Nano-robot for identifying protein in ultralow-concentration culture medium

Abstract

Disclosed herein is a system for quantifying a low concentration of an analyte in a sample, such as a human embryo culture. The system allows for precise identification and quantification of analytes, such as proteins, at a resolution and sensitivity of less than 1 pg / ml. The disclosed system provides a non-invasive, fast, and accurate measurement platform to achieve better patient care through more intelligent medical decisions. Also disclosed herein is a method of quantifying an analyte in a sample using the disclosed system.

Description

[0001] Cross-referencing of related patent applications

[0002] This application claims the benefit and priority of U.S. Provisional Application No. 63 / 667,315, filed July 3, 2024, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The field of this invention is generally in the biomedical diagnostics field, particularly in the quantification of proteins. Background Technology

[0004] A more precise and reliable method is needed to quantify the essential protein concentration of human chorionic gonadotropin (hCG) in embryo culture waste, a crucial biomarker for pregnancy and certain medical conditions, including trophoblastic diseases and some cancers. Traditional protein detection methods, such as enzyme-linked immunosorbent assays (ELISA) and radioimmunoassays (RIA), are often limited in sensitivity and specificity and require large sample volumes. These routine techniques can also cross-react with other substances in the sample, leading to false positives or false negatives, which can significantly impact patient diagnosis and treatment. The system described in this paper overcomes these challenges by allowing the direct, label-free detection of hCG molecules with greater precision and resolution. Improved robotics minimizes the risk of cross-reactivity and erroneous readings, providing clinicians and researchers with a powerful and reliable tool. Therefore, this system fulfills a long-standing need in the medical diagnostics field for a method that ensures rapid, non-invasive, and accurate measurement of proteins in cultured embryos, thereby improving standards of care and potentially enhancing clinical outcomes. Summary of the Invention

[0005] This paper discloses a system for detecting low concentrations of analytes in samples. The disclosed system includes a measurement module, a signal communication module, precise sample tip positioning, and AI-based data processing software, integrating real-time image updates, sample tip positioning accuracy, and an augmented reality system with an enhanced user interface for protein identification measurements.

[0006] This paper also discloses a method for detecting analyte concentration levels using the disclosed system, the method comprising (i) functionalizing probes and platforms, (ii) calibrating and setting up the system, (iii) performing protein measurement experiments, and (iv) analyzing the obtained data using an AI-based data analysis system.

[0007] Additional advantages of the disclosed methods and compositions will be set forth in part in the description which follows, and in part will be understood from the description, or may be learned by practice of the disclosed methods and compositions. The advantages of the disclosed methods and compositions will be realized and obtained by means of these elements and combinations. It should be understood that the foregoing general description and the following detailed description are merely exemplary and illustrative, and do not limit the claimed invention. Attached Figure Description

[0008] The accompanying drawings illustrate several embodiments of the disclosed methods and compositions, and together with the specification, serve to explain the principles of the disclosed methods and compositions.

[0009] Figure 1A This is a schematic diagram showing the architecture and hardware design of a nanorobot system for detecting low-concentration proteins. The main body of the system consists of a measurement module and a signal communication module. The motion of the probe platform is controlled by a motor-driven XYZ motion platform to achieve long-distance movement. For precise motion control, a three-dimensional piezoelectric element is attached to the platform. Figure 1B This is a schematic diagram showing a fabricated scaffold disk with different types of protein binding, securely mounted on an XY piezoelectric motion unit for precise measurements. The probe's motion is controlled by a Z-axis piezoelectric actuator, while the probe's feedback loop is accomplished by a PVDF film attached to the probe cantilever.

[0010] Figure 2 This is a schematic diagram illustrating the measurement principle of a multi-probe nanorobot system during the interaction between functionalized probes and captured proteins. A scaffold disk captures various types of proteins based on a first antibody attached to its surface. Each probe—a PVDF-terminal actuator—is functionalized with a specific second antibody, specifically designed to bind to its corresponding target protein. Upon detecting a rupture event, the probe converts the biochemical signal into a measurable force signal.

[0011] Figure 3A and 3B The fabricated probe with a focused ion beam is shown. Figure 3A A focused ion beam is shown fabricated at the probe tip within a scanning electron microscope. Figure 3B The high aspect ratio probe that was manufactured is shown.

[0012] Figure 4 A schematic diagram illustrating the fabrication of a scaffold disk and functionalized probes for protein measurements is shown. The scaffold disk follows a protocol for binding target protein antibodies onto mica coated with MPTMS, GMBS, and G-protein. A second antibody is linked to the probe using a PEG linker.

[0013] Figure 5The principle of recording antigen-antibody rupture events as force readouts and the construction of force images are illustrated. The left panel shows the spatial distribution of proteins on the scaffold disk; the right panel shows the force-distance curves for detecting rupture events.

[0014] Figure 6 High-resolution morphology of HCG capture disks with different protein concentrations and HCG-HCG antibody profiles is shown.

[0015] Figure 7 Histograms showing the distribution of rupture force readings at different concentrations (0-200 pg / ml) are displayed.

[0016] Figure 8 The regression curves of fracturing force versus protein concentration are shown. The range of the regression curves is 0-50 pg / ml.

[0017] Figure 9 The figure shows the imaging standard determination of HCG at different concentrations. It displays typical protein detection images at HCG concentrations of 0, 1, 5, 10, 50, and 100 pg / ml.

[0018] Figure 10 The architecture of a deep learning method based on a convolutional neural network (CNN) for obtaining protein concentration from force images is shown.

[0019] Figure 11 The architecture of the CNN regression network is shown.

[0020] Figure 12 The training results, including the inhibition curve, are shown. The test loss will be below 50%.

[0021] Figure 13 The protein readings of HCG in human waste culture medium containing embryos from the inventors are shown.

[0022] Figure 14 The force images and distribution of the target protein are shown in the waste culture medium from successful and unsuccessful pregnancies.

