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.

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.

The liver, skeletal muscle, and adipose tissue are central energy-metabolizing organs and insulin-sensitive tissues, playing a crucial role in maintaining glucose homeostasis. As the powerhouse of the cell, mitochondria not only regulate insulin secretion but also oversee the oxidative phosphorylation and β-oxidation of fatty acids, processes vital for the metabolism of carbohydrates and fats, as well as the synthesis of ATP. The mitochondrial quality control system is of paramount importance for sustaining mitochondrial homeostasis, achieved through mechanisms such as protein homeostasis, mitochondrial dynamics, mitophagy, and biogenesis. Evidence suggests that dysfunctional mitochondria may significantly contribute to insulin resistance and ectopic fat storage in the liver, offering new insights into the strong correlation between mitochondrial dysfunction and the development of obesity, diabetes mellitus type 2 (T2DM), and non-alcoholic fatty liver disease (NAFLD). This manuscript aims to delve into the precise mechanisms by which imbalances in mitochondrial quality control lead to metabolic disorders in the liver, skeletal muscle, and adipose tissue, the 3 major insulin-sensitive organs. In the liver, mitochondrial dysfunction can lead to disturbances in glucose and lipid metabolism, resulting in insulin resistance and fat accumulation—a key factor in the development of NAFLD. In skeletal muscle, reduced mitochondrial function can decrease ATP production, weakening the muscle’s ability to uptake glucose, thereby exacerbating insulin resistance. In adipose tissue, mitochondrial dysfunction can impair adipocyte function, leading to lipotoxicity and inflammatory responses,which further contribute to insulin resistance and the onset of metabolic syndrome. Moreover, the interorgan crosstalk among these 3 tissues is essential for overall metabolic homeostasis. For instance, hepatic gluconeogenesis and glucose utilization in skeletal muscle are both influenced by the health status of their respective mitochondrial populations. The conversion between different types of adipose tissue and the ability to store lipids depend on normal mitochondrial function to avert ectopic fat accumulation in other organs. In summary, this manuscript emphasizes the critical role of mitochondrial quality control in maintaining the metabolic stability of the liver, skeletal muscle, and adipose tissue. It elucidates the specific mechanisms by which mitochondrial dysfunction in these organs contributes to the development of metabolic diseases, providing a foundation for future research and the development of therapeutic strategies targeting mitochondrial dysfunction.

ObjectiveTo explore the effects of Kaixuan Jiedu core prescription （KXJD） on sphingolipid metabolism in the mouse model of imiquimod-induced psoriasis-like skin lesions. MethodsThirty-seven male C57BL/6J mice were randomly assigned into five groups： healthy control （n=11）， model （n=11）， methotrexate （MTX， n=5）， low-dose （15.21 g·kg^-1） KXJD （n=5）， and high-dose （30.42 g·kg^-1） KXJD （n=5）. Psoriasis-like skin lesions were induced in mice with 62.5 mg 5% imiquimod cream applied on the back. The KXJD groups and MTX group were treated with 0.2 mL corresponding decoction and MTX， respectively， by gavage daily， while the other groups were given an equal volume of normal saline by the same way. After 5 days of treatment， back skin lesions were collected. Firstly， healthy control and model mice were selected for tandem mass tag （TMT） quantitative proteomics （control vs model=3 vs 3） and targeted lipid metabolomics （control vs model=11 vs 11）. Then， the binding degree between core components and target proteins was predicted via network pharmacology and molecular docking. Finally， an animal experiment was performed to decipher the specific regulation mechanism of KXJD on sphingolipid metabolism. Immunohistochemistry was employed to determine the expression level of sphingosine-1-phosphate （S1P）， and Western blot was employed to determine the expression levels of sphingosine kinase 2 （SPHK2） and monocyte chemotactic protein-1 （MCP-1）. ResultsTMT proteomics and targeted lipid metabolomics suggested that sphingolipid metabolism was active in the psoriatic skin， and key proteases ［serine palmitoyltransferase， long chain base subunit 2 （SPTLC2）， SPHK2， delta（4）-desaturase sphingolipid 1 （Degs1）， and ceramide synthase 4 （CerS4）］ and 8 sphingolipid metabolites （including ceramides， sphingol， sphingomyelin， and glycosphingolipid） expressed abnormally （P<0.05） compared with those in the healthy skin. The molecular docking results indicated that the binding energy between the active components （quercetin， kaempferol， and luteolin） in KXJD and key proteins involved in sphingolipid metabolism was less than-8 kal·mol^-1. Further experimental verification showed elevated expression levels of SPHK2， S1P， and MCP-1 in psoriatic skin compared with healthy skin （P<0.05）， and KXJD down-regulated the expression levels of SPHK2， S1P， and MCP-1 compared with the model group （P<0.05）. ConclusionThis study indicates that there is an imbalance in sphingolipid metabolism in psoriatic skin lesions. KXJD may reduce psoriasis-like lesions in mice by regulating sphingolipid metabolism via the SPHK2/S1P/MCP-1 pathway.

