A method, system, device, medium and application for constructing a diagnostic model for male infertility

Abstract

This invention discloses a method, system, device, medium, and application for constructing a diagnostic model for male infertility, belonging to the fields of male infertility diagnosis, drug screening, and assisted reproductive technology. In this invention, by simultaneously and quantitatively analyzing the pH value, mitochondrial G-quadruplex structure level, and β-galactosidase activity within a single sperm cell, and integrating routine clinical sperm testing parameters and age, a high-precision diagnostic model for male infertility and a drug screening system are established, providing a reference for assisted reproduction to meet practical needs.

Description

Technical Field

[0001] This invention relates to a method, apparatus, device, medium, and application for constructing a diagnostic model, specifically to a method, apparatus, device, medium, and application for constructing a diagnostic model for male infertility based on multiple fluorescent probes, belonging to the fields of male infertility diagnosis, drug screening, and assisted reproductive technology. Background Technology

[0002] Male infertility affects approximately 10-15% of couples of reproductive age worldwide, with male factors accounting for about half of these cases. Currently, clinical practice routinely relies on semen analysis recommended by the World Health Organization to assess basic parameters such as sperm concentration, motility, and morphology. However, these parameters cannot reveal intrinsic functional defects in sperm, such as mitochondrial dysfunction, intracellular pH imbalance, aging state, and genomic instability.

[0003] Although existing technologies such as CN112014367A utilize the AuNPs1-2 pH probe to detect intrasperm pH values ​​to assist in identifying the causes and pathogenesis of infertile male patients; CN118126057A uses the compound RCPH as a ratiometric pH probe for precise quantitative detection of intrasperm pH; and CN116256346A uses the level of mitochondrial DNA G-tetramer in sperm as a reference indicator for semen analysis and applies it to male infertility detection products, providing an effective theoretical reference for male infertility in sperm pathophysiology, existing technologies lack means to simultaneously quantify multidimensional functional biomarkers, resulting in limited diagnostic accuracy and difficulty in providing personalized treatment based on the underlying cause.

[0004] Therefore, developing a technology that can comprehensively assess sperm function and guide precise diagnosis and targeted drug screening is of great clinical significance. Summary of the Invention

[0005] The aim is to provide a method, system, device, medium and application for constructing a diagnostic model for male infertility, in order to solve the problem that the existing technology lacks the means to simultaneously quantify multidimensional functional biomarkers of sperm cells, resulting in low accuracy of the male infertility risk index, which cannot effectively provide doctors with a theoretical basis and thus cannot effectively change the fertility outcome. To achieve the above technical objectives, the following technical solution is proposed: The primary objective of this technical solution is to propose a method for constructing a diagnostic model for male infertility, comprising: The parameters of the sperm samples from clinically tested individuals were obtained, including the pH value of a single sperm cell, the level of mitochondrial G-quadruplex structure, and the activity of β-galactosidase; and the parameters of pHi, ln(mtG4s), and ln(β-gal) were obtained by calculation. The obtained pHi, ln(mtG4s), and ln(β-gal) were combined with routine clinical sperm testing parameters and age of clinically tested individuals to construct a nomogram diagnostic model through multivariate logistic regression. Based on the obtained nomogram diagnostic model, the parameters of the sperm samples from the clinical test subjects are substituted to obtain the total score and infertility risk index.

[0006] Then, doctors can refer to the obtained total score and infertility risk index as a basis for the sperm samples of clinical candidates, thereby providing theoretical support for assisted reproduction, such as: If the infertility risk index is >0.5, it indicates that the clinical test subject has an infertility risk, and it is determined that the sperm sample may have come from an infertile man (i.e., the clinical test subject is an infertile man). If the infertility risk index is ≤ 0.5, it indicates that the infertility risk of the clinical test subject is low, and the sperm sample is determined to be likely from a fertile male (i.e., the clinical test subject is a fertile male).

[0007] Furthermore, in simplified application scenarios where a complete diagnostic model has not yet been established, the 95% confidence intervals of three indicators—pHi, ln(mtG4s), and ln(β-gal)—for fertile males are used as reference ranges. If any one of these parameters in the sperm sample of the clinical test subject exceeds this range, it is judged as abnormal sperm function, indicating that the clinical test subject is an infertile male; conversely, it is judged as normal sperm function, indicating that the clinical test subject is a fertile male.

[0008] Furthermore, regarding the acquisition of sperm sample parameters, it should be noted that the parameters of both clinically tested and clinically prospective sperm samples were obtained using flow cytometry. The activation and detection channel settings are as follows: An RCPH probe (pH ratio) was used for excitation at 405 nm, and fluorescence intensities at detection wavelengths of 465 nm and 525 nm were simultaneously acquired. The ratio R = I was calculated. 525 / I 465 Substitute the values ​​into the human sperm pH standard curve to calculate the intracellular pH value of sperm cells, thus obtaining the intracellular pH value (pHi). The MAPQ probe (mtG4s) was used: excited at 488 nm, detected at 660-720 nm, and the fluorescence intensity was obtained to quantify the level of mitochondrial G-quadruplex. After taking the natural logarithm, ln(mtG4s) was obtained. The Si-β-gal-P probe (β-galactosidase) was used: excitation at 543 nm, detection wavelength at 640-680 nm, fluorescence intensity was obtained, β-galactosidase activity was quantified, and ln(β-gal) was obtained after taking the natural logarithm. In this study, the fluorescence intensity of the RCPH probe, MAPQ probe, and Si-β-gal-P probe was detected by flow cytometry. The independent signals of the RCPH probe, MAPQ probe, and Si-β-gal-P probe were obtained by spectral unmixing. Then, the three parameters obtained were used individually or in combination to evaluate sperm function status. Before detection, sperm samples were incubated with probe sets (RCPH probe final concentration 4-6 μM, MAPQ probe final concentration 1-3 μM, Si-β-gal-P probe final concentration 0.5-1.5 μM) for 30 min. After incubation, the samples were washed once and resuspended in PBS for flow cytometry detection. At least 10,000 sperm were collected from each sample. The structural formula of the RCPH probe is as follows: ; The structural formula of the MAPQ probe is as follows: ; in, ; The structural formula of the Si-β-gal-P probe is as follows: .

[0009] Furthermore, the human sperm pH standard curve is: R = 4.202 × pH value - 21.31, R 2 = 0.9859.

[0010] Furthermore, the routine clinical sperm testing parameters include sperm concentration, sperm count, total motility, forward motility, LIN, STR, WOB, VAP, VSL, VCL, ALH, BCF, sperm volume, and DFI.