[0023] Figure 15 The histogram shows the protein concentration of HCG in waste culture medium from successful and unsuccessful pregnancies. Detailed Implementation

[0024] I. Definition

[0025] "Nanorobotic systems" refers to the design, engineering, and use of extremely small robotic devices—typically measured in nanometers (1 nanometer = ...). Nanorobotic systems (Nanorobotics) can perform specific tasks at the molecular or cellular level. Examples of components that can be included in a nanorobotic system include: sub-nanometer motion control units, force-sensing feedback, sensors, actuators, power supplies, control units, and / or communication systems. The motion control unit combines a high-performance piezoelectric (PZT) actuator with an optimized structural design, while an embedded real-time nonlinear control algorithm maintains accuracy at high speeds. Force-sensing feedback is obtained from a piezoelectric thin film (e.g., a piezoelectric film such as a PVDF film) deposited on the end effector and its integrated circuit, along with a pre-calibrated three-dimensional deformation-force model.

[0026] "Operationally linked" refers to the connection of at least two components in a system, allowing them to work together via a technology that includes, but is not limited to, integrated circuits, cables, Ethernet, the Internet, intranets, Bluetooth, near-field communication, WiFi, or combinations thereof. In one exemplary form, "operationally linked" refers to the functional interaction between two or more components in a system, allowing them to work together to achieve a common goal.

[0027] The term "real-time" refers to the transmission of data to the user interface of a computer-implemented method, system, tool, or device within 1, 2, 3, 4, 5, 10, 15, 20 minutes, or no more than 30 minutes, after the computer-implemented method, system, tool, or device has been used to detect the concentration of an analyte in a sample. The transmitted data may be partly based on the concentration of the analyte in the sample as generated by the processed signal produced by the computer-implemented method, system, tool, or device.

[0028] II. Composition

[0029] This document discloses a nanorobot system for quantifying low concentrations of analytes (e.g., proteins) in samples. In some embodiments, the sample is a spent culture medium, such as a culture of human embryos. This document also discloses a method for using the nanorobot system to detect and measure analytes (e.g., proteins). In some embodiments, the analyte is a key biomarker for pregnancy testing and monitoring, and for certain cancers. The disclosed system comprises a nanorobot system, a chip fabrication protocol, and / or artificial intelligence (AI) processing software, which allows for the accurate identification and quantification of analytes, such as proteins, at high resolution and sensitivity (less than 1 pg / mL). Preferably, the chip fabrication protocol is consistent with a platform fabrication protocol (e.g., a scaffold disk protocol). The disclosed nanorobot system includes a measurement module, a signal communication module, and precise sample tip positioning capabilities. The disclosed nanorobot system provides a significant improvement over existing diagnostic methods by offering a non-invasive, rapid, and highly accurate measurement platform.

[0030] In some embodiments, the system quantifies analyte concentrations between 0.1 pg / ml and 100 pg / ml, 0.1 pg / ml and 90 pg / ml, 0.1 pg / ml and 80 pg / ml, 0.1 pg / ml and 70 pg / ml, 0.1 pg / ml and 60 pg / ml, 0.1 and 50 pg / ml, 0.1 pg / ml and 40 pg / ml, 0.1 pg / ml and 30 pg / ml, 0.1 pg / ml and 20 pg / ml, 0.1 pg / ml and 10 pg / ml, or 0.1 pg / ml and 1 pg / ml. Preferably, the system quantifies analyte concentrations less than 1 pg / ml.

[0031] The disclosed system quantifies the concentration of analytes, such as proteins, in a sample. In some embodiments, the sample is spent embryo culture medium. In some embodiments, the analyte is a protein. In some embodiments, the protein is human chorionic gonadotropin (hCG), a biomarker for pregnancy and certain medical conditions, including trophoblastic diseases and some cancers. The disclosed system is a nanorobotic system that allows for the direct, label-free detection of analytes, such as proteins, with high precision and resolution. The disclosed system minimizes the risk of cross-reactivity and erroneous readings, providing clinicians and researchers with a powerful and reliable tool.

[0032] The disclosed nanorobot system includes a measurement module, a signal communication module, precise sample tip positioning, and AI-based data processing software.

[0033] The disclosed systems and methods can be more readily understood by referring to the following detailed description of specific embodiments and the examples included therein, as well as to the accompanying drawings and the description preceding and following them.

[0034] A. Measurement Module

[0035] The measurement module of the disclosed system includes a configuration for evaluating the surface morphology of molecules and a platform (e.g., a support disk) for fixing analytes for concentration quantification. In some embodiments, the configuration uses probes and cantilevered arms used in atomic force microscopy (AFM), lasers used in optical tweezers, or magnets used in magnetic tweezers.

[0036] The disclosed system includes a scaffold platform for immobilizing the analyte (e.g., protein) to be quantified and a measurement protocol. Performing analyte identification measurements involves four main steps: functionalizing the probe and platform, calibrating and setting up the nanorobotic system, conducting experiments, and analyzing the data.

[0037] 1. Cantilever and probe

[0038] In some embodiments, the measurement module of the disclosed system includes a probe. The probe of the measurement module is designed to manipulate the mechanical properties of individual molecules and determine the fracturing force applied at a specific location with high spatial resolution. In some embodiments, the probe is constructed from a commercially available cantilever, such as an aqueous cantilever, and is modified to have a suitable tip radius and / or internal tip distance.

[0039] In some implementations, the tip radius of the probe is between 10 nm and 100 nm, between 10 nm and 90 nm, between 10 nm and 80 nm, between 10 nm and 70 nm, between 10 nm and 60 nm, between 20 nm and 60 nm, between 30 nm and 60 nm, or between 40 nm and 60 nm.

[0040] In some implementations, the distance between the tips of the probes is 100 nm to 300 nm, 120 nm to 300 nm, 140 nm to 300 nm, 160 nm to 300 nm, 180 nm to 300 nm, 180 nm to 280 nm, 180 nm to 260 nm, 180 nm to 240 nm, or 180 nm to 220 nm.

[0041] In some implementations, the probe length is 50μm-300μm, 50μm-250μm, 50μm-200μm, 50μm-150μm, 100μm-150μm, 100μm-200μm, 100μm-250μm, or 100μm-300μm.

