conjugate base, ammonia (NH3). The PTFE membrane selectively filters ammonia (NH3) gas based on the membrane's hydrophobicity. The ammonia (NH3) sensor has an indicator that changes color from yellow to blue based on how much ammonia (NH3) gas it is exposed to.

[0115] Example 5: Photoelectric Sensor Signal As previously mentioned, bromophenol blue (BpB) was used as a colorimetric detection probe for ammonia (NH3) detection. BpB solutions have a yellow / orange color when exposed to pH levels below 3 and a blue color when exposed to pH levels above 4.6. Ammonium (NH4 + The acid / base equilibrium between OH (acid) and ammonia (NH3) (conjugate base) is - +NH4 + Determined by the pH of a solution of H2O + NH3. Ammonia (NH3) has a vapor pressure of 1062 kPa and a pKa of 9.25 at room temperature. Biologically relevant pH conditions are found in NH4 + For example, in human urine at a relatively high pH of 8, the total NH + Only 6.6% of NH3 exists as NH3 (gas). Dynamic nature of body fluid pH (e.g., urine) and urinary NH4 + Because of the variable ratio of NH3 to urine, alkaline solutions contain NH4 + To ensure 100% conversion of ammonia (liquid) to NH3 (gas), it is necessary to raise the fluid sample pH above ~10. Ammonia (NH3) makes the sensing surface more alkaline, shifting the pH value higher and causing a yellow-to-blue color change. By quantifying the color change using an analyzer (CODA), the corresponding ammonia (NH3) concentration obtained from the sample can be determined.

[0116] Example 6: Gas Sample Preparation - Ammonia Bags The ammonia (NH3) gas samples used in this study were diluted with 100 ppm and 1000 ppm calibration ammonia (NH3) gas purchased from Calibration Technologies, Inc. Dilutions of the gas samples in laboratory compressed air were prepared from 100 ppm and 1000 ppm ammonia (NH3) calibration gases. These calibration gases were introduced into a 40 L bag for a predetermined time using a TOPSFLO micro-diaphragm gas pump (flow rate: 1.6 LPM). Additional clean air was also introduced into the bag for a controlled period until the ammonia (NH3) concentration in the bag reached the desired level. The target ammonia (NH3) gas concentration was adjusted by manipulating the ratio of ammonia (NH3) gas injection to air injection (0.02-0.8). Another ammonia (NH3) bag was prepared by injecting 5 μL of ammonium hydroxide (NH4OH) into a 1 L Tedlar™ bag and allowed to sit at ambient room temperature for 30 minutes to confirm the sensor calibration curve.

[0117] Example 7: Gas Sample Preparation - Urine Headspace Bags Urine test samples were pretreated by adding 0.3 mL of 10 M NaOH to 2.7 mL of urine sample to ensure the sample pH was above 12. The pretreated urine sample was then added to a 4 L Tedlar™ bag and purged with dry air until the bag was full. The Tedlar bag was left at room temperature for 30 minutes to remove all ammonium (NH4 + ) reacted with the base to form its conjugate phase, ammonia (NH3), in the urine headspace. This portion of the study was approved by the Arizona State University Institutional Review Board (IRB protocol #1012005855). Subjects volunteered and provided written consent to participate in the study. All testing in this study was conducted between February 2016 and July 2017. Subjects consumed the ON High Protein Gainer shake at 1 g of protein per kg of body weight and urinated periodically after drinking. Urine samples were collected and immediately stored in a -80°C freezer for later analysis.

[0118] Example 8: Sensor detection procedure The sensitivity, reversibility, and reusability of the ammonia (NH3) sensor were tested using an ammonia (NH3) flow system consisting of a micro-diaphragm gas pump (flow rate: 1.6 LPM), a three-way valve, one 40 L air bag, one 40 L sample bag, and a sensing chamber. Each test was performed with one sensor placed in the sensing chamber. The three-way valve was first switched to connect with the air bag for several seconds, allowing the sensor to be purged with air for several seconds before being exposed to the sample. To study the sensor's sensitivity to different sample exposure times, the sampling time was varied, including 1, 5, 20, and 180 seconds. After exposure to ammonia (NH3), the valve was switched to allow dry air to pass through the system for several seconds to test the sensor's reversibility.