[0011] Furthermore, the construction of the nomogram diagnostic model includes a model queue, a variable score (points) calculation formula, and a total score to risk conversion formula; 1) Model queue: Training queue (n=56): used to fit model parameters and establish diagnostic equations; Independent validation queue (n=74): Used for external validation to evaluate the model's generalization ability.

[0012] 2) Formula for calculating variable scores: The following are the calculation formulas for the scores of each variable obtained by fitting the training queue, which are used to calculate the total score for each sample;

[0013] 3) Total Score and Risk Conversion Formula: Total score = Σ (scores for each variable); The risk conversion formula is: 0.094594854 × total score - 26.528786669 = 0.094594854 × Σ (scores of each variable) - 26.528786669, which gives the infertility risk index.

[0014] The second objective of this technical solution is to propose a diagnostic model construction system for male infertility, comprising: an acquisition module, a model construction module, a calculation module, and a testing module; The acquisition module is used to acquire the detection parameters of sperm samples from clinically tested individuals, routine clinical sperm testing parameters, and age, and to obtain the indicator parameters through calculation. The model building module is used to construct a nomogram diagnostic model based on the index parameters of clinically tested sperm samples, routine clinical sperm testing parameters, and age, through multi-factor logistic regression. The calculation module is used to calculate the infertility risk index of clinical test subjects by combining the index parameters of sperm samples from clinical test subjects, routine clinical sperm testing parameters, and age through a nomogram diagnostic model. The diagnostic module compares the infertility risk index with 0.5 to indicate whether the clinically tested individual is at risk of infertility.

[0015] Furthermore, when the acquisition module acquires the index parameters of the sperm samples from clinically tested individuals, the kit used includes: an RCPH probe with a final concentration of 4–6 μM, a MAPQ probe with a final concentration of 1–3 μM, and a Si-β-gal-P probe with a final concentration of 0.5–1.5 μM. In addition, it should be noted that the index parameters of the sperm samples from the clinical test subjects on which the calculation module is based are also obtained through testing using this kit.

[0016] Furthermore, the acquisition module uses flow cytometry and ELISA (enzyme-linked immunosorbent assay) methods to obtain the index parameters of clinically tested sperm samples. Similarly, it should be noted that the index parameters of the clinically tested sperm samples used by the calculation module are also obtained through these detection methods.

[0017] Furthermore, the judgment criteria of the diagnostic module are as follows: If the infertility risk index is >0.5, it indicates that the clinical test subject has an infertility risk, and it is determined that the sperm sample may have come from an infertile man (i.e., the clinical test subject is an infertile man). If the infertility risk index is ≤ 0.5, it indicates that the infertility risk of the clinical test subject is low, and the sperm sample is determined to be likely from a fertile male (i.e., the clinical test subject is a fertile male).

[0018] The third objective of this technical solution is to propose: a device for constructing a diagnostic model for male infertility, including a memory and a processor; Memory, used to store programs; A processor is used to execute the program to implement the steps of the method for constructing a diagnostic model for male infertility as described above.

[0019] The fourth objective of this technical solution is to propose a readable storage medium storing a computer program, which, when executed by a processor, implements the various steps of the method for constructing a diagnostic model for male infertility as described above.

[0020] The fifth objective of this technical solution is to propose the application of the diagnostic model construction method for male infertility as described above in the screening of compounds that improve sperm function.

[0021] Furthermore, the application includes: before obtaining the detection parameters of the sperm sample, co-incubating the test compound with the sperm in the sperm sample, and then monitoring the changes of three parameters: pHi, ln(mtG4s) and ln(β-gal), and screening for compounds that can increase pHi, decrease ln(mtG4s) and / or decrease ln(β-gal); The sixth objective of this technical solution is to propose a drug screening system, including a diagnostic model construction system for male infertility.

[0022] Furthermore, the drug screening system is based on a diagnostic model construction system for male infertility, constructing a multi-parameter high-throughput screening platform, using sperm cell intracellular pH (pHi), mitochondrial G-quadruplex levels (mtG4s), and β-spermia as parameters. β-galactosidase The activity of β-gal is a functional indicator. After co-incubating the test compound with sperm in sperm samples, the changes of three parameters, pHi, ln(mtG4s) and ln(β-gal), are simultaneously detected by flow cytometry or ELISA. Compounds that can increase pHi, decrease ln(mtG4s) and / or decrease ln(β-gal) are screened. The drug screening system monitors luteolin, 10 The effects of compounds such as hydroxycamptothecin on the fertilization outcomes of frozen and thawed mouse sperm were investigated. Subsequently, 10 compounds were successfully screened from 45 natural products. Hydroxycamptothecin and luteolin can both significantly improve sperm mitochondrial function, increase fertilization rate, and improve embryo development quality in vitro, thus providing a direct technical means for the screening of compounds to improve sperm function and for assisted reproductive treatment.

[0023] The seventh objective of this technical solution is to propose the application of the MAPQ probe in the preparation of a reagent for detecting the structure of sperm mitochondrial G-quadruplexes. Specifically, this includes the application of the MAPQ probe alone in the detection of clinical sperm samples, and the use of the MAPQ probe for the detection of mtG4 levels in clinical sperm, with mtG4 serving as a clinical biomarker. Flow cytometry is used to detect clinical samples. The MAPQ MFI is used as a diagnostic indicator to predict fertility outcomes in older men (≥35 years of age).

[0024] In this technical solution, the index parameters of sperm samples from clinically tested individuals and sperm samples from individuals to be tested in the clinical setting are obtained using the same reagent kits and detection methods. In drug screening, sperm samples are collected from infertile men in clinical trials and / or patients awaiting clinical trials. If the sperm sample comes from an infertile man in a clinical trial, the infertile man in a clinical trial can be directly used based on the drug screening results, i.e., based on his previous medication and his willingness, he can then choose to undergo drug screening again. If the sperm sample comes from a patient awaiting clinical trials, once the patient is determined to be infertile, personalized medication guidance will be provided directly based on his drug screening results.

