BACKGROUND: Renal osteodystrophy (ROD) is a skeletal pathology associated with chronic kidney disease-mineral and bone disorder (CKD-MBD) that is characterized by aberrant bone mineralization and remodeling. ROD increases the risk of fracture and mortality in CKD patients. The underlying mechanisms of ROD remain elusive, partially due to the absence of an appropriate animal model. To address this gap, we established a stable mouse model of ROD using an optimized adenine-enriched diet and conducted exploratory analyses through ribonucleic acid sequencing (RNA-seq). METHODS: Eight-week-old male C57BL/6J mice were randomly allocated into three groups: control group ( n = 5), adenine and high-phosphate (HP) diet group ( n = 20), and the optimized adenine-containing diet group ( n = 20) for 12 weeks. We assessed the skeletal characteristics of model mice through blood biochemistry, microcomputed tomography (micro-CT), and bone histomorphometry. RNA-seq was utilized to profile gene expression changes of ROD. We elucidated the functions of differentially expressed genes (DEGs) using gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and gene set enrichment analysis (GSEA). DEGs were validated via quantitative real-time polymerase chain reaction (qRT-PCR). RESULTS: By the fifth week, adenine followed by an HP diet induced rapid weight loss and high mortality rates in the mouse group, precluding further model development. Mice with optimized adenine diet-induced ROD displayed significant abnormalities in serum creatinine and blood urea nitrogen levels, accompanied by pronounced hyperparathyroidism and hyperphosphatemia. The femur bone mineral density (BMD) of the model mice was lower than that of control mice, with substantial bone loss and cortical porosity. ROD mice exhibited substantial bone turnover with an increase in osteoblast and osteoclast markers. Transcriptomic profiling revealed 1907 genes with upregulated expression and 723 genes with downregulated expression in the femurs of ROD mice relative to those of control mice. Pathway analyses indicated significant enrichment of upregulated genes in the sphingolipid metabolism pathway. The significant upregulation of alkaline ceramidase 1 ( Acer1 ), alkaline ceramidase 2 ( Acer2 ), prosaposin-like 1 ( Psapl1 ), adenosine A1 receptor ( Adora1 ), and sphingosine-1-phosphate receptor 5 ( S1pr5 ) were successfully validated in mouse femurs by qRT-PCR. CONCLUSIONS Optimized adenine diet mouse model may be a valuable proxy for studying ROD. RNA-seq analysis revealed that the sphingolipid metabolism pathway is likely a key player in ROD pathogenesis, thereby providing new avenues for therapeutic intervention.
Animals ; Mice ; Chronic Kidney Disease-Mineral and Bone Disorder/genetics* ; Male ; Disease Models, Animal ; Mice, Inbred C57BL ; Sphingolipids/metabolism* ; Transcriptome/genetics* ; Signal Transduction/genetics* ; X-Ray Microtomography ; Adenine

Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial intelligence (AI), particularly the utilization of deep learning (DL) algorithms, has brought about substantial progress in assisting the diagnosis, treatment, and prognosis prediction of PCa. The introduction of the foundation model has revolutionized the application of AI in medical treatment and facilitated its integration into clinical practice. This review emphasizes the clinical application of AI in PCa by discussing recent advancements from both pathological and imaging perspectives. Furthermore, it explores the current challenges faced by AI in clinical applications while also considering future developments, aiming to provide a valuable point of reference for the integration of AI and clinical applications.
Humans ; Prostatic Neoplasms/diagnosis* ; Male ; Artificial Intelligence ; Deep Learning ; Prognosis

