ObjectiveTo investigate the association between noninvasive liver fibrosis markers and carotid plaque （CP） in patients with lean metabolic dysfunction-associated fatty liver disease （MAFLD）， and to provide a basis for screening high-risk populations. MethodsA total of 957 patients with lean MAFLD who underwent physical examination in Subei People’s Hospital from January 2021 to June 2023 was enrolled as the observation cohort， with the presence or absence of CP as the outcome， and fibrosis-4 （FIB-4） index and nonalcoholic fatty liver disease fibrosis score （NFS） were used to assess liver fibrosis degree. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. The multivariate logistic regression analysis， the restricted cubic spline analysis， the receiver operating characteristic curve， and the mediation effect analysis were used to investigate the association between liver fibrosis degree and CP. ResultsThe prevalence rate of CP was 36.6% in the lean MAFLD population. Compared with the non-CP group（n=607）， the CP group （n=350） had a significantly higher proportion of male patients， a significantly higher proportion of patients with smoking/diabetes/hypertension， and significantly higher levels of age， creatinine， blood urea nitrogen， triglycerides， fasting blood glucose， aspartate aminotransferase， aspartate aminotransferase/alanine aminotransferase ratio， NFS， and FIB-4 index， as well as significantly lower levels of platelet count and albumin （all P<0.05）. The multivariate logistic regression analysis showed that after adjustment for confounding factors， FIB-4 index （odds ratio［OR］=2.979， 95% confidence interval［CI］：2.141 — 4.219， P<0.001） and NFS （OR=1.747， 95%CI： 1.499 — 2.046， P<0.001） were positively correlated with CP. Both FIB-4 index and NFS had a good value in predicting CP. Hypertension had a significant indirect effect on the prevalence rate of CP through its impact on liver fibrosis markers， and its mediating effect accounted for 39.5% — 40.8% of the total effect （P<0.001）. ConclusionIn patients with lean MAFLD， NFS and FIB-4 index are significantly positively correlated with the prevalence rate of CP， and they can be used as potential epidemiological predictive indicators. Liver fibrosis markers may play a mediating role in the association between hypertension and CP. Interventions targeting hypertension and liver fibrosis markers may help to prevent and delay the progression of CP.

ObjectiveTo investigate the association of liver fibrosis scores and inflammation markers with gallstones in patients with metabolic dysfunction-associated fatty liver disease （MAFLD）， as well as the mediating role of liver fibrosis scores in the relationship between inflammation markers and gallstones. MethodsA total of 14 567 patients who received physical examination and were diagnosed with MAFLD in Subei People’s Hospital from January 2014 to June 2023 were enrolled in this study， and according to the results of abdominal color Doppler ultrasound， they were divided into gallstone group with 1 724 patients and non-gallstone group with 12 843 patients. Related clinical data were collected from all patients， including demographic data， medical history， family history， physical examination， Color Doppler ultrasound， and biochemical parameters. The biomarkers associated with metabolic disorders and insulin resistance included triglyceride-glucose index （TyG）， TyG-body mass index （BMI） index， atherogenic index of plasma （AIP）， and non-high-density lipoprotein cholesterol-to-high-density lipoprotein cholesterol ratio （NHHR）； the biomarkers associated with inflammation and nutritional status included neutrophil-to-lymphocyte ratio （NLR）， neutrophil percentage-to-albumin ratio （NPAR）， and monocyte-to-lymphocyte ratio （MLR）； the biomarkers for assessing liver fibrosis degree and liver function included albumin-bilirubin （ALBI） score， NAFLD fibrosis score （NFS）， fibrosis-4 （FIB-4） index， and aspartate aminotransferase-to-platelet ratio index （APRI）. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， while the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. Multivariate Logistic regression analysis， restricted cubic spline analysis， and mediating effect analysis were used to assess the association of liver fibrosis markers and inflammation markers with the risk of gallstones. ResultsThe prevalence rate of gallstones was 11.8% among the MAFLD patients. There were significant differences between the gallstone group and the non-gallstone group in sex， age， smoking history， diabetes， hypertension， lymphocytes， platelets， glucose， albumin， serum uric acid， alanine aminotransferase， aspartate aminotransferase， red blood cell， NLR， NPAR， MLR， NFS， FIB-4 index， and ALBI score （all P<0.05）. The multivariate Logistic regression analysis showed that NLR （odds ratio ［OR］=1.091， 95% confidence interval ［CI］： 1.028　—　1.160， P<0.05）， NPAR （OR=1.073， 95%CI： 1.042　—　1.105， P<0.05）， MLR （OR=1.142， 95%CI： 1.057　—　1.232， P<0.05）， NFS （OR=1.239， 95%CI： 1.190　—　1.291， P<0.05）， and FIB-4 index （OR=1.326， 95%CI： 1.241　—　1.417， P<0.05） were influencing factors for the prevalence rate of gallstones. The restricted cubic spline analysis showed a significant non-linear association between NFS/FIB-4 index and the risk of gallstone （non-linear P<0.05）. The mediating effect analysis further showed that the association of NLR， MLR， and NPAR with gallstones was partially mediated by NFS or FIB-4 index， with a mediating effect accounting for 36.79%、28.09%、29.67% and 18.31%、17.70、11.57%， respectively. ConclusionNFS and FIB-4 index have a non-linear association with the prevalence rate of gallstones in MAFLD patients， and they also mediate the association of NLR， NPAR， and MLR with the risk of gallstone.