[0025] The beneficial technical effects of adopting this technical solution are as follows: I. In this invention, through data acquisition, data processing, and modeling techniques, simultaneous quantitative data collection and analysis are achieved for pH value, mitochondrial G-quadruplex structure level, and β-galactosidase activity within a single sperm cell. Then, by integrating routine clinical sperm testing parameters, age, and other multidimensional clinical data, a high-precision intelligent analysis model for male fertility status—a nomogram diagnostic model—is constructed through algorithm screening and feature training. Simultaneously, a corresponding intelligent drug screening analysis system—a drug screening system—is also constructed. Through multidimensional data fusion and algorithm modeling, the accuracy and efficiency of fertility-related biological data analysis are improved. This provides standardized and intelligent data references for assisted reproductive technology assessment and fertility intervention drug development and screening, filling the gap in existing intelligent fertility assistance analysis technologies and meeting the industry's intelligent application needs. Second, this invention is the first to combine routine clinical sperm testing parameters and age with multi-probe detection indicators (pH value in a single sperm cell, mitochondrial G-quadruplex structure level, and β-galactosidase activity) of clinically tested individuals to construct a diagnostic model for male infertility. The AUC reached 0.93, which is significantly better than the model constructed using only routine clinical sperm parameters (AUC is 0.87). That is, the diagnostic model in this invention can more accurately predict the risk of male infertility. Furthermore, the constructed diagnostic model has no significant impact on sperm motility and is applicable to clinical samples and assisted reproductive laboratories, providing a new tool for the study of the mechanisms of male infertility and personalized treatment. Third, this invention provides a probe set including RCPH probe, MAPQ probe and Si-β-gal-P probe, which for the first time achieves the simultaneous quantification of three key functional indicators (pH value, mitochondrial G-quadruplex structure level and β-galactosidase activity) in a single sperm, with a large amount of information and high accuracy. Compared to the TPE-mTO probe previously developed by the inventors' team (Yu KK, Li K, He HZ, Liu YH, Bao JK, Yu XQ. A label-free fluorescent probe for accurate mitochondrial G-quadruplex structures tracking via assembly hindered rotation induce demission. Sensors and Actuators B-Chemical 2020; 321.; CN116256346A), the TPE-mTO probe is excited at 488nm, with an absorption range around 525nm, resulting in high background fluorescence intensity. After prolonged incubation, it may mis-stain the nucleus and has the defect of overlapping spectra with various probes. In contrast, the MAPQ probe is excited at 488nm, with an absorption range in the near-infrared region, resulting in a cleaner staining background and better mitochondrial staining specificity. The combined use of RCPH probe, MAPQ probe and Si-β-gal-P probe, co-stained, can achieve multi-probe combination to predict male fertility outcomes; IV. This invention can be applied to high-throughput drug screening, and has successfully screened 10-hydroxycamptothecin and luteolin from 45 natural products. It has been verified that these products can improve sperm mitochondrial function and increase IVF fertilization rate and embryo quality. V. The MAPQ probe used in this invention can be used alone or in combination with other probes. When used alone, the ROC curve (receiver operating characteristic curve) shows an AUC of 84.69% for predicting male infertility outcomes. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the probe assembly route and sensing mechanism in this invention (wherein, A shows the structure and response mechanism of the RCPH probe for detecting intracellular pH in sperm cells; B shows the structure and response mechanism of the Si-βgal-P probe for detecting sperm β-galactosidase activity; C shows the structure and response mechanism of the MAPQ probe for detecting sperm mitochondrial G-quadruplex level). Figure 2The diagram shows the results of establishing and optimizing the multiplex probe staining protocol in this invention (where A is a schematic diagram of the experimental workflow, showing the optimal emission spectra of each probe obtained by full-spectrum flow cytometry after human sperm is stained with the multiplex probe kit; B is a diagram showing the optimized concentration results of each probe in the multiplex probe kit for human sperm, showing that the optimal working concentrations of RCPH, MAPQ and Si-βgal-P are 5 μM, 2 μM and 1 μM, respectively). Figure 3 The diagram shows the results of concentration optimization and validation of the multiple probes in mouse sperm in this invention (where A shows the optimal working concentrations of RCPH, MAPQ, and Si-βgal-P as 20 μM, 0.5 μM, and 5 μM, respectively; B shows the fluorescence response of the MAPQ probe in mouse sperm under different treatment conditions (TMPyP4 and H2O2 treatments significantly increased); C shows the standard curve for pH quantification in mouse sperm cells, with a linear regression equation of y = 2.368x - 11.69, R...). 2 = 0.9681); Figure 4 The figures show the functional verification and quantitative application results of the multi-probe group in this invention (where A is the MAPQ channel detection result, showing the changes in human sperm mtG4s levels under different treatment conditions (KCl, PDS, TMPyP4, and H2O2 treatments significantly increased, while spermidine treatment decreased); B is the fluorescence response diagram of the RCPH probe under different pH conditions; C is the standard curve for intracellular pH quantification in sperm cells, with the linear regression equation being y = 4.202x - 21.31, R... 2 = 0.9859; Figure D shows the RCPH channel detection results, indicating the regulatory effect of ZnCl2 and glutamine treatment on sperm pHi; Figure E shows the Si-βgal-P channel detection results, indicating the changes in sperm β-gal activity after H2O2-induced aging; Figure F shows the evaluation results of the effect of multi-probe staining on sperm motility, showing no significant difference between the staining group (MIX) and the control group (CTL). Figure 5 The diagram shows the construction and validation results of the male infertility diagnostic model in this invention (where A is a schematic diagram of the detection model in the training cohort (hospital 1, n=56) and the external cohort (hospital 2, n=74); B is the univariate logistic regression ROC curve of each individual predictor; C is the prediction curve of the traditional multivariate logistic regression model; and D is the prediction curve of the multivariate logistic regression model integrating pHi, mtG4s levels, and β-gal activity). Figure 6 This is a multivariate logistic regression nomogram in this invention, showing the prediction models of the training cohort (with / without probes) and the validation cohort (with / without probes), respectively. Figure 7 The following figures represent further validation results of the diagnostic model in this invention (where A is the clinical impact curve (decision curve), showing that the integrated model has higher net benefits over a wider threshold range; B is the calibration curve, showing that the predicted probability of the integrated model is in better agreement with the actual observation results; C is the precision-recall curve, showing that the integrated model has a higher AUC value). Figure 8 The results of high-throughput screening of natural products based on multiprobe sets in this invention are shown in the figure (where A is a schematic diagram of the process of high-throughput drug screening using an enzyme-linked immunosorbent assay (ELISA) reader and multiprobe sets; B is a heatmap of the screening results of 45 natural products on sperm pHi, mtG4s level and β-gal activity, 10-hydroxycamptothecin (10-HCPT) increases pHi, while luteolin decreases mtG4s level and β-gal activity). Figure 9 The diagram shows the validation results of the candidate compounds in human and mouse sperm (where A is the flow cytometry validation of the regulatory effects of 10-HCPT and luteolin on pHi, mtG4s levels and β-gal activity in human sperm (10 μM, 1 h), showing that 10-HCPT significantly increased pHi and luteolin significantly decreased mtG4s levels and β-gal activity; B shows the regulatory effects of 10-HCPT and luteolin on the corresponding indicators in mouse sperm among the five compounds, with consistent results; C shows the TMRE staining results, showing the effects of 10-HCPT and luteolin on the mitochondrial membrane potential of sperm from patients with asthenospermia, both of which significantly enhanced the TMRE fluorescence intensity). Figure 10 The following diagram shows the functional verification results of the candidate compounds in this invention on sperm fertilization potential and embryonic metabolic status (wherein, AB are FLI analysis results, showing the effects of PDS treatment, luteolin or 10-HCPT treatment on the autofluorescence intensity of reduced nicotinamide adenine dinucleotide phosphate NADPH, flavin adenine dinucleotide FAD and lipofuscin in mouse sperm-derived embryos; C is the result of IVF using cryopreserved-revived mouse sperm, showing the fertilization rate and embryonic development rate of different treatment groups; D is a representative FLI micrograph showing the metabolic status of embryos in different treatment groups). Figure 11 This is a histogram showing the number of clinical samples and the results of MAPQ flow cytometry staining in this invention. Figure 12 The MAPQ staining statistics and ROC curve of the clinical samples in this invention are shown (AUC=0.847). Detailed Implementation

