This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

The prelimbic cortex (PL) plays a critical role in processing both the sensory and affective components of pain. However, the underlying molecular mechanisms remain poorly understood. In this study, we observed a reduction in hyperpolarization-activated cation current (I_h) in layer V pyramidal neurons of the contralateral PL in a mouse model of spared nerve injury (SNI). The expression of hyperpolarization-activated cyclic nucleotide-gated 2 (HCN2) channels was also decreased in the contralateral PL. Conversely, microinjection of fisetin, a partial agonist of HCN2, produced both analgesic and anxiolytic effects. Additionally, we found that cyclin-dependent kinase 5 (CDK5) was activated in the contralateral PL, where it formed a complex with HCN2 and phosphorylated its C-terminus. Knockdown of CDK5 restored HCN2 expression and alleviated both pain hypersensitivity and anxiety-like behaviors. Collectively, these results indicate that CDK5-mediated dysfunction of HCN2 in the PL underlies nerve injury-induced mechanical hypersensitivity and anxiety.
Animals ; Hyperpolarization-Activated Cyclic Nucleotide-Gated Channels/metabolism* ; Hyperalgesia/metabolism* ; Cyclin-Dependent Kinase 5/metabolism* ; Neuralgia/metabolism* ; Male ; Anxiety/metabolism* ; Mice ; Potassium Channels/metabolism* ; Mice, Inbred C57BL ; Disease Models, Animal ; Pyramidal Cells/metabolism*

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Grooming,as an evolutionarily conserved repetitive behavior,is common in various animals,including humans,and serves essential functions including,but not limited to,hygiene maintenance,thermoregulation,de-arousal,stress reduction,and social behaviors.In rodents,grooming involves a patterned and sequenced structure,known as the syntactic chain with four phases that comprise repeated stereotyped movements happening in a cephalocaudal progression style,beginning from the nose to the face,to the head,and finally ending with body licking.The context-dependent occurrence of grooming behavior indicates its adaptive significance.This review briefly summarizes the neural substrates responsible for rodent grooming behavior and explores its relevance in rodent models of neuropsychiatric disorders and neurodegenerative diseases with aberrant grooming phenotypes.We further emphasize the utility of rodent grooming as a reliable measure of repetitive behavior in neuropsychiatric models,holding promise for translational psychiatry.Herein,we mainly focus on rodent self-grooming.Allogrooming(grooming being applied on one animal by its conspecifics via licking or carefully nibbling)and heterogrooming(a form of grooming behavior directing towards another animal,which occurs in other contexts,such as maternal,sexual,aggressive,or social behaviors)are not covered due to space constraints.

Recent advancements in the field of medical artificial intelligence (AI) have led to the widespread adoption of foundational and large language models. This review paper explores their applications within medical AI, introducing a novel classification framework that categorizes them as disease-specific, general-domain, and multi-modal models. The paper also addresses key challenges such as data acquisition and augmentation, including issues related to data volume, annotation, multi-modal fusion, and privacy concerns. Additionally, it discusses the evaluation, validation, limitations, and regulation of medical AI models, emphasizing their transformative potential in healthcare. The importance of continuous improvement, data security, standardized evaluations, and collaborative approaches is highlighted to ensure the responsible and effective integration of AI into clinical applications.

Objective With the widespread of transcatheter aortic valve replacement(TAVR)in patients with severe symptomatic aortic stenosis(AS),the life-cycle management has become a major determinant of prognosis.Methods A total of 408 AS patients who underwent successfully TAVR from June 2021 to August 2023 were consecutively enrolled in Hospital Valve Intervention Center.Patients were assigned to the Usual Care(UC)group between June 2021 and October 2022,while patients were assigned to the Heart Multi-parameter Monitoring(HMM)group between November 2022 and August 2023.The primary endpoint was defined as composite endpoint within 6 months post-TAVR,including all-cause death,cardiovascular death,stroke/transient ischemic attack,conduction block,myocardial infarction,heart failure rehospitalization,and major bleeding events.Secondary endpoints were the time interval(in hours)from event occurrence to medical consultation or advice and patient satisfaction.Statistical analysis was performed using Kaplan-Meier and multivariable Cox proportional hazards models.Results The incidence of primary endpoint in HMM group was significantly lower than that in UC group(8.9％vs.17.7％,P=0.016),the driving event was the rate of diagnosis and recognition of conduction block.The average time intervals from event occurrence to receiving medical advice were 3.02 h in HHM group vs.97.09 h in UC group(P＜0.001).Using cardiac monitoring devices and smart healthcare platforms provided significant improving in patients long-term management(HR 0.439,95％CI 0.244-0.790,P=0.006).Conclusions The utilization of cardiac monitoring devices and smart healthcare platforms effectively alerted clinical events and improved postoperative quality of life during long-term management post TAVR.

