ObjectiveTo explore the academic characteristics of contemporary renowned Chinese medicine masters in treating diabetic kidney disease （DKD） from the perspectives of principles， methods， formulas， and medications. MethodsIn strict accordance with the Systematic Review of Text and Opinion （SrTO） process developed by the Joanna Briggs Institute （JBI）， an Australian evidence-based healthcare center， the databases including China National Knowledge Infrastructure （CNKI）， VIP Database， Wanfang Data， and China Biomedical Literature Service System （SinoMed） were searched. Based on predefined inclusion and exclusion criteria， text information extraction， quality evaluation， and text information synthesis were conducted sequentially. The data were analyzed and presented in the form of text and figures. ResultsA total of 215 articles related to 43 contemporary renowned experts in the fields of Chinese medicine nephrology and endocrinology were included. The study found that the academic thoughts of these masters in the treatment of DKD are extensive， involving multiple levels such as disease understanding， therapeutic strategies， formula application， and medication use. In terms of disease understanding， the primary pathogenesis is characterized by deficiency in the root and excess in the manifestation. It is emphasized that internal factors， such as congenital endowment deficiency， interact with external factors such as improper diet， emotional disturbances， invasion of exogenous pathogens， and delayed or inappropriate treatment， to jointly induce the disease. This further gives rise to various pathogenetic theories， including obstruction of renal collaterals by blood stasis， toxin-induced damage to renal collaterals， latent wind disturbing the kidney， and internal heat leading to mass formation. In terms of therapeutic strategies and medication use， the principal treatment method is to replenish Qi and nourish Yin. Stage-based and syndrome-differentiated treatments are advocated. Flexible use of insect-derived drugs and wind-dispelling drugs is emphasized， along with proficiency in applying classical formulas and drug pairs. Integrated internal and external treatments， as well as the combined application of multiple therapeutic approaches， are commonly employed for comprehensive management. Meanwhile， the concept of "preventive treatment of disease" is upheld， and individualized long-term management of patients is advocated. ConclusionThrough the SrTO process， the academic thoughts of contemporary renowned Chinese medicine masters in the treatment of DKD have been systematically and standardly synthesized， providing a scientific and standardized basis for future theoretical exploration.

ObjectiveTo explore the academic characteristics of contemporary renowned Chinese medicine masters in treating diabetic kidney disease （DKD） from the perspectives of principles， methods， formulas， and medications. MethodsIn strict accordance with the Systematic Review of Text and Opinion （SrTO） process developed by the Joanna Briggs Institute （JBI）， an Australian evidence-based healthcare center， the databases including China National Knowledge Infrastructure （CNKI）， VIP Database， Wanfang Data， and China Biomedical Literature Service System （SinoMed） were searched. Based on predefined inclusion and exclusion criteria， text information extraction， quality evaluation， and text information synthesis were conducted sequentially. The data were analyzed and presented in the form of text and figures. ResultsA total of 215 articles related to 43 contemporary renowned experts in the fields of Chinese medicine nephrology and endocrinology were included. The study found that the academic thoughts of these masters in the treatment of DKD are extensive， involving multiple levels such as disease understanding， therapeutic strategies， formula application， and medication use. In terms of disease understanding， the primary pathogenesis is characterized by deficiency in the root and excess in the manifestation. It is emphasized that internal factors， such as congenital endowment deficiency， interact with external factors such as improper diet， emotional disturbances， invasion of exogenous pathogens， and delayed or inappropriate treatment， to jointly induce the disease. This further gives rise to various pathogenetic theories， including obstruction of renal collaterals by blood stasis， toxin-induced damage to renal collaterals， latent wind disturbing the kidney， and internal heat leading to mass formation. In terms of therapeutic strategies and medication use， the principal treatment method is to replenish Qi and nourish Yin. Stage-based and syndrome-differentiated treatments are advocated. Flexible use of insect-derived drugs and wind-dispelling drugs is emphasized， along with proficiency in applying classical formulas and drug pairs. Integrated internal and external treatments， as well as the combined application of multiple therapeutic approaches， are commonly employed for comprehensive management. Meanwhile， the concept of "preventive treatment of disease" is upheld， and individualized long-term management of patients is advocated. ConclusionThrough the SrTO process， the academic thoughts of contemporary renowned Chinese medicine masters in the treatment of DKD have been systematically and standardly synthesized， providing a scientific and standardized basis for future theoretical exploration.

