Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as a global health issue due to its increasing prevalence associated with lifestyle changes and its strong correlation with metabolic syndrome. Farnesoid X receptor (FXR) is a nuclear receptor that plays a pivotal role in regulating bile acid, lipid, and glucose metabolism, making it an attractive therapeutic target for liver and metabolic diseases. In this study, we investigated the effects of MHY5456, a synthetic agonist of FXR, on hepatic metabolism and fibrosis. MHY5456 enhanced the transcriptional activity of FXR in a concentration-dependent manner.Treatment of AC2F rat liver-derived cells with MHY5456 resulted in the downregulation of genes involved in lipid accumulation and an upregulation of mitochondrial-related gene expression. Additionally, MHY5456 significantly reduced oleic acid (OA)-induced lipid accumulation. To assess its anti-fibrotic potential, we tested its effects on transforming growth factor-beta (TGF-β)-induced fibrosis in LX2 human hepatic stellate cells (HSCs). MHY5456 significantly suppressed the expression of fibrosis-related genes and proteins. In vivo, administration of MHY5456 to mice fed a methionine-choline-deficient (MCD) diet alleviated hepatic fibrosis, inflammation, and lipid accumulation. These results show that FXR activation by MHY5456 modulates lipid metabolism and fibrotic pathways, suggesting its potential as a pharmacological candidate for liver and metabolic disorders, including MASLD. Further pharmacological and toxicological studies are needed to confirm its therapeutic relevance.

Objective:To investigate the clinical characteristics and prognosis of patients with locally advanced or metastatic pulmonary neuroendocrine tumors(NETs).Methods:The clinical records of patients with locally advanced or metastatic pulmonary NETs in Peking Uni-versity Cancer Hospital&Institute were selected from January 2014 to June 2024.The clinical characteristics,treatment,and survival pro-gnosis were then analyzed.Results:There were 32 patients,of which 18 were male and 14 female.The median age was 56 years.Nine pa-tients had typical carcinoid and 23 had atypical carcinoid,with six in stage Ⅲ and 26 in stage Ⅳ.The common metastatic sites included the bones(18 cases),lungs(8 cases),pleura(7 cases),and liver(7 cases).The median length of the measurable primary tumor was 5.2 cm,which was mostly located centrally(22 cases).Five among the 16 patients who underwent somatostatin receptor(SSTR)imaging had high SSTR ex-pression.The initial symptoms mainly included respiratory symptoms,and none of them were combined with carcinoid syndrome.For the first-line treatment,19 patients were treated with chemotherapy,seven were treated with targeted therapy,four were treated with soma-tostatin analogs(SSAs),and two were treated with surgery.The best efficacy was evaluated as a partial response in one case(3.1%),stable disease in 23 cases(71.9%),and non-evaluable or unknown in eight cases(25%)in the first-line treatment.The median progression-free sur-vival(mPFS)of patients who received first-line treatment was 5.2 months(95%CI:0.0-13.9).The PFS of targeted therapy was the longest(11.0 months,95%CI:0.0-29.6),but there was no significant difference compared with the PFS of chemotherapy and SSA groups(P>0.05).The longest PFS(24.5 months,95%CI:0.0-58.7)was found in patients treated with chemotherapy combined with radiotherapy,but there was no significant difference compared to the PFS of the combined immunotherapy and combined anti-angiogenesis groups(P>0.05).The survival rates at 1,3,and 5 years were 79.1%,65.5%,and 58.9%,respectively.Cox regression analysis did not identify independent risk factors for prognosis.Conclusions:The initial symptoms of patients with locally advanced or metastatic NETs were mainly respiratory symp-toms but without specific manifestations.Some of them were accompanied by high SSTR expression,and there was generally no carcinoid syndrome.The first-line systemic therapy mainly included chemotherapy and target therapy,with relatively low objective response and high disease control rates.Targeted therapy and combined radiotherapy have longer PFS than that of chemotherapy.The overall survival of pa-tients with pulmonary NETs was good.

