The oocyte， as the origin of life， provides half the chromosomes to the embryo and supplies the proteins， substrates， energy， and other support necessary for embryonic development. It is the decisive factor determining the embryo's developmental potential. Infertility caused by reproductive endocrine diseases targets the oocyte as the final target cell. Improving oocyte quality represents a key and difficult point in the field of modern reproductive medicine. The decline of oocyte quality is related to meiosis abnormalities， DNA damage， mitochondrial dysfunction， oxidative stress， and other mechanisms. For oocyte quality problems， there is no unified international guideline to recommend drugs. Because the drug intervention research on oocytes involves strict clinical ethical restrictions， the current relevant research only stays in the animal and in vitro experimental stage and has not yet been applied to the clinic. Traditional Chinese medicine compound formula has a multi-target and multi-pathway regulation mechanism and is widely used in clinics. More and more research began to pay attention to the potential mechanism of traditional Chinese medicine compound formulas in improving oocyte quality. Traditional Chinese medicine compound formula has the advantages of multi-target and multi-channel synergy as well as better safety， individualization， and conformity to clinical ethics in improving oocyte quality. This article systematically reviewed the research progress on traditional Chinese medicine compound formula interventions for oocyte quality， aiming to summarize existing findings and provide recommendations to improve oocyte quality and optimize the clinical diagnosis and treatment of female infertility within traditional Chinese medicine.

The oocyte， as the origin of life， provides half the chromosomes to the embryo and supplies the proteins， substrates， energy， and other support necessary for embryonic development. It is the decisive factor determining the embryo's developmental potential. Infertility caused by reproductive endocrine diseases targets the oocyte as the final target cell. Improving oocyte quality represents a key and difficult point in the field of modern reproductive medicine. The decline of oocyte quality is related to meiosis abnormalities， DNA damage， mitochondrial dysfunction， oxidative stress， and other mechanisms. For oocyte quality problems， there is no unified international guideline to recommend drugs. Because the drug intervention research on oocytes involves strict clinical ethical restrictions， the current relevant research only stays in the animal and in vitro experimental stage and has not yet been applied to the clinic. Traditional Chinese medicine compound formula has a multi-target and multi-pathway regulation mechanism and is widely used in clinics. More and more research began to pay attention to the potential mechanism of traditional Chinese medicine compound formulas in improving oocyte quality. Traditional Chinese medicine compound formula has the advantages of multi-target and multi-channel synergy as well as better safety， individualization， and conformity to clinical ethics in improving oocyte quality. This article systematically reviewed the research progress on traditional Chinese medicine compound formula interventions for oocyte quality， aiming to summarize existing findings and provide recommendations to improve oocyte quality and optimize the clinical diagnosis and treatment of female infertility within traditional Chinese medicine.

ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective:To analyze the epidemiological and clinical characteristics of influenza A/B virus (IAV/IBV) infection in children aged 0-4 years in Jining city from 2022 to 2024.Methods:A retrospective analysis was conducted on the data of 3 106 influenza affected children who visited two monitoring outpost hospitals in Jining city from January 2022 to January 2024. They were separated into two groups based on the type of virus infection: IAV group (n=1 829) and IBV group (n=1 277). Two groups were compared for general information, epidemiological characteristics, and laboratory test indicators.Result:The majority of influenza patients were boys (59.01%) and 1-4 years old (63.01%), with peak body temperature mainly ranging from 37.8 to 38.9 ℃ (59.30%). Coughing (69.00%) and runny nose (66.03%) were the main manifestations. The onset season was concentrated in winter (42.43%) and spring (40.44%), and the exposure target were family members (51.90%), and the proportion of influenza vaccine injections (20.90%) was relatively low. The proportions of visit time≤3 d, peak body temperature≥39.0 ℃, myocardial damage, liver function damage, white blood cell count (WBC) of 4-10×10 9/L, and neutrophil percentage (N)>70% in the IAV group were higher than those in the IBV group ( P<0.05). The proportions of preschool children and WBC>10×10 9/L in the IBV group were higher than those in the IAV group ( P<0.05). Conclusions:Children aged 0-4 years who are infected with IAV in Jining City are more common in terms of high fever, early medical attention, impaired heart and liver function, normal WBC, and abnormal N elevation compared to those infected with IBV. However, children aged 0-4 who are infected with IBV have abnormally high WBC and are more common in daycare.

To analyze the epidemiological characteristics and spatiotemporal distribution of pertussis in Tianjin City from 2010 to 2024. Data on pertussis cases reported in Tianjin between January 1, 2010, and December 31, 2024, were extracted from the Infectious Disease Surveillance and Reporting Information System of the China Information System for Disease Control and Prevention. Descriptive epidemiological methods and Joinpoint regression were used to analyze the temporal distribution and incidence trends of pertussis. Spatial autocorrelation analysis and spatial-temporal scanning were employed to characterize the spatial distribution and clustering patterns. The incidence rate of pertussis in Tianjin exhibited an overall upward trend from 2010 to 2024 (AAPC=17.04%, P<0.001), peaking at 11.70 per 100 000 population in 2023. Prior to 2020, the incidence peaked in July and August, whereas from 2023 to 2024, high incidence periods shifted to autumn and winter. The highest average annual incidence rate occurred in the <1-year-old group (165.06 per 100 000), followed by the 5-9-year-old group (20.14 per 100 000). The groups under 1 year old and 1-4 years old showed a trend of first increasing, then decreasing, and subsequently increasing again, with 2018 and 2021 as turning points ( P<0.05). Global spatial autocorrelation analysis revealed significant spatial clustering of pertussis cases in Tianjin districts in 2017 ( Moran′s I=0.19) and 2023 ( Moran′s I=0.51), with both P<0.05. The spatial-temporal scan analysis identified nine high-incidence clusters, with the primary cluster occurring in 2023, covering Jinnan, Dongli, and Hexi districts ( RR=7.37, LLR=568.21, P<0.001). In summary, the incidence of pertussis in Tianjin City has shown an upward trend from 2010 to 2024. The epidemiological characteristics have significantly changed around 2020, with pronounced seasonal and spatial clustering patterns observed in the past two years.

