Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent cause of chronic liver disease worldwide, and its intricate pathogenesis presents challenges in the development of new drugs. As a common way of post-translational modification, acetylation regulates protein stability, enzyme activity, and subcellular localization, occurring extensively in MASLD-associated processes such as lipid metabolism, inflammatory response, and oxidative stress. In this paper, we comprehensively review the mechanism of acetylation in MASLD, analyze the expression levels of acetylases in liver tissues of MASLD patients from the gene expression omnibus (GEO), discuss the changes in relevant enzyme expression and mechanisms in animal models, and further explore the feasibility of targeting acetylation for MASLD treatment, in the hope of offering a new perspective for advancing drug discovery in the field of MASLD.

Objective:To determine the prevalence, risk factors, and longitudinal associations of loneliness during mid- to late pregnancy with anxiety and depressive symptoms in late pregnancy.Methods:In this prospective cohort study, 1 107 pregnant women at 24-28 weeks' gestation were enrolled between June 2021 and December 2022. Psychological status was assessed during mid-pregnancy (24-28 weeks) and late pregnancy (≥32 weeks) using standardized electronic questionnaires, including the Revised University of California Los Angeles Loneliness Scale (UCLA) Loneliness Scale-Short Form (Cronbach's α=0.82), Patient Health Questionnaire-9 ( α=0.86), and Generalized Anxiety Disorder-7 ( α=0.88). Multivariate logistic regression identified independent risk factors for loneliness. Cross-lagged path models analyzed the longitudinal predictions between loneliness and anxiety/depressive symptoms. Results:The prevalence of loneliness decreased significantly from 10.8% (120/1 107) in mid-pregnancy to 4.8% (37/777) in late pregnancy ( χ2=21.81, P<0.001). Multivariate analysis identified independent risk factors for loneliness: age <30 years ( OR=1.70, 95% CI: 1.15-2.50), annual household income <50 000 CNY ( OR=2.53, 95% CI: 1.28-5.02), unemployment during pregnancy ( OR=1.57, 95% CI: 1.03-2.39), history of alcohol consumption ( OR=1.63, 95% CI: 1.03-2.56), and the presence of mid-pregnancy depressive ( OR=2.76, 95% CI: 1.51-5.04) and anxiety symptoms ( OR=1.65, 95% CI: 1.01-2.71) (all P<0.05). Cross-lagged path models indicated bidirectional associations between loneliness and both anxiety ( β=0.32, P<0.01) and depressive symptoms ( β=0.28, P<0.01). However, the predictive effect of loneliness on subsequent depressive and anxiety symptoms ( β=0.28-0.32) was substantially stronger than the reverse prediction (mid-pregnancy anxiety on late-pregnancy loneliness: β=0.12; mid-pregnancy depression on late-pregnancy loneliness: β=0.11). Loneliness demonstrated high temporal stability (autoregressive effects β=0.29-0.32). Conclusion:Loneliness in mid-pregnancy exhibits a symmetric bidirectional association with anxiety and depressive symptoms in late pregnancy, suggesting it may be a core driver in the development of these emotional symptoms. Younger maternal age (<30 years), low household income (<50 000 CNY/year), unemployment during pregnancy, and a history of alcohol consumption were associated with a higher risk of loneliness and should be prioritized for psychological screening and intervention.

Clinical research on rare diseases has always faced multiple challenges in clinical research design and implementation due to small sample sizes of patients,high heterogeneity,and limited research resources.The rapid development of digital intelligence technology has provided innovative solutions for rare disease research.This article systematically explores the current status and response strategies of clinical research on rare diseases in the digital intelligence age.On the one hand,the efficiency of rare disease research has been optimized through adaptive design,mixed trial mode,and precision medicine stratification methods.On the other hand,solutions based on digital technology have been proposed to address the practical challenges of recruitment difficulties and underrepresentation of rare disease clinical research patients,data management and technical barriers,and insufficient coverage of natural medical history and baseline databases through digital intelligence technology.By combining international collaboration,intelligent screening,and remote experiments,a multidisciplinary collaboration and international cooperation,adaptive design,digital data platform,and patient-centered remote research model have been constructed as the core implementation strategies.Typical cases demonstrate that digital intelligence technology not only effectively shortens the drug development cycle,but also significantly enhances patient benefits,providing a replicable practical paradigm for global rare disease research.The practice of digital platforms represented by the International Rare Disease Research Alliance and the China Rare Disease Diagnosis and Treatment Collaboration Network has further verified the feasibility and promotional value of the digitalization path.In summary,digital intelligence technology has shown considerable promise in overcoming the clinical research challenges of rare diseases and accelerating the development of treatment plans,providing systematic references for researchers,regulatory agencies,and patient organizations.It is expected to drive the clinical research of rare diseases towards a more efficient and accurate future.

