OBJECTIVE To systematically evaluate risk prediction models for chemotherapy-induced myelosuppression in breast cancer， and provide a scientific reference for clinical healthcare workers in selecting or developing effective predictive models. METHODS A systematic search was conducted for studies on predictive models of the risk of chemotherapy-induced myelosuppression in breast cancer across the CNKI， VIP， Wanfang， PubMed， Web of Science， Cochrane Library， Embase， and Scopus databases， with a time frame of the establishment of the database to May 7， 2024. Literature was independently screened by 2 investigators， data were extracted according to critical appraisal and data extraction for systematic reviews of predictive model studies， and the risk of bias evaluation tool for predictive model studies was used to analyze the risk of bias and applicability of the included studies. RESULTS There were totally 7 studies， comprising 12 models. Among them， 11 models indicated an area under the subject operating characteristic curve of 0.600-0.908； 2 models indicated calibration. The common predictor variables of the included models were age， pre-chemotherapy neutrophil count， pre-chemotherapy lymphocyte count， and pre-chemotherapy albumin. The overall risk of bias of the 7 studies was high， which was mainly attributed to the flaws in the study design， insufficient sample sizes， inappropriate treatment of variables， non-reporting of missing data， and the lack of indicators for the assessment of the models， but the applicability was good. CONCLUSIONS The predictive performance of risk predictive models for chemotherapy-induced myelosuppression in breast cancer remains to be further enhanced， and the overall risk of model bias is high. Future studies should follow the specifications of model development and reporting， then combine machine learning algorithms to develop risk predictive models with good predictive performance， high stability， and low risk of bias， so as to provide a decision-making basis for the clinic.

ObjectiveThis study aims to observe the effect of sinomenine （SIN） on fatty acid binding protein 4 （FABP4） in synovial tissue of rats with osteoarthritis （OA） and investigate the therapeutic mechanism of SIN on OA， further providing new ideas for the management of osteoarthritis by traditional Chinese medicine （TCM）. MethodsAn OA rat model was constructed and randomly divided into a control group， an OA group， an OA + SIN-L group （50 mg·kg^-1）， an OA + SIN-M （100 mg·kg^-1）， an OA + SIN-H （200 mg·kg^-1）， and an OA + prednisone （PDN） group （5 mg·kg^-1）. Following surgical modeling for three weeks， an appropriate medication was administered for four weeks. During modeling and administration， a hot plate test was performed to detect the pain and swelling of the knee joints of the rats. The periarticular tissue was collected for arthropathological observation at the end of drug administration. The expression of cleaved Caspase-3， B-cell lymphoma-2 （Bcl-2）， Bcl-2 associated X protein （Bax）， and FABP4 in the synovial tissue of rats was detected by Western blot and real-time quantitative polymerase chain reaction （Real-time PCR）， and the expression and distribution of FABP4 protein in the synovial membrane were detected by immunofluorescence. ResultsCompared with those in the control group， the levels of inflammatory factors and FABP4 in the serum of rats in the OA group were significantly increased （P<0.05， P<0.01）， and joint swelling was significantly elevated （P<0.01）. The thermal pain threshold was significantly reduced （P<0.01）， and the expression of FABP4 protein and the fluorescence intensity were significantly increased （P<0.01）. The synovial tissue exhibited significantly increased inflammatory infiltration， proliferated fibroblasts， and an elevated apoptotic index （P<0.05， P<0.01）. Compared with those in the OA group， the serum lipid metabolism indexes of rats in the SIN administration group gradually returned to normal （P<0.05， P<0.01）， while the levels of inflammatory factors and FABP4 in the serum of rats in the SIN-administered group were significantly reduced （P<0.05， P<0.01）， and joint swelling was significantly decreased （P<0.05， P<0.01）. The thermal pain threshold was significantly elevated （P<0.05， P<0.01）， and the expression of FABP4 protein and fluorescence intensity in the synovial tissue were significantly decreased （P<0.05， P<0.01）. The synovial tissue displayed significantly reduced inflammatory infiltration and a decreased apoptotic index （P<0.05， P<0.01）. ConclusionThe therapeutic effect of SIN on OA may be related to the down-regulation of FABP4 expression， reduction of apoptosis， and inhibition of inflammatory factor expression.

