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.

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.

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.

Severe open tibiofibular fractures account for approximately 28.1% of all open fractures. Among them, Gustilo-Anderson type IIIB/C fractures present significant clinical challenges due to associated bone and soft tissue defects, high infection rates, and risk of amputation. Inadequate preoperative assessment may lead to suboptimal emergency surgical planning or intraoperative complications. Historically, external fixation was often preferred, but this approach has been associated with limitations such as restricted joint mobility, delayed bone union, joint stiffness, and disuse osteoporosis, resulting in poor functional recovery. With advancements of debridement techniques, standardization of antibiotic use, and popularization of early soft tissue coverage, early internal fixation has gained broader acceptance. Nevertheless, controversies persist regarding the choice of fixation method, timing of definitive fixation, use of reamed versus unreamed intramedullary nailing, and necessity of fibular fixation. To standardize the diagnosis and early management of severe open tibiofibular fractures, reduce complication rates, and improve functional recovery, the Society of Microsurgery of the Chinese Medical Association organized a panel of domestic experts to develop the Evidence-based guideline for the diagnosis and early fixation of severe open tibiofibular fractures ( version 2025), using evidence-based methodology. The guidelines provided 12 recommendations covering diagnostic and early fixation strategies of severe open tibiofibular fractures, aiming to provide clinicians with scientifically grounded and standardized guidance.

Objective:To develop a treatment-related quality of life scale for Chinese patients with multiple myeloma (MM) and to test its reliability and validity.Methods:The initial scale was constructed through a literature search, Delphi expert correspondence, and cognitive testing. This study conducted a preliminary survey of 379 patients with MM and a formal survey of 865 patients from the hematology departments of 155 hospitals nationwide from February 2024 to March 2024. The final scale was obtained after conducting item analysis and reliability and validity tests on the initial scale.Results:The constructed scale contains 36 items covering six domains: physiological, psychological, social, treatment side effects, general health, and others. In the preliminary survey, the Cronbach’s alpha coefficient of each item ranged from 0.597 to 0.939, and the test-retest reliability was 0.747 ( P<0.001). Exploratory factor analysis extracted eight common factors with a cumulative variance contribution of 60.058%. In the formal survey, the Cronbach’s alpha coefficient of each item ranged from 0.484 to 0.930, and the test-retest reliability was 0.835 ( P<0.001). Confirmatory factor analysis revealed a comparative fit index of 0.750, a root-mean-square error of approximation of 0.090, and a root-mean-square residual of 0.067. Conclusion:The treatment-related quality of life scale for Chinese patients with MM designed in this study exhibited good reliability and validity, reflecting the impact of treatment on the quality of life of patients. This scale can provide a reference to clinicians for assessing the disease status of 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.

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.

Poly(ADP-ribose) polymerase 1 (PARP1) is a multifunctional protein involved in diverse cellular functions, notably DNA damage repair. Pharmacological inhibition of PARP1 has therapeutic benefits for various pathologies. Despite the increased use of PARP inhibitors, challenges persist in achieving PARP1 selectivity and effective blood-brain barrier (BBB) penetration. The development of a PARP1-specific positron emission tomography (PET) radioligand is crucial for understanding disease biology and performing target occupancy studies, which may aid in the development of PARP1-specific inhibitors. In this study, we leverage the recently identified PARP1 inhibitor, AZD9574, to introduce the design and development of its ¹⁸F-isotopologue ([¹⁸F]AZD9574). Our comprehensive approach, encompassing pharmacological, cellular, autoradiographic, and in vivo PET imaging evaluations in non-human primates, demonstrates the capacity of [¹⁸F]AZD9574 to specifically bind to PARP1 and to successfully penetrate the BBB. These findings position [¹⁸F]AZD9574 as a viable molecular imaging tool, poised to facilitate the exploration of pathophysiological changes in PARP1 tissue abundance across various diseases.

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 transformer-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 discovery 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 identification, 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.