Drug development remains a critical issue in the field of biomedicine. With the rapid advancement of information technologies such as artificial intelligence (AI) and the advent of the big data era, AI-assisted drug development has become a new trend, particularly in predicting drug-target associations. To address the challenge of drug-target prediction, AI-driven models have emerged as powerful tools, offering innovative solutions by effectively extracting features from complex biological data, accurately modeling molecular interactions, and precisely predicting potential drug-target outcomes. Traditional machine learning (ML), network-based, and advanced deep learning architectures such as convolutional neural networks (CNNs), graph convolutional networks (GCNs), and transformers play a pivotal role. This review systematically compiles and evaluates AI algorithms for drug- and drug combination-target predictions, highlighting their theoretical frameworks, strengths, and limitations. CNNs effectively identify spatial patterns and molecular features critical for drug-target interactions. GCNs provide deep insights into molecular interactions via relational data, whereas transformers increase prediction accuracy by capturing complex dependencies within biological sequences. Network-based models offer a systematic perspective by integrating diverse data sources, and traditional ML efficiently handles large datasets to improve overall predictive accuracy. Collectively, these AI-driven methods are transforming drug-target predictions and advancing the development of personalized therapy. This review summarizes the application of AI in drug development, particularly in drug-target prediction, and offers recommendations on models and algorithms for researchers engaged in biomedical research. It also provides typical cases to better illustrate how AI can further accelerate development in the fields of biomedicine and drug discovery.

Objective To explore the perceptions,diagnostic criteria and clinical management strategies of joint surgeons regarding perioperative knee extension lag in patients with total knee arthroplasty.Methods From June to July,2024,17 joint surgeons from Peking University the First Hospital and Peking University the Third Hospital were selected as research subjects using purposive and convenience sampling.Semi-structured in-terviews were conducted.The interview data were analyzed and themes were summarized using NVivo 12.0 soft-ware.Results A total of four themes and ten sub-themes emerged from the study.Theme 1 was the basics related to knee exten-sion lag,including definition,diagnosis and incidence.Theme 2 was the attitudes of joint surgeons towards knee extension lag,including clinical value and importance.Theme 3 was the impact of knee extension lag on postop-erative functional outcomes,including the impact of preoperative knee extension lag and postoperative knee ex-tension lag on functional recovery.Theme 4 was management strategies for knee extension lag,including preop-erative rehabilitation,surgical strategies and postoperative management.Conclusion The standardized diagnosis and treatment of knee extension lag are still required further research.It is rec-ommended that relevant content be added and emphasized in the training of joint surgeons and the early rehabili-tation intervention of rehabilitation practitioners to improve the diagnosis and treatment of knee extension lag and to make it a useful addition to the perioperative management of total knee arthroplasty.

Drug development remains a critical issue in the field of biomedicine.With the rapid advancement of information technologies such as artificial intelligence(AI)and the advent of the big data era,AI-assisted drug development has become a new trend,particularly in predicting drug-target associations.To address the challenge of drug-target prediction,AI-driven models have emerged as powerful tools,of-fering innovative solutions by effectively extracting features from complex biological data,accurately modeling molecular interactions,and precisely predicting potential drug-target outcomes.Traditional machine learning(ML),network-based,and advanced deep learning architectures such as convolutional neural networks(CNNs),graph convolutional networks(GCNs),and transformers play a pivotal role.This review systematically compiles and evaluates AI algorithms for drug-and drug combination-target predictions,highlighting their theoretical frameworks,strengths,and limitations.CNNs effectively identify spatial patterns and molecular features critical for drug-target interactions.GCNs provide deep insights into molecular interactions via relational data,whereas transformers increase prediction accu-racy by capturing complex dependencies within biological sequences.Network-based models offer a systematic perspective by integrating diverse data sources,and traditional ML efficiently handles large datasets to improve overall predictive accuracy.Collectively,these AI-driven methods are transforming drug-target predictions and advancing the development of personalized therapy.This review summa-rizes the application of AI in drug development,particularly in drug-target prediction,and offers rec-ommendations on models and algorithms for researchers engaged in biomedical research.It also provides typical cases to better illustrate how AI can further accelerate development in the fields of biomedicine and drug discovery.

Objective:To explore the correlation between weekend moderate-to-vigorous physical activity(MVPA), weekday sedentary behavior(SB)and the risk of frailty in the elderly population monitored by wearable devices, and to provide a scientific basis for lifestyle interventions for frailty in the elderly.Methods:This study was based on the data of the UK Biobank from 2013 to 2015.A cross-sectional study design was adopted, and 33, 212 elderly people aged 60 and above with complete physical activity monitoring data were selected.The Frailty Index(FI)constructed by the deficit accumulation method was used to assess the frailty status.The correlation between the combined effect of weekday SB and weekend MVPA and the frailty status was analyzed, and the differences between genders were explored.Results:There were significant differences in physical activity indicators among the elderly with different frailty statuses.As the degree of frailty increased, the MVPA-related indicators showed a downward trend, while the weekday SB time gradually increased.There were sex differences in physical activity patterns and frailties.Compared with women, men had longer SB time on weekdays, lower metabolic equivalent of weekly MVPA consumption, and higher MVPA time on weekends, but the frailties index of women was slightly higher than that of men.After adjusting for confounding factors, the frailty risks for men and women in the subgroup with the lowest weekday SB and the highest weekend MVPA duration decreased by 46.9% and 59.8%, respectively( P<0.001)when compared to the highest-risk group. Conclusions:Based on the monitoring data from wearable devices, elderly individuals who reduced their SB time during weekdays and increased their MVPA time on weekends were associated with a lower risk of frailty, especially among women; which providing a new perspective for lifestyle-based intervention strategies for frailty among the elderly.

