Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic disorder affecting a substantial proportion of women of reproductive age. It is frequently associated with ovulatory dysfunction, infertility, and an increased risk of chronic metabolic diseases. A hallmark pathological feature of PCOS is the arrest of follicular development, closely linked to impaired intercellular communication between the oocyte and surrounding granulosa cells. Transzonal projections (TZPs) are specialized cytoplasmic extensions derived from granulosa cells that penetrate the zona pellucida to establish direct contact with the oocyte. These structures serve as essential conduits for the transfer of metabolites, signaling molecules (e.g., cAMP, cGMP), and regulatory factors (e.g., microRNAs, growth differentiation factors), thereby maintaining meiotic arrest, facilitating metabolic cooperation, and supporting gene expression regulation in the oocyte. The proper formation and maintenance of TZPs depend on the cytoskeletal integrity of granulosa cells and the regulated expression of key connexins, particularly CX37 and CX43. Recent studies have revealed that in PCOS, TZPs exhibit significant structural and functional abnormalities. Contributing factors—such as hyperandrogenism, insulin resistance, oxidative stress, chronic inflammation, and dysregulation of critical signaling pathways (including PI3K/Akt, Wnt/β‑catenin, and MAPK/ERK)—collectively impair TZP integrity and reduce their formation. This disruption in granulosa-oocyte communication compromises oocyte quality and contributes to follicular arrest and anovulation. This review provides a comprehensive overview of TZP biology, including their formation mechanisms, molecular composition, and stage-specific dynamics during folliculogenesis. We highlight the pathological alterations in TZPs observed in PCOS and elucidate how endocrine and metabolic disturbances—particularly androgen excess and hyperinsulinemia—downregulate CX43 expression and impair gap junction function, thereby exacerbating ovarian microenvironmental dysfunction. Furthermore, we explore emerging therapeutic strategies aimed at preserving or restoring TZP integrity. Anti-androgen therapies (e.g., spironolactone, flutamide), insulin sensitizers (e.g., metformin), and GLP-1 receptor agonists (e.g., liraglutide) have shown potential in modulating connexin expression and enhancing granulosa-oocyte communication. In addition, agents such as melatonin, AMPK activators, and GDF9/BMP15 analogs may promote TZP formation and improve oocyte competence. Advanced technologies, including ovarian organoid models and CRISPR-based gene editing, offer promising platforms for studying TZP regulation and developing targeted interventions. In summary, TZPs are indispensable for maintaining follicular homeostasis, and their disruption plays a pivotal role in the pathogenesis of PCOS-related folliculogenesis failure. Targeting TZP integrity represents a promising therapeutic avenue in PCOS management and warrants further mechanistic and translational investigation.

Objective To establish method for simultaneous determination of hesperidin, cinnamaldehyde and eugenol in Chunyang Zhengqi capsules by high performance liquid chromatography. Methods The column was Agilent PorosheⅡ 120 EC-C₁₈ (4.6 mm×150 mm, 4 μm). The mobile phase was acetonitrile-water with gradient elution. The column temperature was 35℃. The flow rate was 1.0 ml/min, and the detection wavelength was 284 nm. Results The methodological verification showed that hesperidin, cinnamaldehyde and eugenol had a good linearity (r≥0.999 9). The precisions were less than 2.0%. The average recovery was between 98.0% and 101.9%. The stability and repeatability of RSD were also less than 3.0%, which met the requirements of method validation. Conclusion The method is simple, stable, reproducible and accurate, which could be used to the quality control of Chunyang Zhengqi capsules.

