Electromagnetic fields can regulate the fundamental biological processes involved in bone remodeling. As a non-invasive physical therapy, electromagnetic fields with specific parameters have demonstrated therapeutic effects on bone remodeling diseases, such as fractures and osteoporosis. Electromagnetic fields can be generated by the movement of charged particles or induced by varying currents. Based on whether the strength and direction of the electric field change over time, electromagnetic fields can be classified into static and time-varying fields. The treatment of bone remodeling diseases with static magnetic fields primarily focuses on fractures, often using magnetic splints to immobilize the fracture site while studying the effects of static magnetic fields on bone healing. However, there has been relatively little research on the prevention and treatment of osteoporosis using static magnetic fields. Pulsed electromagnetic fields, a type of time-varying field, have been widely used in clinical studies for treating fractures, osteoporosis, and non-union. However, current clinical applications are limited to low-frequency, and research on the relationship between frequency and biological effects remains insufficient. We believe that different types of electromagnetic fields acting on bone can induce various “secondary physical quantities”, such as magnetism, force, electricity, acoustics, and thermal energy, which can stimulate bone cells either individually or simultaneously. Bone cells possess specific electromagnetic properties, and in a static magnetic field, the presence of a magnetic field gradient can exert a certain magnetism on the bone tissue, leading to observable effects. In a time-varying magnetic field, the charged particles within the bone experience varying Lorentz forces, causing vibrations and generating acoustic effects. Additionally, as the frequency of the time-varying field increases, induced currents or potentials can be generated within the bone, leading to electrical effects. When the frequency and power exceed a certain threshold, electromagnetic energy can be converted into thermal energy, producing thermal effects. In summary, external electromagnetic fields with different characteristics can generate multiple physical quantities within biological tissues, such as magnetic, electric, mechanical, acoustic, and thermal effects. These physical quantities may also interact and couple with each other, stimulating the biological tissues in a combined or composite manner, thereby producing biological effects. This understanding is key to elucidating the electromagnetic mechanisms of how electromagnetic fields influence biological tissues. In the study of electromagnetic fields for bone remodeling diseases, attention should be paid to the biological effects of bone remodeling under different electromagnetic wave characteristics. This includes exploring innovative electromagnetic source technologies applicable to bone remodeling, identifying safe and effective electromagnetic field parameters, and combining basic research with technological invention to develop scientifically grounded, advanced key technologies for innovative electromagnetic treatment devices targeting bone remodeling diseases. In conclusion, electromagnetic fields and multiple physical factors have the potential to prevent and treat bone remodeling diseases, and have significant application prospects.

To study the therapeutic effect and mechanisms of ethyl syringate(MD) on ulcerative colitis(UC), the MTT assay was used to detect the proliferation inhibition of RAW264.7 cells and HT-29 cells by different concentrations of MD(50, 100, 200, 400 μmol·L~(-1)). UC cell models were constructed by inducing RAW264.7 cells and HT-29 cells with lipopolysaccharide(LPS) and tumor necrosis factor-α(TNF-α). An animal model was established by inducing mice with 2.5% dextran sulfate sodium(DSS) to verify the therapeutic effect of MD on UC. A control group, a model group(LPS or TNF-α), and groups treated with different concentrations of MD(50, 100, 200, 400 μmol·L~(-1)) were set up in this study. Nitric oxide(NO) levels were measured using a NO detection kit. Intracellular reactive oxygen species(ROS) levels were assessed using a laser confocal microscope and ROS kit. Enzyme-linked immunosorbent assay(ELISA) was used to detect changes in the levels of interleukin-6(IL-6), TNF-α, interferon-γ(INF-γ), interleukin-10(IL-10), and myeloperoxidase(MPO) in cells and animal tissues. Western blot was used to detect the expression levels of phosphorylated Janus kinase 2(p-JAK2), Janus kinase 2(JAK2), phosphorylated signal transducer and activator of transcription 3(p-STAT3), signal transducer and activator of transcription 3(STAT3), zonula occludens-1(ZO-1), occludin, and claudin-1 in cells and animal tissues. The results showed that MD can improve the inflammatory response by inhibiting the production of NO and ROS and regulating the expression of inflammatory factors. It significantly reduced the disease activity index(DAI) in mice, improved the shortening of the colon, and repaired intestinal epithelial damage by inhibiting the activation of the JAK2/STAT3 pathway, thereby exerting anti-UC activity.
Animals ; Colitis, Ulcerative/chemically induced* ; Janus Kinase 2/genetics* ; STAT3 Transcription Factor/genetics* ; Mice ; Humans ; Signal Transduction/drug effects* ; Male ; RAW 264.7 Cells ; Reactive Oxygen Species/metabolism* ; Nitric Oxide/metabolism* ; HT29 Cells ; Salicylates/administration & dosage* ; Protective Agents/administration & dosage*