[0042] Probes are functionalized by modifying their surface or structure with molecules and / or chemical groups that bind to an analyte immobilized on a platform (e.g., a protein). In some embodiments, the molecules or chemical groups used to functionalize the probe are secondary antibodies, such as human chorionic gonadotropin (HCG) antibodies.

[0043] In some embodiments, the probe undergoes silanization to facilitate probe functionalization by attaching alkoxysilane molecules to the probe surface. In some embodiments, the alkoxysilane molecules are attached to the probe surface using a suitable silanizing agent, such as (3-aminopropyl)triethoxysilane (APTES), (3-mercaptopropyl)trimethoxysilane (MPTMS), (3-glycidoxypropyl)trimethoxysilane (GPTMS), (3-chloropropyl)triethoxysilane (CPTES), (3-methpropenoxypropyl)trimethoxysilane (MAPTMS), (3-triethoxysilylpropyl)succinic anhydride (TESPSA), or combinations thereof. Preferably, the agent used for probe silanization is APTES.

[0044] In some embodiments, the connector is used to attach the probe to the molecular and / or chemical groups of the analyte. In some embodiments, the connector is a polyethylene glycol (PEG) connector, an alkyl chain, a disulfide bond, an amide connector, an ester connector, a maleimide connector, a hydrazone connector, a thioether connector, a carbamate connector, or a connector derived from click chemistry, such as a triazole. In some embodiments, the connector is composed of a crosslinking agent. In some embodiments, the crosslinking agent is glutaraldehyde, formaldehyde, disuccinyl succinate (DSS), bis(sulfosuccinyl succinate) (BS3), ethylene glycol bis(succinyl succinate) (EGS), dithiobis(succinyl propionate) (DSP), 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC), N-hydroxysuccinyl succinyl (NHS), O,O'-bis[2-(N-succinyl-succinylamino)ethyl]polyethylene glycol, or combinations thereof. Preferably, the probe is functionalized with APTES attached to a PEG linker, which is further attached to an HCG secondary antibody.

[0045] The probes and cantilever can be made of materials suitable for AFM applications. For example, the probes and cantilever are made of silicon, silicon nitride, doped silicon, silicon oxide, aluminum, or polymers (e.g., polymethyl methacrylate) (PMMA). In some embodiments, one or more probes and cantilever are attached to each other via a probe platform. In some embodiments, the motion of the probe platform is managed by an XYZ motion platform for long-distance movement. In some embodiments, precise motion control of the probe platform is managed by three-dimensional piezoelectric elements.

[0046] 2. Platform (e.g., support plate)

[0047] In some embodiments, the measurement module of the disclosed system includes a platform (e.g., a support disk) to hold the analyte for quantification. In some embodiments, the support disk has one or more layers of material, preferably five layers.

[0048] In some embodiments, the platform (e.g., a support plate) comprises a glass layer or a mica material layer, such as muscovite, for example, A1 grade muscovite. In some embodiments, the mica material layer is coated with alkoxysilane molecules, which are attached to the surface of the mica material layer using a suitable silanizing agent. In some embodiments, the agent used for silanizing the mica material layer is (3-aminopropyl)triethoxysilane (APTES), (3-mercaptopropyl)trimethoxysilane (MPTMS), (3-glycidoxypropyl)trimethoxysilane (GPTMS), (3-chloropropyl)triethoxysilane (CPTES), (3-methacryloyloxypropyl)trimethoxysilane (MAPTMS), (3-triethoxysilylpropyl)succinic anhydride (TESPSA), trimethoxypropylsilane (TMPS), octadecyltrichlorosilane (OTS), hexamethyldisilazane (HMDS), tetraethyl orthosilicate (TEOS), or a combination thereof. Preferably, the reagent used for silanization of the mica material layer is MPTMS.

[0049] In some embodiments, the scaffold platform further comprises a protein crosslinking agent layer. The protein crosslinking agent layer is formed from any suitable protein crosslinking agent reagent. Exemplary embodiments of the protein crosslinking agent reagent include, but are not limited to, amine-amino crosslinking agents, amine-carboxyl crosslinking agents, thiol crosslinking agents, heterobifunctional crosslinking agents, or amine-thiol crosslinking agents. In some embodiments, the protein crosslinking agent reagent is an amine-to-thiol crosslinking agent, such as N-γ-maleimide butyryloxysuccinimide ester (GMBS).

[0050] In some embodiments, the scaffold platform further comprises a G protein layer containing a G protein. This layer facilitates the binding of the scaffold layer. The scaffold layer selectively captures and immobilizes the analyte to be quantified. In some embodiments, the scaffold layer is an antibody scaffold layer for capturing the analyte, such as an anti-HCG antibody (hCGab). In some embodiments, the scaffold layer is made of a first HCG antibody (e.g., a first hCGab).

[0051] Once the platform is equipped with a scaffold layer, the analyte adheres to the surface of the scaffold layer to form a complex on the platform surface. In some embodiments, the analyte in the sample is, for example, a target protein culture medium or an embryo culture medium. In some embodiments, the complex formed on the platform surface is an hCG-hCGab complex.

[0052] B. Signal Communication Module

[0053] The signal communication module of the disclosed system includes piezoelectric materials, circuits, signal detectors, and an augmented reality system.

[0054] 1. Piezoelectric materials

[0055] The signal communication module of the disclosed system includes a piezoelectric material to convert mechanical stress into a measurable electrical signal. In some embodiments, the piezoelectric material is configured in a three-dimensional piezoelectric element, which is divided into an X-piezoelectric unit positioned along the X-axis of the platform, a Y-piezoelectric unit positioned along the Y-axis of the platform, and a Z-piezoelectric unit positioned on a probe and a cantilever. In some embodiments, the XYZ piezoelectric unit also functions as an XYZ piezoelectric scanner, with all movements automatically controlled by a host computer and / or controlled by a user.