ObjectiveTo explore the effects of Kaixuan Jiedu core prescription （KXJD） on sphingolipid metabolism in the mouse model of imiquimod-induced psoriasis-like skin lesions. MethodsThirty-seven male C57BL/6J mice were randomly assigned into five groups： healthy control （n=11）， model （n=11）， methotrexate （MTX， n=5）， low-dose （15.21 g·kg^-1） KXJD （n=5）， and high-dose （30.42 g·kg^-1） KXJD （n=5）. Psoriasis-like skin lesions were induced in mice with 62.5 mg 5% imiquimod cream applied on the back. The KXJD groups and MTX group were treated with 0.2 mL corresponding decoction and MTX， respectively， by gavage daily， while the other groups were given an equal volume of normal saline by the same way. After 5 days of treatment， back skin lesions were collected. Firstly， healthy control and model mice were selected for tandem mass tag （TMT） quantitative proteomics （control vs model=3 vs 3） and targeted lipid metabolomics （control vs model=11 vs 11）. Then， the binding degree between core components and target proteins was predicted via network pharmacology and molecular docking. Finally， an animal experiment was performed to decipher the specific regulation mechanism of KXJD on sphingolipid metabolism. Immunohistochemistry was employed to determine the expression level of sphingosine-1-phosphate （S1P）， and Western blot was employed to determine the expression levels of sphingosine kinase 2 （SPHK2） and monocyte chemotactic protein-1 （MCP-1）. ResultsTMT proteomics and targeted lipid metabolomics suggested that sphingolipid metabolism was active in the psoriatic skin， and key proteases ［serine palmitoyltransferase， long chain base subunit 2 （SPTLC2）， SPHK2， delta（4）-desaturase sphingolipid 1 （Degs1）， and ceramide synthase 4 （CerS4）］ and 8 sphingolipid metabolites （including ceramides， sphingol， sphingomyelin， and glycosphingolipid） expressed abnormally （P<0.05） compared with those in the healthy skin. The molecular docking results indicated that the binding energy between the active components （quercetin， kaempferol， and luteolin） in KXJD and key proteins involved in sphingolipid metabolism was less than-8 kal·mol^-1. Further experimental verification showed elevated expression levels of SPHK2， S1P， and MCP-1 in psoriatic skin compared with healthy skin （P<0.05）， and KXJD down-regulated the expression levels of SPHK2， S1P， and MCP-1 compared with the model group （P<0.05）. ConclusionThis study indicates that there is an imbalance in sphingolipid metabolism in psoriatic skin lesions. KXJD may reduce psoriasis-like lesions in mice by regulating sphingolipid metabolism via the SPHK2/S1P/MCP-1 pathway.

