A REDOX AND ANTIOXIDANT CAPACITY MONITORING SYSTEM AND METHOD OF ACTIVITY

Abstract

The invention relates to a redox and antioxidant capacity monitoring system and study method, a high-content in-vitro platform designed for use in redox biology, toxicology, drug development, and cellular stress research, operating at physiological oxygen levels (1–8 kPa O₂) and quantitatively measuring cellular redox response and antioxidant capacity without the use of animals.

Description

1 TARIFF A REDOX AND ANTIOXIDANT CAPACITY MONITORING SYSTEM AND STUDY METHOD Technical Area 5 The invention has implications for redox biology, toxicology, drug development, and cellular stress research. designed for use in fields with physiological oxygen levels (1–8 kPa O₂) Researchers quantitatively measure cellular redox response and antioxidant capacity without using animals. a high-content in-vitro platform that measures redox and antioxidant capacity tracking. It relates to the system and working method. 10 State of the Art The assessment of drug and chemical toxicity at the cellular level is generally carried out by the OECD. standard viability tests based on guidelines (MTT, LDH, Alamar Blue, etc.) or Gene reporter systems (e.g., KeratinoSens™, LuSens, EpiSensA) are used. This Although methods measure cell death or a single signaling pathway such as NRF2, early oxidative 15 stress responses or cellular adaptation processes in real time They cannot evaluate. Furthermore, almost all in-vitro tests are performed in room air (~20 kPa O₂); Non-physiological hyperoxia conditions artificially increase ROS levels and the drug It overestimates toxicity and can misclassify drug toxicity. 20 Luciferase-based reporting systems are oxygen-dependent, which means they are particularly susceptible to oxygen scarcity. This leads to measurement errors under certain conditions (e.g., skin, tumor, nerve tissue). Furthermore, the market... Platforms typically utilize pericellular O₂ control, genetically encoded biosensors, and live organisms. It does not offer multi-parameter readings together. In other words, 25 of the in-vitro drug and cosmetic safety tests conducted to date... The majority of it is carried out in room air (~20 kPa O₂). However, most of it in the human body Tissue does not contain this level of oxygen; for example, tissues such as skin, brain, and liver contain approximately 5 It operates at around kPa O₂. Therefore, classical test environments are susceptible to reactive oxygen species (ROS). This leads to an artificial increase in toxicity and false positive results. Furthermore, existing test systems (e.g., KeratinoSens™, LuSens) only test a single biological 30 2 It measures the parameter (e.g., NRF2 activity) and the adaptive redox response of cells over time. It cannot assess responses or early stress signals. Included in the state of the art is “Emter R, Ellis G, Natsch A. Performance of a novel keratinocyte-based reporter cell line to screen skin sensitizers in vitro. Toxicol Appl In the article "Pharmacol. 2010 Jun 15;245(3):281-90.", the skin sensitization of chemicals (skin 5 the potential for creating sensitization) in cell-based (in vitro) experiments instead of animal experiments Determining this through tests is being considered. In this context, standardized and highly efficient methods are being employed. A (high-throughput) in vitro test system has been developed; the test is performed on reference chemicals. it can reliably predict the risk of skin sensitivity and is an alternative to animal testing. It has been shown that this is possible. Similarly, in the known state of the technique, 10 commonly used The KeratinoSens™ approach is also based primarily on NRF2 / ARE activation. It offers endpoint reading. However, such approaches can lead to cell death or NRF2 It may be limited to single-parameter (endpoint) measurements such as activity, and the test The conditions may not always accurately reflect the human tissue. In summary, the current solutions are: 15 • Mostly single-parameter studies, such as cell death or NRF2 activity. It provides measurement. • It does not take physiological oxygen levels (1–8 kPa O₂) into account. • Because it does not use genetic sensors, it cannot monitor intracellular dynamic changes. • Living cells do not have the capacity to perform long-term, multi-parameter measurements. 20 Consequently, these systems can lead to false positive / negative toxicity assessments, affecting human health. This leads to obtaining data far removed from its biology and / or the need for high animal use. It opens. Brief Description of the Invention The purpose of the invention is to provide applications in redox biology, toxicology, drug development, and cellular stress research. designed for use in fields with physiological oxygen levels (1–8 kPa O₂) Researchers quantitatively measure cellular redox response and antioxidant capacity without using animals. a high-content in-vitro platform that measures redox and antioxidant capacity tracking. The goal is to develop a system and working method. 3 The subject of the invention is a redox and antioxidant capacity monitoring system (Redox & Antioxidant). Capacity Tracker (R3ACT) is an animal tracking device that operates at physiological oxygen levels (1–8 kPa O₂). a quantitative measure of cellular redox response and antioxidant capacity without using It is a high-content in-vitro platform. The system measures the parameters listed below. Perform these measurements. These measurements are: 5 (i) Real-time H₂O₂ dynamics with HyPer7.2 sensor, (ii) Oxygen-insensitive NRF2 transcriptional activity as detected by the POINTER sensor, (iii) parallel to these is vitality / death monitoring. Pericellular oxygen is strictly controlled within the 1–8 kPa range during culture and reading; Multiparameter live-cell images are analyzed using machine learning algorithms. 10 Dose-response, stress threshold, and toxicity classification are reliably derived. The subject of the invention... R3ACT is a non-correcting enzyme used in the OECD TG 442D validation of HaCaT keratinocytes. From sensitizers to nanoplastics and zinc oxide used in sunscreens, this is a reference range. Suitable for comparison with chemicals. 