[0056] The piezoelectric material can be any suitable piezoelectric material, such as quartz, lead zirconate, lead titanate, barium titanate, zinc oxide, aluminum nitride, polyvinylidene fluoride (PVDF), lithium niobate, gallium orthophosphate, or tourmaline. Preferably, the piezoelectric material comprises PVDF.

[0057] like Figure 1A The nanorobotic system is designed for the detection of low-concentration analytes, such as proteins. Figure 1B As shown, the support platform is securely mounted on the X and Y piezoelectric motion units and serves to bind various types of proteins. A Z-axis piezoelectric actuator controls the probe's movement, while a PVDF film attached to the probe cantilever completes the feedback loop. The XYZ piezoelectric unit can also function as a scanner, with all movements controlled by the main computer.

[0058] The analyte is captured on a scaffold platform by a first antibody attached to its surface. Each probe is functionalized with a specific second antibody, allowing it to bind specifically to its corresponding target protein. The rupture event of each probe is detected individually, converting the biochemical signal into a measurable force signal. These force signals are transmitted as a voltage output via a piezoelectric material to a real-time control module connected to a signal connection board for synchronizing data acquisition and signal output. This multi-probe setup enables the simultaneous identification of different analytes (e.g., proteins) with high specificity and efficiency.

[0059] 2. Circuit

[0060] The signal communication module of this application includes a connector board and a central motherboard. In some embodiments, the connector board acts as an interface to facilitate communication between the PZT material disclosed herein, the sensor, the motor, and the central motherboard. In some embodiments, the central motherboard processes control feedback commands and analyzes data.

[0061] C. Precise sample tip positioning

[0062] The disclosed system's precise sample tip positioning involves compensation for the movement of the nanoscale entity, the probe tip, and the microenvironment of the nanoscale entity. Precise sample tip positioning is achieved through rapid scanning during operation, with the nanorobotic system continuously recalibrating its position using environmental markers.

[0063] In some embodiments, precise sample tip localization is achieved by establishing an initial background of nanoscale imaging in the environment as a baseline and continuously updating it locally based on real-time measurements. In some embodiments, the system's local scanning features utilize an adaptive scanning mode to detect new locations of analytes (e.g., proteins). The scanning pattern of the adaptive scanning mode changes according to the object being observed, with dense scan points in the region of interest and sparse scans in other regions. This adjustment is possible by measuring the height profile determined by the cantilever and functionalized probe to accurately recover the actual location of the analyte. In some embodiments, the method is capable of rapidly recovering the true location of the analyte (e.g., protein) in less than 10 ms, 20 ms, 30 ms, 40 ms, 50 ms, or 60 ms.

[0064] D. AI-based analysis system

[0065] The disclosed AI-based analysis system includes a computer-implemented system configured to analyze surface morphology data of analytes and quantify analyte concentrations. In some embodiments, the AI-based analysis system is based on deep learning, symbolic AI, rule-based systems, classical machine learning, evolutionary algorithms, swarm intelligence, reinforcement learning, fuzzy logic systems, case-based reasoning, Bayesian networks, constraint satisfaction problems, or combinations thereof. In some embodiments, the AI-based analysis system is based on deep learning, such as neural networks, like convolutional neural networks. Examples of neural networks suitable for image analysis include, but are not limited to, convolutional neural networks, AlexNet, VGGNet, ResNet, Inception Network, EfficientNet, U-net, Mask R-CNN, Vision Transformer, etc.

[0066] In some embodiments, the AI-based analysis system is configured to use atomic force microscopy (AFM) to visualize the height and fracture force of the analyte complex fixed on a substrate, and to process the data to plot the relative distribution of the visualized object by height and adhesion force.

[0067] In some embodiments, signal processing is handled by two integrated computers: a conventional interface computer dedicated to post-processing tasks, and an enhanced interface computer responsible for real-time control, enabling automated operation and human interaction via haptic devices.

[0068] III. Instructions for Use

[0069] This document also describes a method for quantifying analytes (e.g., proteins) in a sample using the disclosed system. An exemplary protocol for accurately measuring HCG concentration using the disclosed nanorobot system is as follows, detecting HCG concentration by the binding event of the HCG-HCG antibody complex: Protein G is coated onto a cleaved mica substrate to facilitate the binding of an HCG antibody scaffold layer. This layer is capable of selectively capturing HCG protein. Once the substrate is fitted with a dense antibody layer, target protein culture medium or embryo culture medium is incubated on the scaffold platform to form an HCG-HCGab complex, followed by washing away any unbound components. A second step involves fabricating a functionalized probe using a similar protocol and adding a second HCG antibody. The probe is then blocked with BSA medium to prevent nonspecific binding via PEG linkers.

[0070] In the third step, a nanorobot system is used to visualize the height and fracturing force of the protein complex anchored to the substrate, allowing the determination of the specific fracturing force applied to the functionalized probe at each location with high spatial resolution.

[0071] The final step involves processing the measurement data, where a visualization of the objects is plotted based on their relative distribution by height and adhesion force, r(h), f(h), and the number of these objects per unit area is calculated.

[0072] This system utilizes a semantic compression feedback control mechanism to simplify the recognition process by abandoning traditional feature extraction and complex calibration, thereby reducing computational load and accelerating image processing. In some embodiments, compressed sensing is a learning-based framework that modifies the sampling matrix (W), basis matrix (D), and projection matrix (Q) to reduce scan points while ensuring high-quality reconstruction, improving both sampling and reconstruction.

[0073] The disclosed systems and methods can be further understood through the following numbered paragraphs.

[0074] 1. A nanorobot system for detecting the concentration of an analyte in a sample, the system comprising:

[0075] The measurement module includes functionalized probes and a platform (e.g., a support plate).

[0076] A signal communication module includes a material capable of generating and / or transmitting one or more signals, wherein the one or more signals are optionally selected from electrical signals, electrochemical signals, optical signals, mechanical signals (e.g., derived from pressure, tensile / compressive force, acceleration, vibration, strain / deformation, displacement, and / or shear), acoustic signals, temperature signals, digital signals, and...

