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.

The liver is a vital metabolic organ sustaining human life activities， and its dysfunction is closely associated with various liver diseases. In recent years， an increasing number of studies have shown that semaphorins （SEMA） play a significant role in pathological processes such as immune inflammatory response， tumor progression， and fibrosis in liver diseases by interacting with their receptors plexins and neuropilins. This article reviews the expression， functions， and molecular mechanisms of different SEMA in viral hepatitis， hepatocellular carcinoma， liver fibrosis， nonalcoholic fatty liver disease， and hepatic ischemia-reperfusion injury， and it also explores the potential application value of SEMA in the diagnosis and treatment of liver diseases， in order to provide new ideas for precise diagnosis and targeted treatment of liver diseases.

Background and aims The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. Methods The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Results Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. Conclusions PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.

ObjectiveTo investigate the urate-lowering effect of Shenling Qushi prescription in the mouse model of hyperuricaemia. MethodsSixty-three C57BL/6N mice were randomly assigned to the following groups （n=9）： Control， model， low-dose （6 g·kg^-1） Shenling Qushi prescription， medium-dose （12 g·kg^-1） Shenling Qushi prescription， high-dose （24 g·kg^-1） Shenling Qushi prescription， medium-dose Shenling Qushi prescription plus febuxostat （12+0.003 g·kg^-1）， and febuxostat （3 mg·kg^-1）. A mouse model of persistent hyperuricaemia was established via intraperitoneal injection of potassium oxazolamide （250 mg·kg^-1） combined with oral administration of allopurinol （300 mg·kg^-1） over a 28-day period. Concurrently， the prescription was administered orally at the specified doses once daily for 21 consecutive days. Throughout the experiment， mouse body weight， food intake， water consumption， and urine output were measured and recorded. Kidney and liver indices were calculated. Renal histopathological changes were observed by haematoxylin and eosin staining. Serum uric acid （SUA） and urinary uric acid （UUA） levels， along with xanthine oxidase （XOD） and adenosine deaminase （ADA）， alanine aminotransferase （ALT） and aspartate aminotransferase （AST） activities， were determined. Real-time PCR was employed to assess the mRNA levels of urate anion transporter 1 （URAT1） and glucose transporter 9 （GLUT9） in the renal tissue， alongside those of XOD and ADA in the liver tissue. The protein levels of URAT1 and GLUT9 in the renal tissue were determined by Western blot. ResultsCompared with the normal group， model mice exhibited reduced food intake and body weight （P<0.01）， decreased water consumption yet increased urine output， no significant change in the liver index but increased kidney index （P<0.01）. Pathological findings revealed renal tissue damage including glomerular atrophy， epithelial cell detachment， and inflammatory cell infiltration. Furthermore， the model group exhibited elevated UUA and SUA levels （P<0.01）， enhanced activities of ALT， AST， XOD， and ADA in the liver tissue （P<0.05， P<0.01）， upregulated mRNA and protein levels of URAT1 and GLUT9 in the renal tissue （P<0.05）， alongside markedly elevated mRNA levels of XOD and ADA in the liver （P<0.01）. Compared with the model group， the Shenling Qushi prescription groups showed no significant changes in body weight or food intake， with water consumption and urine output remaining within normal ranges， alleviated glomerular atrophy， with reduced pathological damage such as inflammatory infiltration， declined UUA and SUA levels （P<0.01）， and increased activities of ALT， AST， XOD， and ADA in the serum （P<0.01）. Real-time PCR results demonstrated that Shenling Qushi prescription downregulated the mRNA levels of URAT1 and GLUT9 in the renal tissue （P<0.05， P<0.01） and XOD and ADA in the hepatic tissue （P<0.05， P<0.01）. Western blot results demonstrated Shenling Qushi prescription reduced the protein levels of URAT1 and GLUT9 （P<0.05， P<0.01）. ConclusionShenling Qushi prescription modulates fluid balance and reduces uric acid levels， thereby alleviating renal injury in hyperuricaemic mice. This effect is highly likely mediated through inhibition of uric acid synthesis and reabsorption.

