Phenotypic-driven fish maw uterus-nest double-rearing effect evaluation method

Abstract

The invention relates to a method for evaluating the uterus-nest double-rearing effect of fish maw based on phenotype driving, and belongs to the field of evaluation of the uterus-nest double-rearing effect of the fish maw, and the method comprises the following steps: 1, carrying out the standardized collection of phenotype data, and carrying out the multi-dimensional phenotype definition of uterus-nest double-rearing; 2, intelligent integration of multi-source evidences and association mining of fish maw-nest phenotypes; step 3, automatic generation and priority ranking of verifiable hypotheses; and 4, performing experimental verification and closed-loop feedback. According to the invention, through multidimensional phenotypic correlation analysis of uterus and nest cultivation, it is clear that the fish maw plays a role in improving uterus blood flow, regulating ovarian hormone synthesis or repairing cell apoptosis; clinical research and experimental evidence are integrated, it is assumed that the support degree score is larger than or equal to 0.7, and the conclusion is improved by 40% compared with a traditional method; the limitation of traditional isolated evaluation of the uterus or the ovary is broken through, and the uterus-nest synergistic effect is verified through the function association phenotype; according to the method, key functional components and action targets are quickly locked through evidence priority ranking.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of efficacy evaluation of eel gelatin for uterus and ovary, and in particular to a method for evaluating the efficacy of eel gelatin for uterus and ovary based on phenotype driving. BACKGROUND

[0002] Eel gelatin (dried product of swim bladder) is a traditional tonic food, rich in collagen, polysaccharides and trace elements, and is believed in folk to have the effects of "tonifying qi and blood, nourishing complexion, and regulating gynecological diseases". In recent years, with the upgrading of women's health needs, eel gelatin has been widely used in the development of products related to the maintenance of uterus and ovary functions (coordinated maintenance of uterus and ovary functions), but the scientificity of its efficacy lacks systematic verification, and the efficacy verification has the following problems: 1. Phenotype and mechanism are separated: traditional researches mainly focus on a single index (such as estrogen level), and do not establish a whole picture of "uterus / ovary structure-function-molecule" correlation, so it is not clear whether eel gelatin plays a role by improving blood flow, regulating hormones or repairing cells; 2. Weak evidence support: existing efficacy claims rely mainly on animal experiments or small sample clinical observations, and lack of evidence integration of public databases (such as gene expression profile, clinical cohort) and eel gelatin component-phenotype correlation, so the conclusions are easily disturbed by individual differences; 3. Lack of "uterus and ovary coordination" research: uterus and ovary interact through neural-endocrine-immune network (such as estrogen secreted by ovary acting on uterus), but traditional researches mainly evaluate the function of uterus or ovary in isolation, and do not reflect the synergistic effect of "double maintenance"; 4. Lack of standardization: eel gelatin raw materials differ (such as fish species, processing technology), leading to large fluctuations in components (such as collagen content difference up to 5-10 times), and there is no unified phenotype evaluation index system for uterus and ovary double maintenance, so the comparability of research results is poor.

[0003] Therefore, a systematic research method based on phenotype driving and evidence support is urgently needed to clarify the role of eel gelatin in uterus and ovary double maintenance and provide scientific basis for product development. SUMMARY

[0004] The application provides a method for evaluating the efficacy of eel gelatin for uterus and ovary based on phenotype driving, to solve the defects in the prior art.

[0005] The application is implemented by the following technical solutions: A method for evaluating the efficacy of eel gelatin for uterus and ovary based on phenotype driving, characterized by comprising the following steps: Step 1: Standardized collection of phenotype data and definition of multi-dimensional uterus and ovary phenotype; Step 2: Intelligent integration of multi-source evidence and mining of eel gelatin-uterus and ovary phenotype correlation; Step 3: Automatic generation and priority sorting of verifiable hypotheses; Step four: experimental verification and closed-loop feedback.

[0006] The phenotypic-driven efficacy evaluation method of the flower jelly for uterus and ovary dual cultivation according to the above, wherein the phenotypes in step one include macroscopic phenotype, microscopic phenotype, environmental phenotype and function-related phenotype.

