Objective To investigate the correlation between gut microbiota characteristics and immunotherapy efficacy in patients with advanced microsatellite stable (MSS) advanced gastrointestinal tumors. Methods Thirty patients with advanced MSS gastrointestinal tumors, including fourteen cases of gastric cancer and sixteen cases of colorectal cancer, who were admitted from November 1, 2022, to July 31, 2025 were enrolled. All patients underwent gut microbiota testing and received corresponding interventions on the basis of the results, followed by treatment with antiangiogenic agents combined with immunotherapy. Some patients additionally received probiotics or fecal microbiota transplantation. The primary endpoints were disease control rate (DCR) and objective response rate (ORR). The secondary endpoints were progression-free survival (PFS) and overall survival (OS). Univariate and multivariate Cox regression analyses were used to assess potential prognostic factors. Results Among the thirty patients, no complete response was observed. Two cases of partial response (PR), twelve cases of stable disease, and sixteen cases of progressive disease were recorded. The ORR was 6.7%, and the DCR was 46.7%. The median PFS was 6.4 months, and the median OS was 8.3 months. Both PR patients were classified as having a medium risk of gut microbiota dysbiosis and exhibited a Bacteroides-dominated enterotype. Multivariate analysis indicated that tumor type, liver metastasis, and bone metastasis were potential prognostic factors for PFS and OS. Conclusion Patients with a medium risk of gut dysbiosis may exhibit a relatively favorable response to immunotherapy, suggesting that gut microbiota status could serve as a potential biomarker for predicting treatment efficacy in advanced MSS gastrointestinal tumors.

Combined with elastic network model(ENM),the perturbation response scanning(PRS)has emerged as a robust technique for pinpointing allosteric interactions within proteins.Here,we proposed the PRS analysis of drug-target networks(DTNs),which could provide a promising avenue in network medicine.We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework,for drug repurposing of multiple sclerosis(MS).First,the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes.Then,based on topological analysis and functional annotation,the neurotransmission module was identified as the"therapeutic module"of MS.Further,perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis,giving a list of repurposable drugs for MS.Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of se-rotonin 2B receptor(HTR2B).Finally,we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex.These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS.As a useful systematic method,our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Aim To explore the therapeutic effects of resveratrol(Res)on hepatic inflammation and oxida-tive stress in rheumatoid arthritis(RA),and to eluci-date the relationship of the regulatory mechanism of the Nrf2/Keap1 signaling pathway in it.Methods A mouse model of arthritis was induced using chicken type Ⅱ collagen in combination with complete Freund's adjuvant,and Res was administered by tube feeding for treatment.Serum liver function indices and levels of hepatic inflammation and oxidative stress were detected in mice.An in vitro cellular model of hepatic inflam-mation and oxidative stress was established by treating mouse primary hepatocytes(MPHs)with TNF-α(5μg·L-1),cell proliferation inhibition was detected by CCK-8,and inflammation and oxidative stress-relat-ed indices were detected by protein blotting.The in-trinsic mechanisms by which Res attenuated hepatic in-flammation and oxidative stress in rheumatoid arthritis were explored by treating MPHs with Nrf2 inhibitor and Keap1 overexpression plasmid.Results Res signifi-cantly reduced the levels of inflammation and oxidative stress in hepatic tissues of collagen-induced arthritis mice as well as TNF-α-treated MPHs,and activated the Nrf2/Keap1 signaling pathway.Inflammation and oxidative stress levels in MPHs were exacerbated by the use of Nrf2 inhibitors and Keap1 overexpression,which promoted apoptosis.Conclusion Res attenuates he-patic inflammation and oxidative stress in rheumatoid arthritis via the Nrf2/Keap1 pathway.

Objective To explore the factors that influence major adverse cardiovascular events(MACE)in atrial fibrillation(AF)patients undergoing radiofrequency ablation(RFA),as well as to compare the prognosis of patients with advanced AF to that of the general population.Methods We prospectively recruited AF patients who underwent RFA treatment at Peking University Third Hospital between January 2021 and March 2023.General patient data were collected through the hospital's inpatient system,and MACE were tracked through outpatient visits and telephone follow-ups.Patients were categorized into three age groups:Group 1(under 65 years),Group 2(65 to 75 years),and Group 3(over 75 years).In this study,MACE was defined as include cardiovascular death,all-cause death,readmission for heart failure,acute coronary syndrome(ACS),grade 2 or higher bleeding and stroke.Results A total of 431 patients were included in this study,with an average age of(66.17±12.22)years.Among these patients,259 were male(60.09％),and the mean of CHA2DS2-VASc score was(1.79±1.30).The median follow-up period was 16.0(11.3,21.3)months,during which 28(6.50％)patients experienced MACE,with ACS and stroke being the most common events.Variables were selected using LASSO regression,and a LASSO-Cox regression model was constructed.Age(HR 1.06,95％CI 1.02-1.10,P=0.006)and hypertrophic cardiomyopathy(HR 3.70,95％CI 1.27-8.68,P=0.008)were identified as independent predictors of MACE after RFA for AF.Subgroup analysis revealed that patients under 65 had significantly better prognoses compared to older AF patients(P=0.030 compared with group 2;P=0.021 compared with group 3).Conclusions Age and hypertrophic cardiomyopathy are independent risk factors for MACE in AF patients undergoing RFA.The prognosis for younger patients is better than that for older patients,while the prognosis for advanced patients is comparable to that of patients aged 65-75 years.

