OBJECTIVE To introduce the Dutch system of pharmacy academic education， professional practice and continuing education， and provide new ideas for constructing a “demand-driven， industry-education integrated， and sustainably developing” Chinese-style pharmacy education system. METHODS Through literature and public data retrieval， as well as collection of field visit materials， the study systematically combed the stage characteristics， institutional design， and innovative practices of Dutch pharmacy education， extracted its features and advantages， and proposed suggestions for pharmacy education reform in China. RESULTS & CONCLUSIONS The Dutch pharmacy academic education system is characterized by stepped competency-based training， integrating basic theory with early clinical practice at the undergraduate level， emphasizing specialized division of labor and strengthening clinical competence at the master’s level， and promoting industry-university-research collaborative innovation at the doctoral level. The practice qualification certification and continuing education exhibit multi-dimensional synergy. Specifically， the practice qualification certification process adheres to the guiding principle of “evidence-based competency”， implementing an access system centered on competency assessment， which requires passing national examinations and registration. The continuing education for hospital pharmacists is guided by patient safety， while continuing education for community pharmacists and other pharmacists （such as industrial pharmacists， regulatory science pharmacists， etc.） is guided by the frameworks of “digital situational learning” and a “triple tracks encompassing industry， regulation， and emerging fields”， respectively. China may draw on the five-dimensional path of Dutch pharmacy education in “early integration， vertical coherence， unified standards， industry-university-research collaboration， and intelligent empowerment” to reform its pharmacy education in aspects such as curriculum design， credit systems， evaluation criteria， training models， and training methods， aiming to cultivate pharmacy professionals aligned with China’s practical E-mail：cqqianyan@hospital.cqmu.edu.cn requirements.

The microstructures of pharmaceutical preparations play a pivotal role in determining their critical quality attributes (CQAs), such as drug release, content uniformity, and stability, which greatly impact the safety and efficacy of drugs. Unlike the inherent molecular structures of active pharmaceutical ingredients (APIs) and excipients, the microstructures of pharmaceutical preparations are developed during the formulation process, presenting unique analytical challenges. In this review, we primarily focus on presenting the research methods used to elucidate the microstructures of pharmaceutical preparations, including X-ray imaging (XRI), scanning electron microscopy (SEM), atomic force microscopy (AFM), Raman spectroscopy, infrared (IR) spectroscopy, and rheometer technology. Subsequently, we highlight the applications, advantages, and limitations of these methods. Finally, we discuss the current challenges and future perspectives in this field. This review aims to provide a comprehensive reference for understanding the microstructures of pharmaceutical preparations, offering new insights and potential advancements in their development.

Objective: To explore the experience of self growth among caregivers of adolescents with non suicidal self injury (NSSI), so as to provide practical reference for improving the family support system of adolescents with NSSI. Methods: From August to November 2023, a purposive sampling method was used to select 21 caregivers of adolescents with NSSI who were treated in a tertiary grade A psychiatric hospital in Xinxiang City, Henan Province for semi structured in depth interviews. The Colaizzi s seven step qualitative analysis method was applied to analyze the data and extract themes related to caregiver growth Results: A total of 5 themes and 12 sub themes of benefit finding were extracted from caregivers of adolescents with NSSI: personal growth (increased psychological resilience, enhanced awareness of independent learning, improved self reflection ability, better understanding and acceptance of NSSI behaviors in adolescents), improvement of family relationships (improved parent-child relationship, improved relationships among family members), perceived social support (more peer support, support from close friends), improvement of caregiving ability (creating a favorable rehabilitation environment, improved caregiving skills), and changes in life and education attitudes (adopting a healthier lifestyle, reasonably adjusting expectations for children). Conclusions During the process of caring for adolescents with NSSI, caregivers from positive experiences in multiple aspects such as personal growth, family relationships, social support, and life education attitudes. Improving the mental health level of caregivers and optimize the family rehabilitation environment, will help reduce the occurrence of NSSI behaviors among adolescents.

