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.

Both type 2 diabetes mellitus (T2DM) and metabolic associated fatty liver disease (MAFLD) fall within the spectrum of metabolic diseases, and they exhibit a bi-directional causal relationship and robust reciprocal association. Their shared pathological cornerstone is insulin resistance (IR), which involves the interplay of mitochondrial dysfunction and chronic inflammation, forming a cascading pathological process of “IR-mitochondrial dysfunction-inflammation”. This largely explains the notable upward trend in T2DM-MAFLD co-occurrence observed over recent years. Exercise intervention, as a safe and effective non-pharmacological approach, can improve the pathological progression of these patients at multiple levels. Following the logical framework of “pathogenesis-efficacy comparison-molecular mechanisms-clinical translation”, this article systematically compares the efficacy and molecular mechanisms of moderate-intensity continuous training (MICT), resistance exercise, high-intensity interval training (HIIT), and combined training. MICT reduces intrahepatic triglycerides by promoting lipolysis and improving cardiorespiratory fitness; resistance exercise increases muscle mass and basal metabolic rate, offering unique advantages in preserving muscle while reducing fat and improving insulin sensitivity; HIIT is a time-efficient exercise modality that enhances patients’ cardiorespiratory fitness and insulin sensitivity by alternating brief periods of vigorous exertion with recovery periods, with a prominent short-term triglyceride-lowering effect; combined training produces synergistic effects, comprehensively improving glucolipid metabolism and showing the best long-term adherence. Mechanistically, exercise exerts its beneficial effects through three common pathways: (1) AMPK-mediated lipid oxidation and mitochondrial biogenesis; (2) IRS/PI3K/Akt-mediated insulin signaling sensitization; and (3) Nrf2/ARE anti-oxidation and TGF-β/Smads anti-fibrosis regulation. Different exercise modalities activate these pathways with distinct emphases: MICT most directly and persistently activates the AMPK pathway; resistance exercise uniquely improves IRS/PI3K/Akt signaling through muscle mass gain; HIIT induces the highest AMPK activation intensity and triggers unique lactate-mediated signaling regulation; combined training integrates the above multiple mechanistic advantages. For clinical translation, multidisciplinary team collaboration is essential to ensure safety and adherence. Individualized prescriptions should be formulated according to the FITT-VP principle and patient phenotypes—frequency of 3-5 sessions/week of aerobic exercise combined with 2-3 sessions/week of resistance exercise; intensity of moderate-intensity (40%-60% heart rate reserve (HRR))aerobic exercise and 60%-80% of one-repetition maximum (1-RM) for resistance exercise; time of at least 150 min/week of moderate-intensity aerobic exercise, 30-60 min per session; type of combined training as the preferred modality; total volume of≥500-1 000 MET-min/week; and progression adjusted every 4-6 weeks—with real-time adjustments supported by wearable devices, ultimately forming a closed-loop management system from initial assessment to long-term follow-up. Notably, current studies have limitations such as small sample sizes and short intervention periods. Future research should focus on long-term follow-up, multi-omics biomarkers, and combined exercise-drug strategies. In conclusion, the systematic integration of structured, individualized, and sustainable exercise interventions into the multidisciplinary management pathway for patients with T2DM complicated by MAFLD is an urgent need in current clinical practice.