Purpose To evaluate the predictive value of multifunctional parameters of single photon emission computed tomography gated myocardial perfusion imaging(SPECT G-MPI)for major adverse cardiovascular events(MACE)in chronic kidney disease(CKD)with abnormal stress myocardial perfusion.Materials and Methods A total of 99 patients diagnosed with CKD from June 2017 to March 2024 who underwent stress and rest G-MPI indicating abnormal myocardial perfusion in Beijing Anzhen Hospital,Capital Medical University.The American Heart Association 17-segment 5-point method and PHASE software were used to obtain the left ventricular myocardial perfusion,functional and synchronization parameters.According to the occurrence of MACE,the patients were divided into MACE group and non-MACE group.Cox regression was used to analyze the predictors related to MACE.The receiver operator characteristic curve was used to analyze the performance of predictors,the survival curves were obtained by the Kaplan-Meier method,Log-rank test was used to compare the differences in different groups.Results Finally,we enrolled 99 CKD patients with abnormal stress myocardial perfusion.35 patients(35.35%)developed MACE during the follow-up period.Cox regression analysis showed that stress phase bandwidth(SPBW)(HR=1.015,95%CI 1.002-1.028)and sum difference score(SDS)(HR=1.105,95%CI 1.008-1.211)were independent risk factors for predicting MACE(both P<0.05).The optimal cut-off value of SPBW and SDS for predicting MACE were 69° and 6 points,the area under the curve was 0.801 and 0.778,respectively.The incidence of MACE in the SPBW≥69° group and SDS≥6 points group was higher than that in SPBW<69° group and SDS<6 points group(66.6%vs.13.2%,53.3%vs.20.4%,both P<0.05).Conclusion SPECT G-MPI multifunctional parameters can be used to predict the prognosis of CKD patients with abnormal stress myocardial perfusion.SPBW and SDS are independent risk factors for MACE in these patients.

Objective:To evaluate the clinical predictive value of SPECT myocardial perfusion imaging (MPI) in the occurrence of cardiac death in patients with chronic kidney disease (CKD).Methods:A retrospective follow-up was performed for 160 patients (109 males, 51 females; age: 68.5(61.0, 74.0) years) who underwent MPI in Beijing Anzhen Hospital, Capital Medical University between June 2017 and March 2024. The 17-segment 5-point method was used for image analysis to obtain the left ventricular myocardial perfusion and functional parameters. The patients were followed up for cardiac death, and divided into death group and survival group. Clinical data of those 2 groups were compare by χ2 test, the independent-sample t test or Mann-Whitney U test. Cox proportional hazards regression analysis was used to analyze the predictors related to cardiac death. The ROC curve was used to analyze the performance of predictors. Survival curves were obtained by the Kaplan-Meier method, and log-rank test was performed to compare the difference between 2 groups. Results:The follow-up time of 160 patients with CKD was 26.0(10.0, 46.5) months. Of 160 patients, 17 died and 143 survived. There were statistically significant differences in body mass index (BMI), previous myocardial infarction, previous revascularization, hypersensitive C-reactive protein (hs-CRP), positive MPI, left ventricular end-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF), summed stress score (SSS), summed rest score (SRS) and summed difference score (SDS) between the death group and the survival group ( χ2 values: 4.58-16.13, t values: -2.34, -3.97, Z values: from -2.81 to 5.02, all P<0.05). Multivariate Cox regression analysis showed that SSS (hazard ratio ( HR)=1.153, 95% CI: 1.062-1.252, P=0.001) and hs-CRP ( HR=1.031, 95% CI: 1.004-1.058, P=0.023) were independent risk factors for cardiac death in patients with CKD. The optimal cut-off value of SSS for predicting cardiac death in those patients was determined to be 8 with the AUC of 0.815, and the incidence of cardiac death in the SSS ≥8 group was significantly higher than that in the SSS<8 group (33.3%(12/36) vs 4.0%(5/124); χ2 = 25.44, P<0.001). Conclusion:MPI is an important imaging method for the evaluation of cardiac death in patients with CKD, SSS and hs-CRP are important risk factors in predicting cardiac death in those patients.