[0027] The present invention will be further described below through specific embodiments, but this is not a limitation of the present invention. Those skilled in the art can make various modifications or improvements based on the basic idea of ​​the present invention, but as long as they do not depart from the basic idea of ​​the present invention, they are all within the scope of the present invention.

[0028] Unless otherwise specified, the experimental methods used in the following examples are conventional methods; unless otherwise specified, the experimental materials used in the following examples are all purchased from conventional biochemical reagent suppliers.

[0029] In the embodiments described below, the studies involved were approved by the Ethics Committee of West China Second Hospital, Sichuan University, and each participant signed an informed consent form. The inclusion and exclusion criteria used were selected according to the guidelines of the World Health Organization (WHO).

[0030] Specifically, for the RCPH probe, Si-β-gal-P probe, and MAPQ probe involved, preparation methods and characterization methods are proposed respectively: I. Probe Synthesis RCPH Probe (Ratio-Rating pH Probe): A ratio-Rating pH probe, RCPH, based on a hemicyanine structure, was synthesized using existing techniques. The synthetic route mainly included: reacting 2,3,3-trimethyl-3H-indole with iodoethane to generate a quaternary ammonium salt intermediate; subsequently, condensing 4-diethylaminosalicylic acid with a malonic acid derivative to obtain a hemicyanine precursor; condensing both under piperidine catalysis, followed by column chromatography purification to obtain the target compound, RCPH. The structure was confirmed to be correct by high-resolution mass spectrometry and 1H / 1C NMR spectroscopy (e.g., ...). Figure 1 (A) Si-βgal-P (β-galactosidase probe): Designed and synthesized based on the silirodamine platform. The synthetic steps included: synthesizing a silioxane core and introducing amino reaction sites; linking β-galactose to the silioxane core via a glycosidic bond; and obtaining the target probe through deprotection and column chromatography purification. The purity was confirmed by mass spectrometry and nuclear magnetic resonance (HPLC) to be ≥95%. Figure 1 (Middle B) MAPQ (mitochondrial G-quadruplex probe): The near-infrared probe MAPQ was designed and synthesized based on a novel purine platform. Synthetic route: Using 6-chloropurine as a starting material, a phenylethylpiperazine side chain and a styrene group were sequentially introduced to construct a D-π-A structure; the target compound MAPQ was obtained by column chromatography purification. The correct structure was confirmed by high-resolution mass spectrometry and 1H / 1C NMR spectroscopy (e.g., ...). Figure 1 (C)

[0031] II. Characterization of the photophysical properties of each probe The RCPH, Si-β-gal-P, and MAPQ probes were dissolved in the same PBS buffer (containing 0.1% DMSO, pH 7.4), and their spectral properties were determined using a fluorescence spectrophotometer: RCPH had a maximum excitation wavelength of 405 nm and its emission spectrum showed two peaks at 465 nm and 525 nm, respectively; MAPQ had a maximum excitation wavelength of 488 nm and a maximum emission wavelength of 690 nm; and Si-β-gal-P had a maximum excitation wavelength of 543 nm and a maximum emission wavelength of 650 nm. The emission spectra of the three probes were well separated with no significant overlap, meeting the spectral requirements for multiplex detection.

[0032] III. Construction of multiple fluorescent probe sets (e.g.) Figure 2 (A) 1) Sperm sample processing Freshly collected human or mouse semen samples were washed three times with PBS buffer and centrifuged at 300-600G for 10 min. Viable sperm were obtained using the upstream method (G-IVF PLUS medium, Vitrolife), and the concentration was adjusted to 1-5 × 10⁻⁵. 6 / mL, for later use; 2) Multiple probe staining Three probes were added simultaneously to the sperm suspension: for human sperm, the final concentrations were 4–6 μM RCPH, 1–3 μM MAPQ, and 0.5–1.5 μM Si-βgal-P; for mouse sperm, the final concentrations were 20 μM RCPH, 5 μM Si-βgal-P, and 0.5 μM MAPQ. The suspension was incubated at room temperature in the dark for 30 min, washed once with PBS, and resuspended in an appropriate amount of buffer solution for testing. 3) Spectroscopic flow cytometry detection Detection was performed using Cytek Aurora full-spectrum flow cytometry. Laser configuration and detection channels: RCPH was excited at 405 nm, with detection channels V3 (~525 nm) and V7 (~465 nm) used for ratio calculation; MAPQ was excited at 488 nm, with detection channel YG-7 (~690 nm); Si-βgal-P was excited at 543 nm, with detection channel YG-7 (~650 nm). In actual detection, the UV-7 channel was preferred for optimal resolution. SpectroFlo software was used for spectral unmixing and data analysis, with at least 10,000 sperm counts collected for each sample. 4) Optimization of probe concentration Using signal-to-noise ratio (SNR) as an indicator, the staining effect of each probe at different concentrations was tested. The results showed that RCPH in human sperm achieved the optimal SNR at 5 μM; MAPQ showed the strongest specific signal at 2 μM; and Si-βgal-P exhibited signal saturation and the lowest background fluorescence at 1 μM (e.g., ...). Figure 2 (Middle B). The corresponding concentrations of mouse sperm were 20 μM, 5 μM, and 0.5 μM (e.g., ...). Figure 3 (A)