[0077] Sample tip positioning module (e.g., precise sample tip positioning module),

[0078] The system is operatively linked to an artificial intelligence (AI)-based data analysis system configured to interpret data including analyte-functionalized probe interaction images and / or convert the data into concentration readings.

[0079] Optionally, the AI-based data analysis system utilizes machine learning AI platforms, deep learning AI platforms (e.g., neural networks such as convolutional neural networks (CNNs)) or combinations thereof to interpret the data (e.g., analyte functionalized probe interaction images, such as protein-protein interaction images) and / or convert the data into concentration readings.

[0080] 2. The nanorobot system according to paragraph 1, wherein the nanorobot system is configured to implement a semantic compression feedback control mechanism to selectively interpret the data by simplifying the image recognition process and / or reducing the computational load.

[0081] 3. The nanorobot system according to paragraph 1 or 2, wherein the functionalized probe comprises metal, metal alloy, carbon-based material, polymer, magnetic material, semiconductor material, nucleic acid origami (e.g., DNA origami) or a combination thereof.

[0082] 4. The nanorobot system according to any one of paragraphs 1 to 3, wherein the functionalized probe comprises an alkoxysilane molecule on its outer surface, wherein the alkoxysilane molecule is (3-aminopropyl)triethoxysilane (APTES), (3-mercaptopropyl)trimethoxysilane (MPTMS), (3-glycidoxypropyl)trimethoxysilane (GPTMS), (3-chloropropyl)triethoxysilane (CPTES), (3-methacryloyloxypropyl)trimethoxysilane (MAPTMS), (3-triethoxysilylpropyl)succinic anhydride (TESPSA), or a combination thereof.

[0083] 5. The nanorobot system according to any one of paragraphs 1 to 4, wherein the functionalized probe comprises a connector, wherein the connector comprises a polyethylene glycol (PEG) connector, an alkyl chain, a disulfide bond, an amide connector, an ester connector, a maleimide connector, a hydrazone connector, a thioether connector, a carbamate connector, or a connector derived from click chemistry (e.g., triazole).

[0084] 6. The nanorobot system according to any one of paragraphs 1 to 5, wherein the functionalized probe comprises molecules and / or chemical groups bound to the analyte immobilized on the platform.

[0085] 7. The nanorobot system according to any one of paragraphs 1 to 6, wherein the platform (e.g., a support disk) comprises a mica material (e.g., a mica material layer).

[0086] 8. The nanorobot system according to any one of paragraphs 1 to 7, wherein the functionalized probe has:

[0087] (i) The tip radius is between 10 nm and 100 nm, between 10 nm and 90 nm, between 10 nm and 80 nm, between 10 nm and 70 nm, between 10 nm and 60 nm, between 20 nm and 60 nm, between 30 nm and 60 nm, or between 40 nm and 60 nm, and / or

[0088] (ii) The length is between 50-300μm, 50-250μm, 50-200μm, 50-150μm, 100-150μm, 100-200μm, 100-250μm or 100-300μm.

[0089] 9. The nanorobot system according to any one of paragraphs 1 to 8, wherein the interterminal distance of the functionalized probe is between 100 nm and 300 nm, 120 nm and 300 nm, 140 nm and 300 nm, 160 nm and 300 nm, 180 nm and 300 nm, 180 nm and 280 nm, 180 nm and 260 nm, 180 nm and 240 nm, or 180 nm and 220 nm.

[0090] 10. The nanorobot system according to any one of paragraphs 1 to 9, wherein the system is configured with an analyte concentration between 0.1 pg / ml and 100 pg / ml, between 0.1 pg / ml and 90 pg / ml, between 0.1 pg / ml and 80 pg / ml, between 0.1 pg / ml and 70 pg / ml, between 0.1 pg / ml and 60 pg / ml, between 0.1 and 50 pg / ml, between 0.1 pg / ml and 40 pg / ml, between 0.1 pg / ml and 30 pg / ml, between 0.1 pg / ml and 20 pg / ml, between 0.1 pg / ml and 10 pg / ml, or between 0.1 pg / ml and 1 pg / ml.

[0091] 11. The nanorobot system according to any one of paragraphs 1-10, wherein the signal communication module comprises one or more piezoelectric materials, circuits, or combinations thereof.

[0092] 12. The nanorobot system according to paragraph 11, wherein one or more piezoelectric materials comprise quartz, lead zirconate titanate, barium titanate, zinc oxide, aluminum nitride, polyvinylidene fluoride (PVDF), lithium niobate, gallium orthophosphate, tourmaline, or combinations thereof.

[0093] 13. The nanorobot system according to paragraph 11 or 12, wherein one or more piezoelectric materials comprise PVDF.

[0094] 14. The nanorobot system according to any one of paragraphs 11 to 13, wherein the AR system includes a scanning system (e.g., a microscopic scanning system), a real-time control module, and / or an AR user interface.

[0095] 15. The nanorobot system according to paragraph 14, wherein the real-time control module includes a first controller, a tactile device, a data acquisition board, a signal access module, and an augmentation computer.

[0096] 16. The nanorobot system according to paragraph 14 or 15, wherein the scanning system comprises a probe laser system, an XYZ piezoelectric scanner, a conventional interface computer, a second controller, or a combination thereof, optionally wherein the first controller and the second controller are the same or different.

[0097] 17. The nanorobot system according to any one of paragraphs 14 to 16, wherein the scanning system comprises an elevated microscope, a second-order inverted optical microscope, a CCD (charge-coupled device) camera, or a combination thereof.

[0098] 18. The nanorobot system according to any one of paragraphs 1-17, wherein the analyte is a protein, and optionally, wherein the protein is human chorionic gonadotropin (HCG).

[0099] 19. The nanorobot system according to any one of paragraphs 1-18, wherein the sample is waste culture medium, optionally wherein the waste culture medium is derived from an embryo.

[0100] 20. The nanorobot system according to any one of paragraphs 1 to 19, comprising a cantilever design, including a three-dimensional piezoelectric element attached to the cantilever for precise motion control of a functionalized probe.

