Objective To clarify the role and underlying mechanism of macrophage-to-myofibroblast transition (MMT) in renal fibrosis that develops after acute kidney injury (AKI) induced by ischemia-reperfusion injury (IRI). Methods Mouse AKI model was generated by renal ischemia-reperfusion. Animals were randomized into control (Con), sham operated (Sham), and IRI groups sacrificed at 1 d (IRI 1 d), 3 d (IRI 3 d) and 14 d (IRI 14 d) after reperfusion (n = 5). Renal injury was assessed by renal coefficient, serum creatinine (Scr) and kidney injury molecule-1 (KIM-1). Periodic acid-Schiff (PAS) staining was used to evaluate tubular damage and inflammatory infiltration. Masson staining and immunohistochemistry were employed to quantify collagen deposition, α-smooth muscle actin (α-SMA) and type I collagen (COL I). Flow cytometry was used to determine macrophage infiltration and phenotype. MMT was identified by flow cytometry plus immunofluorescence. Transforming growth factor (TGF)-β1/Smad3 pathway proteins were examined by Western blotting. Results Compared with Sham group, renal coefficient, Scr and KIM-1 rose in IRI 1 d group, renal coefficient and KIM-1 remained elevated in IRI 3 d group. Compared with the IRI 1 d group, the renal coefficient and KIM-1 decreased in the IRI 14 d group. Compared with the IRI 3 d group, the renal coefficient, Scr and KIM-1 decreased in the IRI 14 d group (all P < 0.05). PAS revealed the most severe tubular injury at IRI 3 d. Masson staining showed progressively increasing collagen deposition, while immunohistochemistry demonstrated α-SMA and COL I rising from day 1 and persisting to day 14 (all P < 0.05). Macrophage infiltration increased from day 1 and lasted to day 14 (P < 0.05). M1 macrophages peaked at day 1 then declined, whereas M2 macrophages increased at day 3 and remained high through day 14 (P < 0.05). MMT began to rise at day 3 and continued to day 14 and M2 macrophages were the predominant source of MMT cells (all P < 0.05). Compared with Sham group, TGF-β1 protein was up-regulated and p-Smad3/Smad3 ratio was elevated in all IRI groups (all P < 0.05). Conclusions M2 macrophages promote post-IRI-AKI renal fibrosis via MMT, a process closely linked to activation of the TGF-β1/Smad3 signaling pathway.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveTo investigate the mechanism by which Wumeiwan suppresses the development and progression of colorectal cancer（CRC） through the regulation of fatty acid metabolic reprogramming， thereby providing new experimental evidence for the prevention and treatment of CRC. MethodsA total of 120 C57BL/6 mice were randomly divided into the blank group， model group， Wumeiwan high-， medium-， and low-dose groups（54， 27， 13.5 g·kg^-1）， and the mesalazine group（0.01 g·kg^-1）， with 20 mice in each group. Except for the blank group， all mice were subjected to azoxymethane（AOM）/dextran sulfate sodium（DSS） treatment to establish an inflammation-associated CRC model. One week after AOM injection， mice in the treatment groups received intragastric administration of the designated drugs， while the blank and model groups received an equal volume of purified water， continuing until 20 d after the intervention endpoint. Hematoxylin-eosin（HE） staining was used to observe colonic histopathological alterations， and immunohistochemistry for vascular endothelial growth factor（VEGF） was performed to evaluate neovascularization and tumor invasion. Metabolomics combined with Kyoto Encyclopedia of Genes and Genomes（KEGG） and metabolite set enrichment analysis（MSEA） was applied to identify key CRC-related metabolic pathways， which were further validated by transcriptomic Gene Ontology（GO） enrichment and gene heatmap analysis. Subsequently， Western blot was performed to determine the expression levels of core proteins in these pathways， and immunofluorescence was used to analyze their localization and co-expression patterns in tissues， thereby elucidating the mechanism of Wumeiwan from multiple biological dimensions. ResultsCompared with the blank group， mice in the model group exhibited a significant decrease in body weight and a significant increase in the disease activity index（DAI） score（P<0.05）， with pronounced colonic mucosal damage accompanied by aggravated tumor invasion. Compared with the model group， Wumeiwan intervention markedly improved body weight loss and reduced DAI score， attenuated mucosal injury， and significantly decreased VEGF expression level（P<0.05）. Multi-omics analysis revealed that differential metabolites and genes across groups were commonly enriched in fatty acid metabolism， fatty acid biosynthesis， and other lipid-related pathways. Relative to the blank group， the model group showed significant upregulation levels of fatty acid synthesis-related genes， including sterol regulatory element-binding protein 1（SREBP1）， fatty acid synthase（FASN）， stearoyl-CoA desaturase 1（SCD1）， as well as saturated fatty acids（P<0.05）. Compared with the model group， treatment with Wumeiwan significantly reduced the expression of key genes involved in fatty acid metabolic pathways， including SREBP1， FASN， and SCD1（P<0.05）. Western blot results further confirmed that proteins in this pathway were significantly elevated in the model group， whereas they were markedly downregulated following Wumeiwan treatment（P<0.05）. Immunofluorescence analysis demonstrated enhanced co-localization of SREBP1 with the cancer-associated fibroblast（CAF） marker α-smooth muscle actin（SMA） in the model group， whereas this co-localization signal was attenuated after Wumeiwan intervention（P<0.05）. ConclusionWumeiwan can improve survival outcomes and alleviate colonic pathological damage in CRC mice， its therapeutic mechanism may be closely associated with the regulation of fatty acid metabolic reprogramming mediated by the SREBP1/FASN/SCD1 signaling pathway.