Background The contamination of public baths with Legionella pneumophila contamination has become a growing public health concern in recent years. However, research on its association with bacterial community characteristics in water samples remains limited. The integration of 16S rRNA sequencing and random forest modeling provides a new approach to elucidate the bacterial community characteristics of public bath water and their association with Legionella pneumophila contamination. Objective To investigate the bacterial community structure and diversity of public bath water in Shanghai, explore the association between Legionella pneumophila contamination and bacterial community characteristics, and identify key bacterial genera associated with contamination, thereby providing a scientific basis for formulating hygiene management regulations for public bath water. Methods From February to March 2023, water samples were collected from ten public baths in Shanghai which were selected based on business scale, regional distribution, and functional differences. Water quality parameters were evaluated, and the samples were categorized into Legionella-positive and Legionella-negative groups based on the detection results of Legionella pneumophila. The bacterial community structure, α-diversity, and β-diversity were analyzed using 16S rRNA sequencing. Redundancy analysis (RDA) was employed to examine the relationship between physicochemical factors and bacterial community diversity. A random forest model was employed to identify key bacterial genera distinguishing the two groups, with the importance of genera being evaluated based on the mean decrease accuracy (MDA). Results The oxygen consumption in the Legionella-positive group was significantly lower than that in the Legionella-negative group (mean values: 1.85 mg·L⁻¹ vs. 6.81 mg·L⁻¹, P< 0.05), while no significant differences were observed in other physicochemical indicators. The sequencing results revealed a total of 27 bacterial phyla and 454 bacterial genera, with Proteobacteria (63.00%) being the dominant phylum. The dominant genera included Pelomonas (8.50%), Acidovorax (8.13%), Mycobacterium (7.93%), and Acinetobacter (6.59%). The α-diversity analysis indicated that bacterial community richness (Chao1 and ACE indices) was significantly higher in the Legionella-positive group than in the Legionella-negative group (P<0.01). The β-diversity analysis showed no significant difference in the bacterial community structure between the two groups (P>0.05). The RDA analysis demonstrated that the bacterial community diversity was positively correlated with pH and negatively correlated with oxygen consumption and free residual chlorine. The RDA1 and RDA2 explained 23.92% and 21.30% of the bacterial community diversity, respectively. The random forest model identified 20 key genera significantly influencing the microbial community distribution between the two groups, including unclassified_Bradyrhizobiaceae (MDA=2.42), Meiothermus (MDA=2.37), and Flavihumibacter (MDA=2.26). Conclusion The diversity of bacterial communities in public bath water is influenced by pH, oxygen consumption, and free residual chlorine. Samples contaminated with Legionella pneumophila exhibit greater microbial richness and contain characteristic key bacterial genera that contribute to community differences. Machine learning random forest technology helps identify these distinctive key bacterial genera. The findings provide a basis for carrying out risk early warning strategies in such settings.

ObjectiveTo explore the mechanism of Yishen Qubi Tongluo Formula （益肾祛痹通络方， YQTF） in the treatment of rheumatoid arthritis（RA）. MethodsNetwork pharmacology was employed to retrieve and screen the active components and potential targets of YQTF as well as RA-related targets using databases including TCMSP， BATMAN， ETCM and GEO. The intersection of targets related to active components and RA-related targets was identified， and a protein-protein interaction （PPI） network was constructed. Gene Ontology （GO） functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis were performed， and a drug-active component-common target network of YQTF in the treatment of RA was established. The core components of YQTF were molecularly docked with key targets. Human rheumatoid arthritis synovial fibroblast cell line MH7A was divided into blank group， model group， methotrexate group and YQTF group. The blank group was cultured with 10% fetal bovine serum， while the other three groups were stimulated with 10 μg/L of recombinant human tumor necrosis factor-α （TNF-α） for 24 h to establish the RA cell model. On this basis， the methotrexate group was treated with methotrexate suspension at a concentration of 20 μmol/L， and the YQTF group was treated with 10% YQTF-medicated serum. After 48 h of intervention， the levels of TNF-α and interleukin-17A（IL-17A）contents in cell supernatants were detected by enzyme-linked immunosorbent assay （ELISA）， and mRNA expressions of phosphatidylinositol 3-kinase（PI3K）， protein kinase B（AKT） and mammalian target of rapamycin（mTOR） were detected by real-time quantitative polymerase chain reaction （RT-qPCR）. ResultsNetwork pharmacological analysis identified 209 active components and 583 potential target genes of YQTF， as well as 818 RA-related targets. A total of 29 common targets were obtained from the intersection of drug-related targets and RA-related targets. Quercetin，β-sitosterol， kaempferol， stigmasterol and luteolin were the core active components of YQTF for the treatment of RA， while matrix metalloproteinase-9 （MMP9）， prostaglandin-endoperoxide synthase 2 （PTGS2）， Toll-like receptor 4 （TLR4）， tumor protein p53 （TP53） and transcription factor AP-1 subunit JUN were the key targets. The GO and KEGG pathway enrichment analysis showed that the involved biological processes and pathways were mainly associated with antioxidant responses， PI3K-AKT signaling pathway and Toll-like receptor （TLR） signaling pathway. Molecular docking results showed that MMP9 and PTGS2 exhibited high binding affinities with quercetin， β-sitosterol， kaempferol， stigmasterol and luteolin； TLR4 exhibited high binding activities with β-sitosterol， stigmasterol and luteolin； and TP53 showed high binding affinity with luteolin. The results of cell experiments showed that compared with the control group， the contents of TNF-α and IL-17A as well as the mRNA expressions of AKT and mTOR in the model group significantly increased （P＜0.05 or P＜0.01）. Compared with the model group， all the above indicators significantly decreased in the YQTF group， while the contents of TNF-α and the mRNA expression of AKT significantly decreased in the methotrexate group （P＜0.05 or P＜0.01）. ConclusionThe mechanism of YQTF in the treatment of RA may be associated with reducing inflammatory cytokine secretion and inhibiting the activation of the PI3K-AKT-mTOR signaling pathway.