The purpose of this study was to understand the prevalence of Neoehrlichia mikurensis in rodents in Yunnan commensal rodent plague foci.Lianghe Country,Mangshi City,and Mile City in Yunnan Province were chosen as sampling sites,where rodents were captured with dead-traps.The N.mikurensis groEL gene in rodent spleen samples was detected with nested PCR,and the positive products were sequenced with Sanger bidirectional assays.The infection rate of N.mikurensis a-mong plague foci,habitats,species,and sexes was compared with Chi-square tests or Fisher's exact probability method.Of 656 rodent spleen samples,12 N.mikurensis positive samples were detected in R.tanezumi,R.sladeni,N.confucianus,and B.bowersi.The positivity rate was 1.83％.No significant difference in the N.mikurensis positivity rate was observed a-mong plague foci,habitats,species,and sexes(P＞0.05).Genetic evolution analysis of the groEL gene indicated that the se-quence similarity of nucleic acid sequences in 12 positive samples was 99.5％-100％,and the nucleic acid sequences of N.mikurensis were in the same branch,belonging to cluster Ⅳ.Thus,four species of rodents were found to have low frequency infection with N.mikurensis in Yunnan commensal rodent plague foci.

Platelets have long been recognized as key players in hemostasis and thrombosis; however, there is growing evidence that they are also involved in cancer. Preclinical and clinical studies have shown that platelets can promote tumorigenesis and metastasis through various crosstalks between platelets and cancer cells. Platelets play an active role in all stages of tumorigenesis, including tumor growth, tumor cell extravasation, and metastasis. In addition, thrombocytosis in cancer patients is associated with poor patient survival. Platelets are also well-placed to coordinate local and distant tumor-host interactions due to the a- bundance of microparticles and exosomes. Therefore, antitumor drugs targeting platelets have great development and application prospects. The following will review the research progress of anti-tumor drugs targeting platelets.

Objective:This study investigated the efficacy and safety of denosumab (DENOS) versus zoledronic acid (ZOL) in the bone disease treatment of newly diagnosed multiple myeloma.Methods:The clinical data of 80 patients with myeloma bone disease (MBD) at the Fifth Medical Center of PLA General Hospital between March 1, 2021 and June 30, 2023 were retrospectively reviewed. Eighteen patients with severe renal impairment (SRI, endogenous creatinine clearance rate<30 ml/min) were treated with DENOS, and 62 non-SRI patients were divided into DENOS (30 patients) and ZOL group (32 patients) .Results:Hypocalcemia was observed in 26 (33%) patients, and 22 patients developed hypocalcemia during the first treatment course. The incidence of hypocalcemia in the non-SRI patients of DENOS group was higher than that in the ZOL group [20% (6/30) vs 13% (4/32), P=0.028]. The incidence of hypocalcemia in SRI was 89% (16/18). Multivariate logistic regression analysis revealed that endogenous creatinine clearance rate<30 ml/min was significantly associated with hypocalcemia after DENOS administration ( P<0.001). After 1 month of antiresorptive (AR) drug application, the decrease in the serum β-C-terminal cross-linked carboxy-telopeptide of collagen type I concentrations of SRI and non-SRI patients in the DENOS group were significantly higher than that in the ZOL group (68% vs 59% vs 27%, P<0.001). The increase in serum procollagen type Ⅰ N-terminal propeptide concentrations of patients with or without SRI in the DENOS group were significantly higher than that in the ZOL group (34% vs 20% vs 11%, P<0.05). The level of intact parathyroid hormone in each group increased after AR drug treatment. None of the patients developed osteonecrosis of the jaw and renal adverse events, and no statistically significant differences in the overall response rate, complete remission and stringent complete remission rates were found among the groups ( P>0.05), and the median PFS and OS time were not reached ( P>0.05) . Conclusions:In the treatment of MBD, DENOS minimizes nephrotoxicity and has strong AR effect. Hypocalcemia is a common adverse event but is usually mild or moderate and manageable.