Addressing the enduring challenge of evaluating traditional Chinese medicines (TCMs), the integrated evidence chain-based effectiveness evaluation of TCMs (Eff-iEC) has emerged. This paper explored its capacity through a demonstration study that evaluated the effectiveness evidence of six commonly used anti-hepatic fibrosis Chinese patent medicines (CPMs), including Biejiajian Pill (BP), Dahuang Zhechong Pill (DZP), Biejia Ruangan Compound (BRC), Fuzheng Huayu Capsule (FHC), Anluo Huaxian Pill (AHP), and Heluo Shugan Capsule (HSC), using both Eff-iEC and the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system. The recognition of these CPMs within the TCM academic community was also assessed through their inclusion in relevant medical documents. Results showed that the evidence of BRC and FHC received higher assessments in both Eff-iEC and GRADE system, while the assessments for others varied. Analysis of community recognition revealed that Eff-iEC more accurately reflects the clinical value of these CPMs, exhibiting superior evaluative capabilities. By breaking through the conventional pattern of TCMs effectiveness evaluation, Eff-iEC offers a novel epistemology that better aligns with the clinical realities and reasoning of TCMs, providing a coherent methodology for clinical decision-making, new drug evaluations, and health policy formulation.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

This study aims to investigate the protective effects and mechanisms of polysaccharide extract PCP1 from Polygonatum cyrtonema in ameliorating cerebral ischemia-reperfusion(I/R) injury in rats through modulation of the Toll-like receptor 4(TLR4)/NOD-like receptor protein 3(NLRP3) signaling pathway. In vivo, SD rats were randomly divided into the sham group, model group, PCP1 group, nimodipine(NMDP) group, and TLR4 signaling inhibitor(TAK-242) group. A middle cerebral artery occlusion/reperfusion(MCAO/R) model was established, and neurological deficit scores and infarct size were evaluated 24 hours after reperfusion. Hematoxylin-eosin(HE) and Nissl staining were used to observe pathological changes in ischemic brain tissue. Transmission electron microscopy(TEM) assessed ultrastructural damage in cortical neurons. Enzyme-linked immunosorbent assay(ELISA) was used to measure the levels of interleukin-1β(IL-1β), interleukin-6(IL-6), interleukin-18(IL-18), tumor necrosis factor-α(TNF-α), interleukin-10(IL-10), and nitric oxide(NO) in serum. Immunofluorescence was used to analyze the expression of TLR4 and NLRP3 proteins. In vitro, a BV2 microglial cell oxygen-glucose deprivation/reperfusion(OGD/R) model was established, and cells were divided into the control, OGD/R, PCP1, TAK-242, and PCP1 + TLR4 activator lipopolysaccharide(LPS) groups. The CCK-8 assay evaluated BV2 cell viability, and ELISA determined NO release. Western blot was used to analyze the expression of TLR4, NLRP3, and downstream pathway-related proteins. The results indicated that, compared with the model group, PCP1 significantly reduced neurological deficit scores, infarct size, ischemic tissue pathology, cortical cell damage, and the levels of inflammatory factors IL-1β, IL-6, IL-18, TNF-α, and NO(P<0.01). It also elevated IL-10 levels(P<0.01) and decreased the expression of TLR4 and NLRP3 proteins(P<0.05, P<0.01). Moreover, in vitro results showed that, compared with the OGD/R group, PCP1 significantly improved BV2 cell viability(P<0.05, P<0.01), reduced cell NO levels induced by OGD/R(P<0.01), and inhibited the expression of TLR4-related inflammatory pathway proteins, including TLR4, myeloid differentiation factor 88(MyD88), tumor necrosis factor receptor-associated factor 6(TRAF6), phosphorylated nuclear factor-kappaB dimer RelA(p-p65)/nuclear factor-kappaB dimer RelA(p65), NLRP3, cleaved-caspase-1, apoptosis-associated speck-like protein(ASC), GSDMD-N, IL-1β, and IL-18(P<0.05, P<0.01). The protective effects of PCP1 were reversed by LPS stimulation. In conclusion, PCP1 ameliorates cerebral I/R injury by modulating the TLR4/NLRP3 signaling pathway, exerting anti-inflammatory and anti-pyroptotic effects.
Animals ; Toll-Like Receptor 4/genetics* ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Rats, Sprague-Dawley ; Rats ; Reperfusion Injury/genetics* ; Male ; Signal Transduction/drug effects* ; Polysaccharides/isolation & purification* ; Polygonatum/chemistry* ; Brain Ischemia/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Humans