Asthma and cough variant asthma （CVA） are both chronic heterogeneous diseases characterized by airway microenvironment homeostasis disruption as their core pathological basis. In recent years， micro ribonucleic acid （miRNA）， as core post-transcriptional regulators， have been shown to finely modulate multiple critical signaling pathways， including Janus kinase/signal transducer and activator of transcription （JAK/STAT）， nuclear factor-κB （NF-κB）， transforming growth factor-β/Smad （TGF-β/Smad）， and phosphoinositide 3-kinase/protein kinase B （PI3K/Akt）， as well as various pathological processes such as airway epithelial barrier restoration， type 1 helper T cell（Th1）/Th2 immune balance， M1/M2 macrophage polarization， airway smooth muscle cell function， and airway hyperresponsiveness. miRNAs play a pivotal role in maintaining and disrupting airway microenvironment homeostasis. Based on recent Chinese and international literature， a logical framework centered on "airway microenvironment homeostasis disruption， miRNA regulation， and microenvironment restoration" was constructed. From the perspective of the airway microenvironment， the therapeutic roles of miRNA in asthma and CVA were systematically summarized， and the cascade regulatory mechanisms of miRNA throughout the entire disease course were elucidated. The hub miRNA was identified， and research progress on traditional Chinese medicine intervention strategies was explored. Furthermore， current clinical studies on RNA therapeutics and traditional Chinese medicine in achieving multi-target and multi-pathway integrated treatment by modulating miRNA were analyzed. The value of miRNA as biomarkers for diagnosis， phenotyping， and prognosis assessment， as well as the potential and application prospects of miRNA mimics and antagonists in precision therapy， were summarized， with the ultimate goal of advancing precision therapy for asthma and CVA.

ObjectiveTo investigate the molecular mechanisms by which Acan-Gal-1 regulates macrophage immune phenotypes and Annexin A2/S100A10 membrane translocation in Angiostrongylus cantonensis. MethodsImmunofluorescence assay （IFA） was performed to determine the subcellular localization of Annexin A2 and S100A10 in macrophages. Flow cytometry and ELISA were used to assess functional changes in macrophage. siRNA interference of Annexin A2 was used to detect the effect of Acan-Gal-1 on various indicators. The expression levels of related genes and proteins were analyzed by Western blot， qRT-PCR， and ELISA methods. Bioinformatics analyses were conducted to characterize the structural features of Acan-Gal-1， and sequence alignment and molecular interaction prediction were performed to explore its potential interaction with Annexin A2. ResultsThis study found that Acan-Gal-1 can reverse LPS-induced promotion of macrophage migration and phagocytic function； it significantly upregulated M2-type markers in macrophages （Arg-1， IL-10， TGF-β） while inhibiting the expression of M1-type markers （iNOS， IL-6， IL-1β） induced by LPS. Acan-Gal-1 reduced the protein levels of Annexin A2 in macrophages under an immunologically activated state； after interfering with Annexin A2 expression， Acan-Gal-1 not only fails to induce macrophages to transition to an immunologically inhibitory phenotype but also fails to inhibit LPS-induced transition of macrophages to an immunologically activated phenotype. Although Acan-Gal-1 did not affect the expression of Annexin A2 or its chaperone protein S100A10 in macrophages， it markedly promoted their translocation to the plasma membrane. ConclusionsAcan-Gal-1 facilitates the enrichment of the Annexin A2/S100A10 complex at the macrophage membrane， thereby exerting immunomodulatory effects on macrophage polarization.