Bone metastases are a common and serious complication of solid tumors such as breast cancer, prostate cancer, lung cancer, and kidney cancer, and occur at a high rate in patients with advanced cancer. This pathological process not only frequently leads to skeletal-related events such as severe bone pain, pathological fractures, spinal cord compression, and hypercalcemia—conditions that severely impact patients’ quality of life—but may also significantly increase the risk of death. Cancer bone metastasis is a complex, multistage cascade involving key steps such as the detachment of tumor cells from the primary tumor, their invasion and entry into the bloodstream, and their colonization, dormancy, and reactivation within the bone microenvironment. In recent years, exercise—as a safe and easily implementable non-pharmacological intervention—has demonstrated significant potential in inhibiting bone metastasis, improving the bone microenvironment, and alleviating related clinical symptoms. Its mechanisms of action may involve multiple levels. First, at the mechanical load level, mechanical signals generated by exercise can directly act on bone cells, inhibiting tumor cell infiltration and colonization by regulating endothelial cell permeability and osteoclast activity. Second, at the endocrine and paracrine levels, exercise can alter the expression profiles of microRNAs (such as miR-486 and miR-34b) carried by extracellular vesicles and particles (EVPs) in the circulation, thereby inhibiting tumor cell proliferation and migration by targeting cell cycle-related genes. Furthermore, exercise can remodel the immune microenvironment, enhance the cytotoxic activity of antitumor immune cells, and improve oxygen supply to tumor tissues, thereby alleviating hypoxia-induced immunosuppression. Finally, at the metabolic intervention level, exercise can induce systemic metabolic reprogramming, increasing the nutritional demands of normal tissues, thereby competing with tumor cells for nutrients and forming a “metabolic barrier” in distal organs such as bones. This article reviews the pathogenesis and classification of bone metastases, including osteolytic, osteogenic, and mixed types, and elaborates in detail on the complex processes by which tumor cells undergo colonization, dormancy, and reactivation within the bone microenvironment. Furthermore, based on a comprehensive analysis of human and animal studies on exercise interventions for bone metastases, this paper highlights the mechanisms by which exercise inhibits tumor formation, growth, and spread through the regulation of mechanical loading, extracellular vesicles and granules, as well as via immune and metabolic pathways, thereby interfering with bone metastasis. However, the array of exercise modalities and intensities available for patients grappling with the challenges of cancer-related bone metastases remains markedly constrained, and the formulation of tailored exercise prescriptions continues to be devoid of robust, evidence-based medical backing. This review aims to explore the effects of exercise on bone health in patients with bone metastases, analyze the factors and considerations that should be taken into account in exercise prescriptions, and provide new theoretical support and insights for developing personalized exercise programs for these patients and further advancing relevant clinical research. Future research directions should include the development of evidence-based, personalized exercise prescriptions and further clarification of the safety boundaries and best practice standards for exercise interventions, thereby promoting the advancement of relevant clinical research and ultimately improving patients’ clinical outcomes and quality of life.

OBJECTIVE To analyze the characteristics of imported malaria cases in West China Hospital of Sichuan University in recent years and to provide reference for the prevention and control of imported infectious diseases.METHOD A retrospective analysis of 62 cases of imported malaria from abroad reported in West China Hospital of Sichuan University from 2012 to 2023 were retrospectively analyzed.RESULTS From 2012 to 2023,62 cases of imported malaria were reported,including 49 cases(79.03％)of falciparum malaria,10 cases(16.13％)of vivax malaria,and 3 cases(4.84％)of ovale malaria.Among the imported malaria cases,9 cases were severe malaria,with 8(16.33％,8/49)severe cases caused by falciparum malaria,of which 6 cases(75.00％,6/8)were cere-bral malaria.The cases were mainly Chinese citizens and young-to-middle-aged adults,with the