OBJECTIVE To develop and validate interpretable machine learning models for predicting the risk of medication-related osteonecrosis of the jaw （MRONJ） and surgical outcomes， thereby providing quantitative support for MRONJ risk assessment and treatment decision-making.METHODS Two study cohorts were established. Cohort A adopted a nested case-control study design to develop a predictive model for the risk of MRONJ onset. Cohort B comprised patients with MRONJ from Cohort A who underwent surgical treatment and met the follow-up eligibility criteria， and employed a prospective follow-up cohort study design to develop a predictive model for the efficacy of MRONJ surgery. After missing-data processing， variable standardization， and encoding， predictive features were selected using the least absolute shrinkage and selection operator （LASSO） regression， and collinearity was assessed using the variance inflation factor （VIF）. Random Forest （RF）， eXtreme Gradient Boosting （XGB）， Multi-layer Perceptron （MLP）， Support Vector Machine （SVM）， and Gaussian Naive Bayes （NB） models were subsequently developed using the selected features. Hyperparameter optimization and internal performance evaluation were performed using two-level nested cross-validation repeated 20 times. In Cohort B， the synthetic minority over-sampling technique （SMOTE） was applied within the inner training folds to address class imbalance. Model performance was comprehensively evaluated using the receiver operating characteristic （ROC） curve， the precision-recall （PR） curve， calibration curve， and decision curve analysis （DCA）. Shapley additive explanations （SHAP） were used to quantify the relative contributions of individual clinical features to model predictions.RESULTS Seven clinical features， including alkaline phosphatase and tooth extraction， were retained for Cohort A； whereas eight clinical features， including age and duration of medication use， were retained for Cohort B. In Cohort A， the area under the ROC curve， the area under the PR curve， Brier score， sensitivity， and specificity of the RF model were 0.94， 0.92， 0.09， 0.92， and 0.85， respectively； the corresponding values in Cohort B were 0.93， 0.93， 0.12， 0.83， and 0.93， respectively. The results of calibration curves and DCA indicated that the RF models achieved favorable calibration and clinical net benefit， with VIF values for all variables below 5. SHAP visualization results showed that alkaline phosphatase， tooth extraction， and cumulative drug dose made substantial contributions to MRONJ risk prediction in Cohort A， whereas age， duration of medication use， and MRONJ stage contributed substantially to surgical outcome prediction in Cohort B.CONCLUSIONS The RF-based models for predicting MRONJ risk and surgical outcomes demonstrated good discrimination， accuracy of probabilistic predictions， and potential clinical utility during internal validation. These models may provide decision support for comprehensive MRONJ risk management and individualized clinical decision-making. However， external validation in independent， multicenter， and geographically diverse cohorts is still required.

ObjectiveTo investigate the anti-Alzheimer's disease （AD） effect of Dipsacus asper（DA） in the Caenorhabditis elegans model， and decipher the underlying mechanism via the peroxisome proliferator-activated receptor α （PPARα）/transcription factor EB （TFEB） pathway. MethodsFirst， transgenic AD C. elegans individuals were assigned into the blank control， model， positive control （WY14643， 20 µmol·L^-1）， and low-， medium-， and high-dose （100， 200， and 400 mg·L^-1， respectively） DA groups. The amyloid β-42 （Aβ₄₂） formation in the muscle cells， the paralysis time， and the deposition of amyloid β-protein （Aβ） in the head were detected. The lysosomal autophagy in the BV2 cell model was examined by Rluc-LC3wt/G120A. The expression levels of lysosomal autophagy-related proteins LC3Ⅱ， LC3I， LAMP2， and TFEB were detected by Western blot. Real-time quantitative polymerase chain reaction （Real-time PCR） was employed to determine the mRNA levels of autophagy-related genes beclin1 and Atg5 and lysosome-related genes LAMP2 and CLN2 downstream of PPARα/TFEB. A reporter gene assay was used to detect the transcriptional activities of PPARα and TFEB. Immunofluorescence was used to detect the fluorescence intensity of PPARα， and the active components of the ethanol extract of DA were identified by UPLC-MS. RCSB PDB， Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）， and Autodock were used to analyze the binding between the active components and PPARα-ligand-binding domain （LBD）. ResultsCompared with the model group， the positive control group and 200 and 400 mg·L^-1 DA groups showed prolonged paralysis time （P<0.05）， and all the treatment groups showed decreased Aβ deposition in the head （P<0.01）. DA within the concentration range of 50-500 mg·L^-1 did not affect the viability of BV2 cells. In addition， DA enhanced the autophagy flux （P<0.05）， up-regulated the mRNA levels of beclin1， Atg5， LAMP2， and CLN2 （P<0.05， P<0.01）， promoted the nuclear translocation of TFEB （P<0.05）， increased LAMP2 expression and autophagy flux （P<0.05， P<0.01）， and enhanced the transcriptional activities of PPARα and TFEB （P<0.01）. The positive control group and 200 and 400 mg·L^-1 DA groups showed enhanced fluorescence intensity of PPARα in the BV2 nucleus （P<0.01）. UPLC-MS detected nine known compounds of DA， from which 8 active components of DA were screened out. The docking results suggested that a variety of components in DA could bind to PPARα-LBD and form stable hydrogen bonds. ConclusionDA may reduce the pathological changes in AD by regulating the PPARα-TFEB pathway.

