This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

Radar-based non-contact health monitoring technology (RBNHMT) has emerged as a transformative paradigm in continuous health sensing, enabling non-invasive and continuous monitoring of physiological parameters and behavioral patterns by transmitting electromagnetic waves, analyzing the reflected signals, and detecting subtle bodily movements—ranging from millimeter-scale chest wall displacements due to respiration to micro-scale vibrations associated with cardiac activity—ultimately transforming them into quantifiable health data. Distinguished by its non-contact operation, inherent privacy preservation, and adaptability to diverse scenarios, RBNHMT exhibits stronger resistance to environmental interference than conventional contact-based monitoring, and has solidified its position as a prominent and dynamic research focus in the field of non-contact health monitoring. Currently, significant and multifaceted progress has been made across several key areas. In human activity recognition (HAR), systems leveraging micro-Doppler signatures or point cloud sequences achieve high-precision detection of gait, gestures, and fall events, with state-of-the-art deep learning-based models achieving accuracy rates exceeding 99% in controlled experimental settings. For vital sign and sleep monitoring, it not only tracks respiratory and heart rates continuously but also extracts clinically relevant metrics such as heart rate variability (HRV) for autonomic nervous system assessment and estimates blood pressure through indirect methods like pulse transit time analysis, while maintaining robustness in dynamic settings through advanced motion compensation algorithms. In sleep monitoring, it further enables sleep posture classification and apnea event detection. In emotion and stress recognition, it provides a non-intrusive approach for psychological assessment by analyzing autonomic-response physiological signal patterns or behavioral features. Furthermore, its applications in auxiliary medical diagnosis have expanded to promising interdisciplinary areas such as non-contact heart sound auscultation, radar-based screening for obstructive sleep apnea (OSA), and emerging research into breast cancer detection using microwave and millimeter-wave imaging techniques. However, several challenges impede its practical deployment. Signal quality is significantly compromised by multipath interference in complex indoor environments and clutter from static objects, and by motion artifacts in dynamic scenarios where gross body movements obscure the subtle physiological signals. Algorithmically, separating signals from multiple targets in close proximity and calibrating for substantial individual physiological differences, such as body habitus, baseline vital signs, remain difficult and limit generalizability. Hardware design also faces the challenge of balancing power consumption, cost, integration, and performance, often requiring trade-offs that constrain miniaturization, battery life, or measurement sensitivity. Future advancement, therefore, requires collaborative and targeted innovation across multiple dimensions. Algorithmically, developing adaptive signal processing models based on emerging paradigms such as few-shot learning (for user-specific calibration with minimal data) and reinforcement learning (for dynamic noise suppression) is essential. At the hardware level, highly integrated radar SoCs with embedded processing capabilities and advanced packaging technologies are crucial for achieving the dual goals of device miniaturization and cost reduction without sacrificing performance. At the system level, fusing radar data with complementary modalities such as infrared and acoustic sensing can create a synergistic, multi-modal framework that significantly enhances perceptual robustness and reliability in complex, real-world environments. This review provides a comprehensive synthesis that systematically summarizes the relevant theoretical foundations and application progress, and offers an in-depth analysis of the current technical bottlenecks. It aims to provide a clear development path and a foundational academic reference for the in-depth integration and practical application of RBNHMT in critical scenarios including rehabilitation engineering, smart elderly care, in-vehicle health monitoring, and beyond, thereby offering innovative technical support for the vision of universal, proactive, and personalized health management.

