19 cinnamamide/ester-triazole compounds were designed, synthesized and evaluated for their anti-Alzheimer's disease (AD) activity. Among them, compound 4f displayed excellent anti-β-amyloid protein (Aβ)-mediated cytotoxicity (EC₅₀ = 2.03 ± 2.45 μmol·L^-1) in APPswe cells and acetylcholinesterase inhibiton (IC₅₀ = 4.88 ± 4.70 μmol·L^-1). Further study indicated that, at dosages of (1, 5 and 25 mg·kg^-1), compound 4f was effective in improving spatial learning and memory deficits in Aβ_1-42-impaired mice, which was achieved by promoting the nonamyloidogenic signaling and inhibiting the amyloidogenic pathway, along with the suppression of Aβ-induced Tau phosphorylation. All animal experiments in this study were approved by the Experimental Animal Care and Use Committee of the Institute of Medicinal Biotechnology (IMB-20220908D701). In conclusion, compound 4f holds promise as a lead candidate for AD treatment, and the present study lays the foundation for its subsequent development.

Objective To identify the independent predictors of programmed death-1 (PD-1) inhibitor-related endocrine adverse events and construct a clinically usable risk prediction model. Methods A total of 302 patients with solid tumors treated with PD-1 inhibitors were retrospectively enrolled. According to the presence or absence of endocrine immune-related adverse events (irAEs), the patients were divided into case group and control group. The clinical and laboratory indexes were compared between the two groups. Multivariable logistic regression was used to confirm independent predictors of endocrine irAEs. The nomogram was constructed, while the receiver operating characteristic (ROC) curve was used to test the prediction performance of the model. Results The overall incidence of endocrine irAEs was 21.9% (66/302), and the incidence of hypothyroidism was 19.5% (59/302). The age, PD-1 inhibitors, free thyroxine, thyroid peroxidase antibody (TPOAb), thyroglobulin, amylase, lymphocyte subset CD3 expression were statistically different between the two groups (P＜0.05). Multivariable logistic regression showed that higher expression of lymphocyte subset CD3 was a protective factor to prevent endocrine irAEs occurrence (P＝0.004), while age＜60 years, higher TPOAb and use of pembrolizumab were independent risk factors of endocrine irAEs (P＜0.05). The nomogram model thus constructed, and when the threshold probability of the model exceeded 0.1, its net benefit was higher. ROC curve showed that the AUC of the model to predict endocrine irAEs was 0.760. The prediction result of the model was highly consistent with the actual result. Conclusions The age, type of PD-1 inhibitor, baseline TPOAb level, and baseline CD3 expression can independently predict endocrine irAEs occurrence or not. The nomogram model based on this model has good predictive efficiency, which can provide reference for early identification of high-risk patients and immunotherapy management.

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique

This study was aimed at identifying the pathogenic bacteria responsible for the death of a young tiger at the Fujian Meihua Mountain South China Tiger Breeding Research Institute.Tissue samples from the lungs,liver,and intestines of the deceased tiger were collected,and the bacteria were cultured inasterile environment.The bacterial strains were characterized according to their morphological and molecular biological properties,including assessment of virulence genes and antibiotic resistance genes,mouse lethality tests,and antibiotic susceptibility evaluations.A predominant bacterial strain isolated from the liver of the deceased tiger was identified as enterotoxigenic Escherichia coli(ETEC)strain Tiger22513F.Phylogenetic analysis of the 16S rRNA gene revealed that the Tiger22513F strain exhibited close genetic similarity to the reference strain ETEC(MF919609.1),with 99.9%nucleotide similarity,and resided on the same evolutionary branch.The Tiger22513F strain contained 11 antibiotic resistance genes(tetA,sul1,sul3,cmlA,floR,blaTEM,blaSHV,blaCMY-2,qnrA,qnrS,and qnrD)along with five virulence genes(VT1,fyuA,tsh,iucD,and ST).Mouse lethality tests indicated significant pathogenicity toward mice,affecting primarily the lungs,liver,and intestines.Antibiotic susceptibility testing demonstrated that this strain exhibited resistance to various classes of beta-lactam antibiotics,as well as quinolones and aminoglycosides.This investigation successfully isolated a multi-drug resistant enterotoxigenic Escherichia coli strain with pronounced pathogenicity from the liver of a deceased tiger;thus providing valuable scientific insights for clinical diagnosis,as well as prevention and control measures,against ETEC infections in South China tigers.

This study was aimed at identifying the pathogenic bacteria responsible for the death of a young tiger at the Fujian Meihua Mountain South China Tiger Breeding Research Institute.Tissue samples from the lungs,liver,and intestines of the deceased tiger were collected,and the bacteria were cultured inasterile environment.The bacterial strains were characterized according to their morphological and molecular biological properties,including assessment of virulence genes and antibiotic resistance genes,mouse lethality tests,and antibiotic susceptibility evaluations.A predominant bacterial strain isolated from the liver of the deceased tiger was identified as enterotoxigenic Escherichia coli(ETEC)strain Tiger22513F.Phylogenetic analysis of the 16S rRNA gene revealed that the Tiger22513F strain exhibited close genetic similarity to the reference strain ETEC(MF919609.1),with 99.9%nucleotide similarity,and resided on the same evolutionary branch.The Tiger22513F strain contained 11 antibiotic resistance genes(tetA,sul1,sul3,cmlA,floR,blaTEM,blaSHV,blaCMY-2,qnrA,qnrS,and qnrD)along with five virulence genes(VT1,fyuA,tsh,iucD,and ST).Mouse lethality tests indicated significant pathogenicity toward mice,affecting primarily the lungs,liver,and intestines.Antibiotic susceptibility testing demonstrated that this strain exhibited resistance to various classes of beta-lactam antibiotics,as well as quinolones and aminoglycosides.This investigation successfully isolated a multi-drug resistant enterotoxigenic Escherichia coli strain with pronounced pathogenicity from the liver of a deceased tiger;thus providing valuable scientific insights for clinical diagnosis,as well as prevention and control measures,against ETEC infections in South China tigers.