Objective:To evaluate the clinical predictive value of SPECT myocardial perfusion imaging (MPI) in the occurrence of cardiac death in patients with chronic kidney disease (CKD).Methods:A retrospective follow-up was performed for 160 patients (109 males, 51 females; age: 68.5(61.0, 74.0) years) who underwent MPI in Beijing Anzhen Hospital, Capital Medical University between June 2017 and March 2024. The 17-segment 5-point method was used for image analysis to obtain the left ventricular myocardial perfusion and functional parameters. The patients were followed up for cardiac death, and divided into death group and survival group. Clinical data of those 2 groups were compare by χ2 test, the independent-sample t test or Mann-Whitney U test. Cox proportional hazards regression analysis was used to analyze the predictors related to cardiac death. The ROC curve was used to analyze the performance of predictors. Survival curves were obtained by the Kaplan-Meier method, and log-rank test was performed to compare the difference between 2 groups. Results:The follow-up time of 160 patients with CKD was 26.0(10.0, 46.5) months. Of 160 patients, 17 died and 143 survived. There were statistically significant differences in body mass index (BMI), previous myocardial infarction, previous revascularization, hypersensitive C-reactive protein (hs-CRP), positive MPI, left ventricular end-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF), summed stress score (SSS), summed rest score (SRS) and summed difference score (SDS) between the death group and the survival group ( χ2 values: 4.58-16.13, t values: -2.34, -3.97, Z values: from -2.81 to 5.02, all P<0.05). Multivariate Cox regression analysis showed that SSS (hazard ratio ( HR)=1.153, 95% CI: 1.062-1.252, P=0.001) and hs-CRP ( HR=1.031, 95% CI: 1.004-1.058, P=0.023) were independent risk factors for cardiac death in patients with CKD. The optimal cut-off value of SSS for predicting cardiac death in those patients was determined to be 8 with the AUC of 0.815, and the incidence of cardiac death in the SSS ≥8 group was significantly higher than that in the SSS<8 group (33.3%(12/36) vs 4.0%(5/124); χ2 = 25.44, P<0.001). Conclusion:MPI is an important imaging method for the evaluation of cardiac death in patients with CKD, SSS and hs-CRP are important risk factors in predicting cardiac death in those patients.

Purpose To evaluate the predictive value of multifunctional parameters of single photon emission computed tomography gated myocardial perfusion imaging(SPECT G-MPI)for major adverse cardiovascular events(MACE)in chronic kidney disease(CKD)with abnormal stress myocardial perfusion.Materials and Methods A total of 99 patients diagnosed with CKD from June 2017 to March 2024 who underwent stress and rest G-MPI indicating abnormal myocardial perfusion in Beijing Anzhen Hospital,Capital Medical University.The American Heart Association 17-segment 5-point method and PHASE software were used to obtain the left ventricular myocardial perfusion,functional and synchronization parameters.According to the occurrence of MACE,the patients were divided into MACE group and non-MACE group.Cox regression was used to analyze the predictors related to MACE.The receiver operator characteristic curve was used to analyze the performance of predictors,the survival curves were obtained by the Kaplan-Meier method,Log-rank test was used to compare the differences in different groups.Results Finally,we enrolled 99 CKD patients with abnormal stress myocardial perfusion.35 patients(35.35%)developed MACE during the follow-up period.Cox regression analysis showed that stress phase bandwidth(SPBW)(HR=1.015,95%CI 1.002-1.028)and sum difference score(SDS)(HR=1.105,95%CI 1.008-1.211)were independent risk factors for predicting MACE(both P<0.05).The optimal cut-off value of SPBW and SDS for predicting MACE were 69° and 6 points,the area under the curve was 0.801 and 0.778,respectively.The incidence of MACE in the SPBW≥69° group and SDS≥6 points group was higher than that in SPBW<69° group and SDS<6 points group(66.6%vs.13.2%,53.3%vs.20.4%,both P<0.05).Conclusion SPECT G-MPI multifunctional parameters can be used to predict the prognosis of CKD patients with abnormal stress myocardial perfusion.SPBW and SDS are independent risk factors for MACE in these patients.