A high performance liquid chromatography (HPLC) method utilizing correction factors was established for the quantitative detection of related substances in flumazenil. Separation was achieved using an Agilent Pursuit XRs C18 column (250 mm × 4.6 mm, 5 μm) with an isocratic elution of dilute phosphoric acid, methanol, and tetrahydrofuran as the mobile phases. Correction factors calculated from a standard curve method were applied to determine the impurity content. The quantification of impurities in flumazenil was conducted using both external standard and correction factor methods, followed by validation and comparison of the two. For the identification of degradation products, a forced degradation approach was employed to prepare a flumazenil degradation solution, and the resulting impurities were confirmed by LC-MS analysis. The separation of flumazenil and its impurities was found to be efficient. The limits of quantification for impurities A, B, D, and E were established at 0.169 9, 0.314 7, 0.143 9, and 0.270 8 ng, respectively, with the limits of detection at 0.055 8, 0.096 9, 0.048 8, and 0.089 0 ng. These impurities demonstrated a strong linear relationship across the concentration ranges of 0.034 9-7.847 0, 0.038 7-8.710 7, 0.034 6-7.794 1, and 0.032 4-7.292 8 µg·mL^-1, respectively (n = 7). The method achieved average recoveries between 98.25% and 99.42%, with an RSD of less than 2.0% (n = 9), indicating high accuracy. The external standard and correction factor methods were used to determine the related substances in flumazenil, and the results of the two methods were consistent. The established HPLC method is characterized by its high accuracy, sensitivity, and repeatability, and is suitable for determining related substances in flumazenil.

Objective To investigate the relationship between preoperative coagulation function and prognosis in patients with hypertensive cerebral hemorrhage undergoing emergency craniotomy. Methods Eighty-two patients with hypertensive cerebral hemorrhage who underwent emergency craniotomy (observation group) and 50 healthy volunteers (control group) were retrospectively selected as study subjects. The patients in the observation group were further divided into mild-to-moderate group (31 cases) and severe groups (51 cases) based on Glasgow Coma Score (GCS) at admission, and were divided into poor prognosis group (37 cases) and good prognosis group (45 cases) based on Glasgow Outcome Score (GOS). The differences in preoperative coagulation function indicators among different groups were compared, and the predictive value of coagulation indicators for patients′ prognosis was analyzed. Results The levels of prothrombin time (PT), activated partial thromboplastin time (APTT), international normalized ratio (INR), thrombomodulin (TM), and plasminogen activator inhibitor-1 (PAI-1) in the observation group were significantly higher than those in the control group (P < 0.05). The levels of PT, APTT, INR, TM, and PAI-1 in the severe group were significantly higher than those in the mild-to-moderate group (P < 0.05). Compared with the good prognosis group, patients in the poor prognosis group had older age, longer bleeding time, and higher levels of systolic blood pressure (SBP), diastolic blood pressure (DBP), PT, APTT, INR, TM, and PAI-1 (P < 0.05). Receiver operating characteristic(ROC)curve analysis showed that PT, APTT, INR, TM, and PAI-1 all had certain diagnostic efficiency for poor prognosis in patients with hypertensive cerebral hemorrhage [area under the curve (AUC) values were all over 0.7], with INR of the highest diagnostic efficiency (AUC=0.833) and PT of the lowest (AUC=0.762). Compared with single indicator, the AUC of combined detection of five coagulation function indicators for diagnosing poor prognosis was 0.942, with diagnostic sensitivity and specificity of 100.00% and 97.22%, respectively. Conclusion Hypertensive cerebral hemorrhage patients generally have varying degrees of coagulation dysfunction before emergency craniotomy, and coagulation dysfunction is closely related to the degree of brain injury and poor prognosis. Combined detection of coagulation function indicators (PT, APTT, INR, TM, PAI-1) can provide a reference for clinical assessment of patients′ condition.