Objective To investigate the predictive value of combined radiomic features derived from chest CT scans with clinical characteristics for epidermal growth factor receptor(EGFR)gene mutations in non-small cell lung cancer(NSCLC).Methods A multi-center case-control study was conducted on the clinical data and CT images of 1 070 NSCLC patients from the radiology departments of the 3 medical institutions between January 2013 and October 2023.The 719 NSCLC patients from the First Affiliated Hospital of Army Medical University were randomly divided into a training set and an internal validation set in a ratio of 7∶3;The 173 patients in the Eastern Theatre General Hospital and the 178 patients in Army Medical Centre of PLA were assigned into the external validation set 1 and 2,respectively.Least absolute shrinkage and selection operator(LASSO)regression was employed to identify the optimal radiomic features,which were subsequently used to construct a radiomics model.Univariate and multivariate logistic regression analyses were applied to identify clinical features associated with EGFR mutation,thereby developing a clinical model.The radiomic and clinical features were subsequently combined to develop a comprehensive model.All the 3 classification models were built using random forest(RF)machine learning.The area under curve(AUC),accuracy,sensitivity and specificity were utilized to evaluate the predictive performance of the models.Calibration curve was plotted to assess the goodness of fit of the comprehensive model,while decision curve analysis was performed to assess the clinical utility of the model.Results The AUC value of the radiomics model was 0.762 4(95%CI:0.692 4～0.825 1),0.745 4(95%CI:0.671 1～0.814 3),and 0.724 7(95%CI:0.639 7～0.801 6),respectively,in the internal validation set,external validation set 1,and external validation set 2;The AUC value of the clinical prediction model was 0.691 7(95%CI:0.627 9～0.757 6),0.652 5(95%CI:0.576 7～0.729 1),and 0.779 2(95%CI:0.712 5～0.847 3),respectively in the above sets in turn;The comprehensive model constructed based on clinical features and radiomic features showed the best predictive efficacy,with an AUC value of 0.818 0(95%CI:0.757 7～0.874 3),0.782 4(95%CI:0.703 1～0.848 2),and 0.796 6(95%CI:0.718 1～0.868 6),respectively in the above sets.Calibration curve analysis indicated that the comprehensive model had a good fit,while decision curve analysis revealed that the model provided a favorable net benefit.Conclusion Our comprehensive model constructed based on chest CT radiomic features and clinical characteristics shows superior predictive performance for EGFR gene mutations in NSCLC across multiple center datasets,which may be helpful for clinical decision-making for treatment strategies.

Objective To evaluate the predictive value of deep learning features from chest CT images combined with clinical and radiomics features for epidermal growth factor receptor(EGFR)mutations in non-small cell lung cancer(NSCLC).Methods This case-control study retrospectively analyzed clinical and imaging data of 1 070 NSCLC patients from radiology departments at three hospitals(January 2013 to October 2023).Patients were divided into:a training set(n=502)and internal validation set(n=217)via 7∶3 randomization of 719 cases from the First Affiliated Hospital of Army Medical University;external validation set 1(n=173)from General Hospital of Eastern Theater Command;external validation set 2(n=178)from Daping Hospital of Army Medical University.Deep learning features were extracted using a 2.5D convolutional neural network(CNN)with ResNet101 backbone,radiomics features were derived from CT images,and clinical risk factors were identified to construct models.An integrated model combined deep learning,clinical,and radiomics features.All four models were developed using random forest(RF)classifiers.Calibration curves assessed goodness-of-fit,and decision curve analysis(DCA)evaluated clinical utility.Results The deep learning model achieved AUCs of 0.833 7(95%CI:0.770 6～0.884 7),0.815 1(0.741 6～0.882 8),and 0.810 1(0.745 2～0.873 6)in the internal and two external validation sets,respectively.Clinical models yielded AUCs of 0.731 0(0.660 2～0.802 1),0.746 0(0.666 4～0.824 9),and 0.813 4(0.743 1～0.883 6);radiomics models showed AUCs of 0.762 4(0.692 4～0.825 1),0.745 4(0.671 1～0.814 3),and 0.724 7(0.639 7～0.801 6).The integrated model demonstrated optimal performance with AUCs of 0.905 5(0.857 0～0.945 4),0.832 7(0.763 3～0.896 4),and 0.889 0(0.834 4～0.934 3).DCA indicated significant net benefit for EGFR prediction at threshold probabilities of 0.15～0.85 using the integrated model.Conclusion Deep learning features from CT images effectively predict EGFR mutation status in NSCLC.The integrated model combining deep learning,clinical,and radiomics features further enhances predictive performance.