Objective:To explore the correlation between weekend moderate-to-vigorous physical activity(MVPA), weekday sedentary behavior(SB)and the risk of frailty in the elderly population monitored by wearable devices, and to provide a scientific basis for lifestyle interventions for frailty in the elderly.Methods:This study was based on the data of the UK Biobank from 2013 to 2015.A cross-sectional study design was adopted, and 33, 212 elderly people aged 60 and above with complete physical activity monitoring data were selected.The Frailty Index(FI)constructed by the deficit accumulation method was used to assess the frailty status.The correlation between the combined effect of weekday SB and weekend MVPA and the frailty status was analyzed, and the differences between genders were explored.Results:There were significant differences in physical activity indicators among the elderly with different frailty statuses.As the degree of frailty increased, the MVPA-related indicators showed a downward trend, while the weekday SB time gradually increased.There were sex differences in physical activity patterns and frailties.Compared with women, men had longer SB time on weekdays, lower metabolic equivalent of weekly MVPA consumption, and higher MVPA time on weekends, but the frailties index of women was slightly higher than that of men.After adjusting for confounding factors, the frailty risks for men and women in the subgroup with the lowest weekday SB and the highest weekend MVPA duration decreased by 46.9% and 59.8%, respectively( P<0.001)when compared to the highest-risk group. Conclusions:Based on the monitoring data from wearable devices, elderly individuals who reduced their SB time during weekdays and increased their MVPA time on weekends were associated with a lower risk of frailty, especially among women; which providing a new perspective for lifestyle-based intervention strategies for frailty among the elderly.

Objective To explore the perceptions,diagnostic criteria and clinical management strategies of joint surgeons regarding perioperative knee extension lag in patients with total knee arthroplasty.Methods From June to July,2024,17 joint surgeons from Peking University the First Hospital and Peking University the Third Hospital were selected as research subjects using purposive and convenience sampling.Semi-structured in-terviews were conducted.The interview data were analyzed and themes were summarized using NVivo 12.0 soft-ware.Results A total of four themes and ten sub-themes emerged from the study.Theme 1 was the basics related to knee exten-sion lag,including definition,diagnosis and incidence.Theme 2 was the attitudes of joint surgeons towards knee extension lag,including clinical value and importance.Theme 3 was the impact of knee extension lag on postop-erative functional outcomes,including the impact of preoperative knee extension lag and postoperative knee ex-tension lag on functional recovery.Theme 4 was management strategies for knee extension lag,including preop-erative rehabilitation,surgical strategies and postoperative management.Conclusion The standardized diagnosis and treatment of knee extension lag are still required further research.It is rec-ommended that relevant content be added and emphasized in the training of joint surgeons and the early rehabili-tation intervention of rehabilitation practitioners to improve the diagnosis and treatment of knee extension lag and to make it a useful addition to the perioperative management of total knee arthroplasty.

Objective:To explore the effect of pentraxin 3 (PTX3) on memory improvement and Aβ expression in Alzheimer's disease (AD) model mice.Methods:(1) Ten 5-month-old 5×FAD mice were randomly divided into PTX3 group and model group ( n=5); 5 C57BL/6 wild-type mice at the same age were selected as control group; mice in the PTX3 group and control group were stereotactically injected 4 μL 0.5 g/L PTX3 or same dose of phosphate buffered saline (PBS); Morris water maze test was used to detect the learning and memory abilities, Y maze test was used to detect the short-term memory, and ELISA was used to obsevre the contents of Aβ 40 and Aβ 42 in the brain hemisphere. (2) Twenty-five 3-month-old 5×FAD mice were randomly divided into model group, 2 μg/kg PTX3 group, 4 μg/kg PTX3 group, 8 μg/kg PTX3 group, and 16 μg/kg PTX3 group ( n=5); 5 C57BL/6 wild-type mice at the same age were selected as control group; mice in the PTX3 groups were intranasally injected 2, 4, 8, and 16 μg/kg PTX3, respectively; those in the model group and control group were intranasally injected same dose of PBS; injection was given once every 96 h for a total of 7 times. Morris water maze test was used to detect the learning and memory abilities, Y maze test was used to detect the short-term memory, and ELISA was used to obsevre the contents of Aβ 40 and Aβ 42 in the hippocampus. Results:(1) Compared with the model group, the PTX3 group had significantly shorter platform latency, higher percentage of exploration time and higher percentage of spontaneous alternations ( P<0.05). Compared with those in model group ([63.38±21.42] pg/mL, [29.77±6.11] pg/mL), the concentrations of Aβ 40 and Aβ 42 in the brain tissues of PTX3 group ([15.87±2.11] pg/mL, [16.55±1.95] pg/mL) were statistically lower ( P<0.05). (2) Compared with the model group, the 16 μg/kg PTX3 group had significantly shorter escape latency and higher percentage of exploration time ( P<0.05); compared with the model group, the 2 μg/kg PTX3 group and 16 μg/kg PTX3 group had significantly higher percentage of spontaneous alternations ( P<0.05). The contents of Aβ 40 and Aβ 42 in the hippocampus of 8 μg/kg PTX3 group and 16 μg/kg PTX3 group were statistically lower compared with those in the model group ( P<0.05). Conclusion:PTX3 may attenuate cognitive deficits and decrease Aβ expression in the brain or hippocampus tissues of 5×FAD mice with AD.