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

The oxytocin receptor (OXTR) has garnered increasing attention for its role in regulating both mature behaviors and brain development. It has been established that OXTR mediates a range of effects that are region-specific or period-specific. However, the current studies of OXTR expression patterns in mice only provide limited help due to limitations in resolution. Therefore, our objective was to generate a comprehensive, high-resolution spatiotemporal expression map of Oxtr mRNA across the entire developing mouse brain. We applied RNAscope in situ hybridization to investigate the spatiotemporal expression pattern of Oxtr in the brains of male mice at six distinct postnatal developmental stages (P7, P14, P21, P28, P42, P56). We provide detailed descriptions of Oxtr expression patterns in key brain regions, including the cortex, basal forebrain, hippocampus, and amygdaloid complex, with a focus on the precise localization of Oxtr⁺ cells and the variance of expression between different neurons. Furthermore, we identified some neuronal populations with high Oxtr expression levels that have been little studied, including glutamatergic neurons in the ventral dentate gyrus, Vgat⁺Oxtr⁺ cells in the basal forebrain, and GABAergic neurons in layers 4/5 of the cortex. Our study provides a novel perspective for understanding the distribution of Oxtr and encourages further investigations into its functions.
Animals ; Receptors, Oxytocin/metabolism* ; Male ; Brain/growth & development* ; Mice ; Mice, Inbred C57BL ; Neurons/metabolism* ; Single-Cell Analysis ; Gene Expression Regulation, Developmental ; RNA, Messenger/metabolism* ; Animals, Newborn

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Threatened abortion is a common disease of obstetrics and gynecology and one of the diseases responding specifically to traditional Chinese medicine （TCM）. The China Association of Chinese Medicine organized experts in TCM obstetrics and gynecology， Western medicine obstetrics and gynecology， and pharmacology to deeply discuss the advantages of TCM and integrated Chinese and Western medicine treatment as well as the medication plans for threatened abortion. After discussion， the experts concluded that chromosome， endocrine， and immune abnormalities were the key factors for the occurrence of threatened abortion， and the Qi and blood disorders in thoroughfare and conception vessels were the core pathogenesis. In the treatment of threatened abortion， TCM has advantages in preventing miscarriages， alleviating clinical symptoms and TCM syndromes， relieving anxiety， regulating reproductive endocrine and immune abnormalities， personalized and diversified treatment， enhancing efficiency and reducing toxicity， and preventing the disease before occurrence. The difficulty in diagnosis and treatment of threatened abortion with traditional Chinese and Western medicine lies in identifying the predictors of abortion caused by maternal factors and the treatment of thrombophilia. Recurrent abortion is the breakthrough point of treatment with integrated traditional Chinese and Western medicine. It is urgent to carry out high-quality evidence-based medicine research in the future to improve the modern diagnosis and treatment of threatened abortion with TCM.