OBJECTIVE To construct a prediction model for the efficacy of serotonin-norepinephrine reuptake inhibitor （SNRI） in inpatients with moderate and severe depression by using a machine learning method. METHODS The case records of inpatients with moderate and severe depression treated with SNRI antidepressants were collected from a third-grade class-A hospital in Xinjiang from January 2022 to October 2024； those patients were divided into effective group and ineffective group based on the Hamilton depression scale-24 score reduction rate. After screening the characteristic variables related to the therapeutic efficacy of SNRI drugs through LASSO regression， five prediction models including support vector machine， k-nearest neighbor， random forest， lightweight gradient boosting machine and extreme gradient boosting were constructed using the training set. Bayesian optimization was used to adjust the hyperparameters of these models. The performance of the models was evaluated in the validation set to select the optimal model. The Shapley additive explanations method was used to perform explainable analysis on the best model. RESULTS The medical records from 355 hospitalized patients with moderate and severe depression were collected， comprising 285 cases in the effective group and 70 cases in the ineffective group， resulting in an overall therapeutic response rate of 80.28%. After feature variable screening， five characteristic variables for therapeutic efficacy were obtained， including Hamilton anxiety scale， blood urea nitrogen， combination of anti-anxiety drugs， drinking history， and first onset of the disease. Compared with other models， the random forest model performed the best. The area under the receiver operating characteristic curve was 0.85， the area under the precision-recall curve was 0.87， the accuracy was 0.74， and the recall rate value was 0.75. CONCLUSIONS The random forest model constructed based on five characteristic variables demonstrates potential for predicting the therapeutic efficacy of SNRI antidepressants in hospitalized patients with moderate and severe depression.

RNA-based gene therapy has been widely used for various diseases, and extensive studies have proved that suitable delivery routes greatly help the development of RNA therapeutics. Identifying a safe and effective delivery system is key to realizing RNA therapeutics' clinical translation. Inhalation is a non-invasive pulmonary delivery modality that can enhance the retention of therapeutic agents in the lungs with negligible toxicity, thereby improving patient compliance. Inhaled RNA therapeutics are increasingly becoming an area of focus for researchers; however, only several clinical trials have explored inhaled delivery of RNA for pulmonary diseases. This review presents an overview of recent advances in inhaled delivery systems for RNA therapeutics, including viral and nonviral systems, highlighting state of the art regarding inhalation in the messenger RNA (mRNA) field. We also summarize the applications of mRNA inhalants in infectious and other lung diseases. Simultaneously, the research progresses on small interfering RNAs (siRNAs), antisense oligonucleotides (ASOs), and different types of RNA are also discussed to provide new strategies for developing RNA inhalation therapy. Finally, we clarify the challenges inhaled RNA-based therapeutics face before their widespread adoption and provide insights to help advance this exciting field to the bedside.

Lophatheri Herba (Danzhuye in Chinese) is derived from the dried stems and leaves of Lophatherum gracile and has a long history of use as a medicinal and food source. Flavonoids and phenolic acids are the main active ingredients in Lophatheri Herba, which produce diuretic, anti-inflammatory, and antipyretic effects. Flavonoid glycosides and hydroxybenzoic acids are respectively the main structure in 44 flavonoids and 16 phenolic acids obtained from Lophatheri Herba. Modern pharmacological studies have found that the main chemical constituents of Lophatheri Herba play important roles in anti-inflammatory, cardioprotective, hepatoprotective and hypoglycaemic effects. Studies have demonstrated that flavonoid monomers, for example, luteolin, isoorientin, luteolin-7-O-β-D-glucoside and apigenin are more effective in exerting the above pharmacological effects. In addition, Lophatheri Herba is used in different food products as the main ingredient or as an accessory. This review describes Lophatheri Herba in terms of its chemical composition, pharmacological effects and efficacy, food development and applications, and clinical utility, and discusses the problems facing its use. This study provides valuable ideas and a scientific basis for the future development and use of L. gracile.