OBJECTIVE To explore the characteristics and influential factors of pharmaceutical clinic service demands， providing evidence for optimizing pharmaceutical service models and facilitating pharmaceutical service models of pharmacist role transformation. METHODS A cross-sectional survey design was adopted， and 410 outpatient participants were selected from Fudan University Shanghai Cancer Center through convenience sampling for questionnaire administration from February to May 2025. Kano model was applied to analyze the demand attributes of 25 pharmaceutical services， while questionnaires were used to assess patients’ awareness and demand status. Subgroup analyses were conducted based on key demographic variables such as gender， age， educational attainment， and economic burdens， to SACA- systematically examine the differences in Kano attribute classification among patients in each subgroup. RESULTS The awareness rate of pharmaceutical outpatient services among patients was only 14.63%， yet those who were aware demonstrated a significantly higher demand rate for such services compared to those who were unaware （P＜0.001）. The demand for pharmaceutical clinic services exhibited a hierarchical characteristic： twelve items were identified as attractive attributes （e. g.， providing suggestions for more affordable treatment options， offering online consultation services， etc.）， five items as expected attributes （e.g.， having a good attitude and being able to patiently answer your questions， etc.）， three items as must-have attributes （e.g.， providing guidance on medication dosage and usage， providing guidance on medication precautions， etc.）， five items as indifferent attributes （e.g.， providing treatment plan recommendations based on the patient’s condition）. There were zero items classified as reverse attribute. Subgroup analysis revealed that female patients showed greater concern for “neat and clean attire of medical staff” than male patients （P＜0.001）； patients under 60 years of age demonstrated stronger demand for “providing treatment plan recommendations based on patients’ conditions” compared to patients aged 60 or above （P＝0.016）； those with below high school education placed greater emphasis on “providing guidance on medication precautions” compared to those with a high school education or above （P＝0.011）； patients with lower economic burdens exhibited stronger preferences for “neat and clean attire of medical staff ” （P＝0.002）. CONCLUSIONS The public awareness rate of pharmaceutical clinic services is considerably low； however， those who are aware of such services demonstrate significantly higher demand. The medication safety-related services and convenience-oriented demands should be prioritized in the development of pharmaceutical clinics. Moreover， the study also revealed that factors such as gender， age， educational level， and economic burdens exert significant influences on patients’ service demands.

Objective:To analyze the current status of global clinical trial for botulinum toxin (BTX) drugs, and to provide a reference for BTX drug research priorities and trends.Methods:All registered BTX drug-related clinical trials from the inception of the platforms until December 2024 were retrieved from the International Clinical Trials Registry Platform (ICTRP) and the Center for Drug Evaluation (CDE) Clinical Trial Registration and Information Disclosure Platform of the National Medical Products Administration of China (referred to as the CDE Platform). The data were statistically analyzed using Excel 2021. The analysis was conducted from aspects such as registration volume and annual trend, distribution of conducting countries, drug type, study type and recruitment situation, and indications.Results:A total of 2 053 clinical trials related to BTX were included. The total number of registered trials showed an increasing trend year by year. The country with the largest number of clinical trials was the United States, with 571 trials, while China ranked third with 190 trials. Among the drug formulations, the injection form accounted for the highest proportion (99.02%, 2 033/2 053). A few new formulations included topical ointments, nasal sprays, and eye drops. In terms of drug serotypes and sources, the wild-type BTX-A projects accounted for a relatively high proportion (97.86%, 2 009/2 053), and also included a few wild-type BTX-B, wild-type BTX-E, recombinant BTX-AB, and recombinant BTX-A projects. In terms of research types, 90.4% (1 856/2 053) were intervention studies, 87.5% (1 796/2 053) of the clinical trials did not restrict gender, 90.7% (1 862/2 053) of the clinical trials recruited subjects covering adults, and 9.3% (191/2 053) of the clinical trials only recruited minors. The research indications covered various disciplines, such as skin beauty, neurology, urology, orthopedics, and ophthalmology. In recent years, the types of diseases registered for clinical trials had expanded significantly on the basis of the originally approved indications.Conclusion:Innovative directions in BTX drug research, including BTX drugs of different serotypes, recombinant BTX based on recombinant gene technology, BTX formulations for non-injectable delivery, and innovative areas of clinical application, are driving its continued clinical research.