[0033] IV. Probe Function Verification Experiment 1) Verification of the response of the mtG4s probe MAPQ Human sperm were incubated with the following compounds: control group (0.05% DMSO); KCl group (100 mM KCl, 1 h); PDS group (10 μM PDS, 1 h); TMPyP4 group (10 μM TMPyP4, 1 h); H2O2 group (3% H2O2, 15 min); spermidine group (100 μM KCl pretreatment for 1 h, followed by incubation with 10 μM spermidine for another 1 h). After treatment, MAPQ staining and flow cytometry were performed according to the method described in "Construction of Multiplex Fluorescent Probe Sets". The results showed that KCl, PDS, TMPyP4, and H2O2 treatments significantly increased MAPQ fluorescence intensity (p<0.01), indicating that these treatments promoted the formation or stabilization of mtG4s; spermidine treatment significantly decreased MAPQ fluorescence intensity (p<0.01), indicating that it promoted the clearance of mtG4s. Figure 4 In mouse sperm, treatment with TMPyP4 and H2O2 also significantly increased MAPQ fluorescence ( ). Figure 3 (B). This further confirms that MAPQ can sensitively respond to dynamic changes in the level of mtG4s in sperm; 2) Quantitative calibration of pH probe RCPH Human sperm stained with RCPH were resuspended in PBS buffer at different pH values ​​(6.17, 6.5, 6.79, 7.01, 7.5), and 10 μM nigramycin was added to each. The suspensions were equilibrated at 37°C for 10 min. The fluorescence intensity of channels V7 and V3 was detected by flow cytometry, and the ratio V7 / V3 was calculated. A standard curve was plotted with pH value on the x-axis and the ratio on the y-axis. The linear regression equation was: y = 4.202x - 21.31, R0 2 = 0.9859 ( Figure 4 (BD). The standard curve equation for mouse sperm is y = 2.368x - 11.69, R² = 0.9681 (BD). Figure 3 (C). This equation is used for the quantitative calculation of sperm pHi in subsequent samples; 3) Response verification of the β-gal probe Si-βgal-P Human sperm were incubated with 3% H2O2 for 15 min to induce senescence, and Si-βgal-P staining was performed according to the method in "Construction of Multiplex Fluorescent Probe Kit". Flow cytometry showed that the fluorescence intensity of Si-βgal-P in the H2O2-treated group was significantly increased compared with the control group (p<0.001), indicating that this probe can sensitively detect the increased β-gal activity associated with sperm senescence. Figure 4 (E) 4) Assessment of the impact of multiplex probe detection on sperm motility Human sperm samples were collected and divided into a control group (treated with 0.05% DMSO) and a multiplex staining group (stained according to the method described in "Construction of Multiplex Fluorescent Probe Groups"). The sperm motility parameters of both groups were detected using a computer-assisted sperm analysis system (CASA). The results showed no statistically significant differences between the two groups in terms of progressive motility rate, total sperm motility, and other indicators. Figure 4 (F) demonstrates that the multiple staining scheme of the present invention has no significant adverse effects on sperm function and is suitable for subsequent functional studies and clinical testing.

[0034] Example 1 This embodiment provides a method for constructing a diagnostic model for male infertility, comprising the following steps: S1: Research Cohort and Sample Collection A total of 130 clinical semen samples were included, divided into a training cohort (Hospital 1, n=56) and an independent validation cohort (Hospital 2, n=74). All sample collection was approved by the ethics committee and the participants obtained informed consent. Routine semen analysis was performed according to WHO standards, including sperm concentration, motility, morphology, and DNA fragmentation index (DFI). Baseline characteristics of the training and validation cohorts are shown in Tables 1 and 2, respectively. Table 1 shows the demographic and baseline characteristics of the subjects (Hospital 1).

[0035] Table 2 shows the demographic and baseline characteristics of the subjects (Hospital 2).

[0036] S2: Multiple probe detection Following the method described in "Construction of Multiplex Fluorescent Probe Sets" above, multiplex staining and flow cytometry were performed on each sample to obtain the following indicators: intracellular pH (pHi) of sperm cells, based on the V7 / V3 ratio and the standard curve (…). Figure 4 The β-gal activity was calculated as the average fluorescence intensity of Si-βgal-P and logarithmically transformed (ln(β-gal)); the mtG4s level was expressed as the average fluorescence intensity of MAPQ and logarithmically transformed (ln(mtG4s)). S3: Establishment of Diagnostic Model Statistical analysis was performed using R software. First, univariate logistic regression analysis was conducted on all candidate variables (age, routine clinical sperm testing parameters, DFI, pHi, ln(β-gal), ln(mtG4s)). Figure 5 (AB). Two multivariate logistic regression models were then constructed: a traditional model (incorporating age and all routine clinical sperm testing parameters); and an integrated model (further incorporating pHi, ln(β-gal), and ln(mtG4s) based on the traditional model). The nomogram is shown below. Figure 6 As shown; S4: Model Performance Evaluation In the training cohort, the AUC of the traditional model was 0.87 (95% CI: 0.79–0.96), while the AUC of the ensemble model improved to 0.93 (95% CI: 0.87–0.99), a statistically significant difference (p<0.001). In the independent validation cohort, the AUC of the traditional model was 0.82 (95% CI: 0.68–0.96), while the AUC of the ensemble model was 0.89 (95% CI: 0.79–0.98), also a significant improvement (p<0.01). Figure 5 Medium CD); 10-fold cross-validation showed that the average AUC of the ensemble model in the training cohort increased from 0.65 to 0.70 compared to the traditional model (Table 3). Decision curve analysis showed that the ensemble model had higher net returns over a wider threshold range. Figure 7 (A); The calibration curve shows that the predicted probabilities of the integrated model are in better agreement with the actual observations. Figure 7 (B) The precision-recall curve also confirms the superiority of the ensemble model. Figure 7 (C). These results demonstrate that the multifunctional biomarkers proposed in this invention can significantly improve the diagnostic accuracy of male infertility.

[0037] Table 3 shows the discriminant performance (AUC, sensitivity, and specificity) of the generalized linear model using 10-fold cross-validation.

[0038] Example 2 Based on Example 1, this example involves screening for natural products, such as... Figure 8 The Chinese A-class ... S1: Compound Library and Screening Process Forty-five natural product monomers were purchased from companies such as Sigma-Aldrich and prepared into a 10 mM stock solution using DMSO, which was stored at -20°C for later use. Sperm samples were collected from nine infertile patients, mixed, and the concentration was adjusted to 2 × 10⁻⁶.6 / mL, inoculated into 90 μL per well of a 96-well plate. The compound was added using an automated liquid handling system to a final concentration of 100 μM. Each compound was used in triplicate. A negative control (0.1% DMSO) and a positive control were also included. The mixture was incubated at 37°C for 30 min. S2: Multi-indicator detection Add the mixture of three probes to each well according to the method in "Construction of Multiplex Fluorescent Probe Sets", with the final concentration as above. After incubation for another 30 min, perform fluorescence detection using a multi-mode microplate reader: pHi detection (excitation at 405 nm, detection of emission at 465 nm and 525 nm, calculation of the ratio); β-gal detection (excitation at 543 nm, detection of emission at 650 nm); mtG4s detection (excitation at 488 nm, detection of emission at 690 nm). S3: Filtering Results Calculate the relative changes (ratios to the control group) of each index after treatment with each compound, and plot a heatmap. Figure 8 (Medium B). Candidate compounds were screened using a fold change threshold of ≥1.5-fold or ≤0.67-fold. Results showed that 10-hydroxycamptothecin (10-HCPT) significantly increased the pHi ratio, but had little effect on β-gal and mtG4s; luteolin significantly decreased the β-gal and mtG4s signals, with a moderate effect on pHi. These two compounds were selected for further validation. S4: Dosage effect verification Sperm from a new batch of infertile patients (n=3) and mouse sperm were collected and incubated for 1 h with different concentrations (1, 5, 10, 20, 50 μM) of 10-HCPT or luteolin, respectively. Flow cytometry analysis was performed according to the method described in "Construction of Multiplex Fluorescent Probe Assemblies". The results showed that both compounds significantly regulated the corresponding indicators at a concentration of 10 μM, and a dose-dependent relationship existed. Figure 9 (AB) verified the preliminary screening results.