5 kPa is preferred in an application of the invention. Basal NRF2 activity in O₂ was 15 kPa higher compared to 18 kPa O₂ used in the current technique. Low levels indicate that ambient air exaggerates cellular stress and increases the risk of false positives. R3ACT shows that it increases [human-vivo conditions]. R3ACT is scalable and better reflects human-vivo conditions. It offers a reproducible solution for oxidative stress toxicology and drug discovery. The invention describes the R3ACT system, which provides oxygen-regulated oxygen under physiological O₂ (1–8 kPa). Culture / reading, monitoring intracellular dynamic changes using devices like HyPer7.2 + POINTER 20 It reduces false positives / negatives and provides accurate dosage through sensor combination and machine learning. It produces response curves and death thresholds; thus, early screening is accelerated, costs are reduced, and human interaction is improved. A more consistent safety assessment is provided. Therefore, the subject of the invention is R3ACT The system integrates genetic sensors and controlled oxygen culture to provide accurate results. Positive / negative toxicity assessments are based on data that closely resembles human biology. 25 This ensures that no animals are used with this system and method. The R3ACT system uses genetically encoded biosensors (e.g., HyPer7.2 and POINTER) Using intracellular H₂O₂ levels and NRF2-based antioxidant response, physiological oxygen It measures in real time under certain conditions (1–8 kPa O₂). Applications of the invention: 30 4 • Drug discovery and preclinical toxicology (early identification of compounds affecting redox balance) (evaluating the effects), • Cosmetics and dermatology (sensitivity and oxidative stress tests in keratinocytes), • Biotechnology and food supplement industries (antioxidant effect verification), • Academic research (oxidative stress, adaptive responses, and intracellular signaling pathways) (analysis) is the field. The system described in the invention is compatible with existing plate readers, is scalable, and uses live cells. It is a fundamental measurement system; therefore, it is used in both research and industrial laboratories. It can be applied directly. The main purpose of this discovery is to investigate intracellular oxidative stress, redox balance, and antioxidant activity. Defense responses are reliable and highly effective under physiological oxygen conditions (approximately 1–8 kPa O₂). R3ACT (Redox & Parameters) enables the monitoring of animals in a parameterized and ethically animal-free manner. The goal is to develop a high-content measurement platform called the Antioxidant Capacity Tracker. Physiological oxygen control: Cell cultures and measurements with precision in the 1–8 kPa range. This is carried out at oxygen levels adjusted in this way. This allows the cells to resemble those of a real human being. 15 The tissue exhibits responses similar to those observed under various conditions. A combination of two genetic sensors: HyPer7.2 sensor with intracellular H₂O₂ (reactive oxygen). Antioxidant (type) levels are measured in real time using the POINTER sensor and NRF2-based sensors. Response and transcriptional activity are monitored in an oxygen-independent manner. Machine learning analysis: The obtained multi-parameter live cell images, 20 It is automatically analyzed through algorithms. Thus, dose-response graphs and stress levels are obtained. Thresholds and toxicity classifications are determined with high accuracy. Chemogenetic integration potential: The system can both measure and integrate within the same cell. controlled ROS production using chemogenetic enzymes (e.g., DAAO, stDCyD) It has the potential. This allows for the measurement of the adaptive response capacity of cells. 25 Innovations that the invention brought to the sector Drug development: The effects of oxidative stress, pH change, and redox balance on drug candidates. By identifying it at an early stage, it increases the accuracy of preclinical assessments. Cosmetics and dermatology: OECD TG 442D validation in HaCaT keratinocytes. Alternatively, it offers a testing infrastructure that is animal-free and closer to human biology. 5 Biotechnology and food supplement industry: Antioxidant formulations or redox- Suitable for testing the effects of active compounds with high accuracy. Scientific contribution: Oxygen dependence and antioxidant effects of cellular redox dynamics. This can reveal the true physiological limits of the response; this, in turn, can identify new drug targets. It contributes to its definition. 10 In these respects, the invention facilitates the use of animals in both academic and industrial research. reducing, more suitable to human biology, highly accurate, scalable and repeatable As a platform, it fills a scientific and ethical gap. Advantages of the Invention • By tightly controlling pericellular O₂ below physiological O₂ (1–8 kPa), exaggerated 15 ROS / NRF2 signals decrease, and false positives / negatives drop. • A fast, ethically compliant platform with a pet-free, high-content, and scalable interface. And cost-effective early screening is carried out. • Live, multi-parameter measurement: H₂O₂ (e.g., HyPer7.2 sensor) + NRF2 activity (e.g., POINTER sensor, independent of O₂) + viability is simultaneous. 20 • Comparison of conformity with OECD TG 442D reference chemicals (non-sensitizers) It facilitates regulatory transitions. • Improved translatability to humans: Adaptation to in-vivo conditions with tissue-like O₂ conditions. increases. The unique element of the invention is its physiological properties, which eliminate errors hidden in the ambient air. Oxygen-insensitive NRF2 + real-time H₂O₂ combination in cells By capturing redox changes before death, and thus making more accurate toxicity assessments, It is an animal-free system. In summary, the method and systems approach described in this invention provide a more accurate understanding of physiological oxygen levels. By being able to operate them under similar conditions, a more realistic redox response of the cells can be obtained. 30 6 It aims to; moreover, not to be limited to just an "endpoint" measurement. By tracking outputs over time via genetically encoded biosensors, the results are obtained individually. It supports single-cell validation. This allows... Signal differences that might be lost in the population average are reduced, and the response is optimized for the cell. The distribution / heterogeneity within the system can be revealed more reliably. 