[0101] 21. A method for detecting the concentration level of an analyte using a nanorobot system as described in any one of paragraphs 1 to 20, the method comprising measuring a signal of the interaction between the analyte and a functionalized probe on an indicator platform.

[0102] 22. The method described in paragraph 21 further includes:

[0103] Atomic force microscopy (AFM) is used to generate the height and breaking force of the analyte (e.g., protein) fixed on the platform (e.g., a support disk), and / or

[0104] The height and the fracturing force are processed to plot the relative distribution of the object generated by the height and the adhesion force.

[0105] 23. The method according to paragraph 21 or 22 further includes assessing embryo quality in in vitro fertilization (IVF) treatment by measuring the concentration of β-hCG in the waste culture medium (SCM) from the embryos and / or classifying the embryos into successful and unsuccessful pregnancy outcome groups based on their β-hCG levels.

[0106] 24. The method according to any one of paragraphs 21 to 23, wherein an adhesion force exceeding 120 pN indicates the presence of the analyte bound to the functionalized probe.

[0107] 25. The method according to any one of paragraphs 21 to 24, wherein the nanorobot system detects new locations of the analyte during the protein measurement experiment using an adaptive scanning mode.

[0108] The methods and systems described herein are further illustrated in the following examples, which are provided by way of illustration and not limitation. It should be understood that variations in the proportions of the illustrated components and substitutions of elements will be apparent to those skilled in the art and are within the scope of the disclosure. Unless otherwise stated, all parts or quantities are by weight.

[0109] Example

[0110] Example 1: Nanorobot system for recognizing ultra-low concentrations of proteins

[0111] Materials and methods

[0112] exist Figure 3A and 3B The fabrication of a high aspect ratio probe is described. The initial phase of the study involved precisely fabricating the probe using a focused ion beam (FIB) milling process to improve upon the commercially available ScanAsyst-Fluid cantilever (a commercial probe for imaging relevant samples in cells and fluids) with a resonant frequency of 70 kHz and a force constant of 0.7 N / m. The FIB parameters were carefully configured: ion beam current ranging from 10 to 50 pA, a fixed ion beam dwell time of 1.0 s, and an ion beam acceleration voltage maintained at 30 keV. Electron microscopy images of the FIB-fabricated dual probes were analyzed to determine tip characteristics. The resulting probes were characterized by a tip radius of approximately 50 nm and a tip-to-tip distance of approximately 200 nm. As confirmed by image analysis, this tip configuration was achieved post-fabrication.

[0113] The following text and Figure 4 A detailed experimental protocol for nanorobot measurement of targeted proteins in embryos is described. When preparing the base G-protein-HCGAB, firstly, glass slides were immersed in acetone for 10 minutes to remove organic impurities, followed by rinsing with dedissolved water and ethanol. The slides were then dried under a nitrogen stream. Next, at room temperature, glass slides were immersed in 2% v / v MPTMS ethanol solution for 45 minutes, thoroughly rinsed with ethanol, and dried under a nitrogen stream. Then, the slides were immersed in DMSO containing 5 mM GMBS for 30 minutes at room temperature. The slides were thoroughly rinsed with dedissolved water and dried under a nitrogen stream. Protein G was dissolved in PBS (pH 7.4) to a concentration of 100 g / mL. The slides were immersed in the protein G solution (50 µL) and incubated at room temperature for 45 minutes. The slides were then thoroughly rinsed with PBS to remove unbound protein G. The first HCGAB was dissolved to a concentration of 100 g / mL. The first HCGAB was then applied to the coated slide and incubated in a humidified chamber for 60 minutes. The slide was rinsed with PBS to remove unbound antibody, immersed in 1% BSA solution for 30 minutes for blocking at room temperature (RT), and finally rinsed with PBS.

[0114] To prepare the probe via secondary hCGab functionalization, the probe was first washed with acetone for 10 minutes.

[0115] The slides were rinsed with de-DI water, then with ethanol, and dried under a nitrogen stream. At room temperature, the probe was immersed in 10% v / v APTES solution in acetone for 60 minutes, then thoroughly rinsed with de-DI water and dried under a nitrogen stream. The probe was then immersed in 50 µL of PEG-connector (O,O′-bis[2-(N-succinimidyl-succinamido)ethyl]polyethylene glycol (100 g / mL) diluted in PBS and incubated at room temperature for 45 minutes. The probe was gently rinsed with DI water. Secondary hCGab was incubated with the probe in a humidified chamber for 45 minutes. The probe was gently rinsed with DI water and then immersed in 1% BSA solution for 30 minutes to block at room temperature. The probe was rinsed with DI water and stored in PBS solution.

[0116] To establish a standard assay, pure β-HCG was diluted to concentrations ranging from 0 to 100 μg / ml (0; 0.5; 1; 2; 5; 10; 20; 50; 100). The sensor disk was incubated with β-HCG (10 µL) at room temperature in a humidified chamber for 45 minutes, and the substrate was immersed in PBS for measurement.

[0117] The evaluation of HCG in SCM began with incubating the sensor disk with SCM medium (10 µL) at room temperature for 45 minutes, followed by rinsing the disk with DI water. The substrate was then immersed in PBS for nanorobot measurements.

[0118] Figure 5 The acquisition of binding event images or protein distribution images is described. Protein binding events are described by the rupture force values ​​of the antibody and protein. Force-distance curves are obtained in the force curve version. These curves are recorded with a moderately applied force of less than 5 nN, a ramp size of less than 2 μm, and a ramp frequency of 1 Hz. Each force-distance curve includes an approach portion and a retraction portion, where the tip approaches and leaves the disk, respectively. For each measurement, a map of 64 x 64 curves is recorded within a 5 μm x 5 μm area. The adhesive force of the rupture event is obtained from the retraction portion of the curve, which is equal to the force difference between the contact point and the location of the adhesive force peak.

[0119] Preliminary measurements show that at low concentrations (less than 10 pg / ml for 10 μl), HCG protein accumulates rapidly on the plate. Figure 6 High-resolution morphology of HCG on the scaffold disc is shown at 1 pg / ml and 10 pg / ml conditions. A significant increase in protein capture was observed with small increases in the dosage.

