ObjectiveTo investigate the effects of targeted silencing of Runt-related Transcription Factor 3 （RUNX3） on the proliferation and migration of Mouse Hepatic Stellate Cells （HSCs）， as well as subsequent collagen deposition. MethodsMouse hepatic stellate cell line （JS-1） was selected and then morphologically observed and identified under a microscope. After the cells had fully adhered， they were treated with 5 ng/mL of transforming growth factor beta 1 （TGF-β₁） for 24 hours to induce hepatic stellate cell activation. Furthermore， a RUNX3 silencing model was established using RUNX3 lentiviral infection. The experiment was divided into four groups： Control group， TGF-β₁ group， TGF-β₁+siRNA-NC group， and TGF-β₁+siRNA-RUNX3 group. Protein expression changes of RUNX3， alpha-smooth muscle actin （α-SMA）， and Alpha 1 type I collagen （Collagen I） were detected using Western blot method. Cellular immunofluorescence assays were employed to investigate the deposition changes of α-SMA and RUNX3 in hepatic stellate cells. RT-qPCR was utilized to examine the mRNA expression changes of RUNX3， α-SMA， and Collagen I. The proliferative capacity of hepatic stellate cells was assessed using Edu staining. The migratory ability of hepatic stellate cells was evaluated through wound healing assays and Transwell migration experiments. ResultsCompared with Control group， a significant elevation in RUNX3 was observed in the TGF-β₁-induced activated HSCs （P<0.01）. Meanwhile， the protein and mRNA levels of fibrosis-related markers and α-SMA and Collagen I were significantly upregulated （P<0.001）. Additionally， the proliferation and migration capabilities of HSCs were significantly enhanced （P<0.001）. In contrast， when compared to TGF-β₁+siRNA-NC group， TGF-β₁+siRNA-RUNX3 group exhibited a notable decrease in RUNX3 and other related indicators， such as the protein and mRNA levels of α-SMA and Collagen I （P<0.05）. Concurrently， the proliferation and migration capabilities of HSCs were significantly inhibited in TGF-β₁+siRNA-RUNX3 group （P<0.01）. ConclusionSilencing RUNX3 can inhibit the deposition of collagen and the proliferation and migration of hepatic stellate cells. Conversely， RUNX3 promotes the proliferation and migration capabilities of HSCs， thereby facilitating the activation of HSC.

ObjectiveTo investigate the role of runt-related transcription factor 3 （RUNX3） in transforming growth factor-β₁ （TGF-β₁）-induced activation of mouse primary pulmonary fibroblasts （PFs）， and its effects on fibroblast activation protein （FAP） expression， cell proliferation， and collagen synthesis. MethodsPFs were isolated from C57BL/6 mice and cultured. A RUNX3 knockdown model was established using small interfering RNA （siRNA）. Cells were assigned to the control group （Control）， TGF-β₁-treated group （TGF-β₁）， negative control group （TGF-β₁+siRNA-NC）， and RUNX3-silenced group （TGF-β₁+si-RUNX3）. In addition， a RUNX3 overexpression rescue experiment was performed based on TGF-β₁ stimulation. Protein and mRNA levels of RUNX3， FAP， and typeⅠcollagen （COL1A1） were measured by Western blot and reverse transcription quantitative real-time PCR （RT-qPCR）. Cell proliferation was assessed using CCK-8 and EdU assays. Co-expression of COL1A1 and FAP was examined by double immunofluorescence staining. ResultsCompared with the Control group， RUNX3， FAP， and COL1A1 expression levels were upregulated in PFs in the TGF-β₁ group （P<0.01）. The CCK-8 assay showed that the absorbance value was reduced in the RUNX3 knockdown group compared with the negative control group （P<0.01）. Consistently， the EdU assay demonstrated a lower proportion of EdU-positive cells in the RUNX3 knockdown group than in the negative control group （P<0.01）. Immunofluorescence double staining revealed decreased fluorescence intensities of COL1A1 and FAP in the RUNX3 knockdown group relative to the negative control. Under RUNX3 overexpression conditions， these fluorescence signals exhibited a partial rebound （P<0.01）. ConclusionRUNX3 in TGF-β1-induced PFs may promote cell proliferation and collagen synthesis by positively regulating FAP expression. Targeting the RUNX3/FAP axis may represent a potential therapeutic strategy for pulmonary fibrosis.