5 Explanation of the Figures Figure 1. Diagram of the workflow of the invented method. Figure 2. Functionality of stable HaCaT cell lines under physiological oxygen conditions. It is a test. Figure 3 shows the scan results and decision workflow of the R3ACT system. (A) Stable 10 Biosensors following treatment with auranofin (AF; 1 µM) in HaCaT reporting lines It is the appearance of their reactions over time. Figure 4: Microscopic verification of high-efficiency R3ACT system results: (A, B) Heat map-style plate reader layouts detect predefined IC0–IC30 concentrations. This summarizes R3ACT's high-throughput measurements across the 15 range. Figure 5. HaCaT cells expressing genetically encoded biosensors. These are fluorescence-activated cell separation (FACS) graphs. Figure 6. HaCaT cells under physiological (5 kPa) and room air oxygen conditions. It is a cell viability analysis. Figure 7. Performance of POINTER and HyPer7.2 biosensors using plate reader 20 It is a functional characterization. Figure 8. Two-way ANOVA analysis of the dose-response relationship under different O₂ conditions. Figure 9. PFOA, ZnO, and PS-NP levels in HaCaT cells under physiological oxygen conditions. These are cytotoxicity profiles. Figure 10. View of iron replacement drug screening. 25 Figure 11. Segmentation of imaging data using Cellpose. 7 Detailed Description of the Invention Under physiological oxygen conditions, cellular redox responses and complex interactions are numerous. The invention aims to enable the multimodal analysis of redox and antioxidant substances. capacity monitoring system, - at least one transgenic cell line, for example HyPer7.2 and POINTER, with at least 5 a biosensor expressing keratinocytes or cells from the target tissue, plate a plate-based cell that allows at least one cell culture medium to be inoculated onto it culture module, - the cells in question are best suited to physiological oxygen conditions at approximately 5 kPa O₂ level. adaptation for at least five days or a sufficient period specific to the cell type, and these 10 at least one oxygen species that helps stabilize cellular redox balance in the process. controlled incubator module, - determined by viability / death stains of reference compounds and test compounds. preparation in concentration ranges and multiple doses on the same cell plate at least one microdosing module that enables application to cells at these levels, 15 - measurements in compound-treated cell plates, adapted to the cells to be achieved while maintaining physiological oxygen levels and the first high-efficiency at least one oxygen-regulated plate reader that enables the acquisition of scanning signals module, - control wells of raw data obtained from the license plate reader module in question, 20 normalization taking into account cell density and basal redox levels, application of predefined statistical thresholding algorithms and compounds Classification as positive hit, negative hit, or indeterminate hit, and measurements of at least two types. The process is repeated in an independent round; the conditions found to be significant in both rounds are evaluated as positive / negative. hit, defined as an ambiguous (borderline) hit, is only meaningful in a single round. 25 At least one data processing and hit identification module that enables classification, - with the hit identification module in question, hits are identified or selected for further analysis. in wells, regulating oxygen levels to produce living cells at single-cell resolution. imaging and simultaneous intracellular H₂O₂ in the same cells a biosensor (e.g., HyPer7.2) that enables the detection of the level and NRF2 30 another sensor that enables the detection of pathway activation (for example at least one oxygen-regulated live cell imaging module (or POINTER) containing a POINTER microscope), 8 - Signal intensity, distribution pattern, and from the obtained single-cell image data. extracting temporal variation features and structured data from these features. At least one feature extraction module that enables the conversion of features into sets, - structured datasets obtained with the feature extraction module in question processing with a pre-trained machine learning model, 5 for each compound redox effect profile, antioxidant capacity and sensitizer potential determination and At least one that enables the creation and reporting of dose-response curves and decision thresholds. It includes a machine learning-based profiling and reporting module. The system described in this invention monitors intracellular oxidative status and antioxidant response simultaneously. It contains multiple genetically encoded biosensors. These biosensors are 10 It may have cytoplasmic and / or mitochondrial targeting and may affect different cellular environments. It can detect redox changes in the compartments individually. Under physiological oxygen conditions, cellular redox responses and complex interactions are numerous. To enable the modular analysis of the system described in the invention, the following study will be conducted: The method includes the following steps: 15 - The first step involves at least one transgenic cell line, for example HyPer7.2 and POINTER. keratinocytes expressing at least one biosensor or target tissue cells, through a plate-based cell culture module, at least one cell culture prepared by inoculating it into the medium and providing physiological oxygen at approximately 5 kPa O₂ level. ensuring adaptation, 20 - In the second step, adapted to physiological oxygen conditions (e.g., 5 kPa O2) reference compounds at multiple dose levels on the same plate in cells Application; measuring cell viability with viability / death stains for each compound the concentration window that does not significantly affect cell viability (preferably Identification of the IC0–IC30 range, 25 - In the third step, IC0–IC30 determined via the adapted cells in the second step. Using the concentration window, compounds under physiological oxygen conditions (5 kPa O2) screening and evaluation of R3ACT outputs within this window, - In the fourth step, the raw data obtained from a license