[0039] Example 3 Building upon Examples 1-2, this example discusses the effects of candidate compounds on sperm mitochondrial function: TMRE mitochondrial membrane potential detection, specifically including: Sperm samples were collected from patients with asthenospermia (n=3) and divided into three groups: control group (0.1% DMSO), 10-HCPT group (10 μM), and luteolin group (10 μM). The samples were incubated at 37℃ for 1 h. After washing with PBS, 1 μM TMRE staining solution was added, and the samples were incubated at 37℃ in the dark for 1 h. Flow cytometry was used for detection (excitation 549 nm, emission 575 ± 15 nm). The results showed that compared with the control group, the mean TMRE fluorescence intensity of sperm in the 10-HCPT group and the luteolin group was significantly increased (p<0.05, e.g., 0.1% DMSO). Figure 9 The presence of C indicates that both compounds can enhance sperm mitochondrial membrane potential and improve mitochondrial function.

[0040] Example 4 Building upon Examples 1-2, this example discusses the effects of candidate compounds on mouse embryonic development using a PDS-induced model, specifically including: 1) PDS-induced mtG4s elevation model Epididymal tail sperm from male B6D2F1 mice were collected and divided into four groups: control group (incubated in HTF medium); PDS group (incubated in HTF containing 10 μM PDS for 1 h); PDS + luteolin group (pretreated with 10 μM PDS for 1 h, then incubated with 10 μM luteolin for another 1 h); PDS + 10-HCPT group (pretreated with 10 μM PDS for 1 h, then incubated with 10 μM 10-HCPT for another 1 h). 2) IVF and Embryo Metabolic Testing Following standard IVF procedures: Cumulus-oocyte complexes from superovulated female mice were retrieved and fertilized in vitro with sperm treated as described above. After 4 hours, excess sperm and cumulus cells were removed, and morphologically normal MII oocytes were selected for further culture. Fertilization rate was assessed 24 hours post-fertilization, and morula rate was assessed 96 hours post-fertilization. The metabolic status of early embryos (NAD(P)H, FAD autofluorescence) was detected using a femtosecond label-free imaging system. Results showed that the fertilization rate and morula formation rate in the PDS-treated group were significantly lower than those in the control group, and embryo NAD(P)H levels were decreased. Luteolin treatment significantly reversed these changes, restoring fertilization rate, morula rate, and NAD(P)H levels to near-normal levels. Figure 10 (AB). 10-HCPT did not show a significant rescue effect in the PDS model, suggesting that its mechanism of action may not directly involve mtG4s regulation.

[0041] Example 5 Based on Examples 1-2, this example discusses the repair effects of candidate compounds on frozen sperm damage, specifically including: 1) Sperm freezing and thawing Epididymal tail sperm from male B6D2F1 mice was collected and cryopreserved using vitrification. Upon thawing, the frozen sperm were rapidly immersed in a 37°C water bath, washed, and then divided into three groups: control group (incubated in HTF medium for 1 h); luteolin group (incubated in HTF containing 10 μM luteolin for 1 h); and 10-HCPT group (incubated in HTF containing 10 μM 10-HCPT for 1 h). 2) IVF and embryonic development assessment IVF was performed according to the method in Example 7, and the fertilization rate, 2-cell rate, 4-8-cell rate, and morula rate were statistically analyzed. Femtosecond label-free imaging was used to detect embryo metabolic status. Results showed ( Figure 10 In the CD (Central Developmental Cycle), the fertilization rate in the frozen sperm control group was significantly lower than that in the fresh sperm group, and the morula rate was also reduced. The luteolin-treated group showed significantly higher fertilization rates, 2-cell rates, 4-8-cell rates, and morula rates than the control group (p<0.01), approaching the levels of fresh sperm. The 10-HCPT-treated group also significantly improved all developmental indicators (p<0.05). Metabolic imaging showed that both compound treatments restored the autofluorescence levels of NAD(P)H and FAD in embryos to near-normal levels, indicating improved metabolic function.

[0042] Example 6 Based on Example 1, this example provides: an auxiliary diagnostic kit for male infertility. This auxiliary diagnostic kit is based on multiplex fluorescent probes and a diagnostic model, wherein the kit includes: Probe mixture: PBS solution (10× concentrate) containing 50 μM RCPH, 10 μM Si-βgal-P, and 20 μM MAPQ. Calibrators: Four calibration buffer solutions with different pH values ​​(pH 6.2, 6.6, 7.0, 7.4) are provided, each containing 10 μM nigramycin; Washing buffer: PBS (pH 7.4) containing 1% BSA; Positive control: Lyophilized quality control sperm containing high mtG4s levels (treated with PDS) and low mtG4s levels (treated with spermidine); Instruction manual: Describes in detail the staining procedures, flow cytometer settings, data analysis methods, and calculation formulas in the diagnostic model.

[0043] The procedure involved collecting fresh semen samples, washing and processing them using the upstream method, incubating them with a probe mixture at room temperature for 30 minutes, washing again, and then analyzing the samples using flow cytometry. Sperm pHi was calculated based on a standard curve, and the fluorescence intensity values ​​corresponding to β-gal and mtG4s were obtained. These values ​​were then substituted into a diagnostic model (Logistic regression equation) to calculate the infertility risk index for the subjects. Results were interpreted as follows: a risk index > 0.5 indicated an infertility risk associated with sperm dysfunction, while a risk index ≤ 0.5 indicated no infertility risk associated with sperm dysfunction.