[0007] The phenotypic-driven efficacy evaluation method of the flower jelly for uterus and ovary dual cultivation according to the above, wherein the first-level indicators of the macroscopic phenotype are uterine structure and function and ovarian structure and function, the second-level indicators of the uterine structure and function are endometrial thickness, uterine artery blood flow resistance index and endometrial receptivity, and the second-level indicators of the ovarian structure and function are ovarian volume, antral follicle count, anti-Mullerian hormone and basal antral follicle stimulating hormone.

[0008] The phenotypic-driven efficacy evaluation method of the flower jelly for uterus and ovary dual cultivation according to the above, wherein the first-level indicators of the microscopic phenotype are endometrial molecular state and ovarian function molecular state, the second-level indicators of the endometrial molecular state are endometrial receptivity-related gene expression, integrin beta 3 protein level and apoptosis index, and the second-level indicators of the ovarian function molecular state are ovarian granulosa cell proliferation marker, estrogen synthesis key enzyme mRNA level and oxidative stress indicator.

[0009] The phenotypic-driven efficacy evaluation method of the flower jelly for uterus and ovary dual cultivation according to the above, wherein the first-level indicators of the environmental phenotype are uterus and ovary coordination, and the second-level indicators of the uterus and ovary coordination are Pearson correlation coefficient of estrogen and endometrial thickness and negative correlation intensity of follicle-stimulating hormone and AFC.

[0010] The phenotypic-driven efficacy evaluation method of the flower jelly for uterus and ovary dual cultivation according to the above, wherein the first-level indicators of the environmental phenotype are intervention factors and baseline state, and the second-level indicators of the intervention factors and baseline state are flower jelly intake dose, cycle, subject age, BMI and underlying disease.

[0011] The phenotypic-driven efficacy evaluation method of the flower jelly for uterus and ovary dual cultivation according to the above, wherein the intelligent integration of multi-source evidence in step two is performed by constructing an evidence database, the evidence database includes flower jelly component database, clinical research database and baseline evidence, the flower jelly component database collects chemical components of flower jelly from different sources, and the component spectrum is established by LC-MS / MS, atomic absorption spectroscopy and other detection methods; the clinical research database integrates published clinical trial data of flower jelly intervention in gynecological diseases, and extracts the relationship between phenotype changes and flower jelly dose; the baseline evidence collects the baseline phenotype and baseline data before flower jelly intake of the subjects at the time of enrollment, which is used to exclude interference factors.

[0012] The phenotypic driving-based efficacy evaluation method of the flower jelly for uterus and ovary dual cultivation, in step two, the flower jelly-uterus and ovary phenotype correlation mining adopts a knowledge graph technology to construct a ternary correlation network of "flower jelly component-target-uterus and ovary phenotype", and based on evidence level and timeliness, the correlation edges are weighted and scored to screen high-confidence correlations.

[0013] The phenotypic driving-based efficacy evaluation method of the flower jelly for uterus and ovary dual cultivation, in step three, the automatic generation and priority sorting of verifiable hypotheses are as follows: based on the high-confidence correlation network, a machine learning model is used to generate hypotheses to be verified, including causal hypotheses, correlation hypotheses and synergistic hypotheses.

[0014] The phenotypic driving-based efficacy evaluation method of the flower jelly for uterus and ovary dual cultivation, in step three, the priority sorting combines the following indexes to sort the hypotheses: evidence support degree accounts for 40%, clinical relevance accounts for 30%, operability accounts for 20%, and innovation accounts for 10%.

[0015] The phenotypic driving-based efficacy evaluation method of the flower jelly for uterus and ovary dual cultivation, in step three, the experimental design is based on high-priority hypotheses to design multi-stage verification experiments, including in vitro experiments, animal experiments and population experiments, if the experimental results support the hypotheses, the evidence score of the correlation edge is strengthened, and the correlation is included in the knowledge graph; if the experimental results do not support the hypotheses, the reasons are traced back, the experimental scheme is adjusted, and the next cycle is entered.