Objective To investigate the relationship between occupational noise exposure and glycated hemoglobin (HbA1c) levels, as well as prediabetes diagnosed by HbA1c. Methods A total of 1 181 workers from a cigarette factory were selected as the research subjects using a judgment sampling method. Workers were divided into control, low-level noise exposure and high-level noise exposure groups, consisting of 236, 359, and 586 individuals, respectively. The blood sample was collected for HbA1c test and occupation noise exposure intensity in workplace was detected by an area-sampling method. Results There were no statistical significant differences in HbA1c levels and prediabetes prevalence among the three groups of workers (all P>0.05). After adjusting for potential confounding factors such as years of service, gender, smoking, pack-years of smoking, alcohol consumption, and body mass index, multiple linear regression analysis showed that the high-level noise exposure group had higher HbA1c level than the control group (P<0.05). Multivariable logistic regression analysis results showed that the high-level noise exposure group had higher risk of prediabetes compared with the control group (P<0.05). Conclusion Occupational noise exposure could be a risk factor for the increased HbA1c levels and prediabetes incidence among the occupational population. More attention should be paid to the effects of occupational noise exposure on the HbA1c level in occupational health surveillance.

Aim To investigate the effect of p-hydroxybenzaldehyde ( HD) on intestinal fibrosis in mice based on mouse intestinal fibrosis model and in vitro EMT model,and to explore the underlying mechanism Methods HE staining, Masson staining, immunohisto-chemistry ,qPCR, Western blot and other experimental methods were used to verify the effect of HD on intestinal fibrosis in mice and the potential mechanism. Results In vivo experiments showed that compared with the normal group, the DSS-induced intestinal fibrosis model group had shortened colon, increased colon his-topathological score, increased collagen volume fraction, and significantly increased collagen I expression. After treatment with 4, 10, and 25 mg • kg

Objective: To investigate the effects of the interaction between occupational noise exposure and arterial stiffness on blood glucose, so as to provide insights into for early prevention of diabetes among workers exposed to occupational noise. Methods: A total of 518 noise workers were selected from a tobacco plant in Wuhan City. Participants' gender, age and work duration were collected using questionnaire surveys, and participants' height and weight were measured. Blood glucose and arterial stiffness were detected, and the noise intensity was measured in working environments with a personal noise dosimeter. The effects of occupational noise exposure, arterial stiffness and their interactions on blood glucose were examined using a multiple linear regression model. Results: A total of 518 workers were included, with 398 males (76.83%), a mean age of (40.85±10.68) years, a mean working age of (19.50±12.69) years, a mean body mass index of (23.66±3.31) kg/m2, and a mean blood glucose level of (5.15±0.99) mmol/L. There were 247 workers with occupational noise exposure (47.68%) and 175 workers with arterial stiffness (33.78%). Multiple linear regression analysis showed significant associations of noise (β'=0.112) and arterial stiffness (β'=0.168) with blood glucose, and there was an additive interaction between noise and arterial stiffness on blood glucose (β'=0.314). Conclusion The interaction between occupational noise and arterial stiffness affects blood glucose.