[0119] Example 9: Results and Discussion - Colorimetric Photoelectrodynamic Analyzer (CODA) Wavelength Selection The light source color for the analytical device, which can be called a colorimetric optical dynamics analyzer (CODA), was selected based on the spectral changes induced on the sensing probe (BpB) following ammonia (NH3) exposure. Circular sensors formed from filter paper impregnated with BpB were placed in the sensing chamber of the JS device, and the spectra of each sensor were recorded before and after exposure to ammonia (NH3). Figure 4 shows the visible spectrophotometric changes of the BpB-based sensor, where a significant increase in absorbance in the 575-625 nm range is clearly observed. Based on these results, the LED color was selected to be red, with a wavelength of 610 nm. Once the detection wavelength and initial screening of the sensor substrate were selected, the analytical device, CODA, was constructed and used to carry out the remaining studies.

[0120] Example 10: Results and Discussion - Sensing Probe Sensitivity Table 3 shows the characteristics of various sensing substrates embedded with BpB, and Figure 10 summarizes the sensitivity of the sensing substrates tested with the JS instrument after 180 seconds of exposure to 10 ppm ammonia (NH3) gas. The sensitivity of the sensor to ammonia (NH3) is strongly dependent on the nature of the substrate. The graph in Figure 10 shows that the PVDF substrate has the greatest measurement sensitivity, approximately 10 times greater than all other substrates tested. The sensitivity of the PVDF substrate to the normal total ammonia (NH3) and ammonium (NH4) in urine is approximately 10 times greater than that of the PVDF substrate. + )) concentrations are typically greater than 6 mmol / L, which is due to the presence of ammonium (NH4 + Based on the ideal gas equation of state, the complete conversion of PVDF to ammonia (NH3) and ammonia (NH3) gas extraction (following the ideal gas equation) results in ammonia (NH3) gas concentrations in the urine headspace of greater than 100 ppm at 25 °C. The high sensitivity of PVDF precludes multiple sensor use, as the sensor rapidly saturates after a single use. Therefore, we investigated the sensitivity, specificity, and reversibility characteristics of another substrate, hydrophobic PTFE, compared to PVDF for monitoring urinary ammonia (NH3). [Table 3]

[0121] Example 11: Results and Discussion - Reproducibility of Sensor Response Figure 12 compares the absorbance response of sensors based on PTFE and PVDF support materials, as used in the CODA. Four replicate sensors were fabricated using each material and placed in the CODA. The sensors were then exposed to ammonia (NH3) for 180 seconds, followed by dry air for an additional 60 seconds, and recovery was measured. The sensors exhibit similar response characteristics, with an increase in absorbance when sparged with ammonia (NH3) and a decrease in absorbance when purged with dry air. The absorbance noise of the PTFE substrate was higher compared to the PVDF substrate.

[0122] Table 4 summarizes the sensor response and the percentage of sensor recovery after purging, which is the ratio of the absorbance change during the recovery period to the absorbance change during the exposure period. The sensor responses included 0.64 au with a standard deviation of 0.02 for PVDF and 0.58 au with a standard deviation of 0.03 au for PTFE, resulting in a response variance of less than 5% across the sensor substrates. It is important to note that even though PVDF had similar reproducibility to PTFE, a lower ammonia (NH3) concentration (20-fold lower) required for comparison yielded similar recoveries to PTFE. The recovery characteristics of the sensor response using PTFE over a concentration range within the realistic range of urinary ammonia (NH3) concentrations made PTFE a more attractive candidate for further study of the analytical performance of this sensor substrate. As a result, PTFE sensors were investigated for the remainder of the study. [Table 4]

[0123] Example 12: Results and Discussion—Ammonia (NH 3 ) sensor calibration Two calibration curves were generated for the PTFE sensor using CODA with ammonia (NH) gas levels ranging from 2 ppm to 1000 ppm and a sampling time of 5 seconds, as shown in Figure 13. For the first, upper calibration curve, the Langmuir model was applied, yielding an R of greater than 0.99. 2 For a sampling time of 5 seconds, the calibration equation is: A L represents the absorbance derived from the Langmuir model, and C represents the corresponding concentration.