[0120] To establish a standard assay for protein concentration calculation, tests were set up to establish the relationship between rupture event force and protein concentration, and between rupture force image and protein concentration. In this case, pure HCG medium was used as the standard assay and sample for the dataset. The assays were performed starting from the control group (0 pg / ml), progressing to 1 pg / ml; 5 pg / ml; 10 pg / ml; 20 pg / ml; 50 pg / ml; 100 pg / ml; 200 pg / ml. Figure 7 As shown, the average force during the test varied from 21.3 pN in the control to 287.1 pN at 200 pg / ml. After obtaining the protein attachment data, as... Figure 8 As shown, an experimental regression curve was established using a regression method based on the mean and a preset protein concentration to help evaluate the accuracy and efficiency of the regression curve establishment.

[0121] In some cases, the signal communication module of this system may include an augmented reality (AR) system. The AR system may include a pair of 3D goggles for stereoscopic visual feedback to simulate nanoscale manipulation with depth information. The AR system may include three main components: a microscopic scanning system, a real-time control module including a controller, haptic devices, a signal access module, and an augmentation computer, and an AR user interface.

[0122] The microscopic scanning system may include a probe-laser system, an XYZ piezoelectric scanner, a conventional interface computer, and a controller. Optional accessories may include, such as an elevated microscope, a second-order inverted optical microscope, and a CCD (charge-coupled device) camera, providing low-resolution video of the sample and probe under optical microscopy. A real-time control module is equipped with a data acquisition board for data acquisition and signal output to the signal access module. Ethernet and UDP protocols may be used, allowing for operative linking of data and control signals between the user computer and the conventional interface computer. The AR platform uses spatial and force data collected during nanomanipulation to update the scanned images in real time. A specialized signal access module utilizes the scanner controller's output, with custom software processing the input data using specialized algorithms.

[0123] AI-based data analysis system

[0124] An AI-based data analysis system using convolutional neural networks (CNNs) was employed to interpret protein-protein interaction images and convert them into accurate concentration readings. After obtaining high-resolution images of protein binding events, the images were post-processed using the same standards to construct training data with artificial labels, such as... Figure 9 As shown. These images are then fed into a specially customized convolutional neural network to accurately estimate protein concentrations. To prepare these images for the CNN, they first undergo a series of preprocessing steps designed to enhance and normalize features important for concentration estimation. These steps include rescaling the images to a uniform size suitable for the CNN, normalizing pixel values ​​to aid the training process, and increasing the image dataset with modified versions by redistributing protein pixels among the images. Figure 10 A flowchart showing the architecture of a protein decision system is presented.

[0125] Deep learning networks are generated by solving regression problems using simple models. The architecture of the CNN model used in this study is as follows: Figure 11 As shown. To generate a single floating-point number representing the estimated protein concentration in pg / ml, the model is modified to fit an input image with dimensionality and incorporates convolutional layers that act as feature extractors equipped with varying numbers of neurons, again using the ReLU activation function. Max-pooling layers then reduce the spatial dimensionality of the feature maps, which are subsequently flattened into vectors input to the dense layer. The dimensionality of the output image from the convolutional layers is flattened into a vector of size for forwarding to the next regression input layer. The regression layer consists of three fully connected layers with 2048 hidden nodes. Since the model's output represents the estimated protein concentration (pg / ml), the final output layer is a single neuron and a linear activation function for the regression task of estimating protein concentration.

[0126] result

[0127] Figure 12 Training results with training loss are shown for evaluating training outcomes. Preliminary clinical trials have also been used to test the accessibility of the proposed analytical system. β(beta)HCG present in humanized spent culture medium (SCM) was captured using immobilized anti-HCG antibodies. To quantify βHCG molecules in specific regions, an adhesion force exceeding 120 pN indicates the presence of βHCG molecules binding to the functionalized probe. (See attached image.) Figure 13 As shown, the concentration of βHCG in 10 µl volume of spent culture medium (SCM) ranged from 0.87 pg / ml to 14.00 pg / ml. This paper discloses a linear correlation between βHCG concentrations in the 1–50 pg / ml range and the number of adhesion sites, while ELISA absorbance did not demonstrate this relationship. Further analysis included assessing βHCG levels in women undergoing IVF treatment, categorizing them into two distinct groups based on their pregnancy outcomes: successful and unsuccessful, as... Figure 14 As shown in the figure. Nanorobot detection revealed a gradual increase in βHCG in both groups. Specifically, βHCG concentration was analyzed in the SCM of individual embryos, and the levels in the successful pregnancy group ranged from 0.39 pg / ml to 4.809 pg / ml, while the levels in the unsuccessful pregnancy group ranged from 0.309 pg / ml to 2.63 pg / ml. Figure 15 The successful group showed β-HCG levels of 2.25±0.66 pg / ml and 1.38±0.42 pg / ml, demonstrating that the disclosed system can be used as an evaluation method for assessing embryo grading. Embryo quality can be assessed using the disclosed nanorobot system for in vitro fertilization (IVF) treatment by measuring the β-HCG concentration in the spent culture medium (SCM) from the embryos and classifying embryos into successful and unsuccessful pregnancy outcome groups based on their β-HCG levels.

[0128] It should be understood that, unless otherwise stated, the disclosed methods and compositions are not limited to specific synthetic methods, specific analytical techniques, or specific reagents, and therefore can be varied. It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and not for limitation.

[0129] Those skilled in the art will recognize, or be able to determine, by conventional experimentation alone, many equivalents of the specific embodiments of the invention described herein. These equivalents are intended to be covered by the appended claims.

