Myocardial infarction （MI） and osteoporosis （OP）， as two prevalent metabolic diseases with high morbidity and mortality rates， are respectively characterized by cardiovascular system dysfunction and bone homeostasis imbalance， collectively posing significant global public health challenges. While clinically often considered as independent diseases， recent studies have revealed shared pathological mechanisms between the two. This study initiated its exploration from the traditional Chinese medicine concept of the "heart-bone" axis， systematically analyzing the correlation between MI and OP from perspectives including hemodynamics， neuroendocrinology， calcium homeostasis， inflammation and vascular injury， as well as hormone levels. By discussing the pathological mechanisms of "heart disease affecting the bones and bone disease affecting the heart"， the study also elucidated advancements in both Western and traditional Chinese medicine treatments. The goal is to provide novel insights and methodologies for the prevention and treatment of "heart-bone comorbidities"， thereby facilitating comprehensive management of cardiovascular and skeletal diseases.

Myocardial infarction （MI） and osteoporosis （OP）， as two prevalent metabolic diseases with high morbidity and mortality rates， are respectively characterized by cardiovascular system dysfunction and bone homeostasis imbalance， collectively posing significant global public health challenges. While clinically often considered as independent diseases， recent studies have revealed shared pathological mechanisms between the two. This study initiated its exploration from the traditional Chinese medicine concept of the "heart-bone" axis， systematically analyzing the correlation between MI and OP from perspectives including hemodynamics， neuroendocrinology， calcium homeostasis， inflammation and vascular injury， as well as hormone levels. By discussing the pathological mechanisms of "heart disease affecting the bones and bone disease affecting the heart"， the study also elucidated advancements in both Western and traditional Chinese medicine treatments. The goal is to provide novel insights and methodologies for the prevention and treatment of "heart-bone comorbidities"， thereby facilitating comprehensive management of cardiovascular and skeletal diseases.

Objective To systematically analyze the spatiotemporal distribution characteristics and epidemiological trends of tracheal, bronchus, and lung cancer (TBL) disease burden attributed to air pollution globally and in China and the United States from 1990 to 2021, and to assess the patterns of disease burden changes from 2022 to 2031 based on predictive models, providing a scientific basis for formulating targeted TBL prevention and control strategies. Methods Based on the Global Burden of Disease (GBD) 2021 database, we analyzed the disease burden data of TBL attributed to air pollution globally and in China and the United States from 1990 to 2021. R Studio 4.3.2 software was used to analyze the corresponding trends and the Bayesian age-period-cohort (BAPC) prediction model was used to predict the status of the disease burden of TBL attributed to air pollution in the world and in China and the United States from 2022 to 2031. Results In 2021, China had the highest number of deaths and disability-adjusted life years attributed to air pollution (211 400 patients and 4.8947 million person-years), followed by the United States (6 000 patients and 124 300 person-years). The age-standardized mortality rate (ASMR) and age-standardized disability-adjusted life years rate (ASDR) of TBL due to air pollution in the world and in China and the United States showed a decreasing trend. From 1990 to 2021, the ASMR and ASDR of TBL in China due to air pollution were much higher than those in the United States and the global average. In terms of gender, from 1990 to 2021, the disease burden of male patients with TBL attributed to air pollution was much higher than that of female patients. The BAPC prediction model showed that from 2022 to 2031, the ASMR and ASDR of TBL attributed to air pollution showed an upward trend globally, while they showed a downward trend in China and the United States. Conclusion Over the past 30 years, the air pollution-related TBL disease burden in the world and in China and the United States has continued to decline, but China's disease burden is still significantly higher than the global average. The disease burden in men far exceeds that in women, with men and the population aged ≥50 years being high-risk groups. In the future, the global disease trend may reverse and rise, while China and the United States are expected to continuously decline. However, precise prevention and control for high-risk groups remains a key challenge.

Chronic post-surgical pain (CPSP) is a common long-term complication following lung surgery. Its high incidence significantly impacts patients’ quality of life and functional recovery, and imposes a substantial socioeconomic burden. This consensus aims to systematically establish a standardized integrated Chinese and Western medicine diagnostic and treatment framework for chronic post-lung surgery pain (CPLSP). Based on the latest domestic and international evidence-based medical research and multidisciplinary clinical experience, the working group comprehensively elaborates on core issues regarding CPLSP, including its definition, epidemiology, pathogenesis, clinical assessment, Western medical treatment, traditional Chinese medicine (TCM) treatment, and integrated strategies. The consensus emphasizes a patient-centered approach, adhering to the principles of multimodality, individualization, and stepwise management, highlighting the synergistic advantages of integrating Chinese and Western medicine throughout the entire perioperative management cycle encompassing "perioperative anti-inflammation, acute analgesia, and chronic rehabilitation." Through systematic literature retrieval and evidence integration, a total of 9 core recommendations were established to provide scientifically sound and clinically practical guidance.

This paper proposes a two-stage method integrating visual foundation models （VFM） and diffusion models. The segment anything model （SAM） as VFM is combined with the SegRefiner diffusion model to construct the SAM-SegRefiner framework for automated segmentation of edema， inflammation， and thrombus regions in histopathological images of hemorrhoidal tissue， providing a reproducible technical tool for the objective quantification of pathological morphology and its application in traditional Chinese medicine （TCM） syndrome research. Trained and validated on multi-center retrospective data， the SAM-SegRefiner model achieved an average pixel accuracy of 95.32% and a mean intersection over union （mIoU） of 66.81% on an independent test set， significantly outperfor-ming comparative models such as U-Net， MixU-Net， and SAM-Med2D， and also demonstrating robust cross-center generalization capability. Furthermore， by correlating the quantitatively segmented results from the model with the patients' TCM syndrome