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.

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.

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.

Autism Spectrum Disorder (ASD) is marked by early-onset neurodevelopmental anomalies, yet the temporal dynamics of genetic contributions to these processes remain insufficiently understood. This study aimed to elucidate the role of the Shank3 gene, known to be associated with monogenic causes of autism, in early developmental processes to inform the timing and mechanisms for potential interventions for ASD. Utilizing the Shank3B knockout (KO) mouse model, we examined Shank3 expression and its impact on neuronal maturation through Golgi staining for dendritic morphology and electrophysiological recordings to measure synaptic function in the anterior cingulate cortex (ACC) across different postnatal stages. Our longitudinal analysis revealed that, while Shank3B KO mice displayed normal neuronal morphology at one week postnatal, significant impairments in dendritic growth and synaptic activity emerged by two to three weeks. These findings highlight the critical developmental window during which Shank3 is essential for neuronal and synaptic maturation in the ACC.
Animals ; Nerve Tissue Proteins/metabolism* ; Mice, Knockout ; Dendrites/metabolism* ; Mice ; Synapses/metabolism* ; Gyrus Cinguli/metabolism* ; Male ; Mice, Inbred C57BL ; Autism Spectrum Disorder/genetics* ; Microfilament Proteins

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

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

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.