Alzheimer's disease (AD) is a common neurodegenerative disorder among the elderly, and BuChE has emerged as a potential therapeutic target. In this study, we reported the development of compound 8e, a selective reversible BuChE inhibitor (eqBuChE IC₅₀ = 0.049 μmol/L, huBuChE IC₅₀ = 0.066 μmol/L), identified through extensive virtual screening and lead optimization. Compound 8e demonstrated favorable blood-brain barrier permeability, good drug-likeness property and pronounced neuroprotective efficacy. Additionally, 8e exhibited significant therapeutic effects in zebrafish AD models and scopolamine-induced cognitive impairments in mice. Further, 8e significantly improved cognitive function in APP/PS1 transgenic mice. Proteomics analysis demonstrated that 8e markedly elevated the expression levels of very low-density lipoprotein receptor (VLDLR), offering valuable insights into its potential modulation of the Reelin-mediated signaling pathway. Thus, compound 8e emerges as a novel and potent BuChE inhibitor for the treatment of AD, with significant implications for further exploration into its mechanisms of action and therapeutic applications.

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.

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.

Objective:To evaluate the prevalence of hepatitis C virus (HCV) infection among patients attending a comprehensive tertiary hospital in Beijing and to pinpoint the key demographics for anti-HCV screening.Methods:A comprehensive retrospective analysis was undertaken, examining data from 631 424 patients who underwent anti-HCV testing between 2017 and 2023. Testing for anti-HCV was conducted using the Abbott i2000 fully automated chemiluminescent immunoassay analyzer. HCV nucleic acid testing was performed with the Roche Cobas AmpliPrep/Cobas TaqMan 96 fluorescent quantitative PCR system, while HCV genotyping was achieved through sequencing.Results:The positive rate of HCV antibodies demonstrated a gradual decline over the years, decreasing from 1.62% in 2017 to 1.01% in 2023. The overall positive rate stood at 1.36% (8 574/631 424), with a nucleic acid testing rate of 59.24% (5 079/8 574) and a nucleic acid positive rate of 34.28% (1 741/5 079). The majority of anti-HCV positive patients came from the department of hepatology (12.17%), followed by hepatobiliary surgery (3.03%), emergency medicine (1.68%), cardiovascular medicine (1.24%) and ophthalmology clinic (1.23%). Notably, the anti-HCV positive rate was significantly elevated in the ≥40 years old group compared to the <40 years old group, with statistical significance ( χ2=1 892.577, P=0.000). The highest anti-HCV positive rates were observed within the 60-69- and 80-99-years old brackets (both at 1.85%), while the peak HCV RNA positive rate was recorded in the 50-59 years old group (27.08%). Females exhibited a significantly higher positive rate (18.53%) than males (15.75%) ( χ2=8.066, P<0.01). When anti-HCV levels surpassed 9 S/CO, the HCV RNA positive rate was notably high, exceeding 38.97%. Intriguingly, at antibody levels ranging from 15 to 16 S/CO, the HCV RNA positive rate climbed to a maximum of 56.17%. Conclusions:This study has successfully identified the key populations for anti-HCV screening: Patients aged over 40, particularly female patients within the 50-69 age bracket; Patients in hepatology, hepatobiliary surgery, emergency medicine, cardiovascular medicine and ophthalmology departments.

Objective:To explore the predictive value of baseline serum levels of hepatitis B virus (HBV) RNA for HBeAg seroconversion in chronic hepatitis B (CHB) subjects with advanced fibrosis/compensated cirrhosis undergoing tenofovir disoproxil fumarate (TDF) therapy.Methods:A case-control study was conducted on 141 patients with CHB combined with advanced fibrosis/compensated cirrhosis who were treated with TDF and tested at Peking University People′s Hospital from January 2015 to December 2020. Patients were divided into HBeAg seroconversion (16 cases) group and non-seroconversion (59 cases) group based on whether HBeAg seroconversion occurred at 240 weeks after treatment. The patients were divided into HBeAg positive and negative groups at baseline (75 and 66 cases, repectively) and at 12 weeks treatment (61 and 80 cases, repectively). The baseline serum levels of relevant indicators were analyzed. HBV RNA levels were measured at baseline and at 240 weeks after treatment. The correlation between HBV RNA and HBV DNA was analyzed using Pearson correlation analysis, and the predictive value was evaluated using the receiver operating characteristic (ROC) curve.Results:For the 75 HBeAg-positive patients at baseline, 21.3% (16/75) achieved HBeAg seroconversion. The HBV DNA and HBV RNA in the HBeAg-positive group were significantly higher than that in the HBeAg-negative group (all P<0.001). Compared with the non-seroconversion group, the HBeAg seroconversion group had significantly lower baseline serum levels of HBV RNA ( P<0.05). Pearson correlation analysis showed that serum HBV RNA levels were positively correlated with HBV DNA in both baseline and 12 weeks HBeAg-negative group and HBeAg-positive group, respectively (baseline: r=0.718, 0.794, P<0.001; 12 weeks: r=0.689, 0.750, P<0.001). ROC curve showed that baseline levels of HBV RNA could be used as a predictor of HBeAg seroconversion in CHB patients with advanced fibrosis/compensated cirrhosis treated with TDF. The area under curve was 0.781, the sensitivity was 75.0%, and the specificity was 78.0%. Conclusion:Baseline serum levels of HBV RNA has a predictive value for HBeAg seroconversion in CHB patients with advanced fibrosis/compensated cirrhosis treated with TDF.

