OBJECTIVE To evaluate the clinical comprehensive value of four Chinese patent medicines （Xuezhikang， Zhibitai， Zhibituo， Jiangzhiling） in the treatment of hyperlipidemia， and provide a reference for rational clinical drug use. METHODS A clinical comprehensive evaluation index system was established in accordance with the Evidence and Value： Impact on Decision-Making （EVIDEM） framework and Technical Guideline for Clinical Comprehensive Evaluation of Cardiovascular Drugs （2022 edition， trial implementation）. CNKI， Wanfang data， VIP， PubMed， ScienceDirect， Embase and official websites were retrieved to collect the literature such as drug instructions， guidelines and consensus statements， and systematic reviews/meta-analyses for the four Chinese patent medicines. A comprehensive evaluation was conducted from seven dimensions： effectiveness， safety， economy， suitability， accessibility， innovation and characteristics of traditional Chinese medicine. RESULTS This evaluation index system included 7 first-level indicators， 15 second-level indicators and 30 third-level indicators. Xuezhikang achieved the highest comprehensive evaluation score of 81.4 points， and was classified as class Ⅰ recommendation. Zhibitai with 76.0 points and Zhibituo with 60.9 points were both classified as class Ⅱ recommendation. Jiangzhiling with 48.8 points was classified as class Ⅳ recommendation. CONCLUSIONS Xuezhikang demonstrates the optimal clinical comprehensive value for treating hyperlipidemia. Zhibitai exhibits certain advantages in terms of safety and characteristics of traditional Chinese medicine； Zhibituo shows a moderate performance in all aspects； Jiangzhiling has a relatively low score. Appropriate medicines can be selected clinically according to actual conditions and patients’ characteristics.

OBJECTIVE: To investigate the characteristics of central nervous system regulation in patients with refractory overactive bladder (rOAB) using resting-state functional magnetic resonance imaging (rs-fMRI), and to analyze the differences in brain function and connection between the patients and healthy population. METHODS: From May 1 to November 30, 2024, we performed rs-fMRI for 47 rOAB patients and another 47 matched healthy controls, documented relevant clinical data from all the participants and obtained their Overactive Bladder Symptom Scores (OABSS) and Overactive Bladder Questionnaire (OAB-Q) scores. Based on rs-fMRI, we compared the results of Independent Component Analysis (ICA), amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo) and degree centrality (DC) between the rOAB patients and healthy controls. RESULTS: The rOAB patients, in comparison with the healthy controls, showed dramatically higher daytime urination frequency (11.64 ± 3.85) vs (5.76 ± 0.91), nighttime urination frequency (3.72 ± 1.64) vs (0.31 ± 0.47), OABSS (8.22 ± 2.21) vs (0.64±0.78), OAB-Q1 score (20.85 ± 5.28) vs (6.78 ± 1.04), and OAB-Q2 score (45.04 ± 12.11) vs (14.51 ± 1.66) (all P<0.01). No statistically significant differences were observed in the results of ICA and ALFF between the right superior frontal and right middle frontal regions in the rOAB patients (P>0.05), but fALFF, ReHo and DC were significantly decreased in the patients compared with those in the healthy controls (P<0.01). CONCLUSION Compared with healthy population, the functions and connection of the frontal superior right and frontal middle right brain regions in rOAB patients are significantly down-regulated, which may serve as new therapeutic targets.
Humans ; Urinary Bladder, Overactive/physiopathology* ; Magnetic Resonance Imaging ; Brain/physiopathology* ; Female ; Male ; Adult ; Surveys and Questionnaires ; Case-Control Studies ; Middle Aged ; Rest ; Brain Mapping

To facilitate the early intelligent screening of pediatric genu valgum, this study develops a deep learning-based gait recognition model tailored for clinical application. The model is constructed upon a three-dimensional residual network architecture and incorporates a triplet attention module alongside a spatial hierarchical pooling module, jointly enhancing feature interaction across temporal, spatial, and channel dimensions. This design ensures an optimal balance between representational capacity and computational efficiency. Evaluated on a self-constructed dataset, the model achieves precision of 98.0%, 97.1%, and 96.5%, recall rates of 97.5%, 97.0%, and 95.0%, and F ₁-scores of 0.98, 0.97, and 0.96 on the training, validation, and test sets, respectively, demonstrating excellent recognition performance and strong generalization ability. Ablation experiments confirm the importance of the proposed model's core components in improving performance, and comparative experiments further highlight its significant advantages in recognition accuracy and robustness. Visualization experiments reveal that the model effectively focuses on key regions of gait images, with attention regions aligning closely with clinical anatomical landmarks, thereby enhancing the interpretability of the model's decision-making in clinical applications. In summary, the proposed model not only offers an efficient and reliable technical solution for early intelligent screening of genu valgum in children, but also provides a practical pathway for applying gait recognition technology in medical diagnosis.
Humans ; Gait ; Deep Learning ; Genu Valgum/physiopathology* ; Child ; Neural Networks, Computer ; Algorithms

