OBJECTIVE To study the mechanism of action of Rehmannia glutinosa-medicated serum （RG） in regulating lipopolysaccharide （LPS）-induced polarization of BV2 microglia to interfere with neuroinflammation. METHODS An in vitro neuroinflammation model of BV2 cells induced by LPS was established. Cells were divided into control group， LPS group， 10%RG group， 20%RG group， BAY 11-7082 [nuclear factor kappa B （NF-κB） inhibitor] group， and 20%RG+BAY 11-7082 group. Except for the control group， cells in all other groups were pretreated with corresponding drugs for 12 h and then stimulated with LPS for 24 h. The morphology of cells in each group was observed， and the fluorescence intensity of ionized calcium binding adaptor molecule 1 （Iba-1）， inducible nitric oxide synthase （iNOS）， CD206， the mRNA expression of tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， IL-1β， iNOS， IL-4， IL-10， transforming growth factor-β （TGF-β）， arginase-1 （Arg-1）， and the Toll-like receptor 4 （TLR4）/NF-κB/NOD-like receptor thermal protein domain associated protein 3 （NLRP3） signaling pathway-related protein expression were detected. RESULTS Compared with the control group， the LPS group showed significant changes in cell morphology， exhibiting a typical M1 activated morphology. The fluorescence intensity of Iba-1 and iNOS， the relative expression levels of TNF-α， IL-6， IL-1β， iNOS mRNA， the relative expression levels of TLR4， NLRP3， caspase-1 p20， IL-1β p17 protein， and the phosphorylation levels of NF-κB p65 and inhibitor of nuclear factor kappa B α were significantly increased （P＜0.05）. The fluorescence intensity of CD206 and the relative expression levels of IL-4， IL-10， TGF-β， and Arg-1 mRNA were significantly reduced （P＜0.05）. Compared with the LPS group， the changes in the above indicators in the cells of the 10%RG group， 20%RG group， BAY 11-7082 group， and 20%RG+BAY 11-7082 group were significantly reversed （P＜0.05）， and there was no statistically significant difference in the comparison of the last three groups （P＞0.05）. CONCLUSIONS RG can effectively inhibit the overall activation of microglia and correct their M1/M2 polarization imbalance， and its mechanism may be closely related to the inhibition of excessive activation of the TLR4/NF-κB/NLRP3 signaling pathway.

Centered on the core theme of “making ethics work，” the interview systematically reviewed Professor Eric Meslin’s personal experiences and deep reflections on the American Human Genome Project and the Ethical， Legal， and Social Implications （ELSI） program. As a key practitioner in the field of American bioethics and science policy at the end of the 20th century， Professor Meslin recounted the historical origins， institutionalized operation， and funding mechanisms of ELSI， explained the formation process of interdisciplinary collaboration， policy translation， and governance innovation， and offered insights into the evolution framework of ELSI research over the past three decades. The interview also specifically discussed the expanding trend of bioethics governance in emerging technologies such as genomics， rare disease research， and artificial intelligence， as well as the regulatory challenges of international cooperation， data sharing， and ethical review. This interview provided valuable firsthand materials for understanding the historical experience and future directions of ELSI， offering references for the development of governance systems in medical science and technology ethics in China.

Objective: To evaluate the effectiveness of a family-school collaborative intervention on sleep health among fifth-grade primary school students, so as to provide scientific evidence for promoting sleep health among primary school students. Methods: From April to June 2024, a baseline survey was conducted on 342 fifth-grade students and their parents from one primary school in a district of Beijing, using the convenient sampling method. A semester of sleep health education was implemented from September to December 2024, covering cognitive, behavioral and environmental factors that affected timely bedtime; and the program took various forms, including student courses, popular-science articles for parents, and personalized feedback reports. Another primary school in the same area was conveniently selected as the control group, where 313 fifth-grade students and their parents received routine health education. The subjects were assessed for their baseline and end-point (March to June 2025) sleep conditions using sleep diaries (222 participants in the intervention group and 225 in the control group) and accelerometers (120 participants in the intervention group and 88 in the control group), respectively. The independent samples t-test and the Wilcoxon rank-sum test were used to compare characteristics between groups，and linear mixed models were employed to evaluate the intervention effects. Results: In the sleep diary evaluation, the intervention group had an earlier weekend wake up time and a smaller social jetlag than the control group at baseline ( t/Z =3.42, 7.21); in the accelerometer evaluation, the intervention group exhibited a smaller social jetlag than the control group at baseline ( Z =3.90) (all P <0.05). In the sleep diary evaluation, compared with the control group, the intervention group showed a reduced pre-to-post change in school-day bedtime ( β = -6.70), whereas the pre-to-post changes in school-day sleep duration, weekend wake-up time, weekend sleep duration, and average sleep duration were all increased at baseline and at the end ( β =8.41, 22.58, 27.03,13.74) (all P <0.05). In the accelerometer evaluation, compared with the control group, the intervention group showed reduced pre-to-post changes in school-day sleep onset time and school-day wake time ( β =-14.75, -6.24), whereas the pre-to-post change in school-day sleep duration increased at baseline and at the end ( β =8.01) (all P <0.05). Conclusion A family-school collaborative sleep health intervention may be an effective strategy for improving sleep among fifth-grade primary school students.