number

[0124] For the other lower calibration curve, the calibration curve was divided into two ranges for fitting a linear regression: 2–150 ppm and 150–1000 ppm. Both measurement ranges had an R of greater than 0.98. 2 The calibration equation is as follows: A1 represents the absorbance derived from a linear model from 0 to 150 ppm, and A 2 represents the absorbance derived from the linear model from 150 to 1000 ppm, and C represents the corresponding concentration.

number

number

[0125] In another set of fits, linear regressions of the absorbance change evaluated after a 1-second exposure to ammonia (NH3) were also obtained and compared to those obtained after a 5-second exposure. These regression analyses were used to test unknown sample concentrations resulting from a mixture of ammonium hydroxide (NH4OH) and air in a bag. Table 5 shows the results evaluated for unknown concentration samples by the sensor using 1-second and 5-second exposures, as well as the corresponding calibration curves. Both calibration curves (derived from the 1-second and 5-second exposure data) yielded the same concentration of prepared ammonia (NH3) bags of unknown concentration, demonstrating self-consistency of the calibration. Furthermore, these results demonstrate consistency between each pair of photodiodes in the system (PD1 (sensing) / PD3 (reference), denoted as PD1, and PD2 (sensing) / PD4 (reference), denoted as PD2), since both photodiode pairs produced the same response. [Table 5]

[0126] Example 13: Results and Discussion - Ammonia (NH 3 ) Sensor selectivity To confirm that the sensor was selective only for ammonia (NH), the sensor was exposed to several interfering substances (e.g., acetone, 2-butanone, and methylene chloride) that are reported to be present in urine headspace. Figure 14 shows the selectivity of the sensor for ammonia (NH). Even with relatively high concentrations of interfering substances (e.g., 100 ppm acetone), the sensor only showed a significant response to ammonia (NH). This test confirmed the selectivity of the sensor in the harsh environment of a urine headspace sample.

[0127] Example 14: Results and Discussion - Reversibility and Reusability of the Sensor A healthy adult may urinate every 2–3 hours (8–9 times per day). Current methods for quantifying urinary ammonium (NH4+) in clinical medicine involve requiring a patient to collect all urine excreted for 24 hours. There are no clinically applicable methods for the instantaneous measurement of urinary ammonia (NH3) or total ammonia (ammonia (NH3) and ammonium (NH4+)). The top panel of Figure 15 shows the absorbance response of a PTFE-based sensor to repeated, alternating exposures to 100 ppm ammonia (NH3) and dry air over a 1.2-hour period. The sensor was subjected to a continuous cycle of 5-second exposure to ammonia (NH3), followed by 120-second exposure to dry air. This sensor was reused for over 60 detection cycles without any degradation in performance. In practical clinical applications, ammonia measurements can be performed every 24 minutes for 5 seconds to cover 24-hour monitoring, although much more frequent testing is also possible.

[0128] The bottom panel of Figure 15 shows the measured concentrations derived from successive tests after signal analysis and use of the calibration equation. It is important to note that the sensor required an adjustment period of 5-7 exposures. After this adjustment period, the concentration output remained fairly constant through multiple exposures to ammonia (NH3) and detection events of the same concentration. The detected concentration error was less than 20% and could be further improved with a better enclosure for the CODA, thereby reducing ambient light interference.

[0129] Example 15: Results and Discussion - Sensor Stability To test the stability of the PTFE sensors, a set of sensors was freshly prepared and used for ammonia (NH3) testing immediately after synthesis. Identical sets of sensors were prepared, sealed in black Mylar™ bags, and aged in a convection oven at 45°C for two weeks. According to the aging protocol (ASTM F1980), two weeks of aging at 45°C corresponds to two months of aging at room temperature (25°C). Both sets of sensors were exposed to ammonia (NH3) concentrations of 2, 10, 15, and 20 ppm. Figure 16 shows a comparison of the sensitivity of fresh and aged sensors. Figure 16 shows the linear regression of all data and averaged data. The slope was 0.001 au / ppm and the R2 was greater than 0.99. 2 was obtained for the average data. Figure 16 also shows another set of virgin and aged sensors obtained from different synthesis batches. A t-test between these responses from each batch of membrane for virgin and aged sensors yielded a p-value equal to 0.87, indicating no significant difference. These tests confirmed the stability of the sensing probe (BpB) on a PTFE substrate during long-term heat exposure associated with sensor application and storage. For a commercial product, sensor sensitivity needs to be guaranteed after a period of heat exposure that may occur under realistic shipping or storage conditions.