plate reader module is normalized. and with a hit determination module, compounds can be classified as positive hits, negative hits or 30 Classification as an uncertain hit, 9 - In the fifth step, the wells identified as hits or selected for analysis are given an oxygen- and single-cell display at its resolution, - In the sixth step, the datasets obtained through imaging are processed using a pre-trained system. processing with a machine learning model, signal intensity and distribution for each compound 5 at least one of the following relating to pattern, temporal variation and cellular morphology At least one attribute that enables the conversion of the feature into structured datasets. Determined by the inference module and at least one of the features in question must be present in at least one machine. This is reported through a learning-based profiling and reporting module. Step 1 – Cell Preparation and Physiological Oxygen Adaptation Step • At least one transgenic cell line, for example, expressing HyPer7.2 and POINTER. keratinocytes or cells from the target tissue are placed in a plate-based cell culture system. and the cells in question, inside an oxygen-controlled incubator Physiological oxygen conditions at approximately 5 kPa O₂ level for at least five days or 15 adaptation to the cell type for a sufficient period of time, and during this adaptation period ensuring the stabilization of the redox balance of the cells and also the reference compounds and compounds to be tested at predetermined concentrations preparation within the intervals, Contribution of the first step: Adaptation of cells to physiological oxygen conditions (≈5 kPa O₂) 20 By providing this, a metabolic and redox state closer to that of human tissues is achieved. This is a classic approach. It produces more accurate toxicity data compared to hyperoxic cultures. The system evaluates candidate compounds through high-throughput plate-based screening and then a hybrid platform that includes verification with high-content image analysis It offers. 25 Experiments were conducted under physiological oxygen conditions (approximately 5 kPa O₂) and in room air. A comparative analysis was conducted, oxygen tension: • It significantly modulates the Nrf2 signals (received by the POINTER sensor), • It alters the shape and slope of dose-response curves, • The same compound has different toxicological / antioxidant profiles under different O₂ conditions. It provides. Therefore, the method described in this invention allows cells to adapt to physiological oxygen stress (preferably). This approach involves testing under adapted conditions (approximately 5 kPa O₂). Thanks to this, 5 that cannot be detected or are misinterpreted in measurements taken in the room air Redox and antioxidant responses are distinguishable. Step 2 – Multiple Dose Compound Administration Step • To cells adapted to physiological oxygen conditions (preferably 5 kPa O2), Reference compounds and test compounds at multiple dose levels on the same plate. application; simultaneous testing of cell viability with viability / death stains 10 measuring and, based on these measurements, determining cell viability for each compound in a meaningful way. concentration window that does not affect the level (preferably IC0–IC30 range) identification; thus ensuring that the dose-dependent biological effects of each compound are determined using the same oxygen. ensuring that it is initiated under the given conditions, Step 3 – Initial High-Throughput Screening Step Under Physiological Oxygen Conditions 15 • Compound-applied cell plates are fed into an oxygen-regulated plate reader. taking measurements at the physiological oxygen level to which the cells have adapted the performance and acquisition of initial scan signals and thus normoxic Preliminary data that more accurately represent the physiological redox response compared to measurements ensuring, 20 The contribution of the second and third steps: By keeping the oxygen pressure constant (preferably 5 kPa O2) The actual effects of drugs on the redox response are measured. This is done in room air. False positive redox signals that occur in tests are prevented. The compounds tested were at concentrations that did not significantly affect cell viability. It is evaluated within the range (preferably IC0–IC30). Thus, 25 of the artifact signals related to death are evaluated. Actual redox and antioxidant responses are detected independently. Step 4 – Normalizing License Plate Data and Identifying Hits • Raw data obtained from the plate reader, control wells, basal redox normalization taking into account predefined statistical levels The application of thresholding algorithms categorizes compounds as positive hits, negative hits, or 30. 11 Classified as an uncertain hit, and thus highly efficient but biological. a meaningful preliminary selection process, The contribution of the fourth step: Statistically analyzing positive / negative / ambiguous "hit" calls. It is determined that dozens of compounds can be tested simultaneously thanks to the system's high-performance capacity. It is possible to do so. 5 The sensor signals obtained are the minimum and maximum readings for each biosensor. The values ​​are normalized and statistically significant responses are labeled as "positive hits". It is classified as such. The invention involves analyzing the interaction between oxygen voltage and compound concentration. It was determined that the same dose produced different biological responses under different oxygen conditions. It is done. Normalization Calculation: X(i-norm) = !(#)%!(&#') !(&())%!(&#') Here; • X(i-norm): Represents each normalized reading value. 