The current study aimed to clarify the roles of apolipoprotein A5 (ApoA5) and milk fat globule-epidermal growth factor 8 (Mfge8) in regulating myocardial lipid deposition and the regulatory relationship between them. The serum levels of ApoA5 and Mfge8 in obese and healthy people were compared, and the obesity mouse model induced by the high-fat diet (HFD) was established. In addition, primary cardiomyocytes were purified and identified from the hearts of suckling mice. The 0.8 mmol/L sodium palmitate treatment was used to establish the lipid deposition cardiomyocyte model in vitro. ApoA5-overexpressing adenovirus was used to observe its effects on cardiac function and lipids. The expressions of the fatty acid uptake-related molecules and Mfge8 on transcription or translation levels were detected. Co-immunoprecipitation was used to verify the interaction between ApoA5 and Mfge8 proteins. Immunofluorescence was used to observe the co-localization of Mfge8 protein with ApoA5 or lysosome-associated membrane protein 2 (LAMP2). Recombinant rMfge8 was added to cardiomyocytes to investigate the regulatory mechanism of ApoA5 on Mfge8. The results showed that participants in the simple obesity group had a significant decrease in serum ApoA5 levels (P < 0.05) and a significant increase in Mfge8 levels (P < 0.05) in comparison with the healthy control group. The adenovirus treatment successfully overexpressed ApoA5 in HFD-fed obese mice and palmitic acid-induced lipid deposition cardiomyocytes, respectively. ApoA5 reduced the weight of HFD-fed obese mice (P < 0.05), shortened left ventricular isovolumic relaxation time (IVRT), increased left ventricular ejection fraction (LVEF), and significantly reduced plasma levels of triglycerides (TG) and cholesterol (CHOL) (P < 0.05). In myocardial tissue and cardiomyocytes, the overexpression of ApoA5 significantly reduced the deposition of TG (P < 0.05), transcription of fatty acid translocase (FAT/CD36) (P < 0.05), fatty acid-binding protein (FABP) (P < 0.05), and fatty acid transport protein (FATP) (P < 0.05), and protein expression of Mfge8 (P < 0.05), while the transcription levels of Mfge8 were not significantly altered (P > 0.05). In vitro, the Mfge8 protein was captured using ApoA5 as bait protein, indicating a direct interaction between them. Overexpression of ApoA5 led to an increase in co-localization of Mfge8 with ApoA5 or LAMP2 in cardiomyocytes under lipid deposition status. On this basis, exogenous added recombinant rMfge8 counteracted the improvement of lipid deposition in cardiomyocytes by ApoA5. The above results indicate that the overexpression of ApoA5 can reduce fatty acid uptake in myocardial cells under lipid deposition status by regulating the content and cellular localization of Mfge8 protein, thereby significantly reducing myocardial lipid deposition and improving cardiac diastolic and systolic function.
Animals ; Humans ; Mice ; Myocytes, Cardiac/metabolism* ; Obesity/physiopathology* ; Male ; Apolipoprotein A-V/blood* ; Lipid Metabolism/physiology* ; Milk Proteins/blood* ; Myocardium/metabolism* ; Diet, High-Fat ; Antigens, Surface/physiology* ; Mice, Inbred C57BL ; Cells, Cultured ; Female