[0044] Application Example 1: Differential Diagnosis of Sperm Function Impairment Mechanisms For infertile patients whose routine semen analysis shows abnormalities but whose cause is unclear, the multiple probe detection method involved in this invention can further identify the damage mechanism: If sperm pHi is significantly lower than the normal reference range (e.g., <6.8), while β-gal and mtG4s are normal, it suggests possible intracellular acidification due to ion channel or metabolic abnormalities. Intervention targeting energy metabolism or ion homeostasis is recommended (refer to the application of 10-HCPT). If sperm β-gal activity is significantly elevated, it indicates age-related damage, and antioxidant or senescent cell-clearing treatments are recommended (refer to the application of luteolin). If sperm mtG4s levels are significantly elevated, it suggests mitochondrial genomic instability or oxidative stress. It is recommended to use G4 unwinding or antioxidant intervention (refer to the application of luteolin). If multiple indicators are abnormal at the same time, it suggests that multiple mechanisms exist simultaneously, and comprehensive intervention is recommended.

[0045] By identifying the underlying mechanisms, personalized treatment recommendations can be provided to patients, avoiding the blindness of empirical treatment.

[0046] Application Example 2: Sperm function assessment before assisted reproductive technology Before in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI), the diagnostic model of this invention can be used to perform functional assessment of sperm samples, which can predict fertilization outcomes and guide sperm screening. Multiple probe testing of semen samples from IVF cycles: If pHi, β-gal, and mtG4s are all within the normal range, the fertilization rate is predicted to be high; if any of the indicators are significantly abnormal, the risk of fertilization failure is predicted to increase, and ICSI is recommended. For ICSI cycles, a small number of sperm can be rapidly stained before micromanipulation (shortening the incubation time to 15 min), and the sperm with the best functional state can be selected for injection based on the fluorescence signal to improve the success rate of ICSI. Functional assessment of frozen sperm samples is performed to predict the degree of freezing damage. If necessary, pretreatment with compounds (such as luteolin or 10-HCPT) is carried out to improve function before use in assisted reproduction.

[0047] Application Example 3: Development of Additives for Sperm In Vitro Processing Solutions Based on the screening results of this invention, 10-HCPT and luteolin can be used as functional additives in the development of sperm in vitro processing solutions: Sperm washing solution additive: Adding 10 μM luteolin to sperm washing solution (such as G-IVF PLUS) for washing and treating sperm from infertile patients can improve sperm mitochondrial function and fertilization capacity within 30-60 minutes. Sperm cryopreservation solution additive: Adding 10 μM 10-HCPT to the vitrification cryoprotectant can protect sperm function and reduce cryopreservation damage during the freezing and thawing process; Sperm incubation fluid additives: Adding 5-10 μM luteolin to IVF fertilization fluid can continuously protect mitochondrial function during sperm capacitation and fertilization, thereby improving fertilization rate and embryo quality.

[0048] Application Example 4: Study on the Mechanism of Mitochondrial Protective Effect of Compounds Using the multiplex probe platform of this invention, the molecular mechanisms by which candidate compounds improve sperm function can be studied in depth: Mouse sperm are incubated with different concentrations of candidate compounds (such as luteolin), and the dynamic changes of pHi, β-gal, and mtG4s are detected at different time points to determine the optimal concentration and time window. The metabolic pathways of compound action are analyzed by combining mitochondrial function assays (such as oxygen consumption rate, ATP content, and reactive oxygen species levels). The regulatory effects on sperm function indicators are observed by using specific inhibitors (such as mitochondrial electron transport chain inhibitors and autophagy inhibitors) in combination with the compounds, revealing the target sites and signaling pathways of the compounds. Direct interactions between the compounds and potential target proteins are identified through techniques such as molecular docking and surface plasmon resonance. This multiplex probe platform provides a high-throughput, multi-parameter analytical tool for sperm function research and can be widely applied to basic research and drug development.

[0049] Application Example 5: Rapid Screening for Reproductive Toxicity of Environmental Pollutants The diagnostic model of this invention is applied to assess the toxicity of environmental pollutants to male reproductive function: Sperm from healthy volunteers or mice is incubated with different concentrations of the environmental pollutants to be tested (such as bisphenol A, phthalates, heavy metal ions, etc.) for a certain period of time (1-24 h). Multiplex probe staining and flow cytometry are performed according to the method in "Construction of Multiplex Fluorescent Probe Sets" to obtain changes in pHi, β-gal, and mtG4s. A comprehensive toxicity index is calculated based on the degree of abnormality of the three indicators to assess the reproductive toxicity level of the pollutants. Correlation analysis is performed with traditional sperm motility and morphology detection results to verify the sensitivity and specificity of this method. This method is rapid, multi-parameter, and high-throughput, and can be used for rapid screening of reproductive toxicity in environmental samples and chemicals.

[0050] Application Example 6: Safety Evaluation of Drug Reproductive Toxicity In the process of new drug development, the method of this invention is used to assess the potential reproductive toxicity of candidate drugs: Sperm from experimental animals (such as mice, rats, or rabbits) is incubated with different concentrations of the test drug (10 times and 100 times the clinical exposure concentration) for an appropriate time (simulating in vivo exposure time). Multiple probe detection is performed to analyze the effects of the drug on sperm pHi, β-gal, and mtG4s. If the drug causes a significant abnormality (change exceeding 2 standard deviations) in any of the three indicators at concentrations below cytotoxic levels, it suggests a potential reproductive toxicity risk, requiring further animal reproductive toxicity studies for verification. This method can serve as a supplementary means for early screening of drug reproductive toxicity, improving the predictive ability of safety evaluation and reducing the risks of later development stages.

[0051] Application Example 7: Personalized Treatment Guidance Based on Multiple Probes For patients diagnosed with infertility, the diagnostic model of this invention is used to obtain abnormal patterns in sperm pHi, β-gal, and mtG4s. Combined with screened active compounds (such as 10-HCPT for patients with low pHi, and luteolin for patients with high mtG4s and β-gal), individualized treatment plans are developed. During assisted reproductive cycles, sperm can be treated in vitro with the appropriate compounds to improve function before fertilization. By monitoring changes in indicators before and after treatment, efficacy is assessed and strategies are adjusted promptly. This invention provides a feasible path from empirical treatment to precision medicine.

[0052] Application Example 8: Application of MAPQ probes in clinical sperm sample testing The MAPQ probe was used for clinical detection of sperm mtG4 levels, with mtG4 serving as a clinical biomarker. Flow cytometry was used to detect clinical samples. Figure 11 The results showed that, compared with the age-matched fertile group, the mean MAPQ fluorescence intensity (MFI) of sperm in the ≥35-year-old infertile group was significantly higher. Figure 12); ROC curve analysis showed that, using MAPQ MFI as a diagnostic indicator, its area under the curve (AUC) for distinguishing between advanced maternal age infertility and advanced maternal age fertility reached 0.847, i.e., a sensitivity of 84.69%. Figure 12 ).