highest concentra-tion in the 40-49 age group(37.10％,23/62).There were more males than females,with a male-to-female sex ratio of 11.4∶1;the predominant occupation was worker(38.71％,24/62).The primary region of importation was Africa(90.32％,56/62).There was importation throughout the year,with no distinct seasonal distribution pattern.Two of the admitted cases died(severe cases of falciparum malaria,which developed into cerebral malari-a),while the rest were improved and discharged from the hospital after standardized treatment.CONCLUSIONS Cases of imported malaria from abroad are characterized by Chinese nationality,males,young adults and workers.The type of malaria is mainly falciparum malaria,and the prognosis for most cases is relatively good.It is necessary to strengthen the construction of joint prevention and control systems and other long-term mechanisms,and to continuously and scientifically implement various strategies and measures to prevent the re-emergence of malaria through imported ca-ses,in order to avoid the occurrence of secondary cases resulting from imported infections.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To explore the improvement effect of ultrasound microbubble blasting assisted bone marrow mesenchymal stem cells(BMSC)transplantation on diabetic nephropathy(DN)in terms of inflammatory response and renal function via the Toll like receptor 4(TLR-4)/nuclear factor-kappa B(NF-κB)signaling pathway,as well as its specific mechanism.Methods A rat DN model was estab-lished and randomly grouped into the following:Model group,BMSC group,BMSC+microbubble group,and BMSC+microbubble+TLR-4/NF-κB pathway activator lipopolysaccharide(LPS)group,with 12 rats in each group.Additionally,12 rats were selected as the control(CK)group.Biochemical and biuret analysis,HE and Masson staining,ELISA,and Western blotting testing were employed to detect fasting blood glucose(FBG),total cholesterol(TC),triglyceride(TG),serum creatinine(sCr),blood urea nitrogen(BUN),24-hour urinary total protein(24 h-UTP),pathological changes in renal tissue,fibrosis status,and the expression of interleukin-1 β(IL-1β),tumor necrosis factorα(TNF-α),TLR-4,and NF-κB proteins of rats in each group.Results The renal tissue in the CK group was structurally normal with few collagen fibers.The Model group showed obvious renal tissue lesions and severe collagen fiber deposition;the lesions in the BMSC group and BMSC+microvesicle group were alleviated in turn,while the lesions were aggravated after the addition of LPS compared with the BMSC+microvesicle group.Compared with the CK group,the levels of FBG,TC,TG,sCr,BUN,24 h-UTP,as well as the expression of IL-1β,TNF-α,TLR-4,and NF-κB proteins were increased in the Model group(P＜0.05).Compared with the Model group,the above-men-tioned indices and protein expression were decreased in the BMSC group(P＜0.05).Compared with the BMSC group,the above-men-tioned indices and protein expression were further decreased in the BMSC+microvesicle group(P＜0.05).Compared with the BMSC+mi-crovesicle group,the above-mentioned indices and protein expression were increased in the BMSC+microvesicle+LPS group(P＜0.05).Conclusion The improvement effect of ultrasound microbubble blasting-assisted BMSC transplantation on DN rats may be related to the inhibition of the TLR-4/NF-κB signaling pathway.

The aim of this study was to qualitatively and quantitatively detect coronavirus(CoV)in the feces of bats from Qinghua Cave,Yunnan Province,China.CoV was qualitatively tested with reverse transcription polymerase chain reaction(RT-PCR),and homology and genetic evolution were analyzed with bioinformatics software.The established reverse transcription real-time fluores-cence quantitative PCR(qRT-PCR)method was applied to CoV quantification in bat feces.The positivity rate of CoV in 306 fecal samples collected from the fulvous fruit bat(Rousettus leschenaultia)was 7.8%(24/306)according to RT-PCR.All 24 strains of CoV belonged to β-CoV,and showed a similarity of 86.8%-100.0%at the nucleotide level and 95.2%-100.0%at the amino acid level,with respect to other β-CoV sequences in the NCBI database.The positivity rate of CoV was 18.6%(57/306)according to qRT-PCR,a value higher than that according to RT-PCR(χ2=25.3,P<0.05).The mean β-CoV load was 1.3×103 copies/μL.In conclusion,the bats in Qinghua Cave,Yunnan Province,carried CoV belonging to β-CoV.The established qRT-PCR method achieved good sensitiv-ity,accuracy,reproducibility,and a higher detection rate than that of RT-PCR,and can be used for rapid detection of β-CoV in bats.