Objective To analyze survival outcomes and influencing factors among patients with colorectal cancer in Yunnan Province. Methods Clinical data were retrospectively collected from 4 892 patients with colorectal cancer. Survival data were obtained through follow-up. Overall survival (OS) was calculated by using the Kaplan-Meier method. Univariate analysis was performed by applying the log-rank test. Meanwhile, multivariate analysis employed the Cox proportional hazards regression model. Results The 1-, 3-, 5-, and 10-year OS rates for the entire cohort were 91.90%, 74.40%, 64.40%, and 28.70%, respectively. Univariate analysis revealed that age, ethnicity, region, differentiation grade, TNM stage, clinical stage, metastatic status, histological type, and treatment modality (chemotherapy, radiotherapy, and surgery) were associated with patient prognosis (all P<0.05). Multivariate analysis identified age (HR=1.250), region (HR=1.262), differentiation grade (HR=0.761), clinical stage (HR=3.128), and treatment modality (chemotherapy, HR=0.644; radiotherapy, HR=1.605; surgery, HR=0.384) as independent factors affecting survival prognosis in patients with colorectal cancer (all P<0.001). Conclusion Age, region, clinical stage, and treatment modality are independent factors influencing survival among patients with colorectal cancer in Yunnan Province. In clinical practice, these factors should be integrated to develop individualized prevention and treatment strategies, thereby improving patient outcomes.

AIM: To analyze the current status and influencing factors for insufficient hyperopia reserve in preschool children from Changzhi City, Shanxi Province, and to provide reference and basis for myopia prevention and control in this district.METHODS: A stratified cluster random sampling strategy was used to select 2 854 preschool children(5 708 eyes)from 29 child-care centers in Changzhi City between January and May 2024. Hyperopia reserve was assessed through measurements and questionnaire surveys. Totally 2 820 cases(5 640 eyes)were finally included, with 34 cases excluded(32 cases of uncooperativeness and 2 cases of distractibility). The univariate analysis and multivariate Logistic regression were performed to analyze the associated influencing factors of insufficient hyperopia reserve.RESULTS: A total of 580 preschool children with insufficient hyperopia reserve were detected, with an incidence of 20.57%. Logistic regression analysis revealed that male(OR=1.723, 95% CI: 1.419-2.093), maternal myopia(OR=2.210, 95% CI: 1.681-2.906), paternal myopia(OR=1.426, 95% CI: 1.059-1.921), myopia in both parents(OR=2.761, 95% CI: 2.110-3.612), preterm infants(OR=1.740, 95% CI: 1.294-2.342), the mean daily sleep duration <10 h(OR=1.272, 95% CI: 1.024-1.579), and the mean daily outdoor activity time <2 h(OR=1.222, 95% CI: 1.005-1.485)were risk factors for insufficient hyperopia reserve(all P<0.05). Conversely, using blackout curtains during the day and turning off lights at night(OR=0.598, 95% CI: 0.405-0.883)were identified to be protective factors(P<0.05).CONCLUSION: Sex, genetics, gestational age, sleep duration and environmental conditions, and outdoor activity time are potentially associated with insufficient hyperopia reserve in preschool children. Caregivers should prioritize the management of these risk factors to prevent the occurrence of myopia.

Renal fibrosis is a common pathological change from development to end-stage renal diseases in all progressive chronic kidney diseases. Renal fibrosis after kidney transplantation will severely affect the renal graft function. Macrophages are characterized with high heterogeneity and plasticity. During the process of kidney injury, macrophages are recruited, activated and polarized by local microenvironment, and participate in the process of renal tissue injury, repair and fibrosis through multiple mechanisms. Recent studies have shown that macrophages may transit into myofibroblasts and directly participate in the formation of renal fibrosis. This process is known as macrophage-myofibroblast transition. Nevertheless, the regulatory mechanism remains elusive. In this article, the role of macrophages in renal fibrosis, the characteristics of macrophage-myofibroblast transition and the possible regulatory mechanism were reviewed, aiming to provide reference for relevant research of renal fibrosis.