In recent decades, the global community has encountered several significant viral outbreaks, including the Ebola epidemic in West Africa, the Zika virus epidemic in South America, and the recent worldwide COVID-19 pandemic. In these instances, the deployment of effective vaccines has been instrumental in protecting public health. Nevertheless, as new challenges emerge in the prevention and management of infectious diseases, the traditional model of global vaccine development confronts both unprecedented opportunities and challenges. These circumstances underscore the limitations inherent in conventional vaccine development, particularly the protracted timelines and substantial costs involved. This article examines innovative approaches in contemporary vaccine clinical trials, investigates randomization techniques specific to vaccine studies, and delineates essential statistical considerations pertinent to vaccine trial design. The objective is to provide scientific support for vaccine development and to foster ongoing innovation and optimization within the realm of vaccine research and development.

In recent decades, the global community has encountered several significant viral outbreaks, including the Ebola epidemic in West Africa, the Zika virus epidemic in South America, and the recent worldwide COVID-19 pandemic. In these instances, the deployment of effective vaccines has been instrumental in protecting public health. Nevertheless, as new challenges emerge in the prevention and management of infectious diseases, the traditional model of global vaccine development confronts both unprecedented opportunities and challenges. These circumstances underscore the limitations inherent in conventional vaccine development, particularly the protracted timelines and substantial costs involved. This article examines innovative approaches in contemporary vaccine clinical trials, investigates randomization techniques specific to vaccine studies, and delineates essential statistical considerations pertinent to vaccine trial design. The objective is to provide scientific support for vaccine development and to foster ongoing innovation and optimization within the realm of vaccine research and development.

Clinical research on rare diseases has always faced multiple challenges in clinical research design and implementation due to small sample sizes of patients,high heterogeneity,and limited research resources.The rapid development of digital intelligence technology has provided innovative solutions for rare disease research.This article systematically explores the current status and response strategies of clinical research on rare diseases in the digital intelligence age.On the one hand,the efficiency of rare disease research has been optimized through adaptive design,mixed trial mode,and precision medicine stratification methods.On the other hand,solutions based on digital technology have been proposed to address the practical challenges of recruitment difficulties and underrepresentation of rare disease clinical research patients,data management and technical barriers,and insufficient coverage of natural medical history and baseline databases through digital intelligence technology.By combining international collaboration,intelligent screening,and remote experiments,a multidisciplinary collaboration and international cooperation,adaptive design,digital data platform,and patient-centered remote research model have been constructed as the core implementation strategies.Typical cases demonstrate that digital intelligence technology not only effectively shortens the drug development cycle,but also significantly enhances patient benefits,providing a replicable practical paradigm for global rare disease research.The practice of digital platforms represented by the International Rare Disease Research Alliance and the China Rare Disease Diagnosis and Treatment Collaboration Network has further verified the feasibility and promotional value of the digitalization path.In summary,digital intelligence technology has shown considerable promise in overcoming the clinical research challenges of rare diseases and accelerating the development of treatment plans,providing systematic references for researchers,regulatory agencies,and patient organizations.It is expected to drive the clinical research of rare diseases towards a more efficient and accurate future.