Objective:To evaluate the prevalence of hepatitis C virus (HCV) infection among patients attending a comprehensive tertiary hospital in Beijing and to pinpoint the key demographics for anti-HCV screening.Methods:A comprehensive retrospective analysis was undertaken, examining data from 631 424 patients who underwent anti-HCV testing between 2017 and 2023. Testing for anti-HCV was conducted using the Abbott i2000 fully automated chemiluminescent immunoassay analyzer. HCV nucleic acid testing was performed with the Roche Cobas AmpliPrep/Cobas TaqMan 96 fluorescent quantitative PCR system, while HCV genotyping was achieved through sequencing.Results:The positive rate of HCV antibodies demonstrated a gradual decline over the years, decreasing from 1.62% in 2017 to 1.01% in 2023. The overall positive rate stood at 1.36% (8 574/631 424), with a nucleic acid testing rate of 59.24% (5 079/8 574) and a nucleic acid positive rate of 34.28% (1 741/5 079). The majority of anti-HCV positive patients came from the department of hepatology (12.17%), followed by hepatobiliary surgery (3.03%), emergency medicine (1.68%), cardiovascular medicine (1.24%) and ophthalmology clinic (1.23%). Notably, the anti-HCV positive rate was significantly elevated in the ≥40 years old group compared to the <40 years old group, with statistical significance ( χ2=1 892.577, P=0.000). The highest anti-HCV positive rates were observed within the 60-69- and 80-99-years old brackets (both at 1.85%), while the peak HCV RNA positive rate was recorded in the 50-59 years old group (27.08%). Females exhibited a significantly higher positive rate (18.53%) than males (15.75%) ( χ2=8.066, P<0.01). When anti-HCV levels surpassed 9 S/CO, the HCV RNA positive rate was notably high, exceeding 38.97%. Intriguingly, at antibody levels ranging from 15 to 16 S/CO, the HCV RNA positive rate climbed to a maximum of 56.17%. Conclusions:This study has successfully identified the key populations for anti-HCV screening: Patients aged over 40, particularly female patients within the 50-69 age bracket; Patients in hepatology, hepatobiliary surgery, emergency medicine, cardiovascular medicine and ophthalmology departments.

Objective:To explore the predictive value of baseline serum levels of hepatitis B virus (HBV) RNA for HBeAg seroconversion in chronic hepatitis B (CHB) subjects with advanced fibrosis/compensated cirrhosis undergoing tenofovir disoproxil fumarate (TDF) therapy.Methods:A case-control study was conducted on 141 patients with CHB combined with advanced fibrosis/compensated cirrhosis who were treated with TDF and tested at Peking University People′s Hospital from January 2015 to December 2020. Patients were divided into HBeAg seroconversion (16 cases) group and non-seroconversion (59 cases) group based on whether HBeAg seroconversion occurred at 240 weeks after treatment. The patients were divided into HBeAg positive and negative groups at baseline (75 and 66 cases, repectively) and at 12 weeks treatment (61 and 80 cases, repectively). The baseline serum levels of relevant indicators were analyzed. HBV RNA levels were measured at baseline and at 240 weeks after treatment. The correlation between HBV RNA and HBV DNA was analyzed using Pearson correlation analysis, and the predictive value was evaluated using the receiver operating characteristic (ROC) curve.Results:For the 75 HBeAg-positive patients at baseline, 21.3% (16/75) achieved HBeAg seroconversion. The HBV DNA and HBV RNA in the HBeAg-positive group were significantly higher than that in the HBeAg-negative group (all P<0.001). Compared with the non-seroconversion group, the HBeAg seroconversion group had significantly lower baseline serum levels of HBV RNA ( P<0.05). Pearson correlation analysis showed that serum HBV RNA levels were positively correlated with HBV DNA in both baseline and 12 weeks HBeAg-negative group and HBeAg-positive group, respectively (baseline: r=0.718, 0.794, P<0.001; 12 weeks: r=0.689, 0.750, P<0.001). ROC curve showed that baseline levels of HBV RNA could be used as a predictor of HBeAg seroconversion in CHB patients with advanced fibrosis/compensated cirrhosis treated with TDF. The area under curve was 0.781, the sensitivity was 75.0%, and the specificity was 78.0%. Conclusion:Baseline serum levels of HBV RNA has a predictive value for HBeAg seroconversion in CHB patients with advanced fibrosis/compensated cirrhosis treated with TDF.