Objective To evaluate the efficacy of Puerariae lobatae radix （PLR） and Anemarrhenae Rhizoma （AR） in preventing and treating Alzheimer’s disease （AD） and explore its potential mechanism of action by LC-MS serum metabolomics strategy. Methods The AD rat model was established by administering aluminum chloride （AlCl₃） and D-galactose （D-gal） for 20 weeks. The traditional Chinese medicine intervention group was given the PLR, AR, and PLR-AR extracts for 8 weeks by gavage. The model effect and efficacy were evaluated by Morris water maze test and biochemical indicators including SOD, NO, and MDA; Metabolomics research based on the UHPLC-Q/TOF-MS method was conducted, and relevant metabolic pathways were analyzed through the MetaboAnalyst online website. Results The learning and memory abilities of AD model rats were significantly decreased compared with the control group, and the levels of oxidative stress and lipid peroxides were significantly increased （P<0.05）, while the SOD content was decreased considerably （P<0.01）. The learning and memory abilities of AD model rats were improved, oxidative stress and lipid peroxidation levels were reversed, and serum SOD content was increased significantly after the intervention of PLR-AR, with better effects than single drugs. Through metabolomics, 70 differential metabolites were identified between the AD model group and the control group, mainly involving 10 pathways, including phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, and unsaturated fatty acid biosynthesis, et.al. The intervention of PLR-AR could adjust 47 metabolites, with 20 metabolites showing significant differences （P<0.05）. The significantly adjusted metabolites involve 6 pathways, including phenylalanine, tyrosine, and tryptophan biosynthesis, et al. Conclusion The combination of PLR and AR could significantly improve the learning and memory abilities of AD rat models. The mechanism may be related to the improvement of oxidative stress and lipid peroxidation levels, the increase of serum SOD content, and the regulation of phenylalanine, tyrosine, and tryptophan biosynthesis pathways.

ObjectiveTo explore the potential mechanism of moxibustion at Guanyuan （CV 4） in delaying skin photoaging. MethodsThirty-two male Wistar rats were randomly divided into four groups， namely blank group， model group， vitamin E group， and moxibustion group， with 8 rats in each group. Except for the blank group， dorsal skin of rats were exposed to ultraviolet （UV） radiation to establish a skin photoaging model. One week after modeling， the moxibustion group received moxibustion at "Guanyuan （CV 4）" once a day， five days per week； the vitamin E group received vitamin E （25 mg/kg·d） once a day by gavage， five days per week； the blank group， model group， and moxibustion group received an equivalent volume of normal saline via gavage； the intervention lasted for 7 weeks. After 7 weeks， dorsal skin tissues were collected to analyze the following indicators， such as skin tissue moisture content， histomorphological changes using hematoxylin-eosin （HE） staining， Collagen Ⅰ and collagen Ⅲ content using ELISA. Malondialdehyde （MDA）， glutathione peroxidase （GSH-Px）， superoxide dismutase （SOD）， hydrogen peroxide （H₂O₂）， and catalase （CAT） activity in skin tissue were dectected. Western Blot was used to determin autophagy-related proteins， including microtubule-associated protein 1A/1B-light chain 3 （LC3）， polyubiquitin-binding protein （p62）， and autophagy-specific gene （Beclin-1）； LC3， p62， and Beclin-1 mRNA expression was detected via qRT-PCR， and autophagosome formation was observed using transmission electron microscopy （TEM）. ResultsHE staining showed that the epidermal structure in the blank group was orderly and evenly thick， while the model group exhibited uneven epidermal thickness. In the moxibustion group， the epidermis was well-structured， smooth， and uniform， with densely arranged dermal layers； the epidermis in the vitamin E group was thicker than that in the model group. Compared with the blank group， the model group exhibited decreased skin moisture content and reduced level of Collagen Ⅰ and collagen Ⅲ， reduced SOD， CAT， and GSH-Px activity in skin tissue， increased H₂O₂ and MDA activity， elevated p62 protein and mRNA expression， reduced LC3 and Beclin-1 protein and mRNA expression （P＜0.05 or P＜0.01）. Compared with the model group， the moxibustion group showed significant improvement in all these indicators （P＜0.05 or P＜0.01）； whereas the vitamin E group did not show a statistically significant difference in Collagen Ⅰ and collagen Ⅲ levels （P＞0.05）. TEM results showed that， compared with the blank group， the model group had atrophic skin cells， extensive mitochondrial vacuolization， and degraded cellular structures； the moxibustion group exhibited crescent- or cup-shaped autophagosomes with a significantly increased number of autophagosomes per unit area， whereas the vitamin E group showed less improvement than the moxibustion group. ConclusionMoxibustion at "Guanyuan （CV 4）" may alleviate skin photoaging by regulating oxidative stress imba-lance， modulating cellular autophagy， and promoting collagen synthesis， thereby slowing the aging process of the skin.