[0016] The advantages of the present application are: The present application clearly shows that the flower jelly plays a role by improving uterine blood flow, regulating ovarian hormone synthesis or repairing cell apoptosis through multi-dimensional phenotype correlation analysis of uterus and ovary dual cultivation; The present application integrates clinical research and experimental evidence, and the hypothesis support score is greater than or equal to 0.7, and the conclusion repeatability is improved by 40% compared with traditional methods; The present application breaks through the limitations of traditional isolated evaluation of the uterus or ovary, and verifies the synergistic effect of uterus and ovary through functional correlation phenotype; The present application quickly locks the key efficacy components and action targets through evidence priority sorting, and provides a scientific basis for the formula optimization of flower jelly products. DETAILED DESCRIPTION

[0017] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0018] A phenotypic driving-based efficacy evaluation method of flower glue uterus nest double cultivation, comprising the following steps: Step one: standardization collection of phenotypic data and multi-dimensional phenotypic definition of uterus nest double cultivation; Step two: intelligent integration of multi-source evidence and flower glue-uterus nest phenotypic correlation mining; Step three: automatic generation and priority sorting of verifiable hypotheses; Step four: experimental verification and closed-loop feedback.

[0019] Preferably, the phenotypes in step one described in the embodiments include macroscopic phenotypes, microscopic phenotypes, environmental phenotypes and functional correlation phenotypes.

[0020] Preferably, the first-level indicators of the macroscopic phenotypes described in the embodiments are uterine structure and function and ovarian structure and function, the second-level indicators of the uterine structure and function are endometrial thickness, uterine artery blood flow resistance index and endometrial receptivity (detection methods include transvaginal ultrasound, color Doppler blood flow imaging and ERA detection), and the second-level indicators of the ovarian structure and function are ovarian volume, antral follicle count, anti-Mullerian hormone and basal antral follicle stimulating hormone (detection methods include pelvic ultrasound and chemiluminescence immunoassay).

[0021] Preferably, the first-level indicators of the microscopic phenotypes described in the embodiments are endometrial molecular state and ovarian function molecular state, the second-level indicators of the endometrial molecular state are endometrial receptivity related gene expression, integrin beta 3 protein level and apoptosis index (detection methods include qRT-PCR, Western Blot and TUNEL flow cytometry), and the second-level indicators of the ovarian function molecular state are ovarian granulosa cell proliferation marker, estrogen synthesis key enzyme mRNA level and oxidative stress indicator (detection methods include immunohistochemistry, real-time fluorescent quantitative PCR and colorimetry).

[0022] Preferably, the first-level indicators of the environmental phenotypes described in the embodiments are uterus nest synergy, and the second-level indicators of the uterus nest synergy are Pearson correlation coefficient of estrogen and endometrial thickness and negative correlation intensity of anti-Mullerian hormone and AFC (detection methods include statistical correlation analysis).

[0023] Preferably, the primary indicators of the environmental phenotype described in this embodiment are: intervention factors and baseline state, and the secondary indicators of the intervention factors and baseline state are: chitosan intake dose, cycle, subject age, BMI, and underlying diseases (detection methods include questionnaires and clinical records).

[0024] Preferably, the intelligent integration of multi-source evidence in step two described in this embodiment is carried out by constructing an evidence library, which includes: a chitosan component database, a clinical research database, and baseline evidence. The chitosan component database collects chemical components of chitosan from different sources (such as collagen type and content, polysaccharide composition, trace elements), and establishes a component spectrum through detection methods such as LC-MS / MS and atomic absorption spectroscopy. The clinical research database integrates the data of published clinical trials of chitosan intervention in gynecological diseases (such as improving thin endometrium and regulating hormone level), and extracts the relationship between phenotype changes and chitosan dose. The baseline evidence collects the baseline phenotype of the subjects at the time of enrollment (such as AMH and AFC) and the baseline data before chitosan intake, which is used to exclude interference factors.

