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.

Background Cadmium (Cd) is a highly toxic heavy metal. Chronic low-dose cadmium exposure can lead to renal tubular dysfunction. However, the precise mechanisms by which cadmium induces renal tubular injury through disruption of intracellular metabolic networks remain incompletely understood. Objective To investigate the toxic effects of cadmium exposure on human renal tubular epithelial cells (HK-2) and to elucidate the associated metabolic regulatory network from the perspective of metabolic reprogramming. Methods An in vitro HK-2 cell injury model was established using 5 μmol·L⁻¹ cadmium chloride (CdCl₂). The expression of the renal injury marker kidney injury molecule-1 (KIM-1) was determined by Western blot (WB). Glycolytic capacity was evaluated by metabolic flux analysis. Mitochondrial reactive oxygen species (ROS) production was assessed with a fluorescent probe. Mitochondrial membrane potential (MMP) was evaluated after JC-1 staining. Intracellular adenosine triphosphate (ATP) levels were measured using an ATP assay kit. In addition, untargeted metabolomics analysis was conducted to characterize alterations in the intracellular metabolic fingerprint profile and to explore the metabolic pathway changes underlying cadmium-induced renal tubular epithelial cell injury. Results Cadmium exposure induced injury in HK-2 cells, as indicated by mitochondrial membrane depolarization, increased mitochondrial ROS levels, and decreased intracellular ATP levels. Metabolic flux analysis further revealed significant metabolic reprogramming, characterized by compensatory increases in basal glycolytic rate and maximal glycolytic capacity. Untargeted metabolomics showed depletion of the long-chain acylcarnitine pool and deficiency of key metabolic cofactors, suggesting impaired fatty acid oxidation and mitochondrial energy metabolism. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis indicated that the differential metabolites were mainly enriched in oxidative phosphorylation and glycerophospholipid metabolism. Correlation analysis showed that acylcarnitines were negatively correlated with nucleic acid metabolism-related metabolites, whereas ATP was positively correlated with lysophosphatidylcholine, suggesting that cadmium exposure-induced mitochondrial dysfunction may be accompanied by abnormal DNA metabolism and lipid peroxidation. Conclusion Cadmium exposure could induce impaired mitochondrial function, and promote glycolytic metabolic reprogramming in renal tubular epithelial cells. These findings provide new insights into the metabolic mechanisms underlying cadmium-induced nephrotoxicity and may help identify potential metabolic targets for intervention.

Acupuncture-moxibustion therapy has been known to ameliorate the symptoms of functional gastrointestinal disorders (FGIDs), although its mechanism remains unclear. The paper reviews the articles on acupuncture-moxibustion therapy for FGIDs in recent 5 years, and it is revealed that acupuncture-moxibustion therapy can alleviate FGIDs symptoms through regulating gastrointestinal motility, modulating visceral hypersensitivity, improving the impaired gastric-duodenal mucosal barrier and inflammation, balancing intestinal microbiota, and adjusting the gut-brain axis. Currently, the molecular mechanism of acupuncture-moxibustion therapy remains unknown for FGIDs, the specific disease target is not identified, and the interaction among various molecules is not elucidated adequately. The researches in the future should employ advanced technologies and methodologies to comprehensively and deeply explore and clarify the mechanism of acupuncture- moxibustion therapy for FGIDs.