15 • X(i): Represents the raw average value of three technical repetitions. • X(max): Represents the maximum reading obtained for each biosensor. • X(min): Represents the minimum reading obtained for each biosensor. Step 5 – Oxygen-Regulated Single-Cell High-Content Imaging Step • Oxygen-regulated live 20 wells identified as hits or selected for analysis taking the cells into the imaging microscope, in the same well and at the same time Simultaneously in cells: intracellular H₂O₂ levels using the HyPer7.2 biosensor, NRF2 pathway activation at single-cell resolution using the POINTER biosensor. visualization and thus temporal and spatial analysis of multiple biological parameters obtained together as, 25 12 The contribution of the fifth step: In a single cell, both oxidative stress and antioxidant response, as well as Cell viability can be monitored; this multi-parameter approach is the most innovative feature of the R3ACT platform. It is an element. In a single-cell system: HyPer7.2 (H₂O₂ / redox dynamics) or POINTER (Nrf2 / ARE) With biosensors (activation), cytoplasmic and mitochondrial targeting can be performed, and 5 Simultaneous measurements can be taken within the same dose range. Therefore, the system described in this invention, multiple to simultaneously monitor redox status and antioxidant response It contains genetically encoded biosensors. These biosensors are preferably cytoplasmic. and / or has mitochondrial targeting and intracellular H₂O₂ signaling via the Nrf2 pathway It allows for the joint assessment of their activation. 10 Step 6 – Post-Visualization Machine Learning-Based Reporting Step • Datasets obtained through imaging are processed using pre-trained machine learning. processing with the model, redox effect profile for each compound, antioxidant by determining its capacity and creating dose-response curves and decision thresholds. It is reporting. 15 The contribution of the sixth step: Redox effect profile and antioxidant level at the single-cell level. They are automatically classified. This step increases the predictive power of the system and facilitates cross-experiment classification. It reduces variation. EXPERIMENTAL STUDIES: Figure 2 shows the functionality of stable HaCaT cell lines under physiological oxygen conditions. The test results are shown. Light gray = cells adapted to 5 kPa O₂ for 5 days; black = Cells kept in room air (~20 kPa O₂). (A) Specified cell perimeter O₂ levels Cytoplasmic HyPer7.2 after adaptation - cytoplasm (left), mitochondrial HyPer7.2 High-resolution representation of HaCaT cells expressing either (middle) or POINTER (right). (B) HyPer7.2-cytoplasm of living cell 25 after application of 100 µM H₂O₂. Display. Scale bars: basal rate (middle) and maximum response (right). Statistics: Unpaired two-tailed Student's t-test. Data are mean ± standard deviation. (C) 100 Live cell imaging of mitochondrial HyPer7.2 after µM H₂O₂ administration, Basal and maximum responses were quantitatively determined as in (B). Statistics and data The presentation is the same as (B). (D) Adaptation of POINTER to 5 kPa O₂. Sol: 0-16 days 30 13 The change in mean fluorescence (± SD) over time, compared to room air controls. Compared to: Right: after basal, 5 kPa O₂ adaptation and re-adaptation to room air O₂. Average density after adaptation. (E) Adapted to room air and 5 kPa O₂. Pointer response of cells to 1 µM auranofin (AF). Asterisks indicate between groups. shows differences, one-way ANOVA Tukey post-test (***P < 0.001). (F) Room air 5 and the viability of HaCaT cells adapted to 5 kPa O₂ throughout AF doses, TO-PRO- It was evaluated with 3 staining and flow cytometry (IC50 is shown in the graph). (N / n = 3 / 20, where N is the number of biological repeats and n is the number of cells. All error bars are ±SD. It represents. How the cells adapt to 20 kPa O2 conditions and how these conditions affect cell 10 The effect on this is explained by the data presented in Figure 2. In Figure 2 NRF2 activity and cell viability results were presented together at 20 kPa O2. At that level, the conditions did not have a significant negative effect on the cell, and experimentally... It is shown that the system can operate in this environment. Figure 3 shows the R3ACT screening results and decision workflow. (A) Stable HaCaT 15 Biosensor time following treatment with auranofin (AF; 1 µM) in reporting lines The reactions within are shown. The curves show HyPer7.2 in the cytoplasm and mitochondria. It shows their responses and the POINTER Nrf2 reporting signal over hours. Measurements were performed under room air and physiological oxygen (5 kPa O₂) conditions; The red curves show data obtained from cells adapted to 5 kPa O₂. 20 (Room air curves are also shown for comparison). The # symbol indicates 5 at the same concentration. A significant difference between kPa O₂ and room air is indicated by an asterisk (*), where 5 kPa O₂ condition is the target (red curve). This shows a significant difference between the base value and the base value (time 0) (Tukey's multiple (A) Specifically, comparison test with one-way ANOVA). Error bars represent ±SD. (B) Specific Output of the R3ACT statistical analysis pipeline created as follows: 25 in the IC0–IC30 range. (Described from viability measurements) in the form of a heat map of concentration-dependent effects. Summary. Light gray boxes represent significant HyPer (H₂O₂) responses (mitochondrial and cytosolic), dark .... Gray boxes indicate significant POINTER / Nrf2 activation, and black boxes indicate activation determined by FACS. It shows cell death. For each reading, the top lines are obtained in room air. The bottom lines show the results, and the bottom lines show the responses after adaptation to 5 kPa O₂. 30 Asterisks indicate relative statistical significance. (C) As explained in the text A decision algorithm for executing R3ACT, such as... 14 Figure 4 shows microscopic verification of high-efficiency R3ACT results: (A, B) Heat Map-style license plate reader layouts, predefined IC0–IC30 concentrations The R3ACT high-throughput measurements are summarized within this range. White / gray shaded squares, The minor undulations around the baseline are represented by colored (light gray / dark gray) squares. It shows the key result responses (light grey: HyPer7.2 / H₂O₂; light grey: 5 POINTER / Nrf2). Positive heat map results are based on the baseline condition. This was determined using Dunnett's post hoc test and one-way ANOVA. A and B are different. (C) Bar graphs show only the selected results. High-content microscopy verification performed against baseline for the conditions The diagram shows the mean ± standard deviation, and the dots represent the number of independent repetitions. This shows that the baseline and outcome conditions are one-wayly compared using Dunnett's post hoc test. The test materials presented were compared using ANOVA. perfluorooctanoic acid (PFOA; a PFAS, IC30), polystyrene