[0130] Example 16: Results and Discussion - Sensor Use with Urine Samples To verify the feasibility of CODA and the use of the sensor in real-world conditions, urine sample analysis was performed and measurements from a calibrated batch of sensors were recorded. An ion-selective electrode (ISE) [Thermo Fisher Scientific Ammonia High-Performance Ion-Selective Electrode (no. 9512HPBNWP)] was used as a reference method for ammonia (NH3) detection. Subjects were first asked to urinate and then drank a protein shake. Urine samples were collected from the subjects before and after drinking the shake at 0, 0.5, 2.5, and 3.5 hours. These samples were stored at -80°C before measurement. The samples were then measured with the ISE electrode and then with CODA. The top panel of Figure 17 shows an example of measurements from one subject. Similar results can be found in the literature using SIFT-MS. The bottom panel of Figure 17 shows a correlation plot of the results evaluated from the CODA and ISE methods. Good agreement was observed between the CODA and ISE electrode measurements, with accuracy approaching 100%.

[0131] Example 17: Results and Discussion - Use of the sensor in a urine sample as an insert in a diaper or adhesive patch or card As shown in Figure 18, in some embodiments, the sensors described herein may be used in the form of an insert for a diaper or wearable cloth. The use of a sensor with an extraction membrane can be carried out in the form of an insert for a diaper or wearable cloth or device (e.g., a bracelet), or an adhesive patch for the skin, or a card (e.g., a badge) for in vitro testing. Under these conditions, the total ammonia (ammonia (NH3)) and ammonium (NH4) in the body fluids are measured. + )) and / or ammonium (NH4 + Quantification of the sensor response (i.e., color change) by detecting NH3 as ammonia (NH3) can be performed using any method capable of detecting small color changes, such as RGB deconvolution software.

[0132] Example 18: Results and Discussion - Use of the Sensor for Continuous Samples 19 shows components of an example CODA device. In some embodiments, the sensors described herein can be used for continuous ammonia monitoring from biological samples and inserted into a device that can manage liquid from the sample and gas from the extraction process within the sensor, as well as regenerate the sensor surface (sensing probe) with a clean source of air, such as from a scrubber.

[0133] Example 19: Results and Discussion - Extraction membrane of the sensor and subsequent use for sample quantification. As shown in Figures 20a-20o, a model of the extraction membrane from the sensor can be constructed to optimize the geometry, chemical / physical design, and lifespan. Along these lines, models can be utilized that have an extraction membrane that chemically converts NH4+ to NH3 via an alkaline substance, or that electrochemically generates an alkaline substance to convert NH4+ to NH3, or that electrochemically converts NH4+ directly to NH3. Based on this model, the NH4 + At concentrations in the range of 3.6-100.0 mM, which are typically found in urine samples, the incoming NH4 + The concentration of alkaline material (e.g., fixed hydroxide (OH - It can be concluded that the concentration profile of the alkaline substance (OH) is not affected by the inlet velocity. In other words, the concentration of alkaline substances in the chemical extraction membrane is mainly affected by the inlet velocity, which is a parameter modeled as a change in the limit state (e.g., inlet velocity u0). This model also - The number of consecutive uses of the chemical extraction membrane can be determined before the alkaline substance (NH4) in the sample is depleted. Embodiments such as the CODA device shown in Figure 19 can be modeled by assuming that the sensor has a source of alkaline substance that is depleted after each use. Figures 20a-20o also show how different variables in the extraction membrane can be tested. These variables include porosity, boundary conditions, and the initial NH4 content in the sample. + The various variables, including concentration, and geometry, can be analyzed to determine how they affect the alkaline substance concentration profile of the extraction membrane.

[0134] As an example, Figures 21a and 21b show model results of cross-sectional concentration profiles of alkaline substances in a chemical extraction membrane after the first cycle (shown in Figure 21a) and after the 20th cycle (shown in Figure 21b).