In recent years, the ongoing development of transcranial electrical stimulation (TES) and transcranial magnetic stimulation (TMS) has demonstrated significant potential in the treatment and rehabilitation of various brain diseases. In particular, the combined application of TES and TMS has shown considerable clinical value due to their potential synergistic effects. This paper first systematically reviews the mechanisms underlying TES and TMS, highlighting their respective advantages and limitations. Subsequently, the potential mechanisms of transcranial electromagnetic combined stimulation are explored, with a particular focus on three combined stimulation protocols: Repetitive TMS (rTMS) with transcranial direct current stimulation (tDCS), rTMS with transcranial alternating current stimulation (tACS), and theta burst TMS (TBS) with tACS, as well as their clinical applications in brain diseases. Finally, the paper analyzes the key challenges in transcranial electromagnetic combined stimulation research and outlines its future development directions. The aim of this paper is to provide a reference for the optimization and application of transcranial electromagnetic combined stimulation schemes in the treatment and rehabilitation of brain diseases.
Humans ; Transcranial Magnetic Stimulation/methods* ; Transcranial Direct Current Stimulation/methods* ; Brain Diseases/therapy*

[This corrects the article DOI: 10.1016/j.apsb.2022.05.019.].

Early-stage treatment of malignant tumors has a significant effect on improving the prognosis. In ASCO and ESMO 2024, several important advancements have been made in the field of systemic therapy for early-stage breast cancer, particularly in the diversification of treatment plans and the individualization of strategies for different molecular subtypes of breast cancer. The importance of adjuvant endocrine therapy (AET) has been highlighted on treating hormone receptor positive/human epidermal growth factor receptor 2 negative early breast cancer.The adjuvant therapy with Cyclin-dependent kinase 4/6 inhibitor (CDK4/6i) has been proven successful in treating HR+/HER2- early breast cancer. Neoadjuvant immunotherapy targeting early triple positive breast cancer (TNBC) has shown unique advantages. The possibility of having down-grade chemotherapy safely in treating HR+/HER2+ stage breast cancer has been explored.

Objective:To develop a deep learning-based segmentation model MT-UNet to automatically segment bone metastases and benign bone lesions in bone scintigraphy with SPECT/CT.Methods:A total of 93 patients (48 males and 45 females, age 28-84 years) who underwent bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from June 2023 to December 2023 were enrolled retrospectively in this study, with a total of 184 bone lesions (94 benign lesions and 90 metastatic tumors). The MT-UNet was employed to segment bone lesions in SPECT, CT and SPECT/CT images respectively. Comparative analysis with 8 segmentation models was performed. The training set and validation set were divided by using 5-fold cross-validation and transfer learning was introduced to further enhance the robustness of the model. An additional cohort of 22 patients (15 males and 7 females, age 37-87 years) who received bone SPECT/CT in the Department of Nuclear Medicine, General Hospital of Northern Theater Command from April 2023 to May 2023 were included, comprising 40 bone lesions (22 benign lesions and 18 metastatic tumors) as the test set of MT-UNet. Segmentation performance of different models was assessed using accuracy, sensitivity, specificity, AUC, intersection over union and Dice similarity coefficient (DSC). Delong test was used to compare the segmentation efficacy among different models in the test set.Results:In the validation set, MT-UNet demonstrated DSC of 0.940, 0.962, and 0.963 for SPECT, CT, and SPECT/CT bone lesion segmentation, respectively, which were outperformed other models. Following transfer learning implementation, the SPECT/CT model′s DSC was improved to 0.984. In the test set, MT-UNet maintained comparable segmentation performance to the validation set, with significant AUC differences among the three models ( Z values: from -15.42 to -9.27, all P<0.01). Compared with conventional image interpretation, MT-UNet-based segmentation reduced physician interpretation time from 164min to 102min. Conclusion:MT-UNet has shown good performance in automatic segmentation of bone metastases and benign bone lesions, and is expected to become an important part of SPECT/CT image intelligent diagnosis system for bone metastases.