The incidence of osteoporotic thoracolumbar vertebral fracture (OTLVF) in the elderly is gradually increasing. The kyphotic deformity caused by various factors has become an important characteristic of OTLVF and has received increasing attention. Its clinical manifestations include pain, delayed nerve damage, sagittal imbalance, etc. Currently, the definition and diagnosis of OTLVF with kyphotic deformity in the elderly are still unclear. Although there are many treatment options, they are controversial. Existing guidelines or consensuses pay little attention to this type of fracture with kyphotic deformity. To this end, the Lumbar Education Working Group of the Spine Branch of the Chinese Medicine Education Association and Editorial Committee of Chinese Journal of Trauma organized the experts in the relevant fields to jointly develop Clinical guidelines for the diagnosis and treatment of osteoporotic thoracolumbar vertebral fractures with kyphotic deformity in the elderly ( version 2024), based on evidence-based medical advancements and the principles of scientificity, practicality, and advanced nature, which provided 18 recommendations to standardize the clinical diagnosis and treatment.

Periarticular fracture of the shoulder is a common type of fractures in the elderly. Postoperative adverse events such as internal fixation failure, humeral head ischemic necrosis and upper limb dysfunction occur frequently, which seriously endangers the exercise and health of the elderly. Compared with the fracture with normal bone mass, the osteoporotic periarticular fracture of the shoulder is complicated with slow healing and poor rehabilitation, so the clinical management becomes more difficult. At present, there is no targeted guideline or consensus for this type of fracture in China. In such context, experts from Youth Osteoporosis Group of Chinese Orthopedic Association, Orthopedic Expert Committee of Geriatrics Branch of Chinese Association of Gerontology and Geriatrics, Osteoporosis Group of Youth Committee of Chinese Association of Orthopedic Surgeons and Osteoporosis Committee of Shanghai Association of Chinese Integrative Medicine developed the Chinese expert consensus on the diagnosis and treatment of osteoporotic periarticular fracture of the shoulder in the elderly ( version 2023). Nine recommendations were put forward from the aspects of diagnosis, treatment strategies and rehabilitation of osteoporotic periarticular fracture of the shoulder, hoping to promote the standardized, systematic and personalized diagnosis and treatment concept and improve functional outcomes and quality of life in elderly patients with osteoporotic periarticular fracture of the shoulder.

Objective:To assess the predictive values of bioelectrical impedance analysis(BIA)-measured body fat indices to abnormal lipid profiles, and to preliminary propose optimal cut-off values of body fat in children and adolescents.Methods:Children and adolescents, aged 6-16 years, were selected from 30 schools (8 primary schools, 21 middle schools and one 12-year education school) in Dongcheng, Tongzhou, Fangshan and Miyun districts of Beijing by adopting a stratified cluster sampling method from November 2017 to January 2018.Questionnaire survey, body mass index(BMI), body fat mass index (FMI), fat mass percentage (FMP) and four lipid profiles were conducted.Results:A total of 14 309 participants, aged (11.0±3.3) years, were enrolled in the analysis, with 49.9% boys.In boys and girls, the percentile values ( P60- P95) fitted by FMI and FMP with K-median-coefficient of variation(LMS) method were taken as the cutting points, and P75 values were selected as the cut-off points of excessive body fat for their better sensitivity, specificity, predictive value and area under curve (AUC) for identification of abnormal lipid profiles.Boys with FMI above P75 accounted for 28% of the total population, and controlling boys with FMI below P75 could prevent dyslipidemia of 8%-57%.FMI in girl population occupied about 26% of the above, and controlling FMI in girl population below this cut-off point may prevent dyslipidemia from 8%-42%.FMP observed similar results to FMI.Assessed by FMI or FMP with P75 cut-off values, adiposity performed better than BMI for recognizing abnormal lipid profiles in boys (AUC: 52.4%-69.6% vs.50.2%-67.1%, P<0.05) rather than in girls ( P>0.05). In addition, when FMI or FMP beyond P90, the specificity of each abnormal lipid profiles was around 90%. Conclusions:The recommend cut-off points for body fat may be to assess children′s adiposity, and can be applied in preventive activities.