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.

Kounis syndrome is an acute coronary syndrome triggered by an allergic reaction, which is clinically rare and frequently subject to misdiagnosis or missed diagnosis. This article presents a case report of a 70-year-old male patient who developed a rash, pruritus, and chest pain following colon polyp resection. Coronary angiography revealed occlusion of the left anterior descending artery, and blood flow was restored after stent implantation. However, the patient experienced recurrent symptoms accompanied by loss of consciousness. Drug skin tests confirmed positive reactions to chlorhexidine and fondaparinux sodium, leading to a diagnosis of type Ⅱ Kounis syndrome. By avoiding allergenic drugs and combining antihistamines with symptomatic treatment to correct myocardial ischemia, the patient′s clinical symptoms significantly improved, and he eventually recovered and was discharged from the hospital. This case underscores the importance of maintaining vigilance for this syndrome in patients with allergies accompanied by chest pain and promptly identifying and avoiding allergens.

Objective To examine the expression pattern of apoptosis signal-regulating kinase 1(ASK1)in the intestinal tissues of patients with Crohn's disease(CD),and analyze its mechanistic impact on intestinal epithelial barrier function and inflammatory responses.Methods Ileal tissue samples from Crohn's disease patients and healthy controls were collected.ASK1 protein level was assessed by immunohistochemistry,and its relationship with the Crohn's disease activity index(CDAI)was analyzed.A mouse model of acute colitis was constructed using TNBS,and subjected to qRT-PCR,Western blotting and immunohistochemistry for ASK1 expression,and the association between ASK1 expression and the disease activity index was examined.Lentivirus transfection was employed to create stable Caco-2 cell lines with altered ASK1 expression,and the intestinal barrier integrity and inflammation were assessed by measuring transepithelial electrical resistance(TEER),FITC-dextran leakage,and IL-6,IL-1β levels.Furthermore,the effects of ASK1 expression on Krüppel-like factor 4(KLF4)levels was examined using qRT-PCR and Western blotting.Results ASK1 was highly expressed in the ileum of CD patients and positively correlated with CDAI.In a TNBS-induced mouse model of acute colitis,ASK1 expression was up-regulated and positively correlated with DAI.Inflammation-induced ASK1 overexpression weakened the Caco-2 cell intestinal barrier,whereas ASK1 knockdown strengthened it.Moreover,ASK1 had the capability to enhance the expression of inflammatory factors.Additionally,ASK1 knockdown increased KLF4 expression,while overexpression decreased it,indicating a negative correlation between ASK1 and KLF4.Conclusion ASK1 expression is notably higher in CD and positively correlates with disease activity.ASK1 can influence intestinal barrier integrity and inflammatory factor expression,possibly through its impact on KLF4 expression.

