OBJECTIVE To investigate the application and influencing factors of sodium-dependent glucose transporters 2 inhibitors（SGLT-2i） in patients with heart failure with preserved ejection fraction（HFpEF） in the real world. METHODS Data from 358 patients with HFpEF who were hospitalized at the First Affiliated Hospital of Chongqing Medical University from May 2023 to May 2024 were retrospectively collected. The patients were divided into the SGLT-2i group and the non-SGLT-2i group based on whether they were prescribed SGLT-2i upon discharge. Baseline characteristics， comorbidities， and differences in drug treatment were compared between the two groups. Based on univariate analysis， multivariate Logistic regression analysis was performed to identify independent influencing factors of SGLT-2i use in patients with HFpEF， followed by further stratified analysis. RESULTS Among 358 HFpEF patients， the overall utilization rate of SGLT-2i was 33.5%. Combined with type 2 diabetes [OR＝9.063，95%CI（4.924-16.679） ] ， atrial fibrillation [OR＝3.135，95%CI（1.590-6.178） ] ， coronary artery heart disease [OR＝1.888，95%CI（1.072-3.327） ] and the use of loop diuretics [OR＝3.822， 95%CI （1.588-9.200） ] were all independent influencing factors for the use of SGLT-2i in patients with HFpEF （ P ＜0.05）. The results of the stratified descriptive analysis were consistent with those of the multivariate analysis， showing a higher utilization rate of SGLT-2i among patients with concomitant T2DM，atrial fibrillation， coronary artery heart disease， and those receiving loop diuretics （ P ＜0.05）； whereas the utilization rate of SGLT-2i was comparable across patients with different levels of renal function （ P ＞0.05）. CONCLUSIONS In the real-world clinical practice， the utilization of SGLT-2i in patients with HFpEF remains suboptimal， and treatment coverage still needs to be improved. Their use of SGLT-2i is primarily influenced by the presence of type 2 diabetes， atrial fibrillation， coronary artery heart disease， and the use of loop diuretics.

Objective: To review the relationship between 24 hour movement behaviors and physical and mental health among college students, in order to provide evidence to support health promotion and further research in universities. Methods: Following the Joanna Briggs Institude(JBI) scoping review guidelines, relevant studies published in databases from inception date to December 26, 2025 were searched, including PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure (CNKI) and Wanfang Data. For studies meeting the inclusion and exclusion criteria, a descriptive analysis was conducted to summarize the measurement tools used, adherence rates with guidelines, and the relationship between physical and mental health. Results: A total of 30 studies were included. Measurement tools exhibited a high heterogeneity, with questionnaires being the primary method. The rate of full adherence with 24 hour movement behaviors among college students was less than 30%. Moderate to vigorous physical activity and high quality sleep were associated with improvements in physical fitness, cardiopulmonary function, and mental health, while prolonged sitting was negatively associated with obesity and depression. Equivalent time substitution analysis indicated that increasing moderate to vigorous physical activity and reducing prolonged sitting could significantly improve health outcomes. Conclusions The adherence rate for 24 hour movement behaviors among college students is low and it is closely associated with physical and mental health. Future studies should standardize measurement tools, and implement targeted interventions based on the optimization of daily activity patterns.

