Objective To explore the clinical efficacy and mechanism of FuKe Yangrong capsule(FKYRC)in treating anovulatory infertility(AI)using network pharmacology and clinical observation meth-ods.Methods A total of 110 AI patients who visited the hospital from January 2023 to July 2024 were select-ed as the research subjects.They were divided into three groups according to the treatment method:traditional Chinese medicine treatment group(n=30,treated only with FKYRC),western medicine treatment group(n=40,treated only with letrozole),and combination treatment group(n=40,treated only with FKYRC+letrozole).After 4 cycles of treatment,the total effective rate,maximum follicle diameter,pre-ovulation endo-metrial thickness,ovulation rate and pregnancy rate,and embryo survival rate of each group were compared af-ter treatment.Using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP)and GeneCards database,the core active ingredients,target proteins,and AI related targets of FKYRC were obtained,and common targets were screened.Then,a protein-protein interaction(PPI)network was constructed,and gene ontology(GO)function and Kyoto Gene and Genome Database(KEGG)pathway enrichment analysis were performed using a bioinformatics platform for visualization.Finally,three-dimen-sional visualization analysis was performed.Results The total clinical efficacy of the traditional Chinese medi-cine group,western medicine group,and combination therapy group were 90.00％,92.50％,and 97.50％,re-spectively.The ovulation rates were 60.00％,70.00％,and 87.50％,respectively.The pregnancy rates were 33.33％,37.5％,and 60.00％,respectively.The survival rates of embryos were 60.00％,73.30％,and 95.80％,respectively,and the differences between the groups were statistically significant(P＜0.05).The maximum follicle diameter and pre-ovulation endometrial thickness in the combination therapy group were higher than those in the traditional Chinese medicine group and the western medicine group,and the difference was statistically significant(P＜0.05).Network pharmacology discovered 239 active ingredients and 3 977 target genes in FKYRC.After screening,200 active ingredients and 299 target genes were identified.A total of 478 disease target genes,38 potential interaction targets,and 19 core targets were obtained.Molecular func-tions,cellular components,and biological processes mainly involved steroid protein binding,estrogen response elements,estrogen receptor activity,nuclear chromatin,and other aspects.KEGG pathway enrichment analysis showed that FKYRC anti AI core targets were mainly enriched in estrogen signaling pathway,P53 signaling pathway,advanced glycation end product receptor(AGE-RAGE)of diabetes complications and other signaling pathways.The key targets of FKYRC against AI were two estrogen receptors(ESR1 and ESR2),steroid re-ceptor(AR),and peroxisome proliferator activated receptor-γ(PPARG).Conclusion The combined treat-ment of FKYRC and letrozole can improve AI patients' clinical symptoms,increase ovulation rate,pregnancy rate,and embryo survival rate.The active ingredients in FKYRC can comprehensively regulate the core targets of AI,and may promote follicular development and maturation in infertile patients with ovulation disorders through signaling pathways such as estrogen,P53,and AGE-RAGE,thereby increasing pregnancy rate.

Objective:To analyze the association between visceral fat area (VFA) and fatty liver based on quantitative CT (QCT) in people receiving health examination with normal body mass index (BMI).Methods:A cross-sectional study. A total of 1 305 physical examiners who underwent chest CT and QCT examination in the Department of Health Management of Henan Provincial People′s Hospital from January to December 2021 were retrospectively selected as subjects. The physical components at the central level of the lumbar two cone were measured with QCT, including subcutaneous fat area (SFA), VFA and liver fat content (LFC). And the metabolic indexes, such as blood lipids and blood glucose, were collected. The t-test and χ2 test were used to analyze the correlation between the detection rate of fatty live and LFCr and age and gender. According to level of VFA (<100 cm 2, 100-150 cm 2 and≥150 cm 2), the subjects were divided into three groups, and one-way ANOVA and χ2 test were used in comparison between groups. Multiple linear regression was used to analyze the correlation between VFA and metabolic indexes and LFC. Results:Of the 1 305 subjects, there were 634 males and 671 females. The detection rate of fatty liver in normal BMI population was 65.67%, and it was 72.71% and 59.02% respectively in men and women ( χ2=27.12, P<0.001), and the detection rate of fatty liver and LFC increased with age (both P<0.05). With the increase of VFA, the age, BMI, SFA, LFC, total cholesterol (TC), triacylglycerol (TG), low-density lipoprotein cholesterol (LDL-C), fasting blood glucose (FBG), alanine aminotransferase (ALT), blood uric acid and prevalence of fatty liver increased (all P<0.05), and the low-density lipoprotein cholesterol (HDL-C) decreased ( P<0.001). Multiple linear regression analysis showed that after adjustment for age factors, regardless of male or female, LFC was independently positively related with VFA, BMI, and ALT (male β=0.206, 0.145, 0.174, female β=0.194, 0.150, 0.184; all P<0.05). FBG was positively correlated with male independently ( β=0.134; P<0.001). The indicators related to female independently were TC, TG, and blood uric acid ( β=-0.121, 0.145, 0.141, all P<0.05) Conclusion:In the population receiving health examination with normal BMI, the VFA measured by QCT technique is closely related to fatty liver.