In China, the number of chronic pain patients has exceeded 300 million, making chronic pain the third major health problem after tumors and cardiovascular diseases. Particularly concerning is the gradual emergence of hypertension and chronic low back pain as public health problems that threaten public health and increase the global economic burden. Modern research shows that the incidence of coexisting hypertension is higher among patients with chronic low back pain. Additionally, evidence indicates that the use of NSAIDs for pain relief can have adverse effects on blood pressure, and some antihypertensive medications may trigger symptoms of low back pain. Thus, addressing chronic pain in hypertensive patients while stabilizing blood pressure is one of the important research questions in the modern treatment of hypertension among middle-aged and elderly individuals. From ancient to modern traditional Chinese medicine(TCM) theory, kidney deficiency has been regarded as the core pathogenesis of low back pain. Recent clinical practices and literature indicate that kidney deficiency plays a crucial role in the modern pathogenesis of hypertension. Both hypertension and chronic low back pain are closely associated with kidney deficiency in TCM theory, revealing a potential mechanism linking the two conditions. Combining the theories of " kidney-essence-marrow" and " nourishing water to moisten wood", a therapeutic strategy centered on tobifying kidney was proposed, including selecting single drugs with kidney-tonifying effects as well as compound formulations and elaborating modern research evidence. The aim is to achieve stable blood pressure control in hypertension patients with chronic low back pain while providing a new treatment perspective for chronic low back pain. This article systematically elaborates on the understanding of hypertension combined with chronic low back pain from both TCM and modern medicine, as well as the therapeutic strategy involving kidney-tonifying drugs, to offer useful references for clinical practice.
Humans ; Hypertension/complications* ; Low Back Pain/complications* ; Drugs, Chinese Herbal/therapeutic use* ; Kidney/drug effects* ; Medicine, Chinese Traditional ; Chronic Pain/drug therapy*

The chemical constituents of the petroleum ether extract derived from the 90% ethanol extract of Elephantopus scaber were investigated. By silica gel column chromatography, C_(18), MCI column chromatography and semi-preparative high performance liquid chromatography, ten compounds were isolated. Their structures were identified as 3β-hydroxy-6β,7β-epoxytaraxeran-14-ene(1), 3β-hydroxyolean-12-en-28-oic acid(2), D-friedoolean-14-ene-3β,7α-diol(3), 3β-hydroxy-11α-methoxyolean-12-ene(4), 3β-hydroxyolean-11,13(18)-diene(5), 11α-hydroxy-β-amyrin(6), betulinic acid(7), 3β-hydroxy-30-norlupan-20-one(8), 6-acetonylchelerythrine(9), and 4',5'-dehydrodiodictyonema A(10) by analysis of the 1D NMR, 2D NMR, MS, and IR spectral data. Among them, compound 1 was a new triterpene and other compounds except compounds 2 and 7 were isolated from this plant for the first time.
Triterpenes/isolation & purification* ; Drugs, Chinese Herbal/isolation & purification* ; Molecular Structure ; Asteraceae/chemistry* ; Chromatography, High Pressure Liquid ; Magnetic Resonance Spectroscopy

Early screening, diagnosis, and intervention for congenital muscular torticollis (CMT) in infants are crucial for improving clinical outcomes. However, in China, limited awareness of CMT among child healthcare institutions and caregivers, as well as inconsistent professional standards among rehabilitation personnel, pose significant challenges to the effective diagnosis and management of CMT. The "Physical therapy management of congenital muscular torticollis: a 2024 evidence-based clinical practice guideline from the American Physical Therapy Association Academy of Pediatric Physical Therapy" includes 17 action statements, primarily addressing the prevention, identification, assessment, and intervention of CMT. This guideline is expected to facilitate early detection of CMT in infants, enhance the treatment capabilities of physical therapists, and improve clinical outcomes. This article provides an interpretation of the guideline in the context of the current status of CMT diagnosis and management in China, aiming to offer a reference for improving the ability of primary child healthcare providers and physical therapists to recognize and manage CMTropriately.
Humans ; Torticollis/diagnosis* ; Physical Therapy Modalities ; Practice Guidelines as Topic ; Infant ; United States