Claims

1. A nanorobot system for detecting a concentration of an analyte in a sample, the system comprising: a measurement module comprising a functionalized probe and a platform (e.g., a scaffold disk), a signal communication module comprising a material capable of generating and / or transmitting one or more signals, the one or more signals optionally selected from the group consisting of electrical signals, electrochemical signals, optical signals, mechanical signals (e.g., derived from pressure, tensile / compressive forces, acceleration, vibration, strain / deformation, displacement, and / or shear), acoustic signals, temperature signals, digital signals, and a sample tip positioning module (e.g., a precise sample tip positioning module), wherein the system is operatively linked to an artificial intelligence (AI)-based data analysis system configured to interpret data comprising analyte functionalized probe interaction images and / or convert the data into a concentration readout, optionally, wherein the AI-based data analysis system utilizes a machine learning AI platform, a deep learning AI platform (e.g., a neural network such as a convolutional neural network (CNN)), or a combination thereof to interpret the data (e.g., analyte functionalized probe interaction images, such as protein-protein interaction images) and / or convert the data into a concentration readout.

2. The nanorobot system of claim 1, wherein, The nanorobot system is configured to implement a semantic compression feedback control mechanism to selectively interpret the data by simplifying the image recognition process and / or reducing computational load.

3. The nanorobot system of claim 1, wherein the functionalized probe comprises a metal, a metal alloy, a carbon-based material, a polymer, a magnetic material, a semiconductor material, a nucleic acid origami (e.g., a DNA origami), or a combination thereof.

4. The nanorobot system of claim 1, wherein the functionalized probe comprises an alkoxysilane molecule on an outer surface, wherein the alkoxysilane molecule is (3- aminopropyl)triethoxysilane (APTES), (3-mercaptopropyl)trimethoxysilane (MPTMS), (3-glycidyloxypropyl)trimethoxysilane (GPTMS), (3-chloropropyl)triethoxysilane (CPTES), (3-methacryloyloxypropyl)trimethoxysilane (MAPTMS), (3- triethoxysilylpropyl)succinic anhydride (TESPSA), trimethoxysilylpropylsilane (TMPS), octadecyltrichlorosilane (OTS), hexamethyldisilazane (HMDS), tetraethoxysilane (TEOS), or a combination thereof.

5. The nanorobot system of claim 1, wherein the functionalized probe comprises a linker, wherein the linker comprises a polyethylene glycol (PEG) linker, an alkyl chain, a disulfide bond, an amide linker, an ester linker, a maleimide linker, a hydrazone linker, a thioether linker, a carbamate linker, or a linker derived from click chemistry (e.g., a triazole).

6. The nanorobot system of claim 1, wherein the functionalized probe comprises a molecule and / or a chemical group that binds to the analyte immobilized on the platform.

7. The nanorobot system of claim 1, wherein the platform (e.g., a scaffold disk) comprises a mica material (e.g., a layer of Al grade white mica material).

8. The nanorobot system of claim 1, wherein the functionalized probe has: (i) a tip radius between 10 nm and 100 nm, between 10 nm and 90 nm, between 10 nm and 80 nm, between 10 nm and 70 nm, between 10 nm and 60 nm, between 20 nm and 60 nm, between 30 nm and 60 nm, or between 40 nm and 60 nm, and / or (ii) a length between 50-300 pm, 50-250 pm, 50-200 pm, 50-150 pm, 100-150 pm, 100-200 pm, 100-250 pm, or 100-300 pm.

9. The nanorobot system of claim 1, wherein the distance between tips of the functionalized probe is between 100 nm and 300 nm, between 120 nm and 300 nm, between 140 nm and 300 nm, between 160 nm and 300 nm, between 180 nm and 300 nm, between 180 nm and 280 nm, between 180 nm and 260 nm, between 180 nm and 240 nm, or between 180 nm and 220 nm.

10. The nanorobot system of claim 1, wherein the system is configured to quantify an analyte concentration between 0.1 pg / ml and 100 pg / ml, between 0.1 pg / ml and 90 pg / ml, between 0.1 pg / ml and 80 pg / ml, between 0.1 pg / ml and 70 pg / ml, between 0.1 pg / ml and 60 pg / ml, between 0.1 and 50 pg / ml, between 0.1 pg / ml and 40 pg / ml, between 0.1 pg / ml and 30 pg / ml, between 0.1 pg / ml and 20 pg / ml, between 0.1 pg / ml and 10 pg / ml, or between 0.1 pg / ml and 1 pg / ml.

11. The nanorobot system of claim 1, wherein, The signal communication module comprises one or more piezoelectric materials, a connector plate, and / or a central mother plate.

12. The nanorobot system of claim 11, wherein (i) the one or more piezoelectric materials comprise quartz, lead zirconate titanate, barium titanate, zinc oxide, aluminum nitride, polyvinylidene fluoride (PVDF), lithium niobate, gallium orthophosphate, or tourmaline, or (ii) the one or more piezoelectric materials comprise PVDF.

13. The nanorobot system of claim 1, wherein the analyte is a protein, optionally wherein the protein is human chorionic gonadotropin (HCG).

14. The nanorobot system of claim 1, wherein the sample is spent culture medium, optionally wherein the spent culture medium is from an embryo.

15. The nanorobot system of claim 1, comprising a cantilever design, comprising a three- dimensional piezoelectric element attached to the cantilever, for precise motion control of the functionalized probe.

16. A method of using the nanorobot system of claim 1 to detect concentration levels of an analyte, comprising measuring a signal indicative of interaction between the analyte and a functionalized probe on a platform.

17. The method of claim 16, further comprising: generating height and rupture force of the analyte (e.g., protein) immobilized on the platform (e.g., a holder disk) using an atomic force microscope (AFM), and / or processing the height and the rupture force to map the relative distribution of objects generated from the height and adhesion force.

18. The method of claim 16, further comprising assessing embryo quality in in vitro fertilization (IVF) treatment by measuring the concentration of beta-hCG in spent culture medium (SCM) from an embryo and / or grouping the embryo into successful and unsuccessful pregnancy outcome groups based on their beta-hCG levels.

19. The method of claim 16, wherein, An adhesion force of over 120 pN indicates the presence of the analyte in contact with the functionalized probe.

20. The method of claim 16, wherein, The nanorobot system detects new locations of the analyte during a protein measurement experiment using an adaptive scanning mode.

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