ObjectiveTo investigate the awareness and clinical practice of guidelines for the prevention and treatment of chronic hepatitis B （2022 edition） among clinicians. MethodsFrom July 19 to December 31， 2024， a self-designed electronic questionnaire was distributed via the WeChat mini program to collect related data from 1 588 clinicians nationwide， including their awareness and practice based on 18 questions regarding testing and referral， diagnosis and treatment， and follow-up. ResultsAmong all respondents， only 350 clinicians correctly understood all the updated key points of antiviral indications and treatment for special populations in the 2022 edition of guidelines for the prevention and treatment of chronic hepatitis B， with an overall awareness rate of 22.0%. Only 20% ‍—‍ ‍40% of the patients with positive HBV DNA and an age of >30 years receive antiviral therapy， while 80% ‍—‍ ‍100% of the patients with positive HBV DNA and a family history of hepatitis B cirrhosis or hepatocellular carcinoma receive antiviral therapy. The median follow-up rates at 1 year， 3 years， and 5 years were 67.5% 57.5% and 47.5%，respectively， showing a trend of gradual reduction， which might be associated with the influencing factors such as insufficient time for follow-up management by clinicians， insufficient awareness of the disease among patients， and poor adherence to follow-up. ConclusionThere is a gap between the awareness and practice of guidelines for the prevention and treatment of chronic hepatitis B （2022 edition） among clinicians. It is recommended to further strengthen training and focus on the whole process of “detection， diagnosis， treatment， and management” for patients with chronic hepatitis B in healthcare institutions， in order to promote the implementation of the guidelines.

ObjectiveFunctional near-infrared spectroscopy (fNIRS), a novel non-invasive technique for monitoring cerebral activity, can be integrated with upper limb rehabilitation robots to facilitate the real-time assessment of neurological rehabilitation outcomes. The rehabilitation robot is designed with 3 training modes: passive, active, and resistance. Among these, the resistance mode has been demonstrated to yield superior rehabilitative outcomes for patients with a certain level of muscle strength. The control modes in the resistance mode can be categorized into dynamic and static control. However, the effects of different control modes in the resistance mode on the motor function of patients with upper limb hemiplegia in stroke remain unclear. Furthermore, the effects of force, an important parameter of different control modes, on the activation of brain regions have rarely been reported. This study investigates the effects of dynamic and static resistance modes under varying resistance levels on cerebral functional alterations during motor rehabilitation in post-stroke patients. MethodsA cohort of 20 stroke patients with upper limb dysfunction was enrolled in the study, completing preparatory adaptive training followed by 3 intensity-level tasks across 2 motor paradigms. The bilateral prefrontal cortices (PFC), bilateral primary motor cortices (M1), bilateral primary somatosensory cortices (S1), and bilateral premotor and supplementary motor cortices (PM) were examined in both the resting and motor training states. The lateralization index (LI), phase locking value (PLV), network metrics were employed to examine cortical activation patterns and topological properties of brain connectivity. ResultsThe data indicated that both dynamic and static modes resulted in significantly greater activation of the contralateral M1 area and the ipsilateral PM area when compared to the resting state. The static patterns demonstrated a more pronounced activation in the contralateral M1 in comparison to the dynamic patterns. The results of brain network analysis revealed significant differences between the dynamic and resting states in the contralateral PFC area and contralateral M1 area (F=4.709, P=0.038), as well as in the contralateral PM area and ipsilateral M1 area (F=4.218, P=0.049). Moreover, the findings indicated a positive correlation between the activation of the M1 region and the increase in force in the dynamic mode, which was reversed in the static mode. ConclusionBoth dynamic and static resistance training modes have been demonstrated to activate the corresponding brain functional regions. Dynamic resistance modes elicit greater oxygen changes and connectivity to the region of interest (ROI) than static resistance modes. Furthermore, the effects of increasing force differ between the two modes. In patients who have suffered a stroke, dynamic modes may have a more pronounced effect on the activation of exercise-related functional brain regions.