Artificial intelligence technologies, particularly large language models and generative artificial intelligence, which have advanced rapidly in recent years, are profoundly reshaping the technological landscape of innovative drug discovery and development. This article systematically reviews representative achievements made by Chinese researchers in AI-assisted drug design from 2022 to 2025. These advances cover multiple key stages, including target discovery, virtual screening, molecular generation, drug property prediction, synthetic route planning, and database construction. The review highlights China’s rapid progress in achieving core technological breakthroughs and translating artificial intelligence technologies into practical applications in drug discovery and development.

Objective:To analyze the trend of the health literacy level of Chinese residents from 2012 to 2023 and predict the health literacy level from 2024 to 2027.Methods:The study collected data on the health literacy surveillance of Chinese residents from 2012 to 2023. The Joinpoint regression model was used to calculate the average annual percent change (AAPC) and analyze the trend. The interrupted time series analysis with Prais-Winsten transformed generalized least squares estimation was employed to investigate the impact of the"Healthy China 2030" policy on residents′ health literacy levels. Joinpoint regression, autoregressive integrated moving average model and grey forecasting models were established to select the optimal model for forecasting health literacy levels from 2024 to 2027.Results:The results showed that the health literacy level of Chinese residents increased from 8.80% in 2012 to 29.70% in 2023 (AAPC=11.65%, P<0.05). The health literacy level of urban and rural residents increased from 11.79% and 7.13% in 2012 to 33.25% and 26.23% in 2023, respectively (AAPC=9.57% and 12.60%, both P<0.05). Rural (1.59% per year) saw a lower average annual increase than urban (1.79% per year), widening the urban-rural health literacy gap. All aspects of health literacy, including basic knowledge and concepts, healthy lifestyles and behaviors, and health skills, showed an upward trend. The literacy level of six health issues—safety and first aid, scientific health views, health information, infectious disease prevention, chronic disease prevention, and basic medical care—also exhibited rising trends. Interrupted time series analysis indicated a significant further increase in the health literacy level of Chinese residents after the implementation of the "Healthy China 2030" policy, with the growth rate increasing from 0.615% per year before implementation to 2.655% per year afterwards. The Joinpoint regression model showed superior predictive performance compared to autoregressive integrated moving average model and grey forecasting models. The prediction results suggested a continued upward trend in the health literacy level from 2024 to 2027, reaching 32.68%, 35.62%, 38.84%, and 42.34%, respectively. Conclusion:From 2012 to 2023, the overall and various aspects of health literacy among Chinese residents show a continuous upward trend. This study predicts that the level of residents′ health literacy will continue to rise by 2027.