Dysregulated RNA splicing is a well-recognized characteristic of colorectal cancer (CRC); however, its intricacies remain obscure, partly due to challenges in profiling full-length transcript variants at the single-cell level. Here, we employ high-depth long-read scRNA-seq to define the full-length transcriptome of colorectal epithelial cells in 12 CRC patients, revealing extensive isoform diversities and splicing alterations. Cancer cells exhibited increased transcript complexity, with widespread 3'-UTR shortening and reduced intron retention. Distinct splicing regulation patterns were observed between intrinsic-consensus molecular subtypes (iCMS), with iCMS3 displaying even higher splicing factor activities and more pronounced 3'-UTR shortening. Furthermore, we revealed substantial shifts in isoform usage that result in alterations of protein sequences from the same gene with distinct carcinogenic effects during tumorigenesis of CRC. Allele-specific expression analysis revealed dominant mutant allele expression in key oncogenes and tumor suppressors. Moreover, mutated PPIG was linked to widespread splicing dysregulation, and functional validation experiments confirmed its critical role in modulating RNA splicing and tumor-associated processes. Our findings highlight the transcriptomic plasticity in CRC and suggest novel candidate targets for splicing-based therapeutic strategies.
Humans ; Colorectal Neoplasms/metabolism* ; RNA Isoforms/metabolism* ; Single-Cell Analysis ; RNA Splicing ; Gene Expression Regulation, Neoplastic ; RNA, Neoplasm/metabolism* ; Transcriptome

Objective To propose an improved Y OLOv8-based visible small target detection method to solve the problems of the UAV visible light system in accuracy and timeliness when applied to measuring small targets.Methods A YOLOv8 network consisting of Backbone,Neck and Head was used as the base framework to construct an AGC-YOLO model.Firstly,a convolutional block attention module(CBAM)was incorporated into Backbone to improve the feature expression of the model;secondly,some traditional convolution modules were replaced with the changeable kernel convolution module AKconv to reduce the network parameters;finally,a Gold-YOLO module was involved in Neck to enhance the detection ability for targets with different sizes.VisDrone2019 dataset was used to carry out ablation and comparison experiments,and the efficacy of the AGC-YOLO model for detecting small targets was evaluated in terms of mean average precision(mAP),frames per second(FPS),giga floating-point operations per second(GFLOPs)and parameters.Results The AGC-YOLO model had the FPS,GFLOPs and parameters being 31.90,9.20 and 11.30 M respectively,meeting the real-time detection speed requirements of drones(FPS not lower than 30),in which the mAP50(the mAP with the intersection over union being 0.5)was increased by 15％,6％and 5％when compared with those of the lightweight YOLOv8n,Ghost-YOLO and YOLO-BiFPN models.Conclusion The method proposed behaves well in speed,decreased parameters and precision,and is worthy promoting for UAV visible small target detection.[Chinese Medical Equipment Journal,2025,46(1):1-6]

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.

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.

Objective To propose an improved Y OLOv8-based visible small target detection method to solve the problems of the UAV visible light system in accuracy and timeliness when applied to measuring small targets.Methods A YOLOv8 network consisting of Backbone,Neck and Head was used as the base framework to construct an AGC-YOLO model.Firstly,a convolutional block attention module(CBAM)was incorporated into Backbone to improve the feature expression of the model;secondly,some traditional convolution modules were replaced with the changeable kernel convolution module AKconv to reduce the network parameters;finally,a Gold-YOLO module was involved in Neck to enhance the detection ability for targets with different sizes.VisDrone2019 dataset was used to carry out ablation and comparison experiments,and the efficacy of the AGC-YOLO model for detecting small targets was evaluated in terms of mean average precision(mAP),frames per second(FPS),giga floating-point operations per second(GFLOPs)and parameters.Results The AGC-YOLO model had the FPS,GFLOPs and parameters being 31.90,9.20 and 11.30 M respectively,meeting the real-time detection speed requirements of drones(FPS not lower than 30),in which the mAP50(the mAP with the intersection over union being 0.5)was increased by 15％,6％and 5％when compared with those of the lightweight YOLOv8n,Ghost-YOLO and YOLO-BiFPN models.Conclusion The method proposed behaves well in speed,decreased parameters and precision,and is worthy promoting for UAV visible small target detection.[Chinese Medical Equipment Journal,2025,46(1):1-6]

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.