Objective To compare effectiveness between the modified and traditional pressure-overload myocardial hypertrophy(POMH) model by abdominal aorta coarctation (AAC) method. Methods Totally 45 rats were divided into three groups(n = 15 per group), sham group, traditional group, and modified group. In the traditional group, the diameter ol the abdominal aorta was narrowed to 0. 70 mm through a midline incision for 4 weeks; in the modified group, the diameter of the abdominal aorta was narrowed above the left kidney to 0. 45 mm for 1 week, and then the narrowing was lifted postoperatively. The cardiac index, heart weight (HW) /body weight (BW) and left ventricular index, left ventricular weight (LVW)/BW were measured from the heart specimens, and the cross-sectional area of cardiac myocytes, myocardial collagen area, and myocardial collagen area Iraction were measured in the pathological sections by HE staining and Masson staining. Results Compared with the sham group, the differences in end-systolic interventricular septum thickness (IVSs), left ventricular end-systolic posterior wall thickness (LVPWs), HW/BW, LVW/BW, cardiomyocyte cross-sectional area, myocardial collagen area, myocardial collagen area fraction, and brain natriuretic peptide (BNP) expression levels were statistically significant (P<0. 05) in the modilied and traditional groups of rats. The differences in these indices were not statistically significant between the modified and traditional groups (P>0. 05). Conclusion The modified abdominal aortic constriction method used in this experiment is time-saving, stable, homogeneous and easy to replicate, and is a more ideal approach to establish a rat model of POMH.

Objective To analyze the causal relationship between genetically predicted body mass index(BMI)and prostate cancer(PCa)risk with Mendelian randomization(MR),in order to explore the potential risk factors for PCa and the development of prevention strategies.Methods Two-sample MR was performed using BMI genome-wide association study(GWAS)data of 339 224 samples and PCa GWAS data of 463 010 samples.After that,69 single nucleotide polymorphisms(SNP)of BMI were used as instrumental variables to perform MR analysis on PCa.MR analysis adopted the inverse variance weighting method(IVW),MR-Egger method,weighted median method(WME),simple mode method(SM)and weighted mode method(WM).Heterogeneity test,plciotropy test and leave-one-out sensitivity test were used to verify the stability and reliability of the data.Results In the IVW analysis,it was found that BMI was associated with the risk of PCa(OR:0.997,95％CI:0.995-0.999,P=0.001).In the WME(OR:0.996,95％CI:0.994-0.999,P=0.009),and WM(OR:0.995,95％CI:0.991-1.000,P=0.045),the same results were obtained.There was no statistical significant difference between the MR-Egger method(OR:0.996,95％CI:0.991-1.002,P=0.205)and SM(OR:0.995,95％CI:0.990-1.000,P=0.079).Conclusion There is a causal relationship between a genetically predicted higher BMI and a lower risk of PCa by two sample MR analysis.This finding can prove a reference for identifying potential risk factors for PCa and the development of prevention strategies.

The new generation of artificial intelligence technology,represented by deep learning,has emerged as a crucial driving force in the advancement of new drug research and development.This article creatively proposes a workflow named"Molecular Factory"for the design and optimization of drug molecules based on artificial intelligence technology.This workflow integrates intelligent molecular generation models,high-performance molecular docking algorithms,and accurate protein-ligand binding affinity prediction methods.It has been integrated as a core module into DrugFlow,a one-stop drug design software platform,providing a comprehensive set of mature solutions for the discovery and optimization of lead compounds.Utilizing the"Molecular Factory"module,we conducted the research of second-generation inhibitors against Menin that can combat drug resistance.Through the integration of computational and experimental approaches,we rapidly identified multiple promising compounds.Among them,compound RG-10 exhibited the IC50 values of 9.681 nmol/L,233.2 nmol/L,and 40.09 nmol/L against the wild-type Menin,M327I mutant,and T349M mutant,respectively.Compared to the positive reference molecule SNDX-5613,which has entered Phase Ⅱ clinical trials,RG-10 demonstrated significantly enhanced inhibitory activity against the M327I and T349M mutants.These findings fully demonstrate the unique advantages of the"Molecular Factory"technology in practical drug design and development scenarios.It can rapidly and efficiently generate high-quality active molecules targeting specific protein structures,holding significant value and profound implications for advancing new drug discovery.