[0025] Preferably, the chitosan-ovary phenotype association mining in step two described in this embodiment adopts knowledge graph technology to construct a "chitosan component-target-ovary phenotype" ternary association network (example nodes: chitosan collagen protein→estrogen receptor ERα→endometrial thickness; chitosan polysaccharide→antioxidant enzyme SOD→ovarian granulosa cell apoptosis rate). Based on evidence level (such as randomized controlled trial> cohort study> animal experiment> in vitro experiment), consistency (correlation coefficient r>0.7 for different research results is high consistency), timeliness (data within the last 5 years are weighted by 1.5), the association edges are scored (score range 0-1), and high confidence associations (score≥0.7) are screened.

[0026] Preferably, the operation of automatic generation and priority sorting of verifiable hypotheses in step three described in this embodiment is: based on the high-confidence association network, a machine learning model is used to generate hypotheses to be verified, which include causal hypotheses (type 6 collagen protein in chitosan improves endometrial receptivity by up-regulating endometrial ITGβ3 expression), correlation hypotheses (chitosan polysaccharide intake is positively correlated with ovarian granulosa cell Ki67 expression), and synergistic hypotheses (chitosan combined with folic acid intervention can synergistically improve AMH level, which is 20% higher than chitosan alone).

[0027] Preferably, in step three of this embodiment, the priority ranking of hypotheses is based on the following indicators: evidence support (total association score) accounts for 40%, clinical relevance (whether the phenotype involved in the hypothesis directly affects fertility / gynecological health, such as endometrial receptivity > ovarian volume) accounts for 30%, feasibility (experimental cost, difficulty in recruiting subjects, such as animal experiments < human trials) accounts for 20%, and novelty (hypothesis has not been reported in previous studies) accounts for 10%.

[0028] Preferably, in step three of this embodiment, the experimental design is based on high-priority hypotheses, and a multi-stage verification experiment is designed. The verification experiment includes in vitro experiments, animal experiments, and human trials. If the experimental results support the hypothesis (e.g., p < 0.05 and effect size > 0.5), the evidence score of the association edge is strengthened (e.g., from 0.7 to 0.85), and the association is incorporated into the knowledge graph. If the experimental results do not support the hypothesis (e.g., p ≥ 0.05), the cause is traced (e.g., insufficient component extraction, inappropriate selection of phenotypic indicators), the experimental plan is adjusted (e.g., changing the fish maw extraction process, adding detection indicators), and the next cycle begins.

[0029] Preferably, the in vitro experiments described in this embodiment use human endometrial glandular epithelial cells (HEC-1A) or ovarian granulosa cells (KGN), with the addition of fish maw extract (concentration gradient: 0, 10, 50, 100 μg / mL), to detect target phenotypes (such as ITGβ3 protein expression and Ki67 mRNA level).

[0030] Preferably, the animal experiments described in this embodiment use PCOS model rats (simulating ovulation disorders) or thin endometrial model mice, which are divided into groups and given low / medium / high doses of fish maw (50, 100, 200 mg / kg·d). After 4-8 weeks of intervention, macroscopic (uterine / ovarian ultrasound) and microscopic (histopathology, molecular expression) phenotypes are detected.

[0031] Preferably, the population trial described in this embodiment recruits women preparing for pregnancy (aged 25-35 years, AMH 1.1-2.0 ng / mL), who are randomly assigned to a placebo group and a fish maw intervention group (10 g / day). The intervention lasts for 12 weeks, and endometrial thickness, AFC, hormone levels and pregnancy outcomes are monitored.

[0032] Preferably, this embodiment is implemented using a phenotypic-driven bitrophic uterus-ovary research system, which includes the following modules: Phenotypic acquisition module: Connects to devices such as ultrasound, chemiluminescence analyzer, and flow cytometer to automatically acquire and clean macroscopic / microscopic phenotypic data; Evidence integration module: integrates Neo4j knowledge graph tool (to build association networks), NLP literature mining tool (to extract literature associations), and Python machine learning framework (to train models). Hypothesis management module: supports hypothesis generation, priority sorting, and progress tracking; Experimental Management Module: Connects to the LIMS (Laboratory Information Management) system to record experimental processes and results, and supports data backtracking and model iteration.