[0053] The embodiments described above are merely illustrative of specific implementations of the present invention, and while the descriptions are detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. A method for constructing a diagnostic model for male infertility, characterized in that, include: The detection parameters of sperm samples from clinically tested individuals were obtained, including intracellular pH, mitochondrial G-quadruplex structure level, and β-galactosidase activity. The index parameters were calculated to obtain pHi, ln(mtG4s), and ln(β-gal). The obtained pHi, ln(mtG4s), and ln(β-gal) were combined with routine clinical sperm testing parameters and age of clinically tested individuals to construct a nomogram diagnostic model through multivariate logistic regression. Based on the obtained nomogram diagnostic model, the index parameters of the sperm sample of the clinical test subject, the clinical routine sperm test parameters and age are substituted into the data to obtain the total score and infertility risk index.

2. The method for constructing a diagnostic model for male infertility according to claim 1, characterized in that, In simplified application scenarios where a complete diagnostic model has not been established, the 95% confidence intervals of three indicators—pHi, ln(mtG4s), and ln(β-gal)—of fertile males are used as reference ranges. If any one of these parameters in the sperm sample of the clinical test subject exceeds this range, it is judged as abnormal sperm function, indicating that the clinical test subject is an infertile male.

3. The method for constructing a diagnostic model for male infertility according to claim 2, characterized in that, The acquisition of the index parameters of the sperm sample includes: Sperm samples were analyzed using flow cytometry, with the excitation and detection channels configured as follows: Using RCPH probe, 405nm excitation, while obtaining the fluorescence intensity of 465nm and 525nm detection wavelength, calculating the ratio R=I 525 / I 465 , substituting the pH standard curve of human sperm, pHi is obtained; Using a MAPQ probe, excited at 488 nm, and detected at wavelengths of 660–720 nm, the fluorescence intensity was obtained, and the natural logarithm was taken to obtain ln(mtG4s). A Si-β-gal-P probe was used: excitation at 543 nm, detection wavelength at 640–680 nm, fluorescence intensity was obtained, and ln(β-gal) was obtained by taking the natural logarithm.

4. The method for constructing a diagnostic model for male infertility according to claim 3, characterized in that, The final concentration of the RCPH probe is 4–6 μM, the final concentration of the MAPQ probe is 1–3 μM, and the final concentration of the Si-β-gal-P probe is 0.5–1.5 μM.

5. The method for constructing a diagnostic model for male infertility according to claim 3, characterized in that, The pH standard curve for human sperm is: R = 4.202 × pH value - 21.31, R 2 = 0.9859.

6. The method for constructing a diagnostic model for male infertility according to any one of claims 1-5, characterized in that, The routine clinical sperm testing parameters include sperm concentration, sperm count, total motility, forward motility, LIN, STR, WOB, VAP, VSL, VCL, ALH, BCF, sperm volume, and DFI.

7. A diagnostic model construction system for male infertility, characterized in that, The system used in the construction method according to any one of claims 1-6, the system comprising: an acquisition module, a model construction module, a calculation module, and a testing module; The acquisition module is used to acquire the detection parameters of sperm samples from clinically tested individuals, routine clinical sperm testing parameters, and age, and to obtain the indicator parameters through calculation. The model building module is used to construct a nomogram diagnostic model based on the index parameters of clinically tested sperm samples, routine clinical sperm testing parameters, and age, through multi-factor logistic regression. The calculation module is used to calculate the infertility risk index of clinical test subjects by combining the index parameters of sperm samples from clinical test subjects, routine clinical sperm testing parameters, and age through a nomogram diagnostic model. The diagnostic module compares the infertility risk index with 0.5 to indicate whether the clinically tested individual is at risk of infertility.

8. The diagnostic model construction system for male infertility according to claim 7, characterized in that, When the acquisition module acquires the index parameters of sperm samples from clinically tested individuals, the kit it uses includes a probe set. The probe set includes RCPH probes with a final concentration of 4–6 μM, MAPQ probes with a final concentration of 1–3 μM, and Si-β-gal-P probes with a final concentration of 0.5–1.5 μM.

9. The diagnostic model construction system for male infertility according to claim 8, characterized in that, When acquiring the index parameters of sperm samples from clinically tested individuals, the acquisition module uses detection methods including flow cytometry and ELISA.

10. The diagnostic model construction system for male infertility according to claim 8, characterized in that, The diagnostic module's judgment criteria are as follows: If the infertility risk index is >0.5, it indicates that the person being tested clinically has a risk of infertility. If the infertility risk index is ≤0.5, it indicates that the infertility risk of the clinical test subject is low.

11. A device for constructing a diagnostic model for male infertility, characterized in that, Including memory and processor; Memory, used to store programs; A processor for executing the program to implement the steps of the method for constructing a diagnostic model for male infertility as described in any one of claims 1-6.

12. A readable storage medium, characterized in that, The system contains a computer program that, when executed by a processor, implements the steps of the method for constructing a diagnostic model for male infertility as described in any one of claims 1-6.

13. An application characterized in that, To apply the diagnostic model construction method for male infertility as described in any one of claims 1-6 to the screening of compounds that improve sperm function.

14. The application according to claim 13, characterized in that, The application includes: before obtaining the detection parameters of sperm samples from clinical test subjects, co-incubating the test compound with sperm in the sperm samples from clinical test subjects, and then monitoring the changes of three parameters: pHi, ln(mtG4s) and ln(β-gal), and screening for compounds that can increase pHi, decrease ln(mtG4s) and / or decrease ln(β-gal).

15. A drug screening system, characterized in that, The drug screening system includes the diagnostic model building system for male infertility as described in any one of claims 7-10.

16. The drug screening system according to claim 15, characterized in that, The drug screening system is based on a diagnostic model construction system for male infertility, and constructs a multi-parameter high-throughput screening platform, using sperm cell intracellular pH, mitochondrial G-quadruplex levels, and β-spermia as parameters. Galactosidase activity is a functional indicator. After co-incubating the test compound with sperm in sperm samples, the changes in three parameters, pHi, ln(mtG4s) and ln(β-gal), are simultaneously detected by flow cytometry or enzyme-linked immunosorbent assay (ELISA). Compounds that can increase pHi and decrease ln(mtG4s) and / or decrease ln(β-gal) are screened.

17. The drug screening system according to claim 16, characterized in that, The compound includes 10 Hydroxycamptothecin and luteolin, 10 Both hydroxycamptothecin and luteolin can improve sperm mitochondrial function, increase fertilization rate, and improve embryo development quality in vitro.

18. An application characterized in that, This refers to the application of the MAPQ probe described in claim 3 in the preparation of a reagent for detecting the structure of sperm mitochondrial G-quadruplexes.

19. The application according to claim 18, characterized in that, The test reagent uses MAPQ MFI as a diagnostic indicator to predict fertility outcomes in older men.

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