Objective:To analyze the prognostic factors of patients with liver cirrhosis and portal vein thrombosis (PVT), and to construct a prognostic prediction model based on machine learning methods.Methods:The clinical data of 388 patients with liver cirrhosis and PVT admitted to the Fifth Medical Center of PLA General Hospital from January 2022 to April 2024 were retrospectively collected and analyzed, including 243 males and 145 females, aged (56.9±10.9) years. A total of 388 patients were randomly divided into the training set ( n=310) and the testing set ( n=78) in a 4∶1 ratio. The Boruta algorithm was used to screen the key features in the training set, and then four machine learning algorithms, including random forest, support vector machine, generalized linear model and Bayesian, were used to establish a survival prediction model. Model performance was evaluated by the receiver operating characteristic (ROC) curves of the test set and the training set. The patients were followed up for 1 year for survival. Sort the importance of features based on the SHAP value. Results:There were 250 patients (80.6%) who survived and 60 (19.4%) who died. The model for end-stage liver disease score, total bilirubin, serum creatinine, prothrombin time, international normalized ratio, D-dimer, white blood cell count, severe ascites ratio, and Child-Pugh grade C ratio of liver function in the death group were higher than those in the survival group, and the red blood cell count and hematocrit were lower than those in the survival group, and the differences were statistically significant (all P<0.05). The areas under the ROC curve for predicting survival by random forest, support vector machine, generalized linear model and Bayesian model were 0.92, 0.78, 0.81 and 0.71 in the training set, and the area under the ROC curve in the testing set were 0.81, 0.72, 0.67 and 0.68, respectively. Random forest had the best prediction performance, with an accuracy of 81.7%, a sensitivity of 84.6%, and a specificity of 76.9% in the testing set. In the analysis of the importance of characteristic parameters of the random forest model, total bilirubin, red blood cells, hematocrit, serum creatinine, ascites classification, etc. had a relatively high contribution to the model. Conclusion:In the survival prediction model of patients with liver cirrhosis and PVT based on machine learning algorithm, the random forest model had high prediction performance, and total bilirubin may be the most important factor affecting the survival prognosis of patients.

Objective:To analyze the prognostic factors of patients with liver cirrhosis and portal vein thrombosis (PVT), and to construct a prognostic prediction model based on machine learning methods.Methods:The clinical data of 388 patients with liver cirrhosis and PVT admitted to the Fifth Medical Center of PLA General Hospital from January 2022 to April 2024 were retrospectively collected and analyzed, including 243 males and 145 females, aged (56.9±10.9) years. A total of 388 patients were randomly divided into the training set ( n=310) and the testing set ( n=78) in a 4∶1 ratio. The Boruta algorithm was used to screen the key features in the training set, and then four machine learning algorithms, including random forest, support vector machine, generalized linear model and Bayesian, were used to establish a survival prediction model. Model performance was evaluated by the receiver operating characteristic (ROC) curves of the test set and the training set. The patients were followed up for 1 year for survival. Sort the importance of features based on the SHAP value. Results:There were 250 patients (80.6%) who survived and 60 (19.4%) who died. The model for end-stage liver disease score, total bilirubin, serum creatinine, prothrombin time, international normalized ratio, D-dimer, white blood cell count, severe ascites ratio, and Child-Pugh grade C ratio of liver function in the death group were higher than those in the survival group, and the red blood cell count and hematocrit were lower than those in the survival group, and the differences were statistically significant (all P<0.05). The areas under the ROC curve for predicting survival by random forest, support vector machine, generalized linear model and Bayesian model were 0.92, 0.78, 0.81 and 0.71 in the training set, and the area under the ROC curve in the testing set were 0.81, 0.72, 0.67 and 0.68, respectively. Random forest had the best prediction performance, with an accuracy of 81.7%, a sensitivity of 84.6%, and a specificity of 76.9% in the testing set. In the analysis of the importance of characteristic parameters of the random forest model, total bilirubin, red blood cells, hematocrit, serum creatinine, ascites classification, etc. had a relatively high contribution to the model. Conclusion:In the survival prediction model of patients with liver cirrhosis and PVT based on machine learning algorithm, the random forest model had high prediction performance, and total bilirubin may be the most important factor affecting the survival prognosis of patients.