nanoparticles (PS-NPs, These compounds include zinc oxide (ZnO, IC30), zinc oxide (ZnO, IC30), and salicylic acid (SA, IC10). The concentrations tested are given in Table 1. All plate reader experiments were conducted for at least 15 minutes. Two rounds were repeated, and in each round, each compound technique was examined with triple repetitions. p*<0.05, p***<0.001. ADDITIONAL EXPERIMENTAL STUDIES: Figure 5 shows cytoplasmic HyPer7 (A), mitochondria-targeted HyPer7 (B), and POINTER. Representative FACS 20 of HaCaT cells expressing the Nrf2 reporter (C) stably. Profiles are shown. For each biosensor, pre-separation cell populations are shown. (right panels) and corresponding post-segregation enriched cell populations (left panels) are presented. The separation process is used in advanced imaging and functional analysis. High-expression and homogeneous cell populations are isolated for use. It was carried out with the aim of doing so. 25 The obtained biosensor signals are the minimum and maximum values ​​determined for each biosensor. Normalized according to maximum reading values. Normalized data, repeated The measurements are evaluated by averaging them and based on predefined threshold values. The responses that remain are classified as meaningful biological responses (hits). In Figure 6 (A), under 5 kPa O₂ (light grey) or room air (black) conditions, increasing 30 showing cell viability after 24 hours of exposure to auranofine at certain concentrations Dose-response curves are given. Cell viability was determined using flow cytometry. Each panel was evaluated and normalized to untreated control groups. It represents an independent biological replicate. Data are mean ± standard deviation (SD). It has been presented as follows. (B) Cell 5 after 24 hours of exposure to increasing concentrations of three representative compounds. Dose-response curves showing viability: (left) non-sensitizing (salicylic acid, SA), (center) sensitizer (4-Methylaminophenol sulfate, Metol) and (right) hypersensitizer. (1-chloro-2,4-dinitrobenzene, CDNB) is observed. Cell viability is untreated. Data are normalized to controls and are presented as mean ± standard deviation (SD). It has been presented. 10 Within the scope of the invention, cells are designed to withstand low oxygen levels, representing physiological oxygen stress. The tests are performed by adapting the settings (preferably around 5 kPa O₂). This allows the chamber to be tested. redox and Differences in antioxidant response can be detected. The substances tested were at concentrations of 15 that did not significantly affect cell viability. They are evaluated within these ranges. In this way, signal disruptions due to cell death are excluded. This allows for the detection of true redox and antioxidant responses. Figure 7, (A) Physiological oxygen tension (5 kPa O₂; light grey) or room air conditions. (Black) Below, POINTER after administration of increasing concentrations of auranofin. It provides a measurement of the sensor response. 20 (B) HaCaT cells exposed to increasing concentrations of exogenous H₂O₂ This is the ratiometric HyPer7.2 sensor response. R² values ​​are shown for each regression. Data are presented as mean ± standard deviation (SD). An application of the invention. The “Hit score” data generated for the auranofin compound (Figure 8B) were obtained for each biosensor. Normalized based on (including 5 kPa oxygen and room air conditions). 25 Figure 8 shows the IC of the average response for a treated HaCaT cell line in each panel. It presents the representation of the value versus the curve. Curves: black = room air, light gray = 5 kPa O₂. These are adapted conditions. The “Hit scores” in Figure 8 are only for the 5 kPa oxygen condition. Below, each biosensor is normalized. Cell death (blue gradient) 16 The data is presented using direct raw values ​​(in the range of 0–100), and these data No normalization has been applied for this. Statistical analysis was performed bidirectionally using O₂ condition and compound concentration factors. This was performed using ANOVA; asterisks in the graph indicate the significance of the interaction (O₂ × (concentration) indicates. (*P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001). 5 The invention relates to the relationship between oxygen tension and the concentration of the substance being tested. By analyzing the interaction, it can be seen that the same concentration can have different biological effects under different oxygen conditions. It is shown that it can generate responses. Additional Explanation Regarding Figure 8: Oxygen-dependent dose-response of R3ACT outputs. behavior 10 Figure 8 illustrates the concentration-response relationship of biosensors based on pericellular oxygen tension. It shows that it can modulate. The responses for each compound and measurement output are the IC value. Room air (O₂; black) and physiological oxygen are correlated with the IC0–IC30 range. The conditions (5 kPa O₂; red) were compared. The presence of a significant O₂-concentration interaction (indicated by asterisks) indicates that the increasing dose is 15 that the effect is not uniform across oxygen conditions, meaning the slope of the dose-response curve and / or reveals that its shape varies between 5 kPa and room air. These interaction effects are most clearly observed in POINTER (Nrf2) signals, HyPer7.2 outputs generally indicate less or no oxygen throughout the tested range. The dependent change has not been observed. 20 Overall, this analysis examines oxygen stress in terms of redox and antioxidant response measurements. that it is an important experimental marker and tested within a non-cytotoxic window. This supports the idea that even if done correctly, it could affect the interpretation of the combined effects. Figure 9 shows the increasing levels of oxygen in HaCaT cells under conditions adapted to 5 kPa O₂. PFOA, ZnO, and polystyrene nanoparticles (PS-NP) at concentrations of 24 and 25 (from left to right). Dose-response curves showing cell viability after hours of exposure are presented. Viability The values ​​were normalized to the untreated control groups. Linear 17 IC50 values ​​obtained with non-regression analysis within each panel The data are shown. The data represent the standard deviation (SD). Figure 10, (A) Plate arrangements in heatmap format, iron sucrose (IS) and Predefined IC0–IC30 concentrations for ferric carboxymaltose (FCM) This summarizes the R3ACT high-throughput screening results obtained within the range. White / gray 5 The squares shown in color indicate levels close to the baseline and not statistically significant. The fluctuations are shown in the colored squares, which indicate meaningful "hit" responses (light gray: HyPer7.2 / H₂O₂ signaling; dark gray: POINTER / Nrf2 activation). Positive hits, basal. Using the Dunnett post hova test and one-way ANOVA with reference to the condition. It has been determined. 