[0135] Additionally, other design aspects of the extraction membrane are important. One of them is the elimination of potential ammonia leakage. Based on practice and simulation, multiple but narrow liquid pathways and a smaller exposure area to the liquid / air interface minimize ammonia gas leakage from the membrane. Furthermore, further modification of the extraction membrane with a potential agent to chelate amine groups eliminates interference from nonenzymatic degradation of primary amine-based molecules, which can render ammonia not originally present in the sample and therefore physiologically unrelevant. This modification eliminates the problem of ammonia overestimation (Figure 22a), which is known to be a problem under current testing conditions (Figure 23). Indeed, the combination of all of the above factors results in an extraction membrane with high specificity, as shown in Figures 22a and 22b.

[0136] Figures 20a-20o show the results of the analysis with different variables, i.e., porosity, boundary conditions, initial NH4 + An example of how concentration and geometry affect the concentration profile of alkaline substances in an extraction membrane is shown. + The concentration, inlet velocity and porosity of -1 and was set to a value of 0.34. The results shown here are the concentration profiles for (Fig. 20a) the 1st, (Fig. 20b) the 10th, and (Fig. 20c) the 20th measurements. + The concentration and inlet velocity were 37.8 mM and 0.05 msec, respectively. -1 The results shown here are for the 20th measurement at porosities of (Fig. 20d) 0.34, (Fig. 20e) 0.66, and (Fig. 20f) 0.90. + The concentration and porosity of 0.0035 ms are set to 37.8 mM and 0.34. The results shown here are (Figure 20g) 0.0035 ms -1 (Figure 20h) 0.05ms-1 , and (Fig. 20i) 0.5 ms -1 The inlet velocity and porosity of the sample were 0.05 m / s, respectively. -1 The values ​​were set to 0.34 and 0.35. The results shown here show that the NH4 + This is the 20th measurement of the concentration. + The concentration and porosity of OH were set to values ​​of 37.8 mM and 0.34, respectively. - ) is depleted in configurations with (Fig. 20m) 3 cm length and 2.5 cm diameter, (Fig. 20n) 1.5 cm length and 2.5 cm diameter, and (Fig. 20o) 1.5 cm length and 2.0 cm diameter.

[0137] Figures 22a and 22b show the analytical performance of the extraction membrane and overall sensor for complex body fluids. In Figure 22a, the fluid was treated with a copper ion chelating material. These copper ions chelated (bound) with amine groups in amino acids and primary amine residues in other molecules, thus preventing enzymatic and non-enzymatic degradation (degradation of these molecules would result in a spurious increase in ammonia levels). Figure 22b shows the overall selectivity of the extraction membrane in the sensor for whole blood using 170 μM ammonia (as ammonium). Figure 22b) shows that the extraction membrane and sensor have negligible response to the maximum known concentrations of other blood constituents: 5,000 mg / dL albumin, 3 mg / dL ascorbic acid, 5 mg / dL creatinine, 2656 mg / dL glucose, 370 mg / dL (5 mM) potassium ion, 228 mg / dL (3.9 mM) sodium ion, 1,000 mg / dL phosphate, 107 mg / dL urea, and 6.8 mg / dL uric acid.

[0138] Figure 23 shows the response of an enzymatic reference method (Roche Cobas®) to plasma collected from the body, plasma spike 1 (spiked with glutamine), and plasma spike 2 (added with the amino acids glutamine, L-arginine, L-asparagine, and creatinine, and urea, a metabolite of ammonia). The concentrations of the spiking agents range from 10 to 100 µM, simulating physiologically expected levels. This demonstrates that the enzymatic method is confounded by spontaneous non-enzymatic deamination of amino acids, resulting in excessively high ammonia readings.

[0139] Example 20: Results and Discussion - Use of the sensor for free calibration for the determination of ammonia An intelligent algorithm can be built based on the quantified general sensor sensitivity and used as a means to avoid sensor calibration (either before each sensor use or for the device and sensor being used). The intelligent algorithm is fed with physical / chemical behavior, such as the sensor sensitivity for different sensor initial operating conditions, such as the initial signal (V) before analyte detection. Figure 24 shows a demonstration of quantifiable general sensor sensitivity, enabling a calibration-free approach for ammonia quantification.