Objective:To explore the therapeutic effect of drug-coated balloon(DCB)combined drug-eluting stent(DES)on coronary bifurcation lesions.Methods:A total of 108 patients with coronary bifurcation lesions admitted in Shanghai Ninth People's Hospital Huangpu Branch,Shanghai Jiaotong University School of Medicine between February 2021 and March 2023 were enrolled in this randomized controlled study.Patients were randomly divided into combined treatment group(n=54,DCB was implanted in the sub-branch,and DES was implanted in the main branch)and DES group(n=54,DES were implanted in both main branch and sub-branch).Clinical therapeutic effect,coronary angiography quantitative parameters before,instant and 9 months after operation and clinical out-comes during 1-year follow-up after operation were compared between two groups.Results:The total effective rate of combined treatment group was significantly higher than that of DES group(96.30％vs.87.04％,P=0.030).Compared to those in DES group,instant and 9 months after operation,patients in the combined treatment group had significant higher diameters of main branch vessel[(3.13±0.31)mm vs.(3.01±0.25)mm,(2.99±0.33)mm vs.(2.84±0.23)mm],sub-branch vessel[(2.51±0.26)mm vs.(2.42±0.13)mm,(2.44±0.24)mm vs.(2.29±0.36)mm],and significant lower main branch stenosis rate[(6.05±0.21)％vs.(6.24±0.31)％,(9.06±0.23)％vs.(10.12±0.12)％]and sub-branch stenosis rate[(7.38±0.42)％vs.(7.63±0.18)％,(8.07±0.39)％vs.(11.25±0.22)％](P＜0.05 or＜0.01).There were no significant difference in incidence of target lesion revascularization,cardiogenic death and major adverse cardiovascular events between two groups(P＞0.05 all).Conclusion:Drug-eluting stent combined drug-coated balloon may promote vascular branch dilation of coro-nary artery lesions,increase the minimum lumen diameter of sub-branch vessels,and reduce the occurrence of ste-nosis in the treatment of coronary bifurcation lesion,which had similar effectiveness and safety with drug-eluting stent technique.

Objective The pathogenic characteristics of Escherichia coli(E.coli)in bacterial infections were analyzed using a combination of multiple molecular typing techniques in order to provide evidence for the management of clinical medication safety.Methods Samples from some bacterial infection-related cases in a district of Chongqing in 2021 were collected.A total of 30 E.coli strains were selected by a completely random method,and phoA gene PCR assay was performed for identification.Molecular typing of the strains was analyzed using pulsed-field gel electrophoresis(PFGE)and multilocus sequence typing(MLST).Antimicrobial susceptibility testing was conducted to determine the drug resistance of the strains,and four β-lactamase-encoding genes(blaCTX-M,blaTEM,blaSHV,blaZ)were selected to detect the carriage of resistance genes.Results All 30 E.coli strains displayed the phoA gene target band.Their PFGE banding patterns,with a similarity of 50%～98%,could be classified into 8 clusters.Cluster C was the dominant group,accounting for 53.3%(16/30).C1 and C2 exhibited high genetic correlation,indicating a close phylogenetic relationship.One E.coli strain could not be assigned a sequence type(ST)by MLST,while the remaining 29 E.coli isolates were classified into 16 different STs,demonstrating a polymorphic distribution.Among them,10 isolates belonged to ST131(10/30,33.33%).Evolutionary analysis of the 10 ST131 E.coli strains revealed their distribution across different branches,indicating varying degrees of genetic relatedness.Antimicrobial susceptibility testing revealed that all 30 E.coli strains exhibited varying degrees of resistance,with the highest resistance rate observed against the β-lactam antibiotic ampicillin(25/30,83.33%).Among them,60.0%were multidrug-resistant bacteria(MDRB).These MDRB strains exhibited 16 distinct resistance profiles,displaying a scattered distribution without a dominant resistance pattern.50.0%(9/18)of the MDRB strains exhibited six-drug resistance,while the most drug-resistant strain showed eight-drug resistance.Furthermore,the blaCTX-M gene carriage rate among the 30 E.coli strains was 86.67%(26/30),while no blaZ gene was detected.Conclusion E.coli related to bacterial infections from a Chongqing district exhibited diverse PFGE/MLST patterns and significant drug resistance.The application of multiple molecular typing techniques can reveal the genetic diversity,evolutionary relationships,and antimicrobial resistance characteristics of pathogenic bacteria.Countermeasures It is recommended to enhance the molecular typing and drug resistance surveillance network for pathogenic bacteria,establish an early warning mechanism,and implement hierarchical management of antibiotics,thereby improving targeted prevention and epidemic traceability capabilities for key drug-resistant bacteria such as ST131.