Objective:To analyze the correlation between body fat distribution measured by quantitative CT (QCT) and body mass index in adults receiving physical examination.Methods:It was a cross-sectional study. From January to December 2021, 3 205 adults undergoing physical examination who met the inclusion criteria and underwent chest CT and QCT examination in the health management discipline of Henan Provincial People′s Hospital were selected as the research objects. The general data were collected; and the subcutaneous fat area, visceral fat area, total abdominal fat area, liver fat content, abdominal obesity and fatty liver detection rate were measured by QCT. According to body mass index, the subjects were divided into normal group (18.5-<24.0 kg/m 2, 1 343 cases), overweight group (24.0-<28.0 kg/m 2, 1 427 cases) and obesity group (≥28.0 kg/m 2, 435 cases). One-way analysis of variance and χ2 test were used to compare the differences of QCT indexes among the three groups. Pearson and Spearman correlation analysis were used to evaluate the correlation between QCT indexes and body mass index. Receiver operating characteristic (ROC) curve was drawn to analyze the diagnostic effect of QCT on obesity and fatty liver. Results:Subcutaneous fat area, visceral fat area, total abdominal fat area, liver fat content, abdominal obesity and fatty liver detection rate in obese group were all significantly higher than those in overweight group and normal group [males, (147.60±46.44) vs (104.33±27.68), (73.46±22.65) cm 2; (297.46±54.70) vs (229.40±53.12), (159.57±49.68) cm 2; (445.06±70.24) vs (333.73±62.91), (233.02±61.87) cm 2; 11.30% (7.90%, 15.55%) vs 8.75% (6.50%, 11.70%), 6.60% (4.80%, 8.70%); 100.0% vs 96.0%, 64.0%; 92.9% vs 86.7%, 73.3%; females, (213.96±48.61) vs (155.85±35.31), (107.24±31.01) cm 2; (185.41±43.88) vs (142.48±41.75), (96.56±36.50) cm 2; (399.37±68.07) vs (298.33±56.86), (203.80±57.53) cm 2; 9.80% (6.90%, 13.30%) vs 7.30% (5.05%, 9.80%), 5.40%(3.50%, 7.20%); 96.4% vs 74.8%, 28.9%; 87.3% vs 75.6%, 56.5%], and were all positively correlated with body mass index (males, r/ rs=0.709, 0.738, 0.831, 0.402, 0.464, 0.225; females, r/ rs=0.798, 0.695, 0.841, 0.416, 0.605, 0.276) (all P<0.001). In both male and female subjects, the detection rates of obesity based on QCT were significantly higher than those based on body mass index (male, 86.9% vs 16.6%; female, 49.3% vs 8.9%), and the detection rates of fatty liver based on QCT were significantly higher than those based on ultrasound (male, 83.6% vs 57.1%; female, 65.2% vs 27.6%) (all P<0.001). ROC curve showed that when the visceral fat area of 142 cm 2 was used as the cut-off value for the diagnosis of obesity in male subjects, the sensitivity and specificity was 100% and 15.8%, respectively; and when the cut-off value of liver fat content 5.0% was used to diagnose fatty liver, the sensitivity and specificity was 88.9% and 25.1%, respectively. When the visceral fat area of 115 cm 2 was set as the cut-off value for the diagnosis of obesity in female subjects, the sensitivity and specificity was 96.4% and 55.3%, respectively; when the liver fat content of 5.0% was set as the cut-off value for the diagnosis of fatty liver, the sensitivity and specificity was 83.7% and 43.2%, respectively. Conclusions:The indexes of abdominal fat and liver fat measured by QCT in adults receiving physical examination are all positively correlated with body mass index. The effect of QCT in the diagnosis of obesity and fatty liver are both better than body mass index and ultrasound.