10 (B) Column graphs where selected hit conditions are compared only with the baseline condition. High-content microscopy verification shows (IS, IC30 = 214.29 µg / ml; FCM, IC30 = 428.57 µg / ml). Columns represent mean ± SD, and the points are independent. It shows biological replicates. Statistical analysis was performed using the Dunnett post hoc test (one-way test). This was performed using ANOVA. All plate reader experiments were conducted by at least two independent 15-person teams. The tests were performed in rounds, and each compound was technically measured in triple repetitions in each round. ****p < 0.0001. Figure 11, upper panel, shows a broad range of stable HaCaT cells expressing the POINTER biosensor. The image shows the field of view. The central panel shows the mitochondria-targeted HyPer7.2 biosensor. The lower panel expresses HaCaT cells; the lower panel expresses the cytosolically targeted HyPer7.2 variant 20 The images on the left show the raw data for each biosensor. Fluorescence data was obtained using the Cellpose algorithm, while the images on the right were obtained using the same algorithm. These represent the segmentation masks obtained. Industrial Applicability of the Invention The invention has implications for redox biology, toxicology, drug development, and cellular stress research. 25 designed for use in fields with physiological oxygen levels (1–8 kPa O₂) Researchers quantitatively measure cellular redox response and antioxidant capacity without using animals. a high-content in-vitro platform that measures redox and antioxidant capacity tracking. It relates to the method and is applicable to industry. 18 The developed R3ACT platform is for cell-based drug efficacy analysis and toxicity testing. It has been optimized and is a standard process used especially in drug development processes. It is fully compatible with well plate readers. In this respect, the platform is suitable for research. in laboratories as well as directly in the R&D units of pharmaceutical and biotechnology companies It is available. This platform is used by biotechnology companies, the cosmetics industry, and antioxidant companies. 5 also integrates into the industry through testing services or licensing with food supplement manufacturers. It can be done. The invention is not limited to the above descriptions; a person skilled in the field can easily create the invention. It can present different applications. These are the claims of the invention and the protection sought. should be evaluated within this scope. 10 20 30

Claims

19 REQUESTS 1. Cellular redox responses and compound effects under physiological oxygen conditions to enable multimodal analysis, - at least one transgenic cell line, for example HyPer7.2 and POINTER, a biosensor expressing keratinocytes or cells belonging to the target tissue, plate 5 a plate-based cell that allows at least one cell culture medium to be inoculated onto it culture module, - the cells in question are best suited to physiological oxygen conditions at approximately 5 kPa O₂ level. adaptation for at least five days or a sufficient period specific to the cell type, and this at least one oxygen-10 that helps stabilize cellular redox balance in the process controlled incubator module, - determined by viability / death stains of reference compounds and test compounds. preparation in concentration ranges and multiple doses on the same cell plate at least one microdosing module that enables application to cells at these levels, - Measurements in compound-treated cell plates, adapted to the 15 cells to be achieved while maintaining physiological oxygen levels and the first high-efficiency at least one oxygen-regulated plate reader that enables the acquisition of scanning signals module, - control wells of raw data obtained from the license plate reader module in question, normalization taking into account cell density and basal redox levels, 20 application of predefined statistical thresholding algorithms and compounds Classification as positive hit, negative hit, or indeterminate hit, and measurements of at least two types. The process is repeated in an independent round; the conditions found to be significant in both rounds are evaluated as positive / negative. a hit is defined as an ambiguous (borderline) hit, where the conditions are meaningful only in a single round. at least one data processing and hit identification module that enables classification, 25 - with the hit identification module in question, hits are identified or selected for further analysis. in wells, regulating oxygen levels to produce living cells at single-cell resolution. imaging and simultaneous intracellular H₂O₂ in the same cells a biosensor that enables the detection of the level (e.g., HyPer7.2) and NRF2 another sensor that enables the detection of pathway activation (e.g., 30 at least one oxygen-regulated live cell imaging module (or POINTER) containing a POINTER microscope), - Signal intensity, distribution pattern, and from the obtained single-cell image data. extracting temporal variation features and structured data from these features. At least one feature extraction module that enables the conversion of features into sets, - structured datasets obtained with the feature extraction module in question processing with a pre-trained machine learning model, 5 for each compound redox effect profile, antioxidant capacity and sensitizer potential determination and At least one that enables the creation and reporting of dose-response curves and decision thresholds. by including a machine learning-based profiling and reporting module A characterized redox and antioxidant capacity monitoring system.