Objective To examine the expression pattern of apoptosis signal-regulating kinase 1(ASK1)in the intestinal tissues of patients with Crohn's disease(CD),and analyze its mechanistic impact on intestinal epithelial barrier function and inflammatory responses.Methods Ileal tissue samples from Crohn's disease patients and healthy controls were collected.ASK1 protein level was assessed by immunohistochemistry,and its relationship with the Crohn's disease activity index(CDAI)was analyzed.A mouse model of acute colitis was constructed using TNBS,and subjected to qRT-PCR,Western blotting and immunohistochemistry for ASK1 expression,and the association between ASK1 expression and the disease activity index was examined.Lentivirus transfection was employed to create stable Caco-2 cell lines with altered ASK1 expression,and the intestinal barrier integrity and inflammation were assessed by measuring transepithelial electrical resistance(TEER),FITC-dextran leakage,and IL-6,IL-1β levels.Furthermore,the effects of ASK1 expression on Krüppel-like factor 4(KLF4)levels was examined using qRT-PCR and Western blotting.Results ASK1 was highly expressed in the ileum of CD patients and positively correlated with CDAI.In a TNBS-induced mouse model of acute colitis,ASK1 expression was up-regulated and positively correlated with DAI.Inflammation-induced ASK1 overexpression weakened the Caco-2 cell intestinal barrier,whereas ASK1 knockdown strengthened it.Moreover,ASK1 had the capability to enhance the expression of inflammatory factors.Additionally,ASK1 knockdown increased KLF4 expression,while overexpression decreased it,indicating a negative correlation between ASK1 and KLF4.Conclusion ASK1 expression is notably higher in CD and positively correlates with disease activity.ASK1 can influence intestinal barrier integrity and inflammatory factor expression,possibly through its impact on KLF4 expression.

This document targets digital human metabolic chamber platforms and specifies construction standards and testing protocols covering the full lifecycle of " build-test-operate." It encompasses chamber engineering and environmental control, digital platform and cybersecurity architecture, metabolic measurement and multimodal data acquisition, as well as quantitative system performance and data quality indicators with verifiable acceptance tests. By standardizing architecture, interfaces, and quality control, the specification enables multicenter data interoperability and harmonized quality management, providing high-quality, verifiable, and traceable infrastructure to support precision metabolism research and clinical translation in China.

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.

Objective:To investigate the metabolic pathways and potential molecular targets associated with dapagliflozin in the treatment of type 2 diabetes mellitus.Methods:Plasma samples from patients with type 2 diabetes mellitus were collected before and after 12 months of dapagliflozin treatment and analyzed using UPLC-VION IMS Q-Tof-based metabolomics and timsTOF Pro2 diaPASEF-based proteomics. Multivariate statistical analyses were performed to identify significant differences pre- and post-treatment. Correlation analysis was then conducted to assess relationships between differentially expressed metabolites and proteins closely associated with type 2 diabetes mellitus. Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analyses were used to construct metabolic pathway maps and predict therapeutic targets.Results:After 12 months of dapagliflozin treatment, 162 differential metabolites were identified, with 59 upregulated and 103 downregulated. A total of 440 differentially expressed proteins were detected, of which 272 were upregulated and 168 were downregulated. The main classes of differential metabolites included sphingolipids, glycerophospholipids, and glycosphingolipids. Key differentially expressed proteins included importin subunit alpha-11, synemin, Janus kinase 1, and far upstream element-binding protein 2. Correlation analysis revealed 98 shared enriched pathways between differential metabolites and proteins, involving neurotrophin signaling, chemokine signaling, and B cell receptor signaling pathways. Metabolic pathway analysis suggested that dapagliflozin might regulate insulin secretion by modulating glucose-dependent insulinotropic polypeptide, calmodulin-dependent protein kinase, and diacylglycerol levels.Conclusion:Dapagliflozin may exert therapeutic effects in type 2 diabetes mellitus through multiple mechanisms, including the modulation of metabolic and proteomic profiles, participation in key cellular signaling pathways, and regulation of insulin secretion.