Objective:To explore the impact of the two-way referral model on compliance and prognosis in patients with heart failure.Methods:This bidirectional cohort study enrolled chronic heart failure (CHF) patients treated at Qilu Hospital of Shandong University or designated primary hospitals between March 2018 and March 2022. Patients were categorized into two groups based on referral status: two-way referral group (participating in the referral model with≥1 follow-up visit at primary hospitals) and the core hospital group (receiving treatment and follow-up exclusively at Qilu Hospital). Baseline clinical characteristics were collected and compared between groups. Patients underwent followed-up, with primary endpoints including follow-up rate, drug (β-blockers, angiotension converting enzyme inhibitor (ACEI)/angiotensin Ⅱ receptor blockers (ARB)/angiotensin receptor-neprilysin inhibitor (ARNI), sodium-glucose cotransporter 2 inhibitors and mineralocorticoid receptor antagonists) utilization rate and target dose achievement rate. Secondary endpoints encompassed changes from baseline in left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDd), and N-terminal pro-brain natriuretic peptide (NT-proBNP), plus cardiovascular mortality and heart failure rehospitalization. Generalized linear mixed models analyzed longitudinal trends in LVEF, LVEDd, and NT-proBNP levels. Kaplan-Meier curves and Cox regression evaluated LVEF recovery rates, supplemented by subgroup analyses. Multivariate logistic regression was used to identify factors influencing target dose achievement rate for β-blockers and ACEI/ARB/ARNI therapies in CHF patients.Results:A total of 357 patients were enrolled, aged 53 (41, 63) years, including 256 males (71.7%). 157 patients were in the two-way referral group and 200 patients in the core hospital-treated group. Compared with the core hospital-treated group, the two-way referral group had lower baseline LVEF (28 (22, 34)% vs. 31 (23, 36)%, P=0.021) and systolic blood pressure (116 (104, 125) mmHg vs. 121 (109, 134) mmHg (1 mmHg=0.133 kPa), P=0.010). The 12-month follow-up rate of the two-way referral group was higher than the core hospital-treated group (73.8% vs. 56.0%, P=0.004). No significant between-group differences were observed in drug utilization rate of β-blockers, ACEI/ARB/ARNI, or sodium-glucose cotransporter 2 inhibitors during follow-up (all P>0.05), while mineralocorticoid receptor antagonists use showed a declining trend in both groups. Although the core hospital-treated group had higher target dose achievement rates for β-blockers (65.4% vs. 49.3%, P=0.042) and ACEI/ARB/ARNI (79.8% vs. 65.8%, P=0.046) than the two-way referral group, multivariate logistic regression indicated that the two-way referral model was not a negative predictor for these outcomes (all P>0.05). Both groups showed improved NT-proBNP, LVEDd, and LVEF from baseline (all P<0.001) with no significant difference in trends between groups (all P>0.05). There was no significant difference in the composite incidence (7.6% vs. 6.5%, P=0.674) and cumulative incidence (log-rank P=0.684) of cardiovascular death and heart failure rehospitalization at 12 months between two groups. Conclusion:The two-way referral model demonstrates advantages in improving medication adherence, drug utilization rates, and targetdoseachievement rates among CHF patients. This model not only promotes cardiac functional recovery but also reduces risks of cardiovascular mortality and heart failure rehospitalization, achieving comparable therapeutic and management outcomes to those observed in core hospital-treated patients.