Humans ; Moxibustion ; Acupuncture Therapy ; Gastrointestinal Diseases/microbiology* ; Animals

OBJECTIVE: To observe the effect of moxibustion on small intestinal mucosal immune barrier in rats with diarrhea-predominant irritable bowel syndrome (IBS-D) and explore its underlying mechanisms. METHODS: Of 38 newborn rats from 4 healthy SPF pregnant rats, 12 neonatal rats were randomly selected in a normal group. IBS-D model was prepared by the combined measures for the rest rats, including neonatal maternal separation, acetic acid enema and chronic restraint stress. Twenty-four successfully-modeled rats were randomized into a model group and a moxibustion group, 12 rats in each one. In the moxibustion group, suspending moxibustion was delivered at bilateral "Tianshu" (ST25) and "Shangjuxu" (ST37), 20 min each time, once daily and for 7 consecutive days. Separately, before acetic acid enema (aged 35 days), after modeling (aged 45 days) and after intervention (aged 53 days), the body mass, loose stool rate (LSR) and and the minimum volume threshold when abdominal withdrawal reflex (AWR) scored 3 were observed in the rats of each group. After intervention (aged 53 days), using HE and PAS staining, the morphology of duodenum was observed, the length of villus and the depth of crypt were measured, the ratio of the length of villus to the depth of crypt was calculated; and the numbers of mucosal intraepithelial lymphocytes (IELs) and goblet cells were counted. With ELISA adopted, the contents of γ-interferon (IFN-γ), interleukin-4 (IL-4) and secretory immunoglobulin A (sIgA) in duodenal mucosa of rats were detected. The proportion of T cell subsets in duodenal mucosa was detected using flow cytometry. The microvilli and tight junctions of duodenal mucosal epithelial cells were observed by transmission electron microscopy, and the integrity of duodenal mucosa observed by scanning electron microscopy. RESULTS: Compared with the normal group, for the rats in the model group, the body mass, the minimum volume threshold when AWR scored 3, the length of duodenal villus and the the ratio of the length of villus to the depth of crypt, as well as the proportion of CD₈⁺ T subset were all reduced (P<0.01, P<0.05), the counts of goblet cells in duodenal mucosa decreased (P<0.01); LRS, the proportion of CD₄⁺ T subset and CD₄⁺/CD₈⁺, as well as the contents of IFN-γ, IL-4 and sIgA in duodenal mucosa and IFN-γ/IL-4 were all elevated (P<0.01); and the numbers of IELs rose (P<0.01). The morphology of duodenal mucosa was irregular, the villi got shorter, sparse and scattered, with uneven density. The morphology of epithelial cells was destroyed and the tight junctions damaged, with larger spaces. When compared with the model group, in the moxibustion group, the body mass, the minimum volume threshold when AWR scored 3, the length of duodenal villus and the ratio of the length of villus to the depth of crypt, as well as the counts of goblet cells in duodenal mucosa increased (P<0.01); LRS, the proportion of CD₄⁺ T subset, and CD₄⁺/CD₈⁺, as well as the contents of IFN-γ, IL-4 and sIgA in duodenal mucosa and IFN-γ/IL-4 were reduced (P<0.01); and the numbers of IELs was dropped (P<0.01). The morphology of duodenal mucosa was more regular, the villi were grew, got longer and arranged regularly, with even density. The morphology of epithelial cells was slightly destroyed, and the tight junctions partially damaged. CONCLUSION Moxibustion at "Tianshu" (ST25) and "Shangjuxu" (ST37) can reduce visceral hypersensitivity in IBS-D rats and relieve abdominal pain, diarrhea and other symptoms. Its effect mechanism may be related to the repair of small intestinal mucosal immune barrier and the improvement in the immune function in IBS-D.