RNA modifications constitute a crucial class of post-transcriptional chemical alterations that profoundly influence RNA stability and translational efficiency, thereby shaping cellular protein expression profiles. These diverse chemical marks are ubiquitously involved in key biological processes, including cell proliferation, differentiation, apoptosis, and metastatic potential, and they exert precise regulatory control over these functions. A major advance in the field is the recognition that RNA modifications do not act in isolation. Instead, they participate in complex, dynamic interactions—through synergistic enhancement, antagonism, competitive binding, and functional crosstalk—forming what is now termed the “RNA modification interactome” or “RNA modification interaction network.” The formation and functional operation of this interactome rely on a multilayered regulatory framework orchestrated by RNA-modifying enzymes—commonly referred to as “writers,” “erasers,” and “readers.” These enzymes exhibit hierarchical organization within signaling cascades, often functioning in upstream-downstream sequences and converging at critical regulatory nodes. Their integration is further mediated through shared regulatory elements or the assembly into multi-enzyme complexes. This intricate enzymatic network directly governs and shapes the interdependent relationships among various RNA modifications. This review systematically elucidates the molecular mechanisms underlying both direct and indirect interactions between RNA modifications. Building upon this foundation, we introduce novel quantitative assessment frameworks and predictive disease models designed to leverage these interaction patterns. Importantly, studies across multiple disease contexts have identified core downstream signaling axes driven by specific constellations of interacting RNA modifications. These findings not only deepen our understanding of how RNA modification crosstalk contributes to disease initiation and progression, but also highlight its translational potential. This potential is exemplified by the discovery of diagnostic biomarkers based on interaction signatures and the development of therapeutic strategies targeting pathogenic modification networks. Together, these insights provide a conceptual framework for understanding the dynamic and multidimensional regulatory roles of RNA modifications in cellular systems. In conclusion, the emerging concept of RNA modification crosstalk reveals the extraordinary complexity of post-transcriptional regulation and opens new research avenues. It offers critical insights into the central question of how RNA-modifying enzymes achieve substrate specificity—determining which nucleotides within specific RNA transcripts are selectively modified during defined developmental or pathological stages. Decoding these specificity determinants, shaped in large part by the modification interactome, is essential for fully understanding the biological and pathological significance of the epitranscriptome.

BACKGROUND: Circadian syndrome (CircS) may be closely linked to lifestyle, psychological, and occupational factors, but evidence is lacking. This study aimed to explore complex associations between lifestyle, psychological and occupational factors and CircS among employed people in southwestern China. METHODS: In this study, network analysis was used to identify complex associations between lifestyle, psychological and occupational factors and CircS in employed people from the Chinese Cohort of Working Adults (CCWA). The centrality of each variable was estimated by strength centrality index, which was calculated by the sum of edge weights connected to the variable. Bridge in the network was identified as the variables in the top 80 th percentile of overall bridge strength, which was defined as the most strongly connected variables across lifestyle, psychological and occupational factors and CircS. The differences were assessed in network structures between subgroups divided by the median score of the variable with the strongest bridge strengthen. RESULTS: Among 31,105 participants from CCWA, 5213 (16.76%) had CircS. In the constructed network, anxiety (edge weights: 0.28), smoking (edge weights: 0.15), drinking (edge weights: 0.10), perceived noise at work (edge weights: 0.08), and implicit health attitude (edge weights: -0.02) were directly related to CircS, with 83.31% of the variance for CircS explained by these neighboring factors. Anxiety was the most central variable (strength centrality: 1.20) in the network and the strongest bridge (bridge strength: 0.84) connecting all domains of variables. A stronger association between anxiety and CircS was observed in the network of participants with more severe anxiety (edge weight: 0.23) than those with less severe anxiety (edge weight: 0.03). CONCLUSION Anxiety had the strongest association with CircS and was the central factor with the highest strength centrality, also the bridge with the highest bridge strength in the network.
Humans ; Male ; Female ; Adult ; China ; Middle Aged ; Life Style ; Chronobiology Disorders/epidemiology*