Objective To explore the efficacy of a compound nutrition preparation on wound healing after acute trauma and investigate the underlying mechanism primarily.Methods After skin wound model was successfully constructed on totally 60 male SD rats surgically,they were randomly divided into control group(CON group),whey protein group(WP group)and low-and high-dose nutritional formula groups(LDF and HDF groups),with 15 animals in per group.From the next day after surgery,the rats in each group were given corresponding nutritional interventions for 2 weeks.During the intervention,the wound conditions were observed and recorded,and the wound area was measured.The samples were collected on the 3rd,7th and 14th days after surgery,respectively.Serum albumin(ALB),prealbumin(PA),total protein(TP),inflammatory factors(TNF-α,IL-1β,IL-6 and IL-10),immunoglobulins(IgA,IgG and IgM)and hydroxyproline(Hyp)were detected by the corresponding reagent kits.The histopathologic changes of wound were observed with HE staining.Masson staining was used to observe the collagen fiber deposition in wound tissue.The angiogenesis of wound tissue was evaluated by immunohistochemical staining.Results Compared with the CON group,the wound healing speed,collagen synthesis and angiogenesis speed were significantly accelerated in the WP group,LDF group and HDF group(P＜0.05),and the effects were the most obvious in the HDF group.On the 3rd day after surgery,in the WP,LDF and HDF groups,the serum ALB,PA and TP levels were significantly increased(P＜0.05),serum TNF-α and IL-1β levels were obviously decreased(P＜0.05),and serum IL-10 level was notably increased(except WP group)when compared with the CON group.The serum IgG and IgM levels were significantly increased in the LDF group and HDF group(P＜0.05)and significant increment of IgA was only observed in the HDF group(P＜0.05).On the 7th day after modeling,the levels of ALB,PA and TP were significantly increased(P＜0.05),the levels of TNF-α,IL-1β and IL-6 were obviously decreased(P＜0.05),and the levels of IL-10 were remarkably increased(P＜0.05)in the HDF group than the CON group;The LDF group and HDF group had significantly elevated serum IgG and IgM levels(P＜0.05),but only the former group had statistically increased serum IgA level(P＜0.05).On the 14th day after modeling,the HDF group had significantly increased levels of ALB and TP(P＜0.05),decreased levels of IL-1β(P＜0.05),and raised levels of IgG and IgM when compared with the CON group(P＜0.05).Conclusion Our compound nutrition preparation promotes wound healing in rat model of acute trauma,which might be related to its improving the nutritional status,promoting collagen synthesis,and thus alleviating inflammatory response and enhancing immune function.

Objective To develop a personalized recommendation strategy for tranexamic acid administration during the perioperative period of orthopedic surgery based on machine learning,aiming to reduce perioperative bleeding and related complications and improving clinical outcomes.Methods A total of 11 727 patients undergoing orthopedic surgery from the INSPIRE database were subjected in this study.Missing data were handled using multiple imputation methods,and relevant feature variables were screened using Boruta analysis.We constructed various machine learning models,including Gradient Boosting Machine(GBM),Generalized Linear Model(GLM),eXtreme Gradient Boosting(XGBoost),K-Nearest Neighbors(KNN),Neural Network(NNET),Naive Bayes(NB),and Random Forest(RF),to evaluate their performance in predicting intraoperative bleeding and prolonged postoperative length of hospital stay.The optimal model was then selected and further integrated using a weighted ensemble,aiming to achieve the best prognosis by recommending usage strategies for tranexamic acid.The predictive performance of the constructed model was then verified against the testing set,and compared with the physician decision-making to complete the evaluation.Results In predicting intraoperative bleeding,the RF model achieved an area under the receiver operating characteristic curve(AUC)of 0.73,which was significantly better than other models.In predicting the prolonged postoperative length of hospital stay,the XGBoost model performed the best,with an AUC value of 0.84.Based on the above best-performing models,an ensemble strategy was implemented.The patients who followed the recommended strategy had reduced intraoperative bleeding and shorter postoperative length of hospital stay.Conclusion The use of tranexamic acid is associated with intraoperative bleeding and postoperative length of hospital stay.Personalized decision-making recommendation based on our constructed model can effectively improve the outcomes of the patients undergoing orthopedic surgery.

Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.