ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Objective Innovatively establish an information management model for the entire lifecycle of equipment ap-plicable to disease prevention and control centers.Methods An in-depth analysis of the current situation of equipment manage-ment and existing problems,relying on the laboratory information management system,combined with the theory of high-quality full-life-cycle management,incorporating advanced information technology management,and adoption of targeted measures to pro-mote the solution of problems one by one.Results Implement and improve the whole life cycle information management node,set up an equipment management committee,innovate the use of new equipment identification plates,develop a mobile platform client,and realize management data visualization.Conclusion The Informatisation management mode of the whole life cycle of equipment with the Center for Disease Control and Prevention characteristics.It realizes the whole life cycle,dynamic and Informatisation man-agement of equipment from demand,acceptance,use,maintenance,measurement,deactivation and scrapping.It strengthens the process management and quality control of equipment and serves to improve disease prevention and control capabilities.

Objective Innovatively establish an information management model for the entire lifecycle of equipment ap-plicable to disease prevention and control centers.Methods An in-depth analysis of the current situation of equipment manage-ment and existing problems,relying on the laboratory information management system,combined with the theory of high-quality full-life-cycle management,incorporating advanced information technology management,and adoption of targeted measures to pro-mote the solution of problems one by one.Results Implement and improve the whole life cycle information management node,set up an equipment management committee,innovate the use of new equipment identification plates,develop a mobile platform client,and realize management data visualization.Conclusion The Informatisation management mode of the whole life cycle of equipment with the Center for Disease Control and Prevention characteristics.It realizes the whole life cycle,dynamic and Informatisation man-agement of equipment from demand,acceptance,use,maintenance,measurement,deactivation and scrapping.It strengthens the process management and quality control of equipment and serves to improve disease prevention and control capabilities.

Family with sequence similarity 3 member A(FAM3A),a novel mitochondrial protein,plays a pivotal role in hepatic glucose and lipid metabolism by enhancing ATP synthesis and secretion and mod-ulating the ATP-P2 receptor-Akt signaling pathway.Dysregulation of FAM3A is closely associated with the pathogenesis of non-alcoholic fatty liver disease(NAFLD)and type 2 diabetes mellitus(T2DM).In this study,targeting FAM3A as a therapeutic candidate,we conducted virtual screening to identify 47 small-molecule compounds with potential binding activity.Surface plasmon resonance(SPR)analysis re-vealed three compounds exhibiting high binding affinity to FAM3 A.Further structural characterization of the FAM3A-compound complexes,combined with intermolecular interaction analysis,elucidated the binding mode of the lead compound Index 2(taxifolin)to FAM3A at atomic resolution.These findings provide critical insights into the molecular mechanisms underlying ligand-FAM3A interactions and deliver valuable chemical scaffolds for the development of therapeutics targeting NAFLD and T2DM.This work establishes a foundation for advancing drug discovery efforts focused on FAM3A-mediated metabolic disor-ders.

Objective To develop a single-person breast surgery teaching system to improve the teaching efficiency of breast surgery.Methods The single-person breast surgery teaching system consisted of a magnetic suspension and retraction device and a breast model.The magnetic suspension and retraction device was composed of a magnetic suspension component and a magnetic retraction component,of which,the magnetic suspension component included a bracket,an outer magnet and an inner magnet and the magnetic retraction component comprised a magnetic base and an elastic grasping forceps.The breast model was established with porcine abdominal tissue obtained from slaughterhouses.Twelve surgical trainees were randomized into an experimental group(n=6)and a control group(n=6),and the 2 groups performed flap release operations on the breast model with skin-preserving mastectomy as the target procedure.The operation was carried out with the developed system in the experimental group and with the traditional procedure in the control group.Results The two groups had the flap-free operation on the breast model finished successufully,which had no significant differences in the length of incision(P>0.05);the experimental group gained advantages over the control group in the number of assistants required,operation time,times of skin flap injuries,times of glandular injuries and effect of exposure,with the differences being statistically significant(all P<0.05).Conclusion The single-person breast surgery teaching system enhances the effect of exposure efficiently,meets the reequirements for single-person training and improves the teaching efficiency.[Chinese Medical Equipment Journal,2025,46(7):34-38]

Objective:To investigate the causal effects of plasma lipidomics on pancreatitis using Mendelian ran-domization(MR)and evaluate the roles of intra-pancreatic fat deposition(IPFD)and gallstone disease in this relation-ship.Methods:A bidirectional MR analysis was conducted,with 179 plasma lipids as exposures and acute pancreati-tis(AP)and chronic pancreatitis(CP)as outcomes.Data were sourced from genome-wide association studies(GWAS),the UK Biobank,and the FinnGen project.Two-step Mendelian randomization(TSMR)and multivariable Mendelian ran-domization(MVMR)analyses were applied to assess the mediating roles of IPFD and gallstone disease in the associa-tion between plasma lipids and pancreatitis.Results:MR analysis identified two sterols negatively associated with AP(P＜0.05)and seven sterols negatively associated with CP(P＜0.05).One phospholipid showed a positive association with CP(P＜0.05).IPFD was positively associated with both AP and CP.Gallstone disease was confirmed as a risk fac-tor for AP.However,TSMR analysis indicated that neither IPFD nor gallstone disease mediated the relationship be-tween plasma lipids and pancreatitis.Conclusion:The causal relationship exists among plasma lipomics and AP/CP,also between IPFD,cholelithiasis and pancreatitis.These findings highlight novel risk factors and potential biomarkers to support early diagnosis and intervention for pancreatitis.