Objective:To investigate the relationships between hyperuricemia and the incidence risk for cardiometabolic abnormity in children.Methods:Data were obtained from School-based Cardiovascular and Bone Health Promotion Program. In 2017, a total of 15 391 children aged 6-16 years in Beijing were selected through stratified cluster sampling at baseline survey. Follow-up investigation was conducted in 2019. Logistic regression model was used to analyze the relationships of uric acid quartiles and change in uric acid levels with incidence risks for cardiometabolic abnormity (hypertension, hyperglycemia and dyslipidemia).Results:A total of 8 807 children (4 376 boys, 4 431 girls) were included in the analysis, the average age of the children was (11.1±3.3) years at baseline survey. The adjusted odds ratios ( ORs) and 95% confidence intervals ( CIs) of incidence risk for hypertension in the third and fourth quartiles of the UA were 1.39 (1.11-1.75) and 1.56 (1.19-1.81), respectively. The ORs and 95% CIs of risk for high LDL-C in the second, third and fourth quartiles were 1.88 (1.16-3.05),1.98 (1.23-3.17) and 2.25 (1.42-3.57). The uric acid level increased by one standard deviation, the risk increased by 17% for hypertension and 27% for high LDL-C. The uric acid level increased by 10 μmol/L, the risk increased by 2.1% for hypertension and 2.9% for high LDL-C. The gender-stratified analysis showed that the similar results. The ORs and 95% CIs were 1.32 (1.09-1.60) and 1.50 (1.05-2.16) for hypertension, 1.90 (1.38-2.60) and 2.96 (1.58-5.52) for high TC, 1.78 (1.26-2.51) and 2.84 (1.60-5.03) for high LDL-C in the groups of newly diagnosed hyperuricemia and persistent hyperuricemia. Conclusions:Higher uric acid level was associated with increased incidence risks for hypertension, abnormal TC and LDL-C. Maintaining optimal uric acid level by children might contribute to the early prevention of cardiovascular diseases.

Objective:To analyze the influence of obesity status on the development of cardiometabolic disorders in school-age children.Methods:Information about children's body weight, body height and cardiovascular risk factors were collected in baseline survey in 2017 and follow-up survey in 2019. The school-age children were divided into four groups based on their baseline and follow-up obesity status, i.e. sustained non-obesity group, restored obesity group, newly classified obesity group, and persistent obesity group. Analysis of covariance was used to compare the difference of change in levels of cardiometabolic factors among the four groups. The multivariate logistic regression model was used to analyze the relationship between obesity status and the incidence risk of cardiometabolic disorders.Results:The present study included 11 379 school-age children (boys accounting for 49.6%). During the 2 years, the incidence of obesity was 3.2% (95% CI: 2.9%-3.5%) with the restoration ratio of obesity of 4.4% (95% CI: 4.0%-4.8%). Compared with the sustained non-obesity group, increases in SBP, DBP, TG, LDL-C and non-HDL-C were much higher in newly classified obesity group and persistent obesity group, but lower in restored obesity groups except for DBP (all P<0.05). In addition, the incidence risk of hypertension, high glucose, dyslipidemia and cardiometabolic disorders (≥2 risks) were much higher in newly classified and persistent obese children than in sustained non-obese children. No difference was found in incidence risks of most cardiovascular disorders between restored obese children and sustained non-obese children, except for hypertension and cardiometabolic risks. Conclusion:Both newly classified obesity and persistent obesity increased the incidence risks for multi cardiovascular disorders, while these risks could be reduced when non-obese status restore.