With the change of infectious disease incidence pattern and the development of related technologies, progresses have been made in the research of infectious disease epidemiology. In recent years, due to the change in the requirements of infectious disease prevention and control, the research focus has expanded from common infectious diseases to diseases which have been eliminated or might be eliminated, as well as emerging and re-emerging infectious diseases. Infectious disease data has been characterized by multiple sources and modalities. Along with the rapid development of pathogen detection methods, infectious disease surveillance has shifted from a single disease-targted one to a comprehensive one. Moreover, novel technologies such as multi-omics and artificial intelligence have been applied in infectious disease epidemiology research. The international cooperation in this field has become increasingly crucial, and the revision of the International Health Regulations and the negotiation of pandemic agreement will have a profound impact. In the future, infectious disease epidemiology research will develop with more powerful tools to improve its capabilities.

Ursodeoxycholic acid(UDCA)is a naturally occurring,low-toxicity,and hydrophilic bile acid(BA)in the human body that is converted by intestinal flora using primary BA.Solute carrier family 7 member 11(SLC7A11)functions to uptake extracellular cystine in exchange for glutamate,and is highly expressed in a variety of human cancers.Retroperitoneal liposarcoma(RLPS)refers to liposarcoma originating from the retroperitoneal area.Lipidomics analysis revealed that UDCA was one of the most significantly down-regulated metabolites in sera of RIPS patients compared with healthy subjects.The augmentation of UDCA concentration(≥25 μg/mL)demonstrated a suppressive effect on the proliferation of liposarcoma cells.[15N2]-cystine and[13Cs]-glutamine isotope tracing revealed that UDCA impairs cystine uptake and glutathione(GSH)synthesis.Mechanistically,UDCA binds to the cystine transporter SLC7A11 to inhibit cystine uptake and impair GSH de novo synthesis,leading to reactive oxygen species(ROS)accumulation and mitochondrial oxidative damage.Furthermore,UDCA can promote the anti-cancer effects of ferroptosis inducers(Erastin,RSL3),the murine double minute 2(MDM2)inhibitors(Nutlin 3a,RG7112),cyclin dependent kinase 4(CDK4)inhibitor(Abemaciclib),and glutaminase inhibitor(CB839).Together,UDCA functions as a cystine exchange factor that binds to SLC7A11 for antitumor activity,and SLC7A11 is not only a new transporter for BA but also a clinically applicable target for UDCA.More importantly,in combination with other antitumor chemotherapy or physiotherapy treatments,UDCA may provide effective and promising treatment strategies for RLPS or other types of tumors in a ROS-dependent manner.

Objective To establish a method for the simultaneous determination of 16 cephalosporin antibiotics of the fourth generation in whole blood by ultra-high performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS),including representative drugs such as cefalexin,cefuroxime axetil,cefetamet pivoxil,ceftizoxime,cefodizime,cefteram pivoxil,cefpodoxime proxetil,cefditoren pivoxil,cefminox sodium,cefoperazone,cefpirome,cefoxitin,cefamandole nafate,cefquinome sulfate,cefpiramide,and ceftiofur.Methods Whole blood was pretreated with acetonitrile for protein precipitation and then determined by ultra-high performance liquid chromatography-triple quadrupole mass spectrometry.The liquid phase used a Hypersil GOLD? C18 column(2.1 mm ×100 mm,1.9 μm).The organic phase was 0.1％formic acid methanol solution,and the aqueous phase was 0.1％formic acid aqueous solution(containing 10 mmol/mL ammonium formate)for gradient elution.Detection was performed in electrospray positive ionization mode with selected reaction monitoring(SRM).Results The 16 drugs showed good linearity within their respective concentration ranges,with R2 values all greater than 0.99.Limits of detection for cefminox sodium and cefpiramide were 50 and 20 ng/mL,respectively,and for the remaining 14 drugs were all lower than 5 ng/mL.The relative standard deviations(RSDs)of intra-day and inter-day precisions at four spiked concentrations for the 16 drugs were all no higher than 10％(n=5).Accuracy ranged within±15％for mosg drugs,except for cefamandole nafate,ceftiofur,and cefetamet pivoxil at the lower limit of quantification,which showed accuracy within±20％.Extraction recoveries exceeded 80％for all compounds.Conclusion This method has high detection sensitivity,rapid speed,and good repeatability for the simultaneously determination of 16 cephalosporin antibiotics in whole blood.