The Animal Molecular Biology course is a crucial and foundational course for both Animal Medicine and Animal Science majors.Apart from teaching fundamental principles of molecular biology,the course provides updated applications of these principles in the field of animal science research.Im-portantly,it plays a fundamental role in cultivating students'research capabilities.With the rise of over-whelming information and their optimal utilization,the demand for integrating digital education with tradi-tional teaching methods is increasing.Based on the five years of teaching practice,this paper summarizes four highlights of the course:the construction of teaching resource,the restructuring of teaching syllabus,the adjustment of classroom teaching hours,and the improvement of assessment methodology.It focuses on Electronic-Learning"E(E-Learning)",offline classroom intensive teaching"C(Classroom)",and post-class extension to construct a blended teaching model that integrates Electronic-Learning and Class-room teaching,namely the"E+C"blended teaching model.Offline classroom teaching emphasizes the combination of theory and knowledge systems,while online Electronic-Learning mainly focuses on popular science and interesting aspects to stimulate students' interests and enthusiasm in learning.Over five years of practice,the"E+C"blended model has been proven to exert a good teaching effect.Students have reported significant gains from the course,with tightly connected and strongly complementary class-room teaching and E-Learning,which greatly aids in mastering professional knowledge.It also cultivates intrinsic motivation for learning and enhances the sense of accomplishment in acquiring knowledge,sig-nificantly improving teaching effectiveness.

The Animal Molecular Biology course is a crucial and foundational course for both Animal Medicine and Animal Science majors.Apart from teaching fundamental principles of molecular biology,the course provides updated applications of these principles in the field of animal science research.Im-portantly,it plays a fundamental role in cultivating students'research capabilities.With the rise of over-whelming information and their optimal utilization,the demand for integrating digital education with tradi-tional teaching methods is increasing.Based on the five years of teaching practice,this paper summarizes four highlights of the course:the construction of teaching resource,the restructuring of teaching syllabus,the adjustment of classroom teaching hours,and the improvement of assessment methodology.It focuses on Electronic-Learning"E(E-Learning)",offline classroom intensive teaching"C(Classroom)",and post-class extension to construct a blended teaching model that integrates Electronic-Learning and Class-room teaching,namely the"E+C"blended teaching model.Offline classroom teaching emphasizes the combination of theory and knowledge systems,while online Electronic-Learning mainly focuses on popular science and interesting aspects to stimulate students' interests and enthusiasm in learning.Over five years of practice,the"E+C"blended model has been proven to exert a good teaching effect.Students have reported significant gains from the course,with tightly connected and strongly complementary class-room teaching and E-Learning,which greatly aids in mastering professional knowledge.It also cultivates intrinsic motivation for learning and enhances the sense of accomplishment in acquiring knowledge,sig-nificantly improving teaching effectiveness.

Objective:To explore the clinical application value of convolutional neural network（CNN）based on deep learning in the automatic measurement of dynamic pelvic floor ultrasound video parameters and the diagnosis and classification of cystocele.Methods:A retrospective analysis was conducted on dynamic pelvic floor ultrasound videos from 398 postpartum women who underwent examinations at the First People's Hospital of Foshan between June 2020 and June 2022. The lowest point of the posterior bladder wall（PWB），urethral rotation angle（URA），and retrovesical angle（RVA）were manually measured by a senior radiologist（R1）and a junior radiologist（R2），and cystocele was classified according to the Green standard. The CNN model was employed to automatically extract the above parameters and to diagnose and classify cystocele. Using R1 measurements as a reference，intraclass correlation coefficient（ICC）was used to evaluate the consistency between the CNN model and R1，as well as between R2 and R1. The Kappa value was used to assess the agreement between the CNN model，R2，and R1 in the diagnosis and classification of cystocele. Additionally，the time consumption of the three measurement methods was compared.Results:The CNN model showed good consistency with R1 in measuring PWB and URA（ICC = 0.983，0.894），while its consistency in measuring RVA was moderate（ICC = 0.614）. The ICC between R2 and R1 in measuring PWB，URA，and RVA was 0.979，0.815，and 0.627，respectively. In the measurement of PWB and URA，the consistency between the CNN model and R1 was superior to that between R2 and R1. For cystocele diagnosis，the Kappa value between the CNN model and R1 was 0.924，which was higher than that between R2 and R1（0.904）. In cystocele classification，the Kappa value between the CNN model and R1 was 0.503，also higher than that between R2 and R1（0.426）. The CNN model processed a single video in 2.5（0.6）s，significantly faster than R1［59.9（16.9）s］and R2［56.8（11.2）s］（all P < 0.001）. Conclusions:The CNN model demonstrates high accuracy and efficiency in the measurement，diagnosis，and classification of cystocele，outperforming a junior radiologist and showing potential for clinical application.