Objective To investigate the reliability and validity of the assessment tools of Brief ICF Core Sets for Arthroplasty of Knee Osteoarthritis in Perioperative Period(ICSAKOPP). Methods From May,2022 to April,2023,320 patients undergoing knee arthroplasty were selected in Peking University Third Hospital,China-Japan Friendship Hospital,Peking University First Hospital and Chinese PLA General Hospital.Trained assessors used Brief ICSAKOPP to evaluate all enrolled patients before arthroplasty,three days(±one day)after arthroplasty,three weeks(±one week)after arthroplasty,and three months(±one month)after ar-throplasty.Western Ontario and McMaster Universities Osteoarthritis Index(WOMAC)scores were recorded at the same time.Five professionals were asked to score all the items of Brief ICSAKOPP,and the content validity index(CVI)was caculated. Results A total of 64 cases were dropped down.CVI of all the items of the Brief ICSAKOPP were above 0.8,with a av-erage CVI of the scale of 0.938.The Cronbach's α coefficient of the Brief ICSAKOPP was 0.813.There was a moderate correlation(r=0.681,P<0.001)between the overall Brief ICSAKOPP and WOMAC scores,as well as body functional dimension score(r=0.668,P<0.001)and activities and participation dimension score(r=0.657,P<0.001). Conclusion Brief ICSAKOPP is good in content validity,internal consistency reliability and criterion validity.

Objective To provide theoretical reference and practical basis for accurately choosing the suitable packaging forms for different Injections. Methods Based on the raw materials in the common packaging forms of injections, the research and application progress on different packaging forms for injections were reviewed by analyzing the characteristics and technical requirements of different packaging forms, and the current registration information of pharmaceutical packaging materials in the Center for Drug Evaluation, NMPA were introduced. Results For preparations with small single-dose and low-cost, the ampoules or injection vials could be chosen. Powder injections are usually packaged in injection vials. For rescue medicines and valuable medicines, the pre-filled syringes could be chosen. For chronic disease treatment drugs (such as insulin) that require long-term injection, or some injections for emergency use, a pen-type syringe package that patients can inject themselves could be used. Neutral glass packaging or plastic packaging should be used for some acidic or alkaline. Conclusion The drug manufacturers should comprehensively consider the physicochemical properties of drugs, the performance of packaging raw materials, compatibility test results, price-cost, and convenience in carrying and use when choosing the appropriate packaging form to ensure the quality, safety, and effectivity of drugs.

ObjectiveTo investigate rehabilitation competence among trainers and trainees whom participated in the training program entitled National Training Program of Shortage Rehabilitation Physicians (NTPSRP) using World Health Organization rehabilitation competency framework (RCF). MethodsBased on RCF, a questionnaire was developed and administrated through network using Questionnaire Star. All the trainers and trainees who participated in NTPSRP were investigated in September, 2023. ResultsA total of 911 subjects were collected from 27 provinces, including 426 trainers (teachers) and 485 trainees (students). The average age of the teachers was older, with more years of work experience and professional experience in rehabilitation medicine. The degree and professional title of the teachers was also higher. The overall internal consistency reliability of the questionnaire was good (Cronbach's α = 0.988), and all the internal consistency reliability in five fields was good (Cronbach's α > 0.9). The five dimensional structure of RCF in the results was consistent with the prior model established by RCF theory. The self-ratings of all physicians in the five fields were higher than the median level, and was higher in the teachers than in the students [(3.42±0.68) vs. (2.73±0.80), P < 0.001]. Gender and years of experience in rehabilitation medicine were independent factors for the total score of the questionnaire. The total self-rating of female students was 9.65 points lower than that of the male (95%CI 4.386 to 14.914); and one more year in rehabilitation medicine would increase 1.78 points in self-rating (95%CI 1.140 to 2.419). ConclusionThe structure and content of RCF can be used to evaluate the competence of rehabilitation physicians. The teachers and students of NTPSRP are eligible to RCF. RCF-based evaluation can be used to guide the development of continuing education courses for rehabilitation professionals.