[0033] Example 1: Study on the mechanism by which fish maw improves ovarian function in a PCOS model rat Research objective: To verify whether fish maw can improve ovulation disorders in PCOS rats by regulating the proliferation of ovarian granulosa cells; Step 1: Phenotypic Data Collection Macroscopic phenotype: Ovarian volume (OV) and antral follicle count (AFC) in rats were measured using transvaginal ultrasound; serum FSH, LH, and E2 levels were measured using chemiluminescence immunoassay. Microscopic phenotype: Ovarian tissue was collected and stained with hematoxylin and eosin (HE) to observe follicular development (number of primordial follicles and mature follicles); IHC was used to detect Ki67 (proliferation marker) expression in granulosa cells; Western blotting was used to detect CYP19A1 (estrogen synthase) protein levels. Environmental phenotype: Record the fish maw intervention dose (100 mg / kg·d), duration (4 weeks), and baseline body weight and blood glucose of rats.

[0034] Step 2: Integration and Correlation Analysis of Multi-Source Evidence Evidence library construction: PCOS rat ovarian transcriptome dataset (GSE126805) was downloaded from the GEO database, and differentially expressed genes (such as Ki67 downregulated by 2-fold) were extracted; 15 articles related to "collagen-ERα-proliferation" were extracted from PubMed; and the content of type 6 collagen in fish maw (3.79%) was obtained from historical laboratory data. Knowledge graph construction: Nodes include “PCOS rat ovary”, “fish maw type 6 collagen”, “Ki67”, and “ERα”, with edge association evidence (such as “high expression of Ki67 is positively correlated with follicle maturation, r=0.72” and “collagen can bind ERα, EC50=5μg / mL”). Evidence score: The association score of "fish maw type 6 collagen → ERα → Ki67 expression" was 0.82 (strong evidence). Step 3: Hypothesis Generation and Priority Sort High-priority hypothesis: "Type 6 collagen from fish maw improves ovulation function in PCOS rats by activating the ERα signaling pathway, upregulating Ki67 expression in ovarian granulosa cells" (evidence score 0.82, high clinical relevance, and strong operability). Step 4: Experimental Validation and Model Update In vitro experiments: Using KGN cells (human ovarian granulosa cells), control (0 μg / mL), low-dose (10 μg / mL), medium-dose (50 μg / mL), and high-dose (100 μg / mL) fish maw groups were set up. After 48 h of culture, the following results were obtained: Ki67 mRNA expression: the high-dose group was upregulated by 2.1 times compared with the control group (p=0.001); ERα protein level: the high-dose group was upregulated by 1.8 times compared with the control group (p=0.002). Animal experiments: PCOS model rats (n=20) were divided into a model group (PBS) and low / medium / high dose groups of fish maw (50, 100, 200 mg / kg·d). After 4 weeks of intervention: OV: High-dose group (0.85±0.05cm) 3 Compared with the model group (0.62±0.04cm) 3 The value increased significantly (p=0.001). AFC: The high-dose group (12.3±1.2) had a significantly higher number of AFCs than the model group (8.1±0.9) (p=0.001). Serum E2: The high-dose group (85.2±10.3 pg / mL) was significantly higher than that of the model group (52.1±8.7 pg / mL) (p=0.001); Model update: The association score of "fish maw type 6 collagen → ERα → Ki67 → ovulation function" was strengthened (from 0.82 to 0.90), and a new hypothesis was added that "fish maw may promote estrogen synthesis by regulating CYP19A1 expression".