AIM To study the chemical constituents from Gymnema tingens Spreng.and their in vitro hypoglycemic activity.METHODS The 70％ethanol extract was isolated and purified by macroporous resin,silica gel,sephadex LH-20,and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical propeties and spectral data.The in vitro hypoglycemic activity was evaluated by glucose uptake test in L6 cells.RESULTS Seventeen compounds were isolated and identified as 7-desoxyneocynapanogenin A(1),glaucogenin(2),cynatratoside A(3),atratcynoside F(4),(+)-lyoniresinol(5),(+)-lyoniresinol 3-O-α-D-rhamnopyranoside-(1→6)-β-D-glucopyranoside(6),fernandoside(7),3,4-dimethoxy-phenyl-1-O-β-D-apiofuranosyl-(1→2)-β-D-glucopyranoside(8),khaephuoside A(9),khaephuoside B(10),3,4,5-trimethoxy-phenyl-O-β-D-glucopyranoside(11),liquiritigenin(12),7,3'-dihydroxy-flavanone-4'-O-β-D-glucopyranoside(13),pinoresinol(14),syringaldehyde(15),(+)-1-hydroxy-pinoresinol-1-β-D-glucopyranoside(16),β-amyrin(17).Compounds 2-5、7、9、10、12、17 could promote the glucose uptake in L6 cells.CONCLUSION Compound 1 is a new compound,and 2-9、11-13、15-17 are isolated from this plant for the first time.Compounds 2-5、7、9、10、12、17 have good hypoglycemic activity.

Objective:To analyze the factors associated with long-term survival after radical resection of hepatitis B virus(HBV)-associated hepatocellular carcinoma(HCC),and to construct random forest and Cox regression models,to evaluate the two models.Methods:A total of 368 patients with HBV-infected HCC who underwent radical resection were selected retrospectively.These patients were categorized as having a good prognosis(n=266)or a poor prognosis(n=102)based on their survival and mortality status.Univariate and Cox regression analysis were used to identify fac-tors that predict poor prognosis in HCC patients after surgery,and Cox regression and random forest prediction models were constructed and evaluated.Results:There were significant differences in smoking history,Child-Pugh classifica-tion,cirrhosis,microvascular invasion,TNM staging,tumor capsule integrity,platelet-to-lymphocyte ratio(PLR),regular antiviral therapy,HBV-DNA load,alpha-fetoprotein(AFP),neutrophil-to-lymphocyte ratio(NLR),systemic immune in-flammatory index(SII),and albumin-to-globulin ratio(AGR)between the two groups(P<0.05);Cox regression showed that cirrhosis,microvascular invasion,regular antiviral treatment,HBV-DNA load,NLR,PLR,SII,and AGR were related factors that negatively affected the prognosis of patients with HBV-infected HCC after surgery(P<0.05),with an AUC of 0.870 for predicting prognosis;the importance ranking obtained by the random forest model was HBV-DNA load,cirrho-sis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII,with an AUC of 0.926 for predicting prog-nosis;the AUC predicted by the random forest model was greater than that predicted by the Cox regression model(Z=2.411,P=0.016).Conclusion:HBV-DNA load,cirrhosis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII are factors that affect the poor prognosis of patients with HBV-related HCC after surgery.The random for-est prediction model constructed based on these factors has high predictive value and is superior to the Cox regression prediction model.