Objective:To clarify the effect of methotrexate on blood uric acid levels and the incidence of hyperuricemia in patients with rheumatic and musculoskeletal diseases (RMDs).Methods:The clinical data were collected from 349 patients with RMDs who took methotrexate for more than 52 weeks and 429 patients with RMDs who did not take methotrexate, who were treated at Anqing Medical Center of Auhui Medical University from June 1, 2022 to June 30, 2024, to compare the differences in serum uric acid concentration and the incidence of hyperuricemia before and after 24 weeks of methotrexate administration in the two groups of patients with RMDs. The changes in serum uric acid concentration and serum creatinine value in the MTX na?ve patients who had taking MTX for 0, 24 and 52 weeks were compared. The relationship between serum uric acid concentration and methotrexate dosage was analyzed. Measurement data were compared using t-test or ANOVA, repeated measures analysis of variance, and count data were compared using χ2 test. Results:①At week 0, there was no significant difference in serum uric acid concentration [(300±63)μmol/L vs. (306±64)μmol/L, t=-1.416, P=0.157] and the incidence of hyperuricemia [9.3%(40/429) vs. 10.3%(36/349) , χ2=0.215, P=0.643] between the two groups. At week24, the serum uric acid concentration (307±70)μmol/L vs. (246±89)μmol/L was statistically significantly ( t=10.909, P<0.001) different. The incidence of hyperuricemia (11.0%, 47/429) vs. (4.6%, 16/349), was statistically significantly different ( χ2=10.497, P<0.001). There was a statistically significant difference in serum uric acid concentration between week 0 and week 24 in the methotrexate group ( t=10.237, P<0.001), and there was a statistically significant difference in the incidence of hyperuricemia ( χ2=8.312, P=0.004). ②The overall serum uric acid concentrations at week 0, weeks 24, and weeks 52 were (306±64)μmol/L, (246±89)μmol/L, and (247±66)μmol/L, respectively. The difference in overall serum uric acid concentration was statistically significant ( F= 29.506, P<0.001). There was no significant difference in serum uric acid concentration between weeks 24 and 52 ( P=1.000). There were significant differences in serum creatinine levels between weeks 0, 24 and 52 ( P<0.001). There was no significant difference in serum creatinine levels between weeks 0 ,52, weeks 24 and 52 ( P=0.077, P=1.000). There were statistically significant differences in the overall serum uric acid concentration and serum creatinine value at weeks 0, 24 and 52 of medication ( P<0.001).③ There was no significant difference in serum uric acid concentration before and after taking hydroxychloroquine, cyclosporine, tripterygium wilfordii, mycophenolate mofetil, tofacitinib, etanercept and adalimumab alone for weeks 0 and 24(all P>0.05). ④There was no significant difference in serum uric acid concentration between patients taking different doses of methotrexate (7.5 mg once weekly, 10 mg once weekly, 12.5 mg once weekly, 15 mg once weekly) at weeks 0 and 24 weeks(all P>0.05). Conclusion:MTX, as an anti-rheumatic drug, reduces the serum uric acid level and the incidence of hyperuricemia in patients with RMDs during the treatment.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To explore the construction of an evaluation model for aortic root anatomy and calcium burden in patients with bicuspid aortic valve (BAV) stenosis before transcatheter aortic valve replacement (TAVR) based on deep learning (DL) algorithms.Methods:A retrospective collection of 362 BAV stenosis patients who underwent TAVR from September 2023 to May 2024 was performed. All patients underwent cardiac CT angiography. The patients were divided into training group ( n=104), internal validation group ( n=206), and external validation group ( n=52). A DL model was trained on the training dataset to assess aortic root anatomy and calcification burden. The evaluation included the segmentation accuracy of the algorithm, the measurement performance of key anatomical structures (i.e., valve leaflets and type-1 and type-2 fusion raphe), and calcification burden, as well as the measurement efficiency. Overall segmentation performance was assessed using the average Dice coefficient (ADC). The fine-scale segmentation quality was validated by the 95th-percentile Hausdorff distance (HD-95) and the average symmetric surface distance (ASSD). The consistency of the measurement results was assessed using the Pearson correlation coefficient and the intraclass correlation coefficient ( ICC) with a two-way mixed model for absolute agreement. In addition, the total time and total mouse movement distance required for manual assessment versus the DL model on the validation datasets were recorded and compared. Results:The algorithm demonstrated excellent segmentation performance on aortic root anatomical targets, achieving outstanding consistency within both internal and external validation datasets (0.955

Proteolysis-targeting chimeras (PROTACs) represent a promising class of drugs that can target disease-causing proteins more effectively than traditional small molecule inhibitors can, potentially revolutionizing drug discovery and treatment strategies. However, the links between in vitro and in vivo data are poorly understood, hindering a comprehensive understanding of the absorption, distribution, metabolism, and excretion (ADME) of PROTACs. In this work, ¹⁴C-labeled vepdegestrant (ARV-471), which is currently in phase III clinical trials for breast cancer, was synthesized as a model PROTAC to characterize its preclinical ADME properties and simulate its clinical pharmacokinetics (PK) by establishing a physiologically based pharmacokinetics (PBPK) model. For in vitro-in vivo extrapolation (IVIVE), hepatocyte clearance correlated more closely with in vivo rat PK data than liver microsomal clearance did. PBPK models, which were initially developed and validated in rats, accurately simulate ARV-471's PK across fed and fasted states, with parameters within 1.75-fold of the observed values. Human models, informed by in vitro ADME data, closely mirrored postoral dose plasma profiles at 30 mg. Furthermore, no human-specific metabolites were identified in vitro and the metabolic profile of rats could overlap that of humans. This work presents a roadmap for developing future PROTAC medications by elucidating the correlation between in vitro and in vivo characteristics.

Proteolysis-targeting chimeras(PROTACs)represent a promising class of drugs that can target disease-causing proteins more effectively than traditional small molecule inhibitors can,potentially revolu-tionizing drug discovery and treatment strategies.However,the links between in vitro and in vivo data are poorly understood,hindering a comprehensive understanding of the absorption,distribution,metabolism,and excretion(ADME)of PROTACs.In this work,14C-labeled vepdegestrant(ARV-471),which is currently in phase Ⅲ clinical trials for breast cancer,was synthesized as a model PROTAC to characterize its preclinical ADME properties and simulate its clinical pharmacokinetics(PK)by estab-lishing a physiologically based pharmacokinetics(PBPK)model.For in vitro-in vivo extrapolation(IVIVE),hepatocyte clearance correlated more closely with in vivo rat PK data than liver microsomal clearance did.PBPK models,which were initially developed and validated in rats,accurately simulate ARV-471's PK across fed and fasted states,with parameters within 1.75-fold of the observed values.Human models,informed by in vitro ADME data,closely mirrored postoral dose plasma profiles at 30 mg.Furthermore,no human-specific metabolites were identified in vitro and the metabolic profile of rats could overlap that of humans.This work presents a roadmap for developing future PROTAC medications by elucidating the correlation between in vitro and in vivo characteristics.