Background:Optimizing cultivation techniques for traditional Chinese medicine has become a crucial means to improve the quality of medicinal materials.Microbial agents,as environmentally friendly and efficient plant growth promoters and soil conditioners,have increasingly attracted attention in eco-agriculture research.Objective:Our understanding remains limited regarding how the application of microbial agents,alone or in combination,affects changes in the rhizosphere microbiome and its association with the bioactive components of medicinal materials.Methods:In this study,Epimedium pubescens Maxim.was employed as a model plant to examine the effects of 2 microbial agents(Paenibacillus mucilaginosus and Bacillus subtilis)applied individually and in combination on plant growth and the accumulation of bioactive components.Additionally,this study explored the relationship between the rhizosphere microbiome and plant development.Results:The application of microbial agents increased the yield of E.pubescens leaves by 20.30％to 33.66％and enhanced the total flavonol glycosides content by 11.40％to 29.94％.Meanwhile,microbial treatments reshaped the rhizosphere microbiome,promoted the enrichment of beneficial microorganisms(e.g.,Frankia and Paenibacillus),suppressed phytopathogenic fungi such as Didymella and Scytalidium,and enhanced the stability of the soil microbial co-occurrence network.The partial least squares path model suggested that microbial agents not only directly impact the quality of medicinal herbs but also indirectly alter the accumula-tion of bioactive components by modulating the soil microbiome.Conclusion:These findings deepen our understanding of the relationship between medicinal plant quality and rhizosphere micro-biomes as mediated by microbial agents.They also provide a basis for designing and manipulating synthetic microbial communities to promote sustainable development in eco-agriculture.

Family with sequence similarity 3 member A(FAM3A),a novel mitochondrial protein,plays a pivotal role in hepatic glucose and lipid metabolism by enhancing ATP synthesis and secretion and mod-ulating the ATP-P2 receptor-Akt signaling pathway.Dysregulation of FAM3A is closely associated with the pathogenesis of non-alcoholic fatty liver disease(NAFLD)and type 2 diabetes mellitus(T2DM).In this study,targeting FAM3A as a therapeutic candidate,we conducted virtual screening to identify 47 small-molecule compounds with potential binding activity.Surface plasmon resonance(SPR)analysis re-vealed three compounds exhibiting high binding affinity to FAM3 A.Further structural characterization of the FAM3A-compound complexes,combined with intermolecular interaction analysis,elucidated the binding mode of the lead compound Index 2(taxifolin)to FAM3A at atomic resolution.These findings provide critical insights into the molecular mechanisms underlying ligand-FAM3A interactions and deliver valuable chemical scaffolds for the development of therapeutics targeting NAFLD and T2DM.This work establishes a foundation for advancing drug discovery efforts focused on FAM3A-mediated metabolic disor-ders.

One of the basic questions in the aging field is whether there is a fundamental difference between the aging of lower invertebrates and mammals. A major difference between the lower invertebrates and mammals is the abundancy of noncoding RNAs, most of which are not conserved. We have previously identified a noncoding RNA Terc-53 that is derived from the RNA component of telomerase Terc. To study its physiological functions, we generated two transgenic mouse models overexpressing the RNA in wild-type and early-aging Terc-/- backgrounds. Terc-53 mice showed age-related cognition decline and shortened life span, even though no developmental defects or physiological abnormality at an early age was observed, indicating its involvement in normal aging of mammals. Subsequent mechanistic study identified hyaluronan-mediated motility receptor (Hmmr) as the main effector of Terc-53. Terc-53 mediates the degradation of Hmmr, leading to an increase of inflammation in the affected tissues, accelerating organismal aging. adeno-associated virus delivered supplementation of Hmmr in the hippocampus reversed the cognition decline in Terc-53 transgenic mice. Neither Terc-53 nor Hmmr has homologs in C. elegans. Neither do arthropods express hyaluronan. These findings demonstrate the complexity of aging in mammals and open new paths for exploring noncoding RNA and Hmmr as means of treating age-related physical debilities and improving healthspan.
Animals ; Mice ; RNA, Untranslated/metabolism* ; Aging/genetics* ; Mice, Transgenic ; Telomerase/metabolism* ; RNA/genetics* ; Hippocampus/metabolism* ; Humans ; Mice, Inbred C57BL