Objective:To explore the clinical application value of convolutional neural network（CNN）based on deep learning in the automatic measurement of dynamic pelvic floor ultrasound video parameters and the diagnosis and classification of cystocele.Methods:A retrospective analysis was conducted on dynamic pelvic floor ultrasound videos from 398 postpartum women who underwent examinations at the First People's Hospital of Foshan between June 2020 and June 2022. The lowest point of the posterior bladder wall（PWB），urethral rotation angle（URA），and retrovesical angle（RVA）were manually measured by a senior radiologist（R1）and a junior radiologist（R2），and cystocele was classified according to the Green standard. The CNN model was employed to automatically extract the above parameters and to diagnose and classify cystocele. Using R1 measurements as a reference，intraclass correlation coefficient（ICC）was used to evaluate the consistency between the CNN model and R1，as well as between R2 and R1. The Kappa value was used to assess the agreement between the CNN model，R2，and R1 in the diagnosis and classification of cystocele. Additionally，the time consumption of the three measurement methods was compared.Results:The CNN model showed good consistency with R1 in measuring PWB and URA（ICC = 0.983，0.894），while its consistency in measuring RVA was moderate（ICC = 0.614）. The ICC between R2 and R1 in measuring PWB，URA，and RVA was 0.979，0.815，and 0.627，respectively. In the measurement of PWB and URA，the consistency between the CNN model and R1 was superior to that between R2 and R1. For cystocele diagnosis，the Kappa value between the CNN model and R1 was 0.924，which was higher than that between R2 and R1（0.904）. In cystocele classification，the Kappa value between the CNN model and R1 was 0.503，also higher than that between R2 and R1（0.426）. The CNN model processed a single video in 2.5（0.6）s，significantly faster than R1［59.9（16.9）s］and R2［56.8（11.2）s］（all P < 0.001）. Conclusions:The CNN model demonstrates high accuracy and efficiency in the measurement，diagnosis，and classification of cystocele，outperforming a junior radiologist and showing potential for clinical application.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

OBJECTIVE: To explore the immunological mechanisms underlying spermatogenetic malfunction in patients with non-obstructive azoospermia (NOA) based on bioinformatics and machine learning, and to screen out the key genes associated with spermatogenesis failure. METHODS: NOA-related datasets were obtained from the GEO database, and the differentially expressed genes identified by differential analysis and weighted gene co-expression network analysis (WGCNA). A model of spermatogenesis scoring was established for analysis of the immunological microenvironment and cell interaction networks related to spermatogenesis failure. The key genes were screened out by machine learning, followed by analysis of their correlation with T cells and macrophages. An NOA mouse model was constructed for validation of transcriptome sequencing. RESULTS: Seventy-five differentially expressed genes were identified for the establishment of the spermatogenesis scoring model. The low spermatogenesis score group showed a higher infiltration of the immune cells, with an increased proportion of T cells and macrophages and a correlation of cell interaction signals with immunity. SOX30, KCTD19, ASRGL1 and DRC7 were identified by machine learning as the key genes related to spermatogenesis, with down-regulated expressions in the NOA group, and their expression levels negatively correlated with the infiltration of T cells and macrophages. The accuracy of the spermatogenesis scoring and machine learning models, as well as the trend of the expression levels of the key genes, was successfully validated with the transcriptome sequencing data on the NOA mouse testis. CONCLUSION The development of NOA is closely associated with enhanced immunological microenvironment in the testis. T cells and macrophages may play important roles in spermatogenesis failure. SOX30, KCTD19, ASRGL1 and DRC7 are potential biomarkers for the diagnosis and treatment of NOA.
Male ; Azoospermia/genetics* ; Machine Learning ; Animals ; Computational Biology ; Mice ; Humans ; Spermatogenesis/genetics* ; Gene Expression Profiling ; Macrophages/immunology* ; Gene Regulatory Networks ; T-Lymphocytes/immunology* ; Transcriptome