BACKGROUND:Unicompartmental knee arthroplasty has been paid more and more attention because of its advantages of fewer traumas,less blood loss,less complications,faster recovery,excellent knee function and high prosthetic survival rate.Most of the relevant reports focused on its clinical effect,but the changes in the levels of relevant inflammatory cytokines in patients after unicompartmental knee arthroplasty were rarely reported. OBJECTIVE:To investigate the effect of unicompartmental knee arthroplasty in patients with medial compartment osteoarthritis of the knee and the changes of interleukin-1,interleukin-6,and tumor necrosis factor-α levels. METHODS:A total of 30 patients with medial compartment osteoarthritis of the knee who received unicompartmental knee arthroplasty from September 2021 to March 2023 and met the inclusion criteria were selected as the study subjects.Medial angle of proximal tibia,femoral and tibial angle,pain visual analog scale score,hospital for special surgery score,knee joint range of motion,synovial fluid interleukin-1,interleukin-6,and tumor necrosis factor-α levels before and after surgery were compared and statistically analyzed. RESULTS AND CONCLUSION:(1)All 30 patients had grade I wound healing.All patients were followed up for more than 6 months after surgery.There were no complications such as prosthesis loosening and dislocation of prosthesis liner in all patients.(2)The medial proximal tibia angle and the femoral and tibial angles measured after operation were significantly improved(P<0.05).(3)The visual analog scale score,hospital for special surgery score and range of motion measured at 1,3,and 6 months after operation were better than those before operation(P<0.05),and showed a gradual improvement(P<0.05).(4)The levels of interleukin-1,interleukin-6,and tumor necrosis factor-α in synovial fluid at 3 and 6 months after operation were decreased gradually compared with those before operation(P<0.05)and showed a gradual downward trend at each time point after operation.(5)It is indicated that unicompartmental knee arthroplasty can effectively treat medial compartment osteoarthritis of the knee,significantly relieve pain,restore knee joint function,improve knee varus deformity and lower limb strength line,and reduce the levels of inflammatory cytokines interleukin-1,interleukin-6,and tumor necrosis factor-α in joints to a certain extent.

Objectives:To establish a comprehensive system of Cardiovascular Academic Performance Evaluation(CAPE)and rank global TOP100 medical institutions in the fields of cardiovascular diseases(CVD). Methods:CVD-related terms were extracted from Medical Subject Headings(MeSH),Embase thesaurus(EMtrees)and International Classification of Diseases(ICD)by CVD-related professionals,as well as by librarians and information professionals.Terminology databases(named as Fuwai Subject Headings)were established,and nine sub-disciplines were proposed,including ischemic heart diseases,hypertension,vascular diseases,arrhythmia,pulmonary vascular diseases,heart failure,congenital heart diseases,cardiomyopathy,and valvular heart diseases.The mapping patterns of sub-discipline,cardiovascular terminology and entry terms were pre-defined.The CVD-related research literature published from January 1,2016 to December 31,2022 were retrieved from Web of Science,PubMed and Scopus.Based on this,metadata were fused and duplicates were excluded.Fuwai Subject Headings were searched and matched into four respects for each literature,including subject words,titles,keywords,and abstracts,which was used to generate an information table of"Position—CVD terminology—Frequency",and to calculate CVD correlation scores and sub-discipline scores.We standardized the names of medical institutions and scholars,and make a ranking system for CAPE based on original articles with strong cardiovascular correlation(correlation score≥4).When evaluating the science and technological performance for Chinese hospitals in cardiovascular diseases,National Natural Science Foundation Projects,authorized invention patents,prize achievements,research platforms,and registered data of drug clinical trials in Center for Drug Evaluation(CDE)were considered besides research papers. Results:During 2016 and 2022,1 545 103 CVD research literatures were found worldwide.After excluding meeting abstracts,books,biographies,news,videos,audio texts,retracted publications,and corrections,1 178 019 CVD research literatures were further evaluated.518 058 literatures were indexed as"strongly correlated to CVD"using Fuwai Subject Headings.Besides papers,other data sources were also collected,including 11 143 CVD-related Natural Science Foundation Projects,19 382 CVD-related effective authorized invention patents,103 CVD-related national prize achievements,24 CVD-related national research platforms,and 2 084 CDE registered data of CVD-related drug clinical trials.Research teams from nine sub-disciplines reviewed and validated research literature in respective fields,and classification rules of corresponding sub-disciplines were created and improved based on their opinions.Finally,eleven individual indexes were chosen to construct CAPE system for ranking global TOP100 medical institutions in overall CVD field and TOP30 in nine sub-disciplines.From 2016 to 2022,the number of cardiovascular disease research papers published by Chinese institutes has increased by 123.5%,with a total of approximately 76.8 thousands papers published(about 30 papers per day on average),ranked the second under the United States(approximately 114.1 thousands papers).However,the proportion of papers published by the Chinese Journal Citation Reports(JCR)and the Chinese Academy of Sciences only ranked eighth in the world.In the comprehensive academic performance of original cardiovascular research papers in global hospitals from 2020 to 2022,only two Chinese medical institutions ranked in the TOP20 as evaluated by CAPE system. Conclusions:Based on multi-source data from 2016 to 2022,CAPE initiated to establish a cardiovascular academic performance evaluation system.