[0035] Example 2: Clinical study on the improvement of female receptivity of thin endometrium by fish maw Research objective: To verify whether fish maw improves fertility outcomes by thickening the endometrium and increasing receptivity; Step 1: Phenotypic Data Collection Macroscopic phenotype: transvaginal ultrasound to detect endometrial thickness (EMT) and uterine artery RI; ERA to assess endometrial receptivity (target rate: window period synchronization rate); Microscopic phenotype: Endometrial tissue was collected on day 7 of the menstrual cycle, and LIF (a key gene for receptivity) expression was detected by qRT-PCR and ITGβ3 (integrin β3) expression was detected by IHC. Environmental phenotype: Record subjects' age (28-32 years), BMI (20-24 kg / m²), etc. 2 ), basal AMH (1.5-2.0 ng / mL), fish maw intake dose (10 g / day), cycle (12 weeks); Step 2: Integration and Correlation Analysis of Multi-Source Evidence Evidence library construction: Endometrial receptivity-related gene expression profiles (TCGA-UCEC) were downloaded from the TCGA database, and the correlation between LIF and EMT was extracted (r=0.68); 12 articles related to "collagen-ITGβ3-endometrium" were extracted from PubMed; and small-sample trials of fish maw intervention for thin endometrium were obtained from clinical research databases (n=30, with an average increase in EMT of 2.1 mm). Knowledge graph construction: Nodes include “thin endometrium”, “fish maw collagen”, “ITGβ3”, “LIF”, and “EMT”, with edges associated with evidence (such as “high expression of ITGβ3 is positively correlated with EMT, r=0.75” and “collagen can promote ITGβ3 secretion, EC50=20μg / mL”). Evidence score: The association score of "fish maw collagen → ITGβ3 → EMT → receptivity" was 0.85 (strong evidence). Step 3: Hypothesis Generation and Priority Sort High-priority hypothesis: "Fish maw improves endometrial receptivity and increases clinical pregnancy rate by upregulating endometrial ITGβ3 expression" (evidence score 0.85, extremely high clinical relevance, and strong operability). Step 4: Experimental Validation and Model Update Population trial: Sixty women with thin endometrium (EMT < 7 mm) who were trying to conceive were enrolled and randomly assigned to a placebo group (n=30) and a fish maw group (n=30). After 12 weeks of intervention; EMT: The fish maw group (8.2±0.8mm) was significantly thicker than the placebo group (6.5±0.7mm) (p=0.001); ITGβ3 expression: The fish maw group (0.82±0.10) was significantly upregulated compared with the placebo group (0.51±0.08) (p=0.001). Tolerance achievement rate: The rate was significantly higher in the fish maw group (63.3%) than in the placebo group (30.0%) (p=0.008). Clinical pregnancy rate: The fish maw group (36.7%) was significantly higher than that of the placebo group (13.3%) (p=0.02). Model update: The association between "fish maw collagen → ITGβ3 → EMT → receptivity" was confirmed (score increased to 0.92), and a new hypothesis was proposed that "fish maw can synergistically improve endometrial blood flow (RI decreased by 0.15)," thus entering the next round of research.

[0036] Compared with traditional research on the efficacy of fish maw, the advantages of this invention are: a. Precise analysis of the mechanism of action: Through multi-dimensional phenotypic correlation analysis of "dual nourishment of the uterus and ovaries", it was determined whether fish maw works by improving uterine blood flow, regulating ovarian hormone synthesis or repairing cell apoptosis (for example, in the example, it was found that fish maw type 6 collagen can upregulate the expression of endometrial ITGβ3, which increases the endometrial receptivity score by 30%). b. Complete and credible chain of evidence: Integrating clinical research and experimental evidence, with a hypothesis support score ≥0.7, the reproducibility of the conclusions is 40% higher than that of traditional methods (verified by 100 clinical cases). c. Focusing on the "synergistic care" characteristic: Breaking through the limitations of traditional isolated evaluation of the uterus or ovary, the synergistic effect of the uterus and ovary is verified through functional association phenotypes (such as the correlation between E2 and endometrial thickness) (in the example, the correlation coefficient between E2 and EMT in the fish maw intervention group was r=0.82, which was significantly higher than r=0.51 in the placebo group). d. Guiding precise product development: By prioritizing evidence, key active ingredients (such as type 6 collagen) and targets (such as ERα) can be quickly identified, providing a scientific basis for optimizing the formulation of fish maw products (such as adding type 6 collagen).

[0037] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A phenotype-driven method for evaluating the dual-nourishing effects of fish maw on the uterus and ovaries, characterized in that: Includes the following steps: Step 1: Standardized collection of phenotypic data and multidimensional phenotypic definition of ovarian dual-nutrition; Step 2: Intelligent integration of multi-source evidence and mining of the association between maw and ovary phenotypes; Step 3: Automatic generation and prioritization of verifiable hypotheses; Step 4: Experimental verification and closed-loop feedback.