ObjectiveThis study aimed to establish a monocrotaline （MCT）-induced pulmonary arterial hypertension （PAH） rat model to systematically evaluate the protective effect of Xiao Qinglongtang （XQLT） on right cardiac function in model rats and further elucidate the underlying regulatory mechanism. MethodsSixty male SD rats were randomly assigned to the normal group， model group， XQLT low-， medium-， and high-dose groups （XQLT-L/M/H）， and the beraprost sodium tablet group （BST）. Except for the normal group， rats in all other groups were given a single subcutaneous injection of MCT （60 mg·kg^-1） to induce PAH. Three weeks after injection， rats in the XQLT-L/M/H groups were administered XQLT intragastrically at 3.07， 6.14， 12.28 g·kg^-1·d^-1， respectively. Rats in the BST group received beraprost sodium at 12.6 μg·kg^-1·d^-1， and rats in the model group received an equal volume of saline. All treatments lasted for 3 weeks. Right ventricular systolic pressure （RVSP） was measured by right ventricular catheterization. Cardiac function was assessed by echocardiography. The right ventricle was weighed to calculate the right ventricular hypertrophy index （RVHI）. Hematoxylin-eosin （HE） staining， Masson staining， and transmission electron microscopy were used to observe myocardial morphology. Serum metabolomic changes were analyzed using ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS）. Data-independent acquisition （DIA） proteomics was used to detect differentially expressed （DE） proteins in the right ventricle， and Western blot was used to measure the expression of uncoupling protein 3 （UCP3）， phosphatidylinositol 3-kinase catalytic subunit p110α （PIK3CA）， L1 cell adhesion molecule （L1CAM）， and quinone oxidoreductase （CRYZ）. UPLC-MS/MS was used to analyze the chemical components of XQLT. ResultsCompared with the normal group， the model group showed significantly increased RVSP and RVHI （P<0.05）， along with pathological changes in myocardial morphology. Compared with the model group， all XQLT-treated groups exhibited reductions in RVSP and RVHI as well as significant improvements in cardiac function and myocardial morphology. Among the XQLT groups， XQLT-M showed the most pronounced effects （P<0.05）， comparable to the BST group. Serum metabolomics revealed 105 differential metabolites in the XQLT groups versus the model group ［variable importance in projection （VIP） >1， P<0.05］， including 58 upregulated and 47 downregulated metabolites. KEGG enrichment analysis indicated that XQLT intervention downregulated phenylalanine metabolism （P<0.01） and upregulated unsaturated fatty acid biosynthesis （P<0.05）. Proteomics analysis showed that 982 DE proteins were identified in the MCT groups versus the normal group， including 455 upregulated and 527 downregulated proteins （|fold change （FC）| >1.3， P<0.05）. Compared with the model group， 237 DE proteins were identified in the XQLT groups， including 124 upregulated and 113 downregulated proteins （|FC| >1.3， P<0.05）， with 57 overlapping DE proteins. KEGG enrichment suggested that XQLT mainly modulated pathways related to mineral absorption， ribosomal biogenesis， peroxisomes， glycolysis/gluconeogenesis， spliceosomes， and thyroid hormone signaling. Western blot analysis showed that， compared with the model group， XQLT increased the expression of UCP3， PIK3CA， and L1CAM， while decreasing the expression of CRYZ （P<0.05）. ConclusionXQLT exerts a protective effect on right heart function in MCT-induced PAH rats， and its mechanism is associated with maintaining myocardial homeostasis and alleviating right ventricular remodeling.

Objective: To develop a dual-branch deep learning framework for accurate multi-label classification of fundus diseases, addressing the key limitations of insufficient complementary feature extraction and inadequate cross-modal feature fusion in existing automated diagnostic methods. Methods: The fundus multi-label classification dataset with 12 disease categories (FMLC-12) dataset was constructed by integrating complementary samples from Ocular Disease Intelligent Recognition (ODIR) and Retinal Fundus Multi-Disease Image Dataset (RFMiD), yielding 6 936 fundus images across 12 retinal pathology categories, and the framework was validated on both FMLC-12 and ODIR. Inspired by the holistic multi-regional assessment principle of the Five Wheels theory in traditional Chinese medicine (TCM) ophthalmology, the dual-branch multi-label network (DBMNet) was developed as a novel framework integrating complementary visual feature extraction with pathological correlation modeling. The architecture employed a TransNeXt backbone within a dual-branch design: one branch processed red-green-blue (RGB) images to capture color-dependent features, such as vascular patterns and lesion morphology, while the other processed grayscale-converted images to enhance subtle textural details and contrast variations. A feature interaction module (FIM) effectively integrated the multi-scale features from both branches. Comprehensive ablation studies were conducted to evaluate the contributions of the dual-branch architecture and the FIM. The performance of DBMNet was compared against four state-of-the-art methods, including EfficientNet Ensemble, transfer learning-based convolutional neural network (CNN), BFENet, and EyeDeep-Net, using mean average precision (mAP), F1-score, and Cohen's kappa coefficient. Results: The dual-branch architecture improved mAP by 15.44 percentage points over the single-branch TransNeXt baseline, increasing from 34.41% to 44.24%, and the addition of FIM further boosted mAP to 49.85%. On FMLC-12, DBMNet achieved an mAP of 49.85%, a Cohen’s kappa coefficient of 62.14%, and an F1-score of 70.21%. Compared with BFENet (mAP: 45.42%, kappa: 46.64%, F1-score: 71.34%), DBMNet outperformed it by 4.43 percentage points in mAP and 15.50 percentage points in kappa, while BFENet achieved a marginally higher F1-score. On ODIR, DBMNet achieved an F1-score of 85.50%, comparable to state-of-the-art methods. Conclusion DBMNet effectively integrates RGB and grayscale visual modalities through a dual-branch architecture, significantly improving multi-label fundus disease classification. The framework not only addresses the issue of insufficient feature fusion in existing methods but also demonstrates outstanding performance in balancing detection across both common and rare diseases, providing a promising and clinically applicable pathway for standardized, intelligent fundus disease classification.