Objective:Non-targeted metabolomics based on ultra-performance liquid chromatography mass spectrometry(UPLC-MS)platform was used to study the metabolic characteristics of multiple myeloma(MM)patients,and explore potential new metabolic mechanisms affecting the occurrence and development of MM.Methods:The study enrolled 42 MM patients,including 21 newly diagnosed(ND)patients and 21 relapsed patients(RP),and 21 age-sex matched healthy controls(HC)as subjects.UPLC-MS analysis platform was used to detect small molecule metabolites in serum of the subjects.Principal component analysis(PCA),orthogonal partial least-squared discriminant analysis(OPLS-DA)and 200 random permutations were used to analyze the differences of metabolic profiles among groups.Identification of differential metabolites was completed in the Human Metabolome Database(HMDB)and abnormal metabolic pathway analysis was performed using the KEGG database.Results:The metabolic profiles of MM patients and healthy controls were significantly separated in both PCA and OPLS-DA models,while the metabolic profiles of newly diagnosed and relapsed MM patients were significantly separated only in OPLS-DA model.In ND vs HC,RP vs HC and RP vs ND cohorts,19,24 and 18 differential metabolites were identified respectively,mainly sphingolipids,glycerophospholipids and fatty acyl amino acids.The metabolic pathway abnormalities in newly diagnosed and relapsed MM patients were mainly manifested in sphingolipid metabolism and glycerophospholipid metabolism compared to healthy controls.Compared with newly diagnosed MM patients,relapsed MM patients were mainly manifested in sphingolipid metabolism and ether-lipid metabolism.Conclusion:The metabolic profiles of MM patients are significantly different from those of healthy people.Relapsed MM patients and newly diagnosed MM patients have similar metabolic profiles,but there are still some differences.Glycerophospholipid metabolism,sphingolipid meta-bolism and ether-lipid metabolism may play important biological roles in the occurrence and development of MM.

Objective To explore the factors that influence major adverse cardiovascular events(MACE)in atrial fibrillation(AF)patients undergoing radiofrequency ablation(RFA),as well as to compare the prognosis of patients with advanced AF to that of the general population.Methods We prospectively recruited AF patients who underwent RFA treatment at Peking University Third Hospital between January 2021 and March 2023.General patient data were collected through the hospital's inpatient system,and MACE were tracked through outpatient visits and telephone follow-ups.Patients were categorized into three age groups:Group 1(under 65 years),Group 2(65 to 75 years),and Group 3(over 75 years).In this study,MACE was defined as include cardiovascular death,all-cause death,readmission for heart failure,acute coronary syndrome(ACS),grade 2 or higher bleeding and stroke.Results A total of 431 patients were included in this study,with an average age of(66.17±12.22)years.Among these patients,259 were male(60.09％),and the mean of CHA2DS2-VASc score was(1.79±1.30).The median follow-up period was 16.0(11.3,21.3)months,during which 28(6.50％)patients experienced MACE,with ACS and stroke being the most common events.Variables were selected using LASSO regression,and a LASSO-Cox regression model was constructed.Age(HR 1.06,95％CI 1.02-1.10,P=0.006)and hypertrophic cardiomyopathy(HR 3.70,95％CI 1.27-8.68,P=0.008)were identified as independent predictors of MACE after RFA for AF.Subgroup analysis revealed that patients under 65 had significantly better prognoses compared to older AF patients(P=0.030 compared with group 2;P=0.021 compared with group 3).Conclusions Age and hypertrophic cardiomyopathy are independent risk factors for MACE in AF patients undergoing RFA.The prognosis for younger patients is better than that for older patients,while the prognosis for advanced patients is comparable to that of patients aged 65-75 years.

Objective:To analyze the factors associated with long-term survival after radical resection of hepatitis B virus(HBV)-associated hepatocellular carcinoma(HCC),and to construct random forest and Cox regression models,to evaluate the two models.Methods:A total of 368 patients with HBV-infected HCC who underwent radical resection were selected retrospectively.These patients were categorized as having a good prognosis(n=266)or a poor prognosis(n=102)based on their survival and mortality status.Univariate and Cox regression analysis were used to identify fac-tors that predict poor prognosis in HCC patients after surgery,and Cox regression and random forest prediction models were constructed and evaluated.Results:There were significant differences in smoking history,Child-Pugh classifica-tion,cirrhosis,microvascular invasion,TNM staging,tumor capsule integrity,platelet-to-lymphocyte ratio(PLR),regular antiviral therapy,HBV-DNA load,alpha-fetoprotein(AFP),neutrophil-to-lymphocyte ratio(NLR),systemic immune in-flammatory index(SII),and albumin-to-globulin ratio(AGR)between the two groups(P<0.05);Cox regression showed that cirrhosis,microvascular invasion,regular antiviral treatment,HBV-DNA load,NLR,PLR,SII,and AGR were related factors that negatively affected the prognosis of patients with HBV-infected HCC after surgery(P<0.05),with an AUC of 0.870 for predicting prognosis;the importance ranking obtained by the random forest model was HBV-DNA load,cirrho-sis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII,with an AUC of 0.926 for predicting prog-nosis;the AUC predicted by the random forest model was greater than that predicted by the Cox regression model(Z=2.411,P=0.016).Conclusion:HBV-DNA load,cirrhosis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII are factors that affect the poor prognosis of patients with HBV-related HCC after surgery.The random for-est prediction model constructed based on these factors has high predictive value and is superior to the Cox regression prediction model.