Objective:To comprehensively evaluate the clinical value of Elecsys serum abnormal prothrombin (PIVKA-Ⅱ) test reagent for auxiliary diagnosis of hepatocellular carcinoma (HCC) in the Chinese population.Methods:A multicenter case-control design was used in the study. Samples from patients with first-time confirmed, diagnosed, and untreated HCC, benign liver disease and interfering controls were collected continuously. Elecsys PIVKA-II and alpha-fetoprotein (AFP) were tested for analysis. Various clinical details of the subjects were collected and analyzed. The efficacy of PIVKA-II (21.29 ng/ml) and AFP (400 ng/ml) for HCC diagnosis was calculated at specific positive cut-off values. Statistical analysis was performed using the Kruskal-Wallis test or receiver operating characteristic curve.Results:A total of 448 subjects were eventually enrolled from five centers, including 185 HCC cases. PIVKA-II had a higher diagnostic sensitivity and accuracy than AFP (84.86% vs. 30.81% and 89.01% vs. 63.66%) when the benign liver disease group was used as the control group, while the specificity was slightly lower. A sensitive analysis showed that PIVKA-II had a sensitivity of >80% at this specific positive cut-off value in the subgroup of AFP-negative subjects, patients with different etiologies, and HCC patients with multiple Barcelona Clinic liver cancer stages (including early-stage HCC). At the same time, the PIVKA-II subject had a slightly higher area under the receiver operating characteristic curve than the AFP (0.920 0 vs. 0.880 9).Conclusion:The clinical efficacy of Elecsys PIVKA-Ⅱ is good and stable in the Chinese population. Additionally, it has the clinical potential to improve the current missed diagnosis status of AFP-negative HCC and HCC monitoring at an early stage, as well as the effectiveness of accuracy promotion for HCC auxiliary diagnosis in China.

Hepatitis C virus （HCV） can develop into liver cirrhosis or hepatocellular carcinoma， imposing a heavy burden on the patient’s family and the society. Hepatitis C is one of the major public threats for humans， and eliminating hepatitis C is a common goal of all humans. Direct-acting antiviral agents （DAAs） are currently a relatively safe treatment regimen for hepatitis C that can reach a relatively high cure rate and can target different HCV genotypes， making it possible to eliminate HCV infection. China actively promotes the clinical application of DAAs， accelerates drug approval， improves the accessibility of DAAs， and strengthens population intervention. National Medical Insurance Administration has gradually included DAAs in the national medical insurance directory， providing strong support for eliminating HCV infection. In response to the WHO’s goal of eliminating viral hepatitis as a public health hazard by 2030， China has successively released national strategic plans and action plans in recent years， making significant achievements in HCV infection elimination， forming a joint prevention and control system across multiple sectors of the society， and ultimately achieving the goal of eliminating HCV infection. With a focus on the current status of HCV infection in China and prominent prevention and control strategies， this article analyzes and summarizes the practical process of the prevention， control， and micro-elimination of HCV infection， in order to provide a policy reference for carrying out HCV elimination in China and help to achieve the goal of comprehensive elimination of HCV infection.

In recent years,radiomics has been developed rapidly in the field of clinical medicine,and the artificial intelligence(AI)technology has been utilized to assist diagnosis.This paper introduced the background of radiomics,analyzed the basic research process of radiomics,and looked forward to its application in the identification of bone and joint injuries in the field of forensic medicine.Reviewing the three aspects is expected to provide a theoretical foundation of radiomics,which will be helpful to develop its application in forensic medicine.