2. Cellular redox responses and compound effects under physiological oxygen conditions 10 to enable multimodal analysis, • The first step involves selecting at least one transgenic cell line, for example HyPer7.2 and POINTER. including at least one biosensor expressing keratinocytes or target tissue cells, through a plate-based cell culture module, at least one cell culture by inoculating it into the medium and providing physiological oxygen at approximately 5 kPa O₂ level 15 ensuring adaptation, • In the second step, adapted to physiological oxygen conditions (preferably 5 kPa O2) reference compounds at multiple dose levels on the same plate in cells The application involves measuring cell viability with viability / death stains for each compound. The concentration window that does not significantly affect cell viability is 20 (preferably within the IC0–IC30 range) • In the third step, IC0–IC30 determined from the adapted cells in the second step. Using the concentration window, compounds under physiological oxygen conditions (5 kPa O2) screening and evaluation of R3ACT outputs within this window, • In the fourth step, the raw data obtained from a license plate reader module is 25 normalization and a hit determination module for compounds, positive hits, negative hits or classified as an uncertain hit, • In the fifth step, one of the wells identified as hits or selected for analysis and imaging at single-cell resolution, 30 • In the sixth step, the datasets obtained through imaging are processed using a pre-trained system. processing with a machine learning model, signal intensity for each compound, the most important aspects include distribution patterns, temporal variation, and cellular morphology. at least one feature that enables the conversion of a few features into structured datasets 21 Determined by the feature extraction module and at least one of the features in question must be present in at least one instance. through a machine learning-based profiling and reporting module a redox and is characterized by including the reporting work steps. Antioxidant capacity monitoring method. 3.5 - The first step involves at least one transgenic cell line, for example HyPer7.2 and POINTER. expressing keratinocytes or cells from the target tissue, plate-based cells the cells are inoculated into a culture system and placed in an oxygen-controlled incubator. inside, physiological oxygen conditions at approximately 5 kPa O₂ level for at least five days or adaptation to the cell type for a sufficient period of time, and this adaptation 10 ensuring the stabilization of the redox balance of the cells during this period and also reference compounds and compounds to be tested at predetermined concentrations preparation within the intervals, - In the second step, cells adapted to physiological oxygen conditions (e.g., 5 kPa O2), Reference compounds and test compounds at multiple dose levels on the same plate 15 application; simultaneous testing of cell viability with viability / death stains measuring and, based on these measurements, determining cell viability for each compound in a meaningful way. concentration window that does not affect the level (preferably IC0–IC30 range) identification; thus ensuring that the dose-dependent biological effects of each compound are determined using the same oxygen. ensuring that it is initiated under the conditions, 20 - In the third step, the compound-applied cell plates are placed in an oxygen-regulated plate. the reader receives the measurements, the physiological oxygen to which the cells have adapted to be carried out at this level and the initial scan signals to be obtained and thus Preliminary measurements that more accurately represent the physiological redox response compared to normoxic measurements. data provision, 25 - In the fourth step, the raw data obtained from the license plate reader is checked. wells should be normalized taking into account basal redox levels, beforehand. The application of defined statistical thresholding algorithms results in positive hits for compounds. Classified as a negative hit or uncertain hit, and thus highly efficient but Performing a biologically meaningful preliminary screening, 30 - In the fifth step, the oxygen levels of the wells identified as hits or selected for analysis... regulated live cell imaging by taking them into the microscope, in the same well and 22 Simultaneously in the same cells: intracellular H₂O₂ levels were measured using the HyPer7.2 biosensor. NRF2 pathway activation at single-cell resolution using the POINTER biosensor. visualization and thus temporal and spatial analysis of multiple biological parameters obtained together, - In the sixth step, the datasets obtained through imaging are combined with a pre-trained 5 redox effect profile for each compound, processed with machine learning model, Determination of antioxidant capacity and dose-response curves and decision thresholds. It is the creation and reporting of this information. A method like the one in claim 2, characterized by including the steps. 15 25

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