Animals ; Irritable Bowel Syndrome/immunology* ; Rats ; Moxibustion ; Intestinal Mucosa/immunology* ; Female ; Diarrhea/therapy* ; Intestine, Small/immunology* ; Male ; Humans ; Rats, Sprague-Dawley ; Disease Models, Animal

OBJECTIVES: To investigate the effect of curcumin on lipid metabolism in non-small cell lung cancer (NSCLC) and its molecular mechanism. METHODS: The inhibitory effect of curcumin (0-70 μmol/L) on proliferation of A549 and H1299 cells was assessed using MTT assay, and 20 and 40 μmol/L curcumin was used in the subsequent experiments. The effect of curcumin on lipid metabolism was evaluated using cellular uptake assay, wound healing assay, triglyceride (TG)/free fatty acid (NEFA) measurements, and Oil Red O staining. Western blotting was performed to detect the expressions of PGC-1α, PPAR-α, and HIF-1α in curcumin-treated cells. Network pharmacology was used to predict the metabolic pathways, and the results were validated by Western blotting. In a nude mouse model bearing A549 cell xenograft, the effects of curcumin (20 mg/kg) on tumor growth and lipid metabolism were assessed by measuring tumor weight and observing the changes in intracellular lipid droplets. RESULTS: Curcumin concentration-dependently inhibited the proliferation of A549 and H1299 cells and significantly reduced TG and NEFA levels and intracellular lipid droplets. Western blotting revealed that curcumin significantly upregulated PGC-1α and PPAR‑α expressions in the cells. KEGG pathway enrichment analysis predicted significant involvement of the HIF-1 signaling pathway in curcumin-treated NSCLC, suggesting a potential interaction between HIF-1α and PPAR‑α. Western blotting confirmed that curcumin downregulated the expression of HIF-1α. In the tumor-bearing mice, curcumin treatment caused significant reduction of the tumor weight and the number of lipid droplets in the tumor cells. CONCLUSIONS Curcumin inhibits NSCLC cell proliferation and lipid metabolism by downregulating the HIF-1α pathway.
Curcumin/pharmacology* ; Humans ; Hypoxia-Inducible Factor 1, alpha Subunit/metabolism* ; Animals ; Lipid Metabolism/drug effects* ; Carcinoma, Non-Small-Cell Lung/pathology* ; Lung Neoplasms/pathology* ; Mice, Nude ; Down-Regulation ; Mice ; Cell Proliferation/drug effects* ; Cell Line, Tumor ; Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-alpha ; PPAR alpha/metabolism* ; Signal Transduction/drug effects* ; A549 Cells

OBJECTIVE: Peritoneal fibrosis (PF) is an adverse event that occurs during long-term peritoneal dialysis, significantly impairing treatment efficiency and adversely affecting patient outcomes. Astragaloside IV (AS-IV), a principal active component derived from Astragalus membranaceus (Fisch.) Bunge, has exhibited anti-inflammatory and antifibrotic effects in various settings. This study aims to investigate the potential therapeutic efficacy and mechanism of AS-IV in the treatment of PF. METHODS: The PF mouse model was established by intraperitoneal injection of 4.25% peritoneal dialysis fluid (100 mL/kg). The epithelial-mesenchymal transition (EMT) of HMrSV5 cells was induced by the addition of 10 ng/mL transforming growth factor β (TGF-β). The differentially expressed genes in HMrSV5 cells treated with AS-IV were screened using transcriptome sequencing analysis. The potential targets of AS-IV were screened using network pharmacology and analyzed using molecular docking and molecular dynamics simulations. RESULTS: Administration of AS-IV at doses of 20, 40, or 80 mg/kg effectively mitigated the increase in peritoneal thickness and the development of fibrosis in mice with PF. The expression of the fibrosis marker α-smooth muscle actin in the peritoneum was significantly decreased in AS-IV-treated mice. The treatment of AS-IV (10, 20, and 40 μmol/L) significantly delayed the EMT of HMrSV5 cells induced by TGF-β, as demonstrated by the decreased number of 5-ethynyl-2'-deoxyuridine-positive cells, reduced migrated area, and decreased expression of fibrosis markers. A total of 460 differentially expressed genes were detected in AS-IV-treated HMrSV5 cells through transcriptome sequencing, with notable enrichment in the phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)-AKT serine/threonine kinase 1 (AKT) signaling pathway. The reduced levels of phosphorylated PI3K (p-PI3K) and p-AKT were detected in HMrSV5 cells with AS-IV treatment. Epidermal growth factor receptor (EGFR) was predicted as a direct target of AS-IV, exhibiting strong hydrogen bond interactions. The activation of the PI3K-AKT pathway by the compound 740Y-P, and the activation of the EGFR pathway by NSC 228155 each partially counteracted the inhibitory effect of AS-IV on the EMT of HMrSV5 cells. CONCLUSION AS-IV delayed the EMT process in peritoneal mesothelial cells and slowed the progression of PF, potentially serving as a therapeutic agent for the early prevention and treatment of PF. Please cite this article as: Huang Y, Chu CL, Qiu WH, Chen JY, Cao LX, Ji SY, Zhu B, Wang GK, Shen QQ. Astragaloside IV delayed the epithelial-mesenchymal transition in peritoneal fibrosis by inhibiting the activation of EGFR and PI3K-AKT pathways. J Integr Med. 2025; 23(6):694-705.