2. The method for evaluating the dual-nourishing effects of fish maw on the uterus and ovaries based on phenotypic driving according to claim 1, characterized in that: The phenotypes in step one include: macroscopic phenotypes, microscopic phenotypes, environmental phenotypes, and functional association phenotypes.

3. The method for evaluating the dual-nourishing effects of fish maw on the uterus and ovaries based on phenotypic driving according to claim 2, characterized in that: The primary indicators of the macro phenotype are: uterine structure and function and ovarian structure and function. The secondary indicators of uterine structure and function are: endometrial thickness, uterine artery blood flow resistance index, and endometrial receptivity. The secondary indicators of ovarian structure and function are: ovarian volume, antral follicle count, anti-Müllerian hormone, and basal antral follicle-stimulating hormone.

4. The method for evaluating the dual-nourishing effects of fish maw on the uterus and ovaries based on phenotypic driving according to claim 2, characterized in that: The primary indicators of the microscopic phenotype are: endometrial molecular status and ovarian functional molecular status. The secondary indicators of the endometrial molecular status are: expression of endometrial receptivity-related genes, integrin β3 protein level, and apoptosis index. The secondary indicators of the ovarian functional molecular status are: ovarian granulosa cell proliferation markers, estrogen synthesis key enzyme mRNA level, and oxidative stress indicators.

5. The method for evaluating the dual-nourishing effects of fish maw on the uterus and ovaries based on phenotypic driving according to claim 2, characterized in that: The primary indicator of the environmental phenotype is utero-ovarian synergy, and the secondary indicators of utero-ovarian synergy are the Pearson correlation coefficient between estrogen and endometrial thickness and the strength of the negative correlation between follicle-stimulating hormone and AFC. The primary indicators of the environmental phenotype are: intervention factors and baseline status. The secondary indicators of the intervention factors and baseline status are: fish maw intake dose, cycle, subject age, BMI, and underlying diseases.

6. The method for evaluating the dual-nourishing effects of fish maw on the uterus and ovaries based on phenotypic driving according to claim 1, characterized in that: In step two, the intelligent integration of multi-source evidence is carried out by constructing an evidence library. The evidence library includes: a fish maw component database, a clinical research database, and baseline evidence. The fish maw component database collects the chemical components of fish maw from different sources and establishes component profiles using detection methods such as LC-MS / MS and atomic absorption spectroscopy. The clinical research database integrates published clinical trial data on fish maw intervention for gynecological diseases and extracts the relationship between phenotypic changes and fish maw dosage. The baseline evidence collects the baseline phenotype of subjects at enrollment and baseline data before fish maw intake to exclude confounding factors.

7. The method for evaluating the dual-nourishing effects of fish maw on the uterus and ovaries based on phenotypic driving according to claim 1, characterized in that: In step two, the association mining of fish maw-ovary phenotype uses knowledge graph technology to construct a ternary association network of "fish maw components-target points-ovary phenotypes"; based on evidence level and timeliness, the association edges are weighted and scored to screen high-confidence associations.

8. The method for evaluating the dual-nourishing effects of fish maw on the uterus and ovaries based on phenotypic driving according to claim 1, characterized in that: The automatic generation and priority ranking of verifiable hypotheses in step three are as follows: based on a high-confidence association network, a machine learning model is used to generate hypotheses to be verified, including causal hypotheses, correlation hypotheses, and co-hypotheses.

9. The method for evaluating the dual-nourishing effects of fish maw on the uterus and ovaries based on phenotypic driving according to claim 1, characterized in that: In step three, the priorities are ranked according to the following indicators: evidence support (40%), clinical relevance (30%), operability (20%), and innovativeness (10%).

10. The method for evaluating the dual-nourishing effects of fish maw on the uterus and ovaries based on phenotypic driving according to claim 1, characterized in that: In step three, the experimental design is based on high-priority hypotheses and involves designing multi-stage verification experiments, including in vitro experiments, animal experiments, and human trials. If the experimental results support the hypothesis, the evidence score of the associated edge is strengthened, and the association is incorporated into the knowledge graph. If the experimental results do not support the hypothesis, the cause is traced, the experimental plan is adjusted, and the cycle begins again.