[0140] Figure 24 shows the relationship between the measured initial signals from the sensing regions of the different sensors with the slopes of the corresponding calibration curves for the sensors ranging from 3.6 mM to 18.6 mM. The relationship between these two variables is expressed as a regression coefficient R 2 =0.88. This linear relationship is useful for building an intelligent calibration-free algorithm for the determination of ammonia.

[0141] Example 21: Results and Discussion - Use of the sensor for continuous determination of ammonia with high accuracy Figure 25 shows the results of NH4 + 25 shows a continuous measurement of NH4, which is consistent with the actual ammonia concentration with an error of less than 15%. As shown in Figure 25, the above application can successfully perform continuous quantification of ammonia, with only a small difference between the ammonia value measured by the sensor in this application and the true ammonia concentration. +It is a parameter defined for CODA that is used to quantify the concentration.

[0142] While the present disclosure has been discussed with respect to particular embodiments, it should be understood that the disclosure is not so limited. While embodiments are described herein by way of example, there are numerous modifications, variations, and other embodiments that could be employed that would still fall within the scope of the present disclosure.

Claims

1. Ammonium (NH ４ ＋ a distribution layer configured to receive a sample of fluid comprising: contacting the distribution layer, ４ ＋ ) by converting at least a portion of the ３ an alkaline layer configured to convert contacting the alkaline layer, ３ and a hydrophobic layer configured to drain at least a portion of the

2. The cartridge of claim 1 , wherein the distribution layer comprises a filter.

3. The cartridge of claim 1 , wherein the alkaline layer comprises at least one of an organic hydroxide, sodium hydroxide, and a buffer solution having a pH of 10 or greater.

4. The cartridge of claim 1 , wherein the alkaline layer comprises a polyethylene (PE) film.

5. The cartridge of claim 1 , wherein the hydrophobic layer comprises polytetrafluoroethylene, a polytetrafluoroethylene derivative, or a cellulose derivative.

6. The ammonia (NH ３ 10. The cartridge of claim 1, further comprising an indicator layer configured to change color in response to the amount of

7. 7. The cartridge of claim 6, wherein the indicator layer comprises filter paper.

8. 7. The cartridge of claim 6, wherein the indicator layer comprises at least one of bromophenol blue, bromothymol blue, and a plant-derived pH indicator.

9. Ammonium (NH ４ ＋ a distribution layer configured to receive a sample of fluid comprising: Ammonia (NH ３ an extraction membrane configured to expel the The discharged ammonia (NH ３ a sensor or sensor chamber configured to receive the sensor; The ammonia (NH ３ ) and quantifying the amount of the quantified ammonia (NH ３ and identifying changes in the amount of the protein over time.

10. The extraction membrane contacting the distribution layer, ４ ＋ ) by converting at least a portion of the ３ an alkaline layer configured to convert contacting the alkaline layer, ３ 10. The analytical device of claim 9, further comprising: a hydrophobic layer configured to expel the

11. The processor further comprises: ３ ) or the amount of the quantified ammonia (NH ３ 10. The analyzer of claim 9, configured to detect at least one of changes in organ function, changes in tissue function, and changes in metabolic state based on changes over time in the amount of

12. 10. The analytical device of claim 9, further comprising a user interface device configured to receive a transmission of at least one piece of information from the sensor, the user interface device having a display including a graphical user interface, the graphical user interface configured to display the information.

13. The information is the quantified ammonia (NH ３ 13. The analytical device of claim 12, wherein the amount of the identified change over time corresponds to at least one of: the amount of the identified change over time;

14. The ammonia (NH ３ an indicator layer configured to change color in response to the amount of 10. The analytical device of claim 9, wherein the sensor or the sensor chamber comprises at least one light-emitting diode configured to irradiate the indicator layer with light and at least one photodiode configured to measure a change in absorbance of the indicator layer.

15. 15. The analytical device of claim 14, wherein the at least one light emitting diode emits light at a wavelength of maximum absorption of the indicator layer, and another one of the at least one light emitting diode emits light at a wavelength of minimum absorption of the indicator layer.

Images