Epithelial-Mesenchymal Transition/drug effects* ; Animals ; Saponins/pharmacology* ; Triterpenes/pharmacology* ; Mice ; Peritoneal Fibrosis/pathology* ; Proto-Oncogene Proteins c-akt/metabolism* ; ErbB Receptors/metabolism* ; Phosphatidylinositol 3-Kinases/metabolism* ; Signal Transduction/drug effects* ; Male ; Humans ; Molecular Docking Simulation ; Cell Line ; Mice, Inbred C57BL

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Objective:To investigate the correlation between occupational ionizing radiation exposure and abnormal metabolic indicators, providing a basis for assessing the health risks of occupational ionizing radiation workers and establishing a risk prediction model for chronic metabolic diseases.Methods:In January 2023, 7708 individuals were randomly selected from the occupational health examination data in Zhejiang Province. After excluding 16 individuals due to record errors, 2698 on-the-job workers exposed to ionizing radiation from 2020 to 2021 were selected as the exposure group, 2027 pre-employment workers exposed to ionizing radiation from 2016 to 2022 were selected as the pre-employment control group, and 2967 non-ionizing radiation workers from 2016 to 2022 were selected as the control group. Demographic data, blood routine, urine routine, biochemical indicators, and peripheral blood lymphocyte micronucleus rate of each group were collected. One-way ANOVA and rank sum test were used for comparison of indicators. The exposure group was divided into different groups based on age, exposure duration, and body mass index (BMI), and the correlation between indicators and occupational ionizing radiation was analyzed. Lasso variable selection was conducted by constructing a penalty coefficient (λ), and a complete regression model was established.Results:There were statistically significant differences in indicators such as blood pressure, heart rate, and average hemoglobin concentration between the exposure group and the control group, as well as the pre-employment control group ( P<0.05). Through Lasso variable selection, 19 indicators including exposure length, systolic blood pressure (SBP), diastolic blood pressure (DBP), body weight, body mass index (BMI), urine pH value, red blood cell count, microscopic white blood cells, casts, absolute value of monocytes, mean corpuscular volume of red blood cells, mean hemoglobin concentration, alkaline phosphatase, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, and low-density lipoprotein cholesterol (LDL-C). There were statistically significant differences in exposure length, SBP, DBP, body weight, BMI, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, and mean corpuscular volume of red blood cells among workers of different ages in the exposure group ( P<0.05) ; there were statistically significant differences in SBP, DBP, body weight, BMI, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, and mean corpuscular volume of red blood cells among workers with different exposure durations ( P<0.05) ; there were statistically significant differences in exposure length, SBP, DBP, body weight, BMI, red blood cells, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, absolute value of monocytes, mean corpuscular volume of red blood cells, and mean hemoglobin concentration among workers with different BMIs ( P<0.05) . Conclusion:Occupational ionizing radiation is associated with abnormal metabolic indicators such as blood pressure, heart rate, total bile acid, α-L-fucosidase, urea, and creatinine in the human body. More attention should be paid to the risk of chronic metabolic diseases among workers exposed to ionizing radiation.