Objective:To investigate the feasibility of deep learning based on computed tomography(CT)radiomics in improving diagnostic accuracy for pulmonary nodules.Methods:A total of 500 patients with pulmonary nodules who admitted to our hospital from January 2023 to January 2024 were selected as study subjects,and they were randomly divided into a training set(350 patients)and a test set(150 patients)as 7:3 ratio.All patients underwent CT examination,and pathological diagnosis was used as gold standard to record pulmonary nodules that were judged by clinical judgment.The radiomics features were screened from the CT images of the patients,and these features were used to construct multiple machine learning models.The predictive value of different models in diagnosing pulmonary nodules was analyzed through confusion matrices and receiver operating characteristic(ROC)curve.Results:A total of 1,594 radiomics features,including 1,195 texture features(74.97%)that was the largest ratio,334 first-order histograms(20.95%),and 65 second-order histograms(4.08%),were extracted in this study.After least absolute shrinkage and selection operator(LASSO)regression analysis and ten-fold cross-validation processing,a total of six radiomics features were screened out.The screened radiomics features were incorporated respectively into four assembled models with machine learning,including ResNet50,DenseNet121,Inception_V3 and VGG19.The constructed models were evaluated respectively using the training set and the test set.The results showed that the assembled model had the highest accuracies in both training set and the test set(96.57%and 95.33%),which area under curve(AUC)values were 0.934 and 0.923,and specificities were 81.64%and 80.52%,and sensitivities were 90.25%and 88.71%,respectively.The results of consistency test indicated that the assembled model had the best classification consistency(Kappa=0.856,P<0.001)in the constructed diagnostic model for pulmonary nodule,which was the best-performing model.Conclusion:The deep learning technique based on CT radiomics has a certain feasibility in improving the diagnostic accuracy for pulmonary nodules,and the machine learning model that is included in this study has favorable predictive value in diagnosing pulmonary nodules.In them,the assembled model that is constructed on the basis of ResNet50,DenseNet121,Inception_V3,and VGG19 has better classification ability.

Objective To explore the protective effect of salidroside on retinal ganglion cells(RGC)in diabetic rats and its possible molecular mechanism.Methods Forty-five male SD rats were selected and randomly divided into the control group,the model group and the salidroside group,with 15 rats in each group.Diabetes models of rats were established in both the model group and the salidroside group.After successful modeling,rats in the salidroside group were given 50 mg/kg salidroside by gavage daily for 12 consecutive weeks,while rats in the model group received no further treatment.Rats in the control group were given the same amount of normal saline by gavage for 12 consecutive weeks.The fasting blood glucose of rats was detected every 4 weeks.After the experiment,the survival rate of rats in each group was calculated.Pathological HE staining was used to observe the pathological changes of retinal tissue in rats,and RGC counting was performed.The contents of reactive oxygen species(ROS),superoxide dismutase(SOD),malondialdehyde(MAD)and catalase(CAT)in the retinal tissue of rats were detected by ELISA.Western blot was used to detect the expressions of heme oxygenase-1(HO-1),Kelch-like ECH associated protein 1(Keap1),and nuclear factor E2-related factor 2(Nrf2)in the KEAP1-NrF2/HO-1 pathway.Results There was no statistically significant difference in the survival rate among the three groups of rats(P>0.05).The fasting blood glucose levels of rats in the control group fluctuated within the normal range at each time point.The fasting blood glucose levels of rats in the model group and the salidroside group were consistently higher than those in the control group(P<0.05).The fasting blood glucose level of rats in the salidroside group gradually decreased over time(P<0.05).Compared with the control group,the retinal thickness of rats in the model group became thinner,the cell arrangement showed obvious disordered phenomena,and there was obvious edema in the inner and outer nuclear layers and vacuole phenomena.The pathological changes of retinal tissue of rats in the salidroside group were improved compared with those in the model group.Compared with the control group,the contents of ROS and MAD and the protein expressions of Keap1 and Nrf2 in the retinal tissues of rats in the model group were significantly higher(P<0.05),while the contents of CAT and SOD,the number of RGC and the protein expression of HO-1 were significantly lower/less(P<0.05).After intervention with salidroside,the contents of each oxidative stress factor,the number of RGC,and the protein expressions of Keap1 and HO-1 of rats in the salidroside group were significantly reversed compared with the model group(P<0.05).Conclusion Intervention with salidroside can alleviate the oxidative stress response in the retina of diabetic rats and relieve RGC injury,which may exert its effect through the Keap1-Nrf2/HO-1 signaling pathway.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.