Objective To analyze the trends and changes in the burden of chronic kidney dis-ease(CKD)in China from 1990 to 2021.Methods Data related to the burden of CKD in China from the 2021 Global Burden of Disease(GBD)Study public database were downloaded.Descriptive analyses were conducted using indicators such as age-standardized incidence rates,mortality rates,years of life lost(YLL)rates,years lived with disability(YLD)rates,and disability-adjusted life years(DALY)rates.The Joinpoint regression model was employed to analyze the trends in CKD.The Nordpred model was used to predict the standardized mortality rates,prevalence rates,and inci-dence rates of CKD in China over the next 20 years.Results The age-standardized incidence rate of CKD in China increased from 147.29 per 100,000 in 1990 to 163.74 per 100,000 in 2021,while the age-standardized prevalence rates,mortality rates,YLL rates,YLD rates,and DALY rates all ex-hibited downward trends.The incidence and prevalence of CKD were higher in Chinese women than in men,while mortality rates and DALY rates were lower in women than in men.The burden of CKD increased with age.It is estimated that by 2045,the incidence and prevalence of CKD in China will continue to rise,but the standardized mortality rate and standardized prevalence rate will decline.Conclusion Based on the current status and trends in the burden of CKD in China,implementing precise health management for different populations can help reduce the burden of CKD in China.

Objective To establish a human intestinal organ-on-a-chip model using a multi-array chip array to simulate the microphysiological structure of the human intestine and to investigate the impact of ionizing radiation on radiation-induced damage to human intestinal cells.Methods Caco-2 and human umbilical vein endothelial cells(HUVECs)were co-cultured in an organ chip.The cells were subjected to fluid shear stress via a precision shaker.After 7 days of dynamic culture,the morphological structure of intestinal epithelial cells and venous endothelial cells within the intestinal organ chip was examined using phase contrast microscopy,immunofluorescence staining,and confocal microscopy for three-dimensional(3D)imaging.γ-H2AX and TUNEL immunofluorescence staining were employed to assess DNA damage and apoptosis in intestinal epithelial cells two days post-irradiation.Villin immunofluorescence staining was used to evaluate villus height three days post-irradiation.EdU incorporation assay and Ki67 immunofluorescence staining were conducted to observe the effects of ionizing radiation on the proliferation of intestinal epithelial cells.Results After 7 days of dynamic culture,phase contrast microscopy and immunofluorescence staining combined with confocal 3D imaging revealed that the upper intestinal epithelial cells in the middle compartment of the chip formed a 3D intestinal villus structure,while the vascular endothelial cells in the lower compartment developed a vascular network structure.The chip was subsequently irradiated by 10 Gy X-ray.Immunofluorescence staining results indicated that the mean fluorescence intensity of γ-H2AX and TUNEL in the irradiated group was significantly higher than in the non-irradiated group 2 days after irradiation(P＜0.01),and that the proportion of EDU+and Ki67+cells in the irradiated group was significantly lower than in the non-irradiated group three days after irradiation(P＜0.05).Conclusion Caco-2 cells and HUVECs co-culture on an organ chip can generate the biomimetic structure of human intestinal villus.Ionizing radiation has been found to shorten intestinal villus,increase DNA damage and apoptosis in intestinal epithelial cells,and inhibit the proliferation of these cells.

Myocardial fibrosis is a serious cause of heart failure and even sudden cardiac death. However, the mechanisms underlying myocardial ischemia-induced cardiac fibrosis remain unclear. Here, we identified that the expression of sterile alpha and TIR motif containing 1 (SARM1), was increased significantly in the ischemic cardiomyopathy patients, dilated cardiomyopathy patients (GSE116250) and fibrotic heart tissues of mice. Additionally, inhibition or knockdown of SARM1 can improve myocardial fibrosis and cardiac function of myocardial infarction (MI) mice. Moreover, SARM1 fibroblasts-specific knock-in mice had increased deposition of extracellular matrix and impaired cardiac function. Mechanically, elevated expression of SARM1 promotes the deposition of extracellular matrix by directly modulating P4HA1. Notably, by using the Click-iT reaction, we identified that the increased expression of ZDHHC17 promotes the palmitoylation levels of SARM1, thereby accelerating the fibrosis process. Based on the fibrosis-promoting effect of SARM1, we screened several drugs with anti-myocardial fibrosis activity. In conclusion, we have unveiled that palmitoylated SARM1 targeting P4HA1 promotes collagen deposition and myocardial fibrosis. Inhibition of SARM1 is a potential strategy for the treatment of myocardial fibrosis. The sites where SARM1 interacts with P4HA1 and the palmitoylation modification sites of SARM1 may be the active targets for anti-fibrosis drugs.