Objective:This study aims to develop a validated instrument for assessing the degree of integration perceived by patients in the services provided by general practitioner(GP)teams,and to evaluate the current state of integrated medical-prevention services.Methods:The survey tool was initially created through a review of existing literature and semi-structured interviews.It was subsequently refined and enhanced following consultations with experts.The utility of the instrument was confirmed through empirical research,which also facilitated an analysis of the status quo regarding the integration of medical and prevention services.Results:The devised instrument encompasses 18 items distributed across six dimensions:service comprehensiveness,service continuity,depth of service,continuity of relationship,patient-centricity,and service coordination.The cumulative score reflecting patients'perception of the integration level in GP teams'medical-prevention services was 54.30±12.45.Conclusion:The survey instrument developed in this research is characterized by its rationality,novelty,and practical relevance.It offers a patient-centered perspective for assessing the quality of integrated medical and prevention services for primary chronic diseases.While the overall perception of integration among patients is positive,there is a notable deficiency in the depth of services provided.There is a need for optimization of the service process,clarification of the service path,refinement of service management,and development of an integrated incentive mechanism for medical and preventive care,aiming for a deeper integration between medical services and preventive care.

OBJECTIVE: To observe the effects of moxibustion at Yongquan（KI 1） on the cognitive function and lower limb motor function in patients with post-stroke cognitive impairment of kidney essence deficiency. METHODS: Eighty-four patients with post-stroke cognitive impairment of kidney essence deficiency were randomly divided into an observation group（42 cases，1 case dropped off）and a control group（42 cases，1 case dropped off）.The control group was treated with medication，electroacupuncture，rehabilitation training and repetitive transcranial magnetic stimulation（rTMS）；on the basis of the treatment as the control group，moxibustion at bilateral Yongquan（KI 1）was adopted in the observation group.Both groups were treated once a day，5 days a week with 2-day interval，4 weeks were required. The Montreal cognitive assessment (MoCA) score, mini-mental state examination (MMSE) score, Fugl-Meyer assessment-lower extremity (FMA-LE) score, Berg balance scale (BBS) score, functional independence measure (FIM) score, modified fall efficacy scale (MFES) score and scale for the differentiation of syndromes of vascular dementia (SDSVD) score before and after treatment were observed in the two groups. RESULTS: After treatment，the MoCA, MMSE, FMA-LE, BBS, FIM and MFES scores were higher than those before treatment in both groups (P<0.05), and the scores in the observation group were higher than those in the control group (P<0.05). After treatment，the SDSVD scores were lower than those before treatment in both groups (P< 0.05), and the SDSVD score in the observation group was lower than that in the control group (P< 0.05). CONCLUSION Moxibustion at Yongquan（KI 1） can improve the cognitive function and motor and balance function of lower limbs in patients with post-stroke cognitive impairment of kidney essence deficiency，reduce the risk of fall and improve the quality of life.
Humans ; Cognition ; Cognitive Dysfunction/therapy* ; Dementia, Vascular ; Kidney ; Lower Extremity ; Moxibustion ; Quality of Life ; Stroke/complications*

Humans ; Child ; Lymphoma, Large-Cell, Anaplastic ; Neoplasm Recurrence, Local ; Prognosis ; Hodgkin Disease

Humans ; Encephalitis

Objective:To investigate the efficacy of a machine learning model based on radiomics of brain lesions on T 2WI in differentiating multiple sclerosis (MS) from neuromyelitis optica spectrum disorders (NMOSD). Methods:Totally 223 MS and NMOSD patients who were treated from January 2009 to September 2018 in Beijing Tiantan Hospital Affiliated to Capital Medical University, Donghu Branch of the First Affiliated Hospital of Nanchang University, Tianjin Medical University General Hospital, and Xuanwu Hospital of Capital Medical University were analyzed retrospectively, and according to the proportion of 7∶3, 223 patients were completely randomly divided into training set (156 cases) and test set (67 cases). A total of 74 patients with MS and NMOSD who were treated in Huashan Hospital Affiliated to Fudan University and China-Japan Friendship Hospital of Jilin University from January 2009 to September 2018 and in Xianghu Branch of the First Affiliated Hospital of Nanchang University from March 2020 to September 2021 were collected as an independent external validation set. All patients underwent brain cross-sectional MR T 2WI, radiomics features were extracted from T 2WI, and features were selected by max-relevance and min-redundancy and least absolute shrinkage and selection operator algorithms. Then various machine learning classifier models (logistic regression, decision tree, AdaBoost, random forest or support vector machine) were constructed to differentiate MS from NMOSD. The area under curve (AUC) of receiver operating characteristics was used to evaluate the performance of each classifier model in the training set, test set and external validation set. Results:Based on multi-center T 2WI, a total of 11 radiomics features related to the discrimination between MS and NMOSD were extracted and classifier models were constructed. Among them, the random forest model had the best efficiency in distinguishing MS from NMOSD, and its AUC values for distinguishing MS from NMOSD in the training set, test set and external validation set were 1.000, 0.944 and 0.902, with specificity of 100%, 76.9% and 86.0%, and sensitivity of 100%, 92.1% and 79.7%, respectively. Conclusion:The random forest model based on the radiomic features of T 2WI of brain lesions can effectively distinguish MS from NMOSD.