Objective To identify high-risk factors for healthcare-associated infection(HAI)in patients in inten-sive care units(ICUs),and develop a quick response(QR)code-based APP prediction tool.Methods Information of inpatients in general ICUs of three hospitals in Guizhou Province from January to December 2024 were collected.Risk factors were analyzed with a logistic regression model.QR code-based APP was constructed and validated.Results A total of 1 782 patients in general ICUs of three hospitals in Guizhou Province in 2024 were included in the analysis,out of which 410 were HAI cases,and the incidence of HAI was 23.01％.Multivariate logistic regre-ssion analysis results of HAI in ICU inpatients showed that regional gross domestic product(GDP)≥58 685 Yuan,performing pathogen culture during this hospitalization,history of diabetes mellitus,history of cancer,length of hospital stay ≥7 days before infection,and duration of persistent fever＞5 days before infection were independent risk factors for HAI in ICU patients(all P＜0.05).The discrimination of the model(area under the receiver operating characteristic curve[AUC]of 0.841),calibration(Brier score of 0.129),and clinical effectiveness(net benefit of 11.4％when the risk threshold was 5％-74％)all performed well.Conclusion The QR code-based APP prediction tool is of great significance for scientific research transformation and precise HAI control.

Objective To identify high-risk factors for healthcare-associated infection(HAI)in patients in inten-sive care units(ICUs),and develop a quick response(QR)code-based APP prediction tool.Methods Information of inpatients in general ICUs of three hospitals in Guizhou Province from January to December 2024 were collected.Risk factors were analyzed with a logistic regression model.QR code-based APP was constructed and validated.Results A total of 1 782 patients in general ICUs of three hospitals in Guizhou Province in 2024 were included in the analysis,out of which 410 were HAI cases,and the incidence of HAI was 23.01％.Multivariate logistic regre-ssion analysis results of HAI in ICU inpatients showed that regional gross domestic product(GDP)≥58 685 Yuan,performing pathogen culture during this hospitalization,history of diabetes mellitus,history of cancer,length of hospital stay ≥7 days before infection,and duration of persistent fever＞5 days before infection were independent risk factors for HAI in ICU patients(all P＜0.05).The discrimination of the model(area under the receiver operating characteristic curve[AUC]of 0.841),calibration(Brier score of 0.129),and clinical effectiveness(net benefit of 11.4％when the risk threshold was 5％-74％)all performed well.Conclusion The QR code-based APP prediction tool is of great significance for scientific research transformation and precise HAI control.

In order to understand the genetic variation and whole genome characteristics of goose as-trovirus(GoAstV)in Jiangxi Province,a strain of GoAstV was successfully isolated from a typical gosling gout case sample and the whole genome sequencing and genetic characteristics of the isola-ted strain were analyzed.The results showed that the JXNC1 strain could be stably passaged on LMH cells and could cause mild cytopathic effects in LMH cells.Sequencing and analysis showed that the full-length genome of the strain was 7 173 bp,and its genetic relationship was the closest to the GZ2301(PP966939)reference strain,belonging to the GoAstV-Ⅱ genotype.The complete genome of JXNC1 strain shared 98.1％-98.8％nucleotide similarity with 22 GoAstV-Ⅱ reference strains,and the amino acid similarity of ORF2 gene was 97.6％-99.6％.At the same time,the analysis results showed that the mutation of the strain mainly occurred in the ORF2 gene,and there were 13 amino acid site mutations,of which T630I was a unique mutation.Animal regression experiments showed that the inoculation of JXNC1 strain could cause urate deposition in the or-gans of goslings,congestion and dilatation of hepatic sinusoids,and small focal necrosis of some hepatocytes.Renal tissue tubular dilatation,renal interstitial connective tissue hyperplasia.The re-sults of this study laid a foundation for accurate prevention and control of the disease.

In order to understand the genetic variation and whole genome characteristics of goose as-trovirus(GoAstV)in Jiangxi Province,a strain of GoAstV was successfully isolated from a typical gosling gout case sample and the whole genome sequencing and genetic characteristics of the isola-ted strain were analyzed.The results showed that the JXNC1 strain could be stably passaged on LMH cells and could cause mild cytopathic effects in LMH cells.Sequencing and analysis showed that the full-length genome of the strain was 7 173 bp,and its genetic relationship was the closest to the GZ2301(PP966939)reference strain,belonging to the GoAstV-Ⅱ genotype.The complete genome of JXNC1 strain shared 98.1％-98.8％nucleotide similarity with 22 GoAstV-Ⅱ reference strains,and the amino acid similarity of ORF2 gene was 97.6％-99.6％.At the same time,the analysis results showed that the mutation of the strain mainly occurred in the ORF2 gene,and there were 13 amino acid site mutations,of which T630I was a unique mutation.Animal regression experiments showed that the inoculation of JXNC1 strain could cause urate deposition in the or-gans of goslings,congestion and dilatation of hepatic sinusoids,and small focal necrosis of some hepatocytes.Renal tissue tubular dilatation,renal interstitial connective tissue hyperplasia.The re-sults of this study laid a foundation for accurate prevention and control of the disease.