OBJECTIVE To construct a classification prediction model for vancomycin blood concentration， and to optimize its precision dosing strategies. METHODS Patient records meeting inclusion criteria were extracted from the Medical Information Mart for Intensive Care database. Following data cleaning and preprocessing， a final cohort of 9 902 patient was analyzed. Feature selection was performed through correlation analysis and the Boruta feature selection algorithm. Vancomycin blood concentrations were discretized into three categories based on clinical therapeutic windows： low （＜10 μg/mL）， intermediate （10-20 μg/mL）， and high （≥20 μg/mL）. Six machine learning algorithms were employed to construct classification models： tabular prior-data fitted network （TabPFN）， logistic regression （LR）， random forest （RF）， extreme gradient boosting （XGBoost）， support vector machine （SVM）， K-nearest neighbors （KNN）. Model performance was evaluated using 10-fold cross-validation （10-CV）， with primary metrics including： accuracy， balanced accuracy， precision macro， recall macro， macro F1， area under the receiver operating characteristic curve （OvR-AUC）. Shapley Additive Explanations （SHAP） was adopted to analyze the direction and magnitude of the impact that different features had on the model’s predictive outcomes. RESULTS The results showed that the RF and TabPFN models performed the best （with accuracy of 0.741 4 and 0.737 7， and OvR-AUC of 0.907 0 and 0.895 8， respectively）. XGBoost model exhibited moderate performance， while LR， SVM， and KNN models demonstrated relatively poor performance. Confusion matrix heatmap analysis revealed that both RF and TabPFN achieved higher accuracy in predicting high- concentration cases but exhibited slightly lower performance in the low and medium concentration categories. Bootstrap with 10-CV revealed that the RF model demonstrated stable performance across various evaluation metrics （accuracy： 0.741 4； balanced accuracy： 0.740 3； precision macro： 0.732 1； recall macro： 0.736 0； macro F1： 0.736 0； OvR-AUC： 0.907 0）， indicating good classification performance and generalization ability. SHAP analysis revealed that creatinine， urea nitrogen， daily cumulative dose and administration frequency of vancomycin， which were key predictors， had a significant impact on the prediction results. CONCLUSIONS RF and TabPFN models demonstrate certain advantages in the classification prediction of vancomycin trough blood concentrations； however， their performance in the low to moderate concentration categories still requires improvement.

Objective: To investigate the status of salt-restriction spoons use among residents in Zhejiang Province, so as to provide evidence for optimizing salt-reduction intervention strategies and preventing chronic disease. Methods: Residents aged 18-69 from five counties (cities/districts) in Zhejiang Province were selected using a multi-stage stratified random sampling method. Demographic characteristics, dietary habits, and salt-restriction spoons use were collected using questionnaires. The rate of salt-restriction spoons use and correct rate of salt-restriction spoons use were analyzed. Factors affecting salt-restriction spoons use among residents were analyzed by multivariable logistic regression model. Results: Totally 7 601 questionnaires were allocated, and 7 509 valid questionnaires were recovered, with an effective recovery rate of 98.79%. The respondents included 3 744 males (49.86%) and 3 765 females (50.14%). The mean age was (44.81±14.03) years. The rate of salt-restriction spoons use was 11.97%, the correct rate of salt-restriction spoon use was 52.73%. Multivariable logistic regression analysis showed that rural (OR=0.851, 95%CI: 0.731-0.991), education level of primary school and below (illiterate or semi-literate, OR=0.269, 95%CI: 0.172-0.420; primary school, OR=0.595, 95%CI: 0.436-0.811), and excessive dietary salt intake (OR=0.718, 95%CI: 0.559-0.922) were inhibiting factors for salt-restriction spoons use among residents; physical exercise (OR=1.581, 95%CI: 1.362-1.836) and received health education on a low-salt diet (OR=2.082, 95%CI: 1.790-2.421) were promoting factors for salt-restriction spoons use among residents. Conclusions The rate of salt-restriction spoons use among residents in Zhejiang Province was relatively low, primarily influenced by region, educational level, physical activity, dietary salt intake, and health education on a low-salt diet. It is recommended that propose a multi-component intervention strategy centered on skill enhancement and health education, delivered through progressive staged implementation, to promote sustained adoption of salt-restriction spoons among residents.