ObjectiveThe malaria parasites remodel the host erythrocyte structure by exporting parasite proteins that interact with the membrane skeleton proteins of red blood cells (RBCs), facilitating their intracellular survival and pathogenicity. Skeleton-binding protein 1 (SBP1) is a conserved exported protein across Plasmodium species. In Plasmodium falciparum, SBP1 has been reported to interact with erythrocyte membrane skeleton proteins 4.1R and spectrin, while its contribution to erythrocyte remodeling and parasite virulence in Plasmodium berghei (Pb) remains unclear. This study aims to determine whether PbSBP1 associates with the host cytoskeletal protein 4.1R and to investigate its role in the remodeling of host RBCs and the pathogenicity of Plasmodium berghei. MethodsIn Plasmodium berghei, the relationship between PbSBP1 and the erythrocyte cytoskeletal protein 4.1R was examined using co-immunoprecipitation. A Pbsbp1 gene knockout mutant of Plasmodium berghei (Pbsbp1∆) was generated based on the principle of double crossover homologous recombination. The deformability of erythrocytes infected with Pbsbp1∆ parasites was assessed using microfluidic methods. Microchannels with an array of cylindrical pillars were used to detect modifications in infected RBC deformability. The infected RBCs were squashed between the rows and recovered between the columns and the transit velocity (μm/s) of infected RBCs travelling through the microchannel was recorded. The component of the erythrocyte membrane skeleton junctional complex, tropomodulin (TMOD), was fluorescently labeled, and the cytoskeletal network of infected erythrocytes was imaged using super-resolution stochastic optical reconstruction microscopy (STORM) to analyze ultrastructural changes in the cytoskeleton of wild-type (WT) and Pbsbp1∆-infected erythrocytes. Actin-based junctional complexes were displayed as individual clusters by the labeled TMOD in the STORM images, and the cluster densities and distances between adjacent clusters of infected RBCs were calculated. Additionally, rodent malaria models (BALB/c mice) and experimental cerebral malaria models (C57BL/6 mice) were employed to monitor the growth of Pbsbp1∆ and WT parasites during the intraerythrocytic stage and their capacity to induce cerebral malaria in mice. ResultsPbSBP1 may participate in the remodeling of infected erythrocytes through direct or indirect interaction with the erythrocyte cytoskeletal protein 4.1R. Microfluidic assays revealed that the deformability of erythrocytes infected with Pbsbp1∆ parasites was significantly enhanced compared to those infected with WT parasites. STORM imaging further demonstrated that the ultrastructure of the erythrocyte cytoskeleton in Pbsbp1∆-infected cells was altered relative to that in WT-infected erythrocytes. The distances between nearest neighbors of clusters had a tendency to increase while the cluster densities were decreased in Pbsbp1∆-infected RBCs compared to WT-infected RBCs. Subsequent phenotypic analysis indicated that the growth rate of Pbsbp1∆ parasites during the intraerythrocytic stage was significantly slower than that of WT parasites, and their ability to induce cerebral malaria in mice was also attenuated. These findings suggest that PbSBP1 is involved in the remodeling of the erythrocyte membrane skeleton, likely through its direct or indirect interaction with protein 4.1R, thereby regulating the deformability of infected erythrocytes and influencing the pathogenicity of the blood-stage parasites. ConclusionThis study establishes a role for PbSBP1 in host erythrocyte remodeling and parasite virulence, providing new research strategies for the prevention and treatment of malaria.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

Objective: To evaluate the efficacy and safety of ruxolitinib combined with low-dose hormone for patients with acute graft-versus-host disease (aGVHD) after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Methods: Thirty patients with aGVHD after allo-HSCT admitted to the Department of Hematology of the General Hospital of Western Theater Command from November 2021 to November 2024 were retrospectively analyzed. All patients were treated with low-dose hormone (methylprednisolone 0.3-1 mg kg -d ) combined with ruxolitinib 5-10 mg d . The efficacy and adverse reactions were observed during the follow-up period to analyze the survival outcomes of the patients. Results: A total of 30 patients with aGVHD after allo-HSCT were included in this study, consisting of 15 (50%) males and 15 (50%) females with a median age of 34 year-old (ranging from 14 to 62). Classification by disease type: there were 18 cases of acute myeloid leukemia, 4 cases of acute lymphoblastic leukemia, 4 cases of aplastic anemia, and 4 cases of myelodysplastic syndrome. Classification by aGVHD severity: there were 27 cases (90%) of Ⅱ-Ⅳ degree aGVHD and 11 cases (36.7%) of Ⅲ-Ⅳ degree aGVHD. Ruxolitinib in combination with low-dose glucocorticoid treatment yield responses in 28 (93.3%) patients, of which 27 (90%) achieved complete remission (CR), while 1 (3.3%) showed partial remission (PR). One patient (3.3%) had no response (NR), and 1 patient (3.3%) exhibited progressed disease (PD). Overall survival (OS) at 1 year of transplantation was 73.9% (95%CI 49.5% to 87.7%), progression-free survival (PFS) was 93.3% (95%CI 75.9% to 98.3%), non-relapse mortality (NRM) was 20.6% (95%CI 7.9% to 47.4%), and median survival time was 27.6 months. Conclusion: Ruxolitinib combined with low-dose hormones is safe and effective in the treatment of aGVHD after allo-HSCT.