Objective:To analyze the contamination characteristics and pathogenic potential of Listeria monocytogenes (LM) in pre-packaged and refrigerated ready-to-eat cooked meat products in Chengdu City. Methods:From September 2022 to May 2023, pre-packaged and refrigerated ready-to-eat cooked meat products were collected from six districts and counties in Chengdu City. Qualitative and quantitative determination of LM was performed on these samples. Whole genome sequencing was carried out on the isolated strains. Different ST strains were selected for cell adhesion and invasion experiments. The results were expressed as adhesion rate and invasion rate. One-way ANOVA was used for comparison between groups, and the Dunnett t-test was used for pairwise comparison. Results:A total of 145 samples were collected, and LM was detected and isolated in 29 samples. The total detection rate was 20.00%, and the detection rate of braised pork was the highest (68.18%). The contamination level of LM in 9 samples (31.03%) was greater than 100.00 MPN/g. The 29 strains of Listeria monocytogenes belonged to 7 STs, including ST 3 (27.59%), ST 8 (17.24%) and ST 87 (13.79%). The strain of ST 87 carried Listeria pathogenicity islands 4 (LIPI-4), which was a highly virulent strain. The medium and high virulence strains accounted for 79.31%. Some moderately virulent and highly virulent strains of ST 8 and ST 87 were closely related to clinical patient strains. Some LM isolates of the same ST type had little SNP differences (1-6) in the same manufacturer at different stages. In vitro cell experiments showed that the highly virulent strain ST 87 had the strongest adhesion and invasion ability towards Caco-2 cells. Conclusion:The pre-packaged and refrigerated cooked meat products have a high contamination rate. Some samples have high contamination levels and carry medium and high virulence strains, posing potential health risks to human beings. LM residues continue to persist in some manufacturers′ production and processing stages.

Objective:To develop CNN-Dinov2, a deep learning-based automatic classification model for Gram-stained images, enabling rapid diagnosis of three prevalent Gram-negative bacilli in bloodstream infections: Escherichia coli ( E.coli), Klebsiella pneumoniae ( K.pneumoniae), and Pseudomonas aeruginosa ( P.aeruginosa). Methods:This evaluation study analyzed 1 425 Gram-stained microscopic images from patients with bloodstream infections at Houjie Hospital, in Dongguan City, collected between January 2023 and January 2024. The images, all positive for blood culture and identified as target strains, were categorized into Escherichia coli (419 images), Klebsiella pneumoniae (411 images), Pseudomonas aeruginosa (413 images), and other Gram-negative bacilli (182 images). They were randomly split into a training set (1 141 images), a validation set (141 images), and a test set (143 images) in an 8∶1∶1 ratio. A hybrid CNN-Dinov2 model was developed by integrating ResNet′s local feature extraction with Dinov2′s global pre-trained features, followed by a fully connected layer. The model was optimized by inputting the preprocessed images and adjusting parameters through loss calculation and backpropagation. AlexNet, Dinov2, and ResNet18 served as control models. The models′ classification performance was assessed using accuracy, precision, weighted F1 score, and recall rate, derived from the confusion matrix. The PR curve and AP value further evaluated each model′s classification capability across the four image categories. Results:The CNN-Dinov2 model achieved a training accuracy of 99.74%, a validation accuracy of 98.12%, and a validation loss of 0.070 6, demonstrating robust generalization without overfitting. Validation metrics revealed superior performance with an accuracy of 98.60%, precision of 98.65%, a weighted F1 score of 98.60%, and a recall rate of 98.60%, outperforming other models. The confusion matrix confirmed its strong classification capability, with the highest sum of diagonal values for identifying four types of bacteria. The macro average precision (AP) values under the precision-recall (PR) curves were all 1, indicating excellent discrimination across all categories. Overall, the CNN-Dinov2 model exhibited the best performance among the four models evaluated.Conclusion:This study successfully developed CNN-Dinov2, an automated classification model for Gram staining images. It offers valuable support for the rapid diagnosis of bloodstream infections caused by Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa, demonstrating practical utility.

Hereditary diffuse leukoencephalopathy with spheroids (HDLS) is a rare case caused by a mutation in the colony-stimu-lating factor 1 receptor ( CSF1R) gene on chromosome 5. In this paper, we report a case of a young female patient with HDLS, mainly characterized by memory loss, cognitive impairment, delayed movement, and abnormal mental and behavioral states. Genetic testing revealed a missense mutation in the CSF1R gene.

Randomized controlled trials have long been regarded as the gold standard for evaluating vaccine efficacy. However, conducting randomized controlled trials to assess vaccines in real-world settings is often impractical due to limitations in research resources and ethical considerations. In recent years, the emulated target trial has emerged as a novel methodological framework that applies the design principles of randomized trials to observational studies. By using observational data to emulate the randomization and treatment assignment of a clinical trial, this approach enables the evaluation of vaccine effectiveness in the real world. The application of emulated target trials enhances the quality and applicability of real-world evidence. This article explains the fundamental principles, design elements, advantages, and limitations of using emulated target trials to evaluate vaccine effectiveness, providing methodological guidance for conducting such studies in China.