Objective: To investigate the current status and influencing factors for cognitive frailty among the elderly in community, so as to provide the evidence for early identification and prevention of cognitive frailty among the elderly. Methods: Residents aged 60 years and above with local household registration from 11 counties (cities, districts) in Zhejiang Province from 2021 to 2023 were selected as study participants using a multistage random sampling method. Demographic information, lifestyle, and health status were collected through questionnaire surveys. Depressive symptoms were assessed using the Patient Health Questionnaire. Cognitive frailty was evaluated using the FRAIL Scale and the Mini-Mental State Examination. Factors affecting cognitive frailty among the elderly in community were identified using a multivariable logistic regression model. Results: A total of 16 613 individuals were surveyed, including 7 465 males (44.93%) and 9 148 females (55.07%). The average age was (70.97±7.29) years. A total of 784 individuals were detected with depressive symptoms, with a detection rate of 4.72%. A total of 724 individuals were detected with cognitive frailty, with a detection rate of 4.36%. Multivariable logistic regression analysis showed that females (OR=1.419, 95%CI: 1.179-1.708), aged ≥70 years (70-<80 years old, OR=1.869, 95%CI: 1.490-2.345; ≥80 years old, OR=5.017, 95%CI: 3.935-6.398), without a spouse (OR=1.495, 95%CI: 1.234-1.810), sedentary (OR=2.420, 95%CI: 1.829-3.202), chronic diseases (1 type, OR=1.456, 95%CI: 1.175-1.804; ≥2 types, OR=1.639, 95%CI: 1.314-2.045), and depressive symptoms (OR=4.191, 95%CI: 3.361-5.225) were associated with a higher risk of cognitive frailty among the elderly in community. Conversely, a lower risk of cognitive frailty was seen among the elderly in community who had primary school or above (primary school, OR=0.512, 95%CI: 0.389-0.676; junior high school or above, OR=0.464, 95%CI: 0.354-0.608), engaged in physical exercise (OR=0.396, 95%CI: 0.291-0.539), and were reported average or good self-rated health status (average, OR=0.641, 95%CI: 0.475-0.866; good, OR=0.150, 95%CI: 0.109-0.208). Conclusions The detection rate of cognitive frailty among the elderly in community is relatively low and is influenced by demographic factors such as gender, age, education level, as well as lifestyle like sedentary and physical exercise, and health status. It is recommended to reduce the risk of cognitive frailty among the elderly through multidimensional interventions, including health education, promotion of healthy lifestyles, and enhanced mental health support.

OBJECTIVE: To observe the clinical efficacy of acupuncture combined with thunder-fire moxibustion in treating low back pain with cold-damp. METHODS: Seventy-two patients of low back pain with cold-damp were randomly divided into an observation group (36 cases, 1 case was eliminated) and a control group (36 cases, 1 case dropped out). The control group received acupuncture at Jizhong (GV6), Yaoyangguan (GV3), ashi points, bilateral Shenshu (BL23), Dachangshu (BL25), and Weizhong (BL40) for 30 min daily. The observation group was treated with thunder-fire moxibustion in addition to the same acupuncture regimen as the control group, once daily. Both groups were treated for 6 consecutive days followed by one rest day, for a total duration of 4 weeks. The visual analog scale (VAS) score, Oswestry disability index (ODI) score, Japanese Orthopedic Association (JOA) score, present pain intensity (PPI) score, and serum levels of β-endorphin (β-EP), 5-hydroxytryp tamin (5-HT), and substance P (SP) were compared before and after treatment, and the clinical efficacy was also compared between the two groups. RESULTS: Compared before treatment, the VAS scores, ODI scores, PPI scores, and serum levels of 5-HT and SP were decreased (P<0.01), while JOA scores and serum levels of β-EP were increased (P<0.01) in both groups after treatment. The observation group showed lower VAS, ODI, and PPI scores and serum levels of 5-HT and SP than those in the control group (P<0.05), as well as higher JOA score and serum level of β-EP (P<0.05). The total effective rate in the observation group was 94.3% (33/35), higher than 82.9% (29/35) in the control group (P<0.05). CONCLUSION Acupuncture combined with thunder-fire moxibustion could effectively alleviate pain and improve lumbar function in patients of low back pain with cold-damp, possibly by regulating β-EP, 5-HT, and SP levels.
Humans ; Moxibustion ; Low Back Pain/blood* ; Male ; Female ; Adult ; Middle Aged ; Acupuncture Therapy ; Acupuncture Points ; Treatment Outcome ; Combined Modality Therapy ; beta-Endorphin/blood* ; Young Adult ; Aged