Objective:To determine the prevalence, risk factors, and longitudinal associations of loneliness during mid- to late pregnancy with anxiety and depressive symptoms in late pregnancy.Methods:In this prospective cohort study, 1 107 pregnant women at 24-28 weeks' gestation were enrolled between June 2021 and December 2022. Psychological status was assessed during mid-pregnancy (24-28 weeks) and late pregnancy (≥32 weeks) using standardized electronic questionnaires, including the Revised University of California Los Angeles Loneliness Scale (UCLA) Loneliness Scale-Short Form (Cronbach's α=0.82), Patient Health Questionnaire-9 ( α=0.86), and Generalized Anxiety Disorder-7 ( α=0.88). Multivariate logistic regression identified independent risk factors for loneliness. Cross-lagged path models analyzed the longitudinal predictions between loneliness and anxiety/depressive symptoms. Results:The prevalence of loneliness decreased significantly from 10.8% (120/1 107) in mid-pregnancy to 4.8% (37/777) in late pregnancy ( χ2=21.81, P<0.001). Multivariate analysis identified independent risk factors for loneliness: age <30 years ( OR=1.70, 95% CI: 1.15-2.50), annual household income <50 000 CNY ( OR=2.53, 95% CI: 1.28-5.02), unemployment during pregnancy ( OR=1.57, 95% CI: 1.03-2.39), history of alcohol consumption ( OR=1.63, 95% CI: 1.03-2.56), and the presence of mid-pregnancy depressive ( OR=2.76, 95% CI: 1.51-5.04) and anxiety symptoms ( OR=1.65, 95% CI: 1.01-2.71) (all P<0.05). Cross-lagged path models indicated bidirectional associations between loneliness and both anxiety ( β=0.32, P<0.01) and depressive symptoms ( β=0.28, P<0.01). However, the predictive effect of loneliness on subsequent depressive and anxiety symptoms ( β=0.28-0.32) was substantially stronger than the reverse prediction (mid-pregnancy anxiety on late-pregnancy loneliness: β=0.12; mid-pregnancy depression on late-pregnancy loneliness: β=0.11). Loneliness demonstrated high temporal stability (autoregressive effects β=0.29-0.32). Conclusion:Loneliness in mid-pregnancy exhibits a symmetric bidirectional association with anxiety and depressive symptoms in late pregnancy, suggesting it may be a core driver in the development of these emotional symptoms. Younger maternal age (<30 years), low household income (<50 000 CNY/year), unemployment during pregnancy, and a history of alcohol consumption were associated with a higher risk of loneliness and should be prioritized for psychological screening and intervention.

The "Top 10 drug tips for the public in 2023" issued by the Chinese Pharmaceutical Association emphasizes the importance of drinking water correctly to the safety and efficacy of drugs. Each drug has an optimal amount of drinking water, and only the appropriate amount can ensure the efficacy and avoid adverse reactions. According to UpToDate clinical consultant, Micromedex, MCDEX evidence-based databases and the drug labels of the US FDA and the European Medicines Agency, a total of 164 drugs in 20 categories, including drugs for metabolism and endocrine system, anti-infective drugs, anti-tumor drugs, etc., were labeled with the recommendation of adequate water intake. Here we summarize the above-mentioned drugs and their recommended water intake. The common reasons to drink enough water include preventing esophageal and gastric injury, preventing kidney injury, preventing dehydration, water and electrolyte disorders, preventing constipation, reducing bladder toxicity, reducing radiation damage, and promoting stone discharge. In addition, different people have different requirements for the amount of water when taking medicine. Mastering the correct amount of water is conducive to controlling the disease and reducing the adverse drug events.

The "Top 10 drug tips for the public in 2023" issued by the Chinese Pharmaceutical Association emphasizes the importance of drinking water correctly to the safety and efficacy of drugs. Each drug has an optimal amount of drinking water, and only the appropriate amount can ensure the efficacy and avoid adverse reactions. According to UpToDate clinical consultant, Micromedex, MCDEX evidence-based databases and the drug labels of the US FDA and the European Medicines Agency, a total of 164 drugs in 20 categories, including drugs for metabolism and endocrine system, anti-infective drugs, anti-tumor drugs, etc., were labeled with the recommendation of adequate water intake. Here we summarize the above-mentioned drugs and their recommended water intake. The common reasons to drink enough water include preventing esophageal and gastric injury, preventing kidney injury, preventing dehydration, water and electrolyte disorders, preventing constipation, reducing bladder toxicity, reducing radiation damage, and promoting stone discharge. In addition, different people have different requirements for the amount of water when taking medicine. Mastering the correct amount of water is conducive to controlling the disease and reducing the adverse drug events.

Non-alcoholic fatty liver disease (NAFLD) has become a major public health hazard threatening human health worldwide.Yet, due to its complex pathogenesis, new drug development is difficult, with still insufficient clinical medication.Palmitoylation is a universal posttranslational modification of proteins catalyzed by palmitoyltransferase, affecting their stability, membrane localization and function.Recent studies have shown that palmitoylation is closely associated with NAFLD.This review summarizes the mechanisms of palmitoylation in NAFLD and analyzes the expression levels of the palmitoyltransferase family in liver tissues of NAFLD patients from GEO database, aiming to provide important clues to explore new mechanisms for NAFLD.