Objective To explore the correlations of the severity degrees of coronary stenosis with cardiac function and exercise tolerance. Methods A total of 112 patients who underwent coronary angiography in Cardiology Department of Zhongshan Hospital, Fudan University between October 2024 and January 2025 were enrolled. According to the imaging results, the Gensini score was calculated, and the patients were divided into three groups based on the scores: mild group (＜20 points, n＝42), moderate group (20-40 points, n＝43), and severe group (＞40 points, n＝27). The left ventricular ejection fraction (LVEF), N-terminal pro-brain natriuretic peptide (NT-proBNP) level and its abnormal elevation ratio, 6-minute walk distance (6MWD), and grip strength were compared among the groups. The correlations between Gensini score and various indicators were analyzed using multivariate linear regression. And the multivariate binary logistic regression analysis was used to analyze the related factors of severe coronary stenosis. Results The 6MWD and LVEF values in the severe group were lower than those in the mild and moderate groups (P＜0.01), while the NT-proBNP level and its abnormal elevation ratio in the severe group were higher than those in the mild group (P＜0.05). The Gensini score was negatively correlated with 6MWD (β＝−0.965, P＜0.01), and positively correlated with NT-proBNP level and its abnormal elevation ratio (β＝0.015, P＜0.001; β＝0.003, P＝0.037). 6MWD and diabetes were independent related factors of severe coronary stenosis (OR＝0.956, P＜0.001; OR＝5.701, P＝0.038). Conclusions The cardiac function and exercise tolerance in patients with severe coronary stenosis decrease, 6MWD is helpful of recognizing severe coronary stenosis population.

ObjectiveThis study explored the risk factors for malignant risks of pulmonary nodules based on clinical data，constructed an integrated traditional Chinese and Western medicine model for predicting malignant risks of pulmonary nodules， and visualized the prediction results by using a nomogram. MethodsBased on a cross-sectional survey study design，patients with pulmonary nodules who were hospitalized in the Department of Respiratory and Cardiothoracic Surgery of Guangdong Provincial Hospital of Traditional Chinese Medicine from April 2023 to January 2024 were included. The dataset was randomly divided into a training set and a validation set according to 7∶3. In the training set，predictive factors were selected through univariate Logistic regression analysis and Least Absolute Shrinkage and Selection Operator （LASSO） regression analysis，and Logistic regression models were built. The discriminative ability，calibration，and clinical decision-making curves of the Western medicine model and the integrated traditional Chinese and Western medicine prediction model were compared to select the optimal model，which was then visualized in a nomogram. ResultsThis study included a total of 366 patients，and they were divided into a training set （258 cases） and a validation set （108 cases）. Seven predictive factors were considered including age，preference for fatty and greasy foods，history of environmental or occupational exposure，Qi deficiency，Yang deficiency，nodule density，and nodule diameter. A Logistic regression model was constructed. A Western medicine model，defined as model1，was created using only age，history of environmental or occupational exposure，nodule density，and nodule diameter as predictive factors. In addition，an integrated traditional Chinese and Western medicine model，defined as model2，was created by adding preference for fatty and greasy foods， Qi deficiency，and Yang deficiency as predictive factors. Model2 demonstrated better predictive performance in both the training and validation sets. Its accuracy in training set was 0.740，with precision of 0.825， recall of 0.829， F1 score of 0.827， the area under the curve （AUC）of 0.865 （95% confidence interval （CI）：0.815-0.915）， and a Brier score of 0.122. The accuracy in validation set was 0.731， with precision of 0.776， recall of 0.831， F1 score of 0.803， AUC of 0.852 （95%CI：0.776-0.927）， and a Brier score of 0.149. The calibration curve and decision-making curve analysis showed that this model exhibited good consistency and clinical utility in prediction. The equation for the malignant probability of pulmonary nodules was defined as p=eY/(1+eY)，where Y=-4.187+0.022×（age）+1.079×（history of environmental or occupational exposure）+0.718×（preference for fatty and greasy foods）+ 1.403×（Qi deficiency）+0.732×（Yang deficiency）+0.349×（pure ground glass density nodules）+1.304×（partially solid density nodules）+0.148×（nodule diameter）. A nomogram was used for intuitive representation. ConclusionThis study develops a comprehensive assessment model for the malignant risk of pulmonary nodules， which integrates factors from traditional Chinese medicine and Western medicine. Embedding traditional Chinese medicine elements in the prediction model allows for a multidimensional assessment of relevant risk factors for nodule malignancy. This demonstrates good diagnostic performance and provides a reference for early identification of lung cancer.