The chemical constituents were systematically separated from the roots of Berberis polyantha by various chromatographic methods, including silica gel column chromatography, HP20 column chromatography, polyamide column chromatography, reversed-phase C_(18) column chromatography, and preparative high-performance liquid chromatography. The structures of the compounds were identified by physicochemical properties and spectroscopic techniques(1D NMR, 2D NMR, UV, MS, and CD). Four phenylpropanoids were isolated from the methanol extract of the roots of B. polyantha, and they were identified as(2R)-1-(4-hydroxy-3,5-dimethoxyphenyl)-1-propanone-O-β-D-glucopyranoside(1), methyl 4-hydroxy-3,5-dimethoxybenzoate(2),(+)-syringaresinol(3), and syringaresinol-4-O-β-D-glucopyranoside(4). Compound 1 was a new compound, and other compounds were isolated from this plant for the first time. The anti-inflammatory activity of these compounds was evaluated based on the release of nitric oxide(NO) in the culture of lipopolysaccharide(LPS)-induced RAW264.7 macrophages. At a concentration of 10 μmol·L~(-1), all the four compounds inhibited the LPS-induced release of NO in RAW264.7 cells, demonstrating potential anti-inflammatory properties.
Plant Roots/chemistry* ; Animals ; Mice ; Berberis/chemistry* ; RAW 264.7 Cells ; Macrophages/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; Nitric Oxide/metabolism* ; Molecular Structure ; Anti-Inflammatory Agents/isolation & purification*

This study investigated the mechanism by which Jianpi Bushen Yiqi Decoction promotes acetylcholine receptor(AChR) clustering in myasthenia gravis through the Agrin/low-density lipoprotein receptor-related protein 4(LRP4)/muscle-specific receptor tyrosine kinases(MuSK) signaling pathway. A total of 114 female C57BL/6J mice were divided into the normal group, modeling group, and solvent control group. The normal group and the solvent control group were immunized with phosphate-buffered saline(PBS), while the modeling group was established as an experimental autoimmune myasthenia gravis(EAMG) model using the murine-derived AChR-α subunit R97-116 peptide fragment. After successful modeling, the mice were randomly assigned to the model group, the low-, medium-, and high-dose Jianpi Bushen Yiqi Decoction groups, and the prednisone group. After four weeks of continuous treatment, muscle strength was assessed using Lennon scores and grip strength tests. Immunofluorescence staining was conducted on differentiated C2C12 myotubes incubated with a drug-containing serum to observe the number of AChR clusters. The integrity of AChR on myofilaments in mouse gastrocnemius muscles was further assessed by immunofluorescence staining. Hematoxylin-Eosin(HE)staining was applied to examine pathological changes in the gastrocnemius muscles of EAMG mice treated with Jianpi Bushen Yiqi Decoction. Western blot was utilized to detect the expression of key proteins in the Agrin/LRP4/MuSK signaling pathway in both C2C12 myotubes and mouse gastrocnemius muscles. The results demonstrated that compared to the model group, the prednisone group exhibited a significant decrease in the body weights of mice, whereas no significant differences in the body weights of mice were observed among the low-, medium-, and high-dose Jianpi Bushen Yiqi Decoction groups. All treatment groups showed significantly improved grip strength and Lennon scores. Additionally, the formula promoted AChR clustering on myotubes and enhanced AChR integrity in gastrocnemius myofilaments and reduced inflammatory infiltration between muscle tissue and fibrous hyperplasia. Furthermore, Jianpi Bushen Yiqi Decoction upregulated the protein expression of AChRα1, Agrin, and p-MuSK in C2C12 myotubes and increased the protein expression of AChRα1, Agrin, MuSK, p-MuSK, LRP4, and docking protein 7(Dok-7)in gastrocnemius tissue. In conclusion, Jianpi Bushen Yiqi Decoction may promote AChR clustering by targeting key proteins in the Agrin/LRP4/MuSK signaling pathway, thereby improving neuromuscular junction function and enhancing muscle strength.
Animals ; Agrin/genetics* ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Signal Transduction/drug effects* ; Receptors, Cholinergic/genetics* ; Female ; Mice, Inbred C57BL ; Receptor Protein-Tyrosine Kinases/genetics* ; Neuromuscular Junction/metabolism* ; Myasthenia Gravis, Autoimmune, Experimental/physiopathology* ; Humans ; LDL-Receptor Related Proteins