Objective To investigate the virulence and drug resistance characteristics of diarrheagenic Escherichia coli isolated from patients with infectious diarrhea in our hospital.Methods The preliminary identification of microbes was carried out by the VITEK-MS microbial mass spectrometry detection system and virulence genes were detected by the multiplex real-time PCR.Five types of diarrhea-genic Escherichia coli(DEC)clinically isolated from patients with infectious diarrhea in our hospital were identified.The drug resist-ance characteristics of DEC strains were detected by the microbroth dilution and E-test.The drug-resistant molecular characteristics were analyzed by the next-generation sequencing and bioinformatics.The Fisher exact probability method was used for statistical analy-sis.Results The detection rate of DEC in our hospital was 11.9%,with enteroaggregative E.coli(EAEC)accounting for 37.5%,a-typical enteropathogenic Escherichia coli(EPEC)accounting for 34.38%,enterotoxigenic E.coli(ETEC)accounting for 25.0%,and enteroinvasive E.coli(EIEC)accounting for 3.12%.None of enterohemorrhagic E.coli(EHEC)strain was detected.The resistance rates of 32 DEC strains to ampicillin,tetracycline,and trimethoprim/sulfamethoxazole were 53.12%,43.75%,and 37.5%,respec-tively.ESBLs(+)strains accounted for 18.75%,and the detection rate of multidrug-resistant strains was 83.83%,significantly higher than that of ESBLs(-)strains(P=0.042).A total of 25 ST genotypes were obtained from 32 DEC strains.The dominant genotypes were ST10(4 strains,12.5%),followed by ST28(2 strains,6.25%),ST31(2 strains,6.25%),ST3153(2 strains,6.25%),and the other 21 genotypes(1 strain,3.13%).One carbapenem resistant strain carrying the blaNDM-1 gene was detected in EAEC.Conclu-sion Four virulence genes such as aggR,pic,astA,and eae,are more common in the DEC of patients with infectious diarrhea in our hospital,with EAEC and EPEC as the main subtypes.The genotypes are highly polymorphic,and multidrug-resistant strains have been detected.

ObjectiveBased on non-targeted metabolomics， to analyze the regulation of endogenous differential metabolites in serum of type 2 diabetes mellitus（T2DM） rats by Fuling Yunhua granules， and to clarify the metabolic pathways through which this granules exerted its effect on improving T2DM. MethodSeventy SD rats， half male and half female， were randomly divided into the control group， model group， and high， medium， low dose groups of Fuling Yunhua granules（20.70， 10.35， 5.18 g·kg^-1 in raw drug amount） and the positive drug group（pioglitazone hydrochloride tablets， 8.1 mg·kg^-1）. Except for the control group， other groups were fed with high-sugar and high-fat diet combined with intraperitoneal injection of streptozotocin（STZ） to establish a T2DM rat model. After successful modeling， the treatment groups were administered the corresponding drugs by gavage， and the control group and model group were treated with an equal volume of saline by gavage， once/d， for 28 d. Fasting blood glucose（FBG） and glycosylated hemoglobin A1c（GHbA1c） levels were measured in all groups of rats during the administration period， and hematoxylin-eosin（HE） staining was used to observe the pathomorphological changes in the pancreatic tissues of rats at the end of the administration period. The endogenous metabolite levels in rat serum were detected by ultra-performance liquid chromatography-linear ion trap-electrostatic field orbitrap high-resolution mass spectrometry（UPLC-LTQ-Orbitrap MS）， and the data were processed using principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）. Differential metabolites were identified by the Human Metabolome Database（HMDB） and the Kyoto Encyclopedia of Genes and Genomes（KEGG）， and screened for differential metabolites with variable importance in the projection（VIP） value>1， P<0.05， and fold change（FC）<0.6 or FC>1. And the metabolic pathway enrichment analysis of the screened differential metabolites was performed by MetaboAnalyst 5.0， then the screened differential metabolites were diagnosed and evaluated by the receiver operating characteristic（ROC） curves. ResultCompared with the control group， the FBG level of rats in the model group increased significantly（P<0.01）， the GHbA1c content tended to increase， but the difference was not statistically significant， and the pancreatic tissue of rats was obviously damaged， the number of pancreatic islets decreased， and the pancreatic β-cells were obviously reduced， atrophied and enlarged. Compared with the model group， the FBG levels of rats in the high dose group of Fuling Yunhua granules and the positive drug group were significantly reduced after 2 weeks of administration（P<0.05， P<0.01）， the GHbA1c content of rats in the high dose group of Fuling Yunhua granules was significantly reduced（P<0.05）， and the pancreatic tissue lesions of rats in the different dose groups of Fuling Yunhua granules were reduced. The results of non-targeted metabolomics showed that 46 differential metabolites were significantly changed in the model group compared with the blank group. Pathway enrichment analysis found that T2DM mainly affected biological processes including biosynthesis of primary bile acid， D-amino acid metabolism， steroid hormone biosynthesis， and glycerophospholipid metabolism in rats. Compared with the model group， the levels of 8 differential metabolites in the high dose group of Fuling Yunhua granules were significantly adjusted， and the pathway enrichment analysis found that D-amino acid metabolism， retinol metabolism， glycine， serine and threonine metabolism， tryptophan metabolism and other metabolic pathways were mainly involved. ROC curves further analysis revealed that the four characteristic differential markers of 11-cis-retinol， D-piperidinic acid， D-serine， and p-cresol sulfate had high diagnostic value for the treatment of T2DM with Fuling Yunhua granules. ConclusionFuling Yunhua granules can improve the symptoms of T2DM rats by regulating the amino acid metabolic and retinol metabolic pathways through the modulation of endogenous differential metabolites.