ObjectiveTo explore the clinical safety of Feilike Mixture （FLK） in the real world. MethodsThe safety of all children who received FLK from 29 institutions in 12 provinces between January 21，2021 and December 25，2021 was evaluated through prospective centralized surveillance and a nested case control study. ResultsA total of 3 035 juveniles were included. There were 29 research centers involved，which are distributed across 12 provinces，including one traditional Chinese medicine （TCM） hospital and 28 general hospitals. The average age among the juveniles was （4.77±3.56） years old，and the average weight was （21.81±12.97） kg. Among them，119 cases （3.92%） of juveniles had a history of allergies. Acute bronchitis was the main diagnosis for juveniles，with 1 656 cases （54.46%）. FLK was first used in 2 016 cases （66.43%），and 142 juvenile patients had special dosages，accounting for 4.68%. Among them，92 adverse drug reactions （ADRs） occurred，including 73 cases of gastrointestinal system disorders，10 cases of metabolic and nutritional disorders，eight cases of skin and subcutaneous tissue diseases，two cases of vascular and lymphatic disorders，and one case of systemic diseases and various reactions at the administration site. The manifestations of ADRs were mainly diarrhea，stool discoloration，and vomiting，and no serious ADRs occurred. The results of multi-factor analysis indicated that special dosages （the use of FLK）［odds ratio （OR） of 2.642， 95% confidence interval （CI） of 1.105-6.323］，combined administration： spleen aminopeptide （OR of 4.978， 95%CI of 1.200-20.655），and reason for combined administration： anti-infection （OR of 1.814， 95%CI of 1.071-3.075） were the risk factors for ADRs caused by FLK. Conclusion92 ADRs occurred among 3 035 juveniles using FLK. The incidence of ADRs caused by FLK was 3.03%，and the severity was mainly mild or moderate. Generally，the prognosis was favorable after symptomatic treatment such as drug withdrawal or dosage reduction，suggesting that FLK has good clinical safety.

Deep learning method can be used to automatically analyze electrocardiogram (ECG) data and rapidly implement arrhythmia classification, which provides significant clinical value for the early screening of arrhythmias. How to select arrhythmia features effectively under limited abnormal sample supervision is an urgent issue to address. This paper proposed an arrhythmia classification algorithm based on an adaptive multi-feature fusion network. The algorithm extracted RR interval features from ECG signals, employed one-dimensional convolutional neural network (1D-CNN) to extract time-domain deep features, employed Mel frequency cepstral coefficients (MFCC) and two-dimensional convolutional neural network (2D-CNN) to extract frequency-domain deep features. The features were fused using adaptive weighting strategy for arrhythmia classification. The paper used the arrhythmia database jointly developed by the Massachusetts Institute of Technology and Beth Israel Hospital (MIT-BIH) and evaluated the algorithm under the inter-patient paradigm. Experimental results demonstrated that the proposed algorithm achieved an average precision of 75.2%, an average recall of 70.1% and an average F ₁-score of 71.3%, demonstrating high classification accuracy and being able to provide algorithmic support for arrhythmia classification in wearable devices.
Humans ; Arrhythmias, Cardiac/diagnosis* ; Algorithms ; Electrocardiography/methods* ; Neural Networks, Computer ; Signal Processing, Computer-Assisted ; Deep Learning ; Classification Algorithms

Poly(ADP-ribosyl)ation (PARylation) is a specific form of post-translational modification (PTM) predominantly triggered by the activation of poly-ADP-ribose polymerase 1 (PARP1). However, the role and mechanism of PARylation in the advancement of acute kidney injury (AKI) remain undetermined. Here, we demonstrated the significant upregulation of PARP1 and its associated PARylation in murine models of AKI, consistent with renal biopsy findings in patients with AKI. This elevation in PARP1 expression might be attributed to trimethylation of histone H3 lysine 4 (H3K4me3). Furthermore, a reduction in PARylation levels mitigated renal dysfunction in the AKI mouse models. Mechanistically, liquid chromatography-mass spectrometry indicated that PARylation mainly occurred in receptor for activated C kinase 1 (RACK1), thereby facilitating its subsequent phosphorylation. Moreover, the phosphorylation of RACK1 enhanced its dimerization and accelerated the ubiquitination-mediated hypoxia inducible factor-1α (HIF-1α) degradation, thereby exacerbating kidney injury. Additionally, we identified a PARP1 proteolysis-targeting chimera (PROTAC), A19, as a PARP1 degrader that demonstrated superior protective effects against renal injury compared with PJ34, a previously identified PARP1 inhibitor. Collectively, both genetic and drug-based inhibition of PARylation mitigated kidney injury, indicating that the PARylated RACK1/HIF-1α axis could be a promising therapeutic target for AKI treatment.