Objective:To analyze the distribution of body fat with quantitative computed tomography (QCT) in people with normal body mass index (BMI).Methods:A cross-sectional study was conducted in the physical examination population who underwent chest CT and QCT examination in the Department of Health Management, Henan Provincial People′s Hospital from January to December in 2021, and 1 395 physical examination subjects who met the inclusion criteria were selected as the research subjects. The subjects were divided into five groups according to their age. The general data of the subjects were collected. The total abdominal fat area (TFA), visceral fat area (VFA), subcutaneous fat area (SFA), total abdominal muscle area (TMA) and muscle fat content (MFC) in the subjects were measured by QCT. One-way analysis of variance, Welch test and Kruskal-Wallis test were used to compare the above QCT measurement indexes between the two genders among different age groups with normal BMI. Pearson correlation analysis was used to analyze the correlation between VFA and sarcopenia indexes. Multivariate linear regression was used to analyze the relationship between VFA and linear correlation variables in the related indicators of sarcopenia.Results:There were significant differences in TFA, VFA, TMA and SMI among different age groups in subjects with normal BMI (all P<0.05). Pearson correlation analysis showed that VFA was negatively correlated with TMA in some age groups (male: 18-39 years group: r=-0.351; 40-49 years group: r=-0.278; 60-69 years group: r=-0.245; female:40-49 years group: r=-0.251; 50-59 years group: r=-0.270;≥70 years group: r=-0.391; all P<0.01); it was negatively correlated with SMI (male: 18-39 years group: r=-0.352; 40-49 years group: r=-0.340; 50-59 years group: r=-0.266; 60-69 years group: r=-0.316; female: 40-49 years group: r=-0.240; 50-59 years group: r=-0.284; all P<0.001); it was positively correlated with MFC (male: 18-39 years group: r=0.342; 40-49 years group: r=0.291; female: 50-59 years group: r=0.133; 60-69 years group: r=0.284; all P<0.05). Multivariate linear regression analysis showed that VFA was independently and negatively correlated with SMI in both men and women after adjusting for age interference factors (male B=-1.881, t=-6.025, P<0.001; female B=-0.603, t=-2.887, P=0.004), and it was independently positively correlated with MFC (male B=1.230, t=4.271, P<0.001;female B=0.893, t=3.836, P<0.001). There was an independent negative correlation between VFA and TMA in male subjects ( B=0.263, t=2.478, P=0.013). Conclusions:VFA is correlated with TMA, SMI and MFC in people with normal BMI. Regardless of gender, SMI has a negative effect on VFA, and MFC has a positive effect on VFA.

Objective:To investigate the effects of personalized intermittent energy restriction (IER) diet on sleep related gut microbiome in obese patients.Methods:In this single-arm clinical trial, a total of 35 obese patients who visited Henan Provincial People′s Hospital from April to November 2018 were recruited as research subjects. They underwent a strict 32-day IER diet intervention, divided into 4 stages of 8 days each. Nutritional recipes were formulated and nutritious meals were provided to each obese patient with timed meals, including 55% carbohydrates, 15% protein, and 30% fat per meal. In stages 1, 2, 3, and 4, patients were provided with 2/3, 1/2, 1/3, and 1/4 of their previous calorie intake every other day, respectively, with meals at 8:00 and 16:00. During the remaining time, patients were allowed unrestricted eating at home. Physiological indicators (weight, body mass index, body fat percentage, waist circumference, hip circumference, fasting blood glucose, glycosylated hemoglobin, blood pressure, triglycerides, total cholesterol, high-density lipoprotein, low-density lipoprotein and Pittsburgh Sleep Quality Index (PSQI) scores were observed before and after the intervention. Gut microbiota changes were analyzed using metagenomic sequencing technology, and Spearman′s correlation analysis was used to assess the correlation between significantly different bacterial species and PSQI scores.Results:After the intervention, the body weight, body mass index, and PSQI scores of obese patients were all significantly lower than before intervention [(89.92±14.98) vs (97.53±15.67) kg, (31.94±3.95) vs (34.64±4.05) kg/m 2, (3.43±1.16) vs (5.42±2.27)], the abundance of gut microbiota was significantly higher after the intervention (all P<0.05). There were 45 significantly different bacterial species before and after the intervention, of which 6 bacterial species ( Enterobacter cloacae, Escherichia coli, Odoribacter splanchnicus, Oribacterium sinus, Streptococcus gordonii, and Streptococcus parasanguinis) showed significantly positive correlations with PSQI scores ( r=0.476, 0.475, 0.369, 0.391, 0.401, 0.423) (all P<0.05), and they were mainly enriched in the glutamate and tryptophan synthesis pathways. Conclusions:The personalized IER diet intervention can improve the sleep of obese patients while reducing weight, possibly mediated by changes in gut microbiota through the glutamate and tryptophan pathways.

Objective:To analyze the correlation between quantified body fat distribution measured by computed tomography (CT) and blood lipids in overweight and obese individuals undergoing physical examinations.Methods:In this retrospective cohort study, a total of 3 463 physical examination subjects who underwent chest CT combined with quantified CT examination in the Department of Health Management at Henan Provincial People′s Hospital from January to December 2021 were selected using a comprehensive sampling method. The subjects were divided into three groups: normal group (1, 424 cases), overweight group (1, 531 cases), and obese group (508 cases) based on their body mass index: 18.5 to <24.0 kg/m 2, 24.0 to <28.0 kg/m 2, and≥28.0 kg/m 2, respectively. General information, blood lipid parameters, and different body fat distributions measured by quantified CT (subcutaneous fat area, visceral fat area, total abdominal fat area, liver fat content, muscle fat content) were collected in the three groups. One-way analysis of variance was used to compare differences in body fat distribution and blood lipid parameters, and Pearson correlation analysis was performed to evaluate the correlation between body fat distribution and blood lipids. Results:In the obese group, compared to the normal and overweight groups, subcutaneous fat area, visceral fat area, total abdominal fat area, liver fat content, muscle fat content, total cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglyceride levels were significantly higher [males: (152.80±49.27) vs (72.94±22.68), (103.79±28.30) cm 2; (287.95±57.55) vs (156.36±49.40), (224.67±53.10) cm 2; (440.75±72.44) vs (229.31±62.01), (328.46±62.77) cm 2; (12.92±8.61)% vs (6.82±3.31)%, (9.39±4.88)%; (9.06±9.34)% vs (4.55±5.06)%, (6.70±6.73)%; (6.52±0.94) vs (4.87±1.03), (6.27±0.96) mmol/L; (3.05±0.76) vs (2.92±0.86), (2.97±0.77) mmol/L; (2.34±1.42) vs (1.53±0.82), (1.99±1.28) mmol/L; females: (213.82±46.87) vs (104.69±30.62), (155.05±34.90) cm 2; (184.88±46.54) vs (90.67±34.09), (138.92±42.06) cm 2; (398.71±71.28) vs (195.37±55.32), (293.97±57.05) cm 2; (11.36±6.34)% vs (5.51±3.02)%, (7.98±4.77)%; (7.44±7.60)% vs (3.70±3.90)%, (5.56±5.94)%; (5.27±0.96) vs (5.04±0.86), (5.11±0.96) mmol/L; (3.26±0.84) vs (2.92±0.79), (3.01±0.74) mmol/L; (1.74±0.69) vs (1.27±0.65), (1.57±0.77) mmol/L], while high-density lipoprotein cholesterol (HDL-C) was significantly lower [males: (1.17±0.19) vs (1.38±0.28), (1.25±0.25) mmol/L; females: (1.36±0.22) vs (1.59±0.32), (1.42±0.27) mmol/L] (all P<0.001). In males, the visceral fat area and total abdominal fat area in the overweight group were positively correlated with triglycerides ( r=0.175, 0.113) and negatively correlated with HDL-C ( r=-0.125, -0.113), while liver fat content was positively correlated with total cholesterol, LDL-C, and triglycerides ( r=0.083, 0.075, 0.206) and negatively correlated with HDL-C ( r=-0.093) (all P<0.05). In the obese group, the liver fat content was positively correlated with triglycerides ( r=0.170) and negatively correlated with HDL-C ( r=-0.166) in males (both P<0.05). In females, the visceral fat area and total abdominal fat area in the overweight group were positively correlated with total cholesterol, LDL-C, and triglycerides (visceral fat area: r=0.129, 0.160, 0.348; total abdominal fat area: r=0.121, 0.130, 0.283) and negatively correlated with HDL-C ( r=-0.264, -0.173), while liver fat content was positively correlated with triglycerides ( r=0.352) and negatively correlated with HDL-C ( r=-0.195) (all P<0.05). In the obese group, the visceral fat area was positively correlated with triglycerides ( r=0.213) and negatively correlated with HDL-C ( r=-0.223) in females (both P<0.05). Conclusion:Blood lipids are correlated with body fat distribution in overweight and obese individuals undergoing physical examinations, and the degree of correlation varies between different genders and body regions, with triglycerides showing the strongest correlation with liver fat content.

Objective:To explore the correlation between the single nucleotide variation of profibrin-1 (PFN1) gene and secondary osteoporosis (OP) after stroke and its influence on bone metabolism indexes.Methods:120 patients with post-stroke hemiplegia who were treated in our hospital from Jan. 2019 to Jun. 2023 were selected as study objects and divided into OP group and non-OP group. Levels of vitamin D[25- (OH) D], tartrate-resistant acid phosphatase (TRAP) , osteocalcin (BGP) , serum type I procollagen amino terminal prolongation brain (P1NP) and type I collagen basal terminal β special sequence (β-CTX) were detected in all patients. Two SNPS (rs6559 and rs78224458) in PFN1 gene were genotyped.Results:There were significant differences in serum 25- (OH) D, TRAP, P1NP and β-CTX levels between OP group and non-OP group ( P<0.05) . The GG, GA and AA genotypes at rs6559 of PFN1 gene were significantly different between OP and non-OP patients ( P<0.05) . The combined model showed that compared with GG genotype carriers, the risk of secondary OP in GA and AA genotype carriers was 3.250 and 5.417 times higher, respectively. The results of the dominant model showed that the risk of secondary OP was 3.792 times higher in patients with mutant genes (GA or AA) than in patients with GG genotype. Recessive model results showed that patients with AA genotype had a 3.810-fold increased risk of secondary OP compared with GG and GA carriers. There was no significant difference in TT, TC, CC genotype distribution, genetic model and allele frequency at rs78224458 of PFN1 gene between OP patients and non-OP patients ( P>0.05) . There were no significant differences in 25- (OH) D, TRAP or BGP among the rs6559 GG, GA and AA genotypes of PFN1 gene ( P>0.05) , while there were significant differences in P1NP andβ-CTX levels among the three groups ( P<0.05) . Conclusion:The rs78224458 variation of PFN1 gene is associated with secondary OP in patients with hemiplegia after stroke, and may affect the bone metabolism indexes of patients.

Objective To explore the clinical value of resistance index(RI)of prostatic capsular artery in predicting or screening of prostate cancer(PCa)by comparing prostatic capsular artery RI with the serum total prostatic specific antigen(TPSA),fPSA/tPSA ratio and prostatic specific antigen dernsity(PSAD).Methods RI of prostate capsular artery,serum TPSA,of fPSA/tPSA ratio and PSAD were measured with colour Doppler ultrasonography in this subset of 203 patients who had undergone transrectal ultrasound guided prostate puncture biopsy.The patients were divided into two groups [PCa and benign prostatic hyperplasia(BPH)group] for comparative study.Results Of them,the level of TPSA were between 4 and 10 ng/ml(grey area)in 34 cases,accounts for 16.75%of the total subjects.All the others were outside the grey area.ROC curve analysis showed that the area under the curve(AUC)of RI of the capsular artery was 0.77,which was close to 0.84 and 0.86 of TPSA and PSAD.It indicated a similar value in predicting or screening PCa; while the AUC of fPSA/tPSA ratio was only 0.49,which had little clinical value.The fPSA/tPSA ratio and the mean value of PSAD in the grey area had significant differences(t=2.78,3.94,P＜0.02)between the two groups.However,the fPSA/tPSA ratio had no statistical significance in the high value area outside the grey area(t=0.873,P ＞ 0.05).And the mean value of RI of prostatic capsular artery had significant differences between the two groups both in the grey area and in the high value area outside the grey area(t=4.56,5.10,P ＜ 0.001).Conclusions RI of prostatic capsular artery can be steadily used to predict or screen PCa.It is not affected by the gray area of TPSA and is of great value in clinical practice.