BACKGROUND: This study aimed to investigate programmed death-ligand 1 tumor proportion score in predicting the safety and efficacy of PD-1/PD-L1 antibody-based therapy in treating patients with advanced non-small cell lung cancer (NSCLC) in a real-world setting. METHODS: This retrospective, multicenter, observational study enrolled adult patients who received PD-1/PD-L1 antibody-based therapy in China and met the following criteria: (1) had pathologically confirmed, unresectable stage III-IV NSCLC; (2) had a baseline PD-L1 tumor proportion score (TPS); and (3) had confirmed efficacy evaluation results after PD-1/PD-L1 treatment. Logistic regression, Kaplan-Meier analysis, and Cox regression were used to assess the progression-free survival (PFS), overall survival (OS), and immune-related adverse events (irAEs) as appropriate. RESULTS: A total of 409 patients, 65.0% ( n = 266) with a positive PD-L1 TPS (≥1%) and 32.8% ( n = 134) with PD-L1 TPS ≥50%, were included in this study. Cox regression confirmed that patients with a PD-L1 TPS ≥1% had significantly improved PFS (hazard ratio [HR] 0.747, 95% confidence interval [CI] 0.573-0.975, P = 0.032). A total of 160 (39.1%) patients experienced 206 irAEs, and 27 (6.6%) patients experienced 31 grade 3-5 irAEs. The organs most frequently associated with irAEs were the skin (52/409, 12.7%), thyroid (40/409, 9.8%), and lung (34/409, 8.3%). Multivariate logistic regression revealed that a PD-L1 TPS ≥1% (odds ratio [OR] 1.713, 95% CI 1.054-2.784, P = 0.030) was an independent risk factor for irAEs. Other risk factors for irAEs included pretreatment absolute lymphocyte count >2.5 × 10 9 /L (OR 3.772, 95% CI 1.377-10.329, P = 0.010) and pretreatment absolute eosinophil count >0.2 × 10 9 /L (OR 2.006, 95% CI 1.219-3.302, P = 0.006). Moreover, patients who developed irAEs demonstrated improved PFS (13.7 months vs. 8.4 months, P <0.001) and OS (28.0 months vs. 18.0 months, P = 0.007) compared with patients without irAEs. CONCLUSIONS A positive PD-L1 TPS (≥1%) was associated with improved PFS and an increased risk of irAEs in a real-world setting. The onset of irAEs was associated with improved PFS and OS in patients with advanced NSCLC receiving PD-1/PD-L1-based therapy.
Humans ; Carcinoma, Non-Small-Cell Lung/metabolism* ; Male ; Female ; Retrospective Studies ; Middle Aged ; Lung Neoplasms/metabolism* ; Aged ; B7-H1 Antigen/metabolism* ; Programmed Cell Death 1 Receptor/metabolism* ; Adult ; Aged, 80 and over ; Immune Checkpoint Inhibitors/therapeutic use*

The holistic view is the key in the study of traditional Chinese medicine(TCM). The component structure theory is based on the holistic view to investigate the correlation between material basis and efficiency, which enriches the holistic "component-effect" research of TCM. Gintonin is a newly isolated non-saponin component of ginseng. Compared to ginsenosides, gintonin has many different pharmacological activities, and it provides new knowledge for the holistic research of ginseng. Thus, taking the discovery of gintonin from ginseng as an example, this paper explored the linkage between ginsenosides and gintonin from the perspective of "component-effect" correlations and systematically sorted out the similarities and differences between them in terms of structural characteristics, modes of action, and pharmacological activities. Starting from the collaborative interaction of TCM compounds, the study discussed the application and value of the holistic view in TCM "component-effect" research in the light of the component structure theory to provide new thoughts for the development of modern TCM research.
Panax/chemistry* ; Drugs, Chinese Herbal/pharmacology* ; Medicine, Chinese Traditional ; Humans ; Ginsenosides/pharmacology* ; Animals