Autophagy is a cellular self-degradation process that maintains homeostasis and has been shown to promote tumor progression in advanced stages.Pancreatic cancer cells and the surrounding stromal cells exhibit high levels of autophagy.Therefore,targeting au-tophagy has emerged as a promising therapeutic strategy for pancreatic cancer.This review focuses on research targeting autophagy in pancreatic cancer treatment,elaborating on the roles and underlying mechanisms of autophagy in pancreatic cancer cell proliferation,metas-tasis,modulation of the tumor immune microenvironment,and drug resistance.Additional-ly,we summarize preclinical and clinical studies investigating autophagy-targeted therapies both as monotherapy and in combination with other treatments,aiming to provide new theo-retical rationale and therapeutic strategies for pancreatic cancer management.

Objective The aim of this study is to examine the Chinese version of Visual Prostate Symptom Score(CVPSS)and the International Prostate Symptom Score(IPSS)in the assessment of lower urinary tract symptoms in BPH pa-tients.Methods By using convenient sampling,inpatients in the urology department of a tertiary grade A hospital in Shanghai were selected as the survey subjects from March 2023 to March 2024.The lower urinary tract symptoms of the patients were eval-uated using the self-designed general information questionnaire.And the CVPSS and IPSS with their urine flow rate were meas-ured.A comparative analysis was conducted from aspects such as internal consistency,correlation of item scores,completion time of the scale,and assistance rate.Results A total of 246 patients with BPH were recruited.The total score and life quality score were 13.93±3.55 and 4.23±1.02 by CVPSS.And the total score and life quality by IPSS was 18.33±7.55 and 4.36±1.02,respectively.The Cronbach's α coefficient were 0.761 and 0.787,respectively.The time taken on CVPSS was less than that on IPSS(P＜0.01).And the rate of needing assistance was 23.58％for CVPSS,which was significantly lower than that(65.24％)for IPSS.Conclusion CVPSS is significantly correlated with the corresponding items and total scores of IPSS,as well as the quality of life.Moreover,it takes less time and can be used as a simple and effective self-assessment tool for lower urinary tract symptoms in elderly BPH patients with lower education levels.It reduces the burden of medical staffs as well.

As the most common phenotype of type 1 neurofibromatosis(NF1),plexiform neurofibromas(pNF)exhibit early asymptomatic presentation but multisite involvement,with a risk of progression.Imaging serves as vital tool for evaluation and management of NF1-associated pNF.The progresses of imaging for evaluating NF1-related pNF were reviewed in this article.

Aim To investigate the effect of Huangqi injection(HI)and Huangqi oral solution(HO)on cisplatin-induced nephrotoxicity(CIN)based on un-targeted metabolomics technology and the underlying mechanisms.Methods Sprague Dawley(SD)rats were randomly divided into the blank group,cisplatin(CDDP)model group,HI treatment group,and HO treatment group,then the CIN model was built with low dose multiple intraperitoneal injections of CDDP.Pre-liminary evaluation of the renal protective efficacy of HI and HO was performed by measuring serum creatinine(Scr),blood urea nitrogen(BUN),and organ indi-ces.Further screening and identification of potential biomarkers(PBs)related to CIN and HI/HO pharma-cological effects were attained through metabolomics studies of renal tissues,and pathway enrichment analy-sis was conducted.Results HI and HO significantly restored the abnormal increase in renal function indica-tors and abnormal decrease in organ indices caused by CDDP,as well as significantly improved the abnormal renal metabolic profile induced by CDDP,indicating that both HI and HO had good alleviating effects on CIN.HI significantly reversed 47 out of 54 CIN related PBs,mainly involving metabolic pathways such as glycerophospholipid metabolism,tryptophan metabo-lism,pantothenate and CoA biosynthesis;HO signifi-cantly reversed 18 out of 54 CIN related PBs,mainly involving metabolic pathways such as taurine and hypo-taurine metabolism,ascorbate and aldarate metabo-lism,pentose and glucuronate interconversions.Con-clusions Both HI and HO have significant alleviating effects on CIN.In the short term,HI salleviating effect is superior to that of HO.Overall,the mechanisms by which both alleviate CIN are mainly related to regula-ting lipid metabolism,amino acid metabolism.