The emerging biomedical industry has an increasing demand for the professional talents and puts forward higher requirements for the quality, especially the innovation ability of the talents. Exploring a new model for fostering the innovation ability of postgraduates majoring in biological and medical sciences based on the principle of integrating production, education and research is of practical significance for improving the quality of professional talents and empowering the bio-economic development. Taking the training of innovation ability of postgraduates majoring in biological and medical sciences at Jiangnan University as an example, this paper introduced a new training system of "six integration and six optimizations". This system included ideological guidance, discipline system, training program, faculty, research innovation platform, and communication and cooperation. Satisfactory cultivation results were achieved with this new system. This paper is expected to provide reference for the training of innovative talents in the biological and medical industry.
Biological Science Disciplines/education* ; China ; Biomedical Research ; Humans ; Inventions

Objective To investigate the expression of serum Maresin 1 and pro-platelet basic protein(PPBP)in patients with diabetes nephropathy(DN)and their correlation with long-term prognosis.Methods A total of 83 patients with diabetes nephropathy admitted to Tangshan Central Hospital from May 2018 to May 2020 were selected as the diabetes nephropathy group.In the same period,60 patients with simple type 2 diabetes were selected as the diabetes group and 60 healthy people as the control group.Enzyme linked immunosorbent assay(ELISA)was used to detect the levels of serum Maresin1 and PPBP.Spearman correlation analysis was used to analyze the correlation between the levels of serum Maresin1 and PPBP and renal pathological damage.COX proportional hazard regression analysis was used to analyze the factors influencing the long-term poor prognosis of patients with diabetes nephropathy.ROC curve was used to evaluate the predictive value of serum Maresin1 and PPBP for the long-term poor prognosis.Results The levels of serum Maresin1(15.90±4.53 ng/ml,12.34±4.29 ng/ml,9.65±4.38 ng/ml)in the control group,diabetes group and diabetes nephropathy group were decreased in turn while the levels of serum PPBP(263.45±85.22 pg/ml,349.28±80.49 pg/ml,435.76±87.21 pg/ml)were increased in turn,and the differences were statistically significant(F=35.159,72.678,all P＜0.05).With the increase of IFTA score,interstitial inflammation score,and glomerular grading,serum Maresin1 level was decreased(F=25.838,25.187,9.751,all P＜0.05),while serum PPBP level was increased(F=56.513,92.702,58.137,all P＜0.05),and the differences were statistically significant,respectively.Serum Maresin1 was negatively correlated with IFTA score,interstitial inflammation score,and glomerular grading(r=-0.637,-0.581,-0.594,all P＜0.05),while serum PPBP was positively correlated with IFTA score,interstitial inflammation score,and glomerular grading(r=0.659,0.664,0.608,all P＜0.05),with significant differences.The course of diabetes nephropathy(HR=1.135,95％CI:1.012～1.370),24-hour urinary protein(HR=1.087,95％CI:1.016～1.164),PPBP(HR=1.208,95％CI:1.119～1.365),and IFTA score(HR=1.139,95％CI:1.024～1.219),interstitial inflammation score(HR=1.122,95％CI:1.006～1.249)and glomerular grading(HR=1.139,95％CI:1.052～1.273)were independent risk factors for long-term prognosis of diabetes nephropathy patients,while eGFR(HR=0.934,95％CI:0.892～0.993)and Maresin1(HR=0.903,95％CI:0.816～0.982)were protective factors for long-term prognosis(all P＜0.05).The areas under the curve(AUC)of serum Maresin1,PPBP and two indicators combined to predict the long-term poor prognosis of patients with diabetes nephropathy were 0.781,0.777 and 0.901,respectively.The AUC of two indicators combined was higher than that,and the differences were significant(Z=3.049,3.258,all P＜0.05).Conclusion In patients with diabetes nephropathy,serum Maresin1 was decreased and PPBP was increased,and the two indexes were closely related to the degree of renal injury.The combined test could effectively predict the long-term poor prognosis of patients.

Sodium-glucose linked transporter 2 inhibitors（SGLT2i） are novel oral hypoglycaemic agents and are widely used for hypoglycemic therapy in patients with type 2 diabetes mellitus， but differences in the genetic backgrounds of patients often lead to variable responsiveness to drug therapy. By summarizing the pharmacogenomic studies of SGLT2i， the article found that the genetic variants of UGT1A9， UGT2B4， SLC5A2， ABCB1， PNPLA3 and WFS1 may influence the pharmacokinetics of SGLT2i and the external hypoglycemic effects of SGLT2i in improving non-alcoholic fatty liver disease， weight loss and so on， but there is no clinical evidence that genetic polymorphisms affect the hypoglycemic efficacy of SGLT2i.