Epilepsy is an episodic, transient, stereotypic brain dysfunction caused by highly synchronized abnormal neuronal discharges in the brain, with unpredictable timing of seizures, for which the main treatment modalities are antiepileptic drugs and surgery. Its diagnosis and treatment require a large number of aids and clinical experience. For multiple clinical aspects of epilepsy, such as seizure prediction, drug therapy prognosis, and surgical treatment evaluation, machine learning can incorporate multiple clinical and imaging factors through deep mining of data, establish corresponding learning models, improve the efficiency and accuracy of epilepsy diagnosis, realize individualized application of antiepileptic drugs, and improve the preoperative evaluation and prognosis of epilepsy patients.

Objective:To explore the clinical and genetic characteristics of a child with autosomal recessive primary microcephaly (MCPH).Methods:A case study has been carried out on a boy who had presented at the Inner Mongolia Maternity and Child Health Care Hospital for microcephaly and mental deficiency in September 2022. Prenatal ultrasound images were retrospectively analyzed, and whole exome sequencing and Sanger sequencing were carried out for his family. A literature review was also carried out using keywords such as " ASPM gene", "microcephaly", "prenatal diagnosis", "primary microcephaly", " ASPM", "MCPH5", "MCPH", "autosomal recessive microcephaly", and "prenatal diagnosis on ultrasonography" on the PubMed database, Wanfang Data and China National Knowledge until September 2023. This study was approved by Medical Ethics Committee of the Inner Mongolia Maternity and Child Health Care Hospital (Ethics No. 2021-093-1). Results:The proband had shown progressive reduction in biparietal diameter (BPD) and head circumference (HC) during the fetal period. He was found to harbor compound heterozygous variants of the ASPM gene, which included a paternally derived c. 8044C>T (p.R2682X) and a maternally derived c.8652dup (p.A2885Sfs*35). Both variants were classified as pathogenic (PVS1+ PM2_Supporting+ PP4; PVS1+ PM2_Supporting+ PM3) based on the guidelines from the American College of Medical Genetics and Genomics (ACMG). For other fetuses in his family, prenatal ultrasound and genetic testing were all normal. Literature research has identified 11 relevant articles, which included 14 MCPH cases. All of the MCPH5 cases had shown various degrees of reduced BPD/HC on fetal imaging (100%, 15/15). Developmental delay, intellectual disability, and attention deficits were noted in all survived cases, with one case having seizures (12.5%, 1/8). Their genotypes had included homozygotes (46.2%, 6/13) and compound heterozygotes (53.8%, 7/13) for nonsense variants (45%, 9/20) and frameshifting variants (55%, 11/20). Conclusion:The compound heterozygous variants c. 8044C>T (p.R2682X) and c. 8652dup (p.A2885Sfs*35) of the ASPM gene probably underlay the reduced BPD and HC in this proband with MCPH.

Objective:Analysis of the influencing factors of maternal oral health care behavior based on the health belief model.Methods:From July to December 2023, a cross-sectional survey was conducted in Peking Union Medical College Hospital on 316 pregnant women who received the health belief questionnaire and self-efficacy scale。 t test and χ2 test were used to analyze the factors affecting the oral health care behavior of pregnant women from the perspective of social psychology. Results:Among the 316 pregnant women included, 110(34.8%) had poor daily oral health care behavior, 120 (38.1%)did not have oral examination before or during pregnancy. The health beliefs of pregnant women in overall oral care were not high, with a score of 6.63+3.23, Median score is 7 (5).Perceived susceptibility to oral diseases ( OR=1.51, 95% CI:1.026-2.213), self-efficacy of daily living ( OR=2.64, 95% CI: 1.384-5.040), self-efficacy of oral examination ( OR=1.74, 95% CI:1.184-2.570) were independent factors of daily oral health care behavior in pregnant women. Health motivation ( OR=2.47, 95% CI:1.474-4.126) and self-efficacy of oral examination ( OR=4.17, 95% CI:2.626-6.619) were independent factors of oral examination behavior before and during pregnancy. Conclusion:Health beliefs of maternal oral health, especially perceived susceptibility, health motivation and self-efficacy are closely related to maternal oral health care behaviors. To improve the health belief and self-efficacy of pregnant women′s oral health care and avoid potential obstacles, which could be conducive to the effective promotion of oral health care for pregnant women.