The genome tagging project (GTP) plays a pivotal role in addressing a critical gap in the understanding of protein functions. Within this framework, we successfully generated a human influenza hemagglutinin-tagged sperm-specific protein 411 (HA-tagged Ssp411) mouse model. This model is instrumental in probing the expression and function of Ssp411. Our research revealed that Ssp411 is expressed in the round spermatids, elongating spermatids, elongated spermatids, and epididymal spermatozoa. The comprehensive examination of the distribution of Ssp411 in these germ cells offers new perspectives on its involvement in spermiogenesis. Nevertheless, rigorous further inquiry is imperative to elucidate the precise mechanistic underpinnings of these functions. Ssp411 is not detectable in metaphase II (MII) oocytes, zygotes, or 2-cell stage embryos, highlighting its intricate role in early embryonic development. These findings not only advance our understanding of the role of Ssp411 in reproductive physiology but also significantly contribute to the overarching goals of the GTP, fostering groundbreaking advancements in the fields of spermiogenesis and reproductive biology.
Animals ; Female ; Humans ; Male ; Mice ; Spermatids/metabolism* ; Spermatogenesis/physiology* ; Spermatozoa/metabolism* ; Thioredoxins/genetics*

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*

To evaluate the therapeutic effect of a modified Devine procedure with a subcutaneous sliding fixation method for the treatment of congenital concealed penis, we retrospectively selected 45 patients with congenital concealed penises who were admitted to General Hospital of Ningxia Medical University (Yinchuan, China) between September 2020 and November 2023. In all cases, the penis was observed to be short, and retracting the skin at the base revealed a normal penile body, which immediately returned to its original position upon release. All patients underwent the modified Devine procedure with subcutaneous sliding fixation and completed a 12-week postoperative follow-up. A statistically significant increase in penile length was observed postoperatively, with the median length increasing from 4.0 (interquartile range [IQR]: 3.5-4.8; 95% confidence interval [CI]: 3.9-4.4) cm to 8.0 (IQR: 7.8-8.0; 95% CI: 7.7-7.9) cm, with P < 0.001. The parents were satisfied with the outcomes, including increased penile length, improved hygiene, and enhanced esthetics. Except for mild foreskin edema in all cases, no complications (such as infections, skin necrosis, or penile retraction) were observed. The edema was resolved within 4 weeks after the operation. This study demonstrates that the modified Devine procedure utilizing the subcutaneous sliding fixation method yields excellent outcomes with minimal postoperative complications, reduced penile retraction, and high satisfaction rates among patients and their families.
Humans ; Male ; Penis/abnormalities* ; Retrospective Studies ; Urologic Surgical Procedures, Male/methods* ; Treatment Outcome ; Child ; Plastic Surgery Procedures/methods*

OBJECTIVES: To investigate the relationship between the polygenic risks for various psychiatric disorders and clinical and neuropsychological characteristics in children with attention-deficit/hyperactivity disorder (ADHD). METHODS: Using a cross-sectional design, 285 children with ADHD and 107 healthy controls were assessed using the Child Behavior Checklist, the Behavior Rating Inventory of Executive Function for parents, the Wechsler Intelligence Scale for Children, Fourth Edition, and the Cambridge Neuropsychological Test Automated Battery. Blood samples were collected for genetic data. Polygenic risk scores (PRSs) for various psychiatric disorders were calculated using the PRSice-2 software. RESULTS: Compared with the healthy controls, the children with ADHD displayed significantly higher PRSs for ADHD, major depressive disorder, anxiety disorder, and obsessive-compulsive disorder (P<0.05). In terms of daily-life executive function, ADHD-related PRS was significantly correlated with the working memory factor; panic disorder-related PRS was significantly correlated with the initiation factor; bipolar disorder-related PRS was significantly correlated with the shift factor; schizophrenia-related PRS was significantly correlated with the inhibition, emotional control, initiation, working memory, planning, organization, and monitoring factors (P<0.05). The PRS related to anxiety disorders was negatively correlated with total IQ and processing speed index (P<0.05). The PRS related to obsessive-compulsive disorder was negatively correlated with the processing speed index and positively correlated with the stop-signal reaction time index of the stop-signal task (P<0.05). CONCLUSIONS PRSs for various psychiatric disorders are closely correlated with the behavioral and cognitive characteristics in children with ADHD, which provides more insights into the heterogeneity of ADHD.
Humans ; Attention Deficit Disorder with Hyperactivity/genetics* ; Child ; Male ; Female ; Cross-Sectional Studies ; Neuropsychological Tests ; Multifactorial Inheritance ; Adolescent ; Mental Disorders/etiology* ; Executive Function ; Genetic Risk Score