Objective:To detect the expression of interleukin 2 (IL-2)/Janus kinase 3/signal transduction and transcriptional activator 5 (JAK3/STAT5) signaling pathway in peripheral blood of patients with ankylosing spondylitis (AS) and explore its mechanism in the development and progression of AS.Methods:Clinical data, peripheral blood and laboratory tests of 30 patients with active AS (ASA), 30 patients with stable AS (ASS) and 50 healthy subjects (HC) were collected. The mRNA expression levels of JAK3, signal transduction and transcription activator 5a (STAT5a) and signal transduction and transcription activator 5b (STAT5b) were detected by quantitative real-time-polymerase chain reaction (RT-qPCR). The expression levels of JAK3, STAT5a and STAT5b proteins and phosphorylated proteins were detected by Western-blot. Plasma IL-2 concentration was determined by enzyme-linked immunosorbent assay (ELISA). Two independent samples t-test or one-way analysis of variance were used for measurement data consistent with normal distribution, LSD- t test was used for pairwise comparison between the three groups, Mann-Whitney U test or Kruskal-Wallis H test was used for non-normal distribution, χ2 test was used for correlation analysis of categorical variables. Spearman correlation analysis was used for correlation analysis between variables, and receiver operating characteristic (ROC) curve was used to evaluate the value of JAK3, STAT5a and STAT5b mRNA expression levels in monitoring AS activity. Results:① The mRNA expression levels of JAK3, STAT5a and STAT5b were significantly different among the three groups ( F=65.98, P<0.001; F=21.15, P<0.001; F=13.67, P<0.001). JAK3 mRNA expression in ASA group (2.5±0.9) was significantly higher than that in ASS group (1.1±0.4) and healthy subjects (1.0±0.5), the difference was statistically significant (both P<0.001). The mRNA expression level of STAT5a in ASA group (1.4±0.3) was significantly higher than that in ASS group (0.9±0.3) and healthy subjects group (1.0±0.3), the difference was statistically significant (both P<0.001). STAT5b mRNA expression level in ASA group (1.5±0.6) was significantly higher than that in ASS group (1.0±0.4) and healthy subjects (1.0±0.4), the difference was statistically significant (both P<0.001). The expression level of JAK3 mRNA in HLA-B27 positive group (1.9±1.0) was higher than that in HLA-B27 negative group (1.4±0.6), and the difference was statistically significant ( t=-2.22, P=0.032). The phosphorylation levels of JAK3, STAT5a and STAT5b showed statistically significant differences among the three groups ( F=91.56, P<0.001; F=25.15, P< 0.001; F=178.59, P<0.001). The phosphorylation level of JAK3 protein in ASA group (1.04±0.08) was significantly higher than that in ASS group (0.568±0.019) and healthy subjects (0.536±0.064), the difference was statistically significant (both P<0.001). The phosphorylation level of STAT5a protein in ASA group (1.166±0.096) was significantly higher than that in ASS group (0.923±0.018) and healthy subjects (0.911±0.017), the difference was statistically significant (both P<0.001). The phosphorylation level of STAT5b protein in ASA group (0.81±0.05) was significantly higher than that in ASS group (0.21±0.03) and healthy subjects (0.24± 0.07), the difference was statistically significant (both P<0.001). The difference of plasma IL-2 concentration among the three groups was statistically significant ( F=3.32, P=0.040). The IL-2 concentration in the ASA group [(110±40) pg/ml] was significantly higher than that in the ASS group [(89±40) pg/ml] and the healthy group [(88±39) pg/ml], the difference was statistically significant ( P=0.044, P=0.016). ② Spearman correlation analysis showed that STAT5a mRNA expression level was positively correlated with platelets in AS patients ( r=0.353, P=0.006). JAK3 mRNA expression level in ASA group was positively correlated with IL-2 concentration ( r=0.766, P<0.001), and negatively correlated with estimated glomerular filtration rate ( r=-0.485, P=0.007). STAT5a mRNA expression level was positively correlated with erythrocyte sedimentation rate ( r= 0.680, P<0.001), and STAT5b mRNA expression level was positively correlated with hypersensitive C-reactive protein (CRP) ( r=0.823, P<0.001). ③ The ROC curve showed that JAK3 mRNA expression level predicted the area under ROC curve (AUC) of ASA with a 95% CI of 0.920 (0.853, 0.987), sensitivity and specificity of 86.7% and 90.0%, respectively. STAT5a mRNA expression level predicted the AUC 95% CI of ASA was 0.874 (0.787, 0.961), and the sensitivity and specificity were 96.7% and 66.7%, respectively. STAT5b mRNA expression level predicted the AUC 95% CI of ASA was 0.749 (0.617, 0.881), and the sensitivity and specificity were 73.3% and 80.0%, respectively. Conclusion:This study suggests that IL-2/JAK3/STAT5 may be involved in the pathogenesis of AS, and JAK3 mRNA can be used as a biological indicator to monitor the activity of AS disease.

Objective: To investigate the effects of glycogen synthase kinase-3β (GSK3β)/eukaryotic extension factor kinase 2 (eEF2K) signaling pathway on the process of pulmonary fibrosis through in vivo experiments, and find new ideas for clinical treatment of pulmonary fibrosis. Methods: The pulmonary fibrosis model of C57BL/6 male mice was induced by bleomycin with intratracheal injection at the dose of 2 mg/kg. After 14 days of modeling, animals were divided into model group, negative inhibition group and inhibition group (n=5 for each group), and control group was not processed. The inhibition group was treated with TDZD-8 (4 mg/kg) after modeling, the negative inhibition group was given DMSO solution after modeling, and the samples were collected after 28 days. Hematoxylin-eosin staining method was used to detect lung fibrosis in mice and scored according to Ashcroft scale. Expression levels of GSK3β, p-GSK3β, eEF2K, p-eEF2K (Ser70, Ser392, Ser470), precursor protein of matrix metalloproteinase-2 (pro-MMP-2), matrix metalloproteinase-2 (MMP-2), collagen I (Col I), collagen Ⅲ (Col Ⅲ) and α-smooth muscle actin (α-SMA) were detected by Western blot. Results: Compared with control group, the fibrosis score was up-regulated, the expression levels of GSK3β, p-GSK3β, p-eEF2K (Ser70, Ser392, Ser470), pro-MMP-2, MMP-2, Col I, Col Ⅲ and α-SMA were increased, while that of eEF2K was decreased in model group (P＜0.05). Compared with model group, the fibrosis score, expression levels of GSK3β, p-GSK3β, p-eEF2K (Ser70, Ser392, Ser470), pro-MMP-2, MMP-2, Col I, Col Ⅲ and α-SMA were decreased, but the expression level of eEF2K was increased in inhibition group (P＜0.05). Conclusion: GSK3β can activate eEF2K by phosphorylation at the sites of Ser70, Ser392 and Ser470, increase the contents of fibrosis indicators, promote the formation of pulmonary fibrosis, and aggravate lung tissue lesions.
Animals ; Collagen ; Collagen Type I ; Elongation Factor 2 Kinase/metabolism* ; Eukaryota/metabolism* ; Fibrosis ; Glycogen Synthase Kinase 3 beta ; Male ; Matrix Metalloproteinase 2/metabolism* ; Mice ; Mice, Inbred C57BL ; Pulmonary Fibrosis/chemically induced* ; Signal Transduction

AIM: To construct and evaluate a diagnostic model based on transfer learning and data augmentation as a non-invasive tool for fusarium identification of fungal keratitis.

METHODS: A retrospective study. In this study, 2 157 images of fungal keratitis patients who underwent in vivo confocal microscopy examination in the Department of Ophthalmology of the people's Hospital of Guangxi Zhuang Autonomous Region from March 2017 to January 2020 were included as the dataset, which was classified according to the results of microbial culture. The dataset was subsequently randomly divided into training set(1 380 images), validation set(345 images)and test set(432 images). We used the transfer learning Inception-ResNet V2 network to construct a diagnostic model, and to compare the performance of the model trained on different datasets. The performance of the diagnostic model evaluated with specificity, sensitivity, accuracy, and area under the receiver operating characteristics curve(AUC).

RESULTS: The model trained with the original training set had a specificity rate of 71.6%, a sensitivity rate of 72.0%, an accuracy rate of 71.8% and AUC of 0.785(95%CI: 0.742-0.828, P<0.0001). And the model trained with the augmented training set had a specificity rate of 76.6%, a sensitivity rate of 83.1%, an accuracy rate of 79.9% and AUC of 0.876(95%CI: 0.843-0.909, P<0.0001), which made the model's prediction performance boost.

CONCLUSION: In this study, we constructed an intelligent diagnosis system for fungal keratitis fusarium through transfer learning, which has higher accuracy, and realized the intelligent diagnosis of fungal keratitis pathogen fusarium. Furthermore, we verified that the data augmentation strategy can improve the performance of the intelligent diagnosis system when the original dataset is limited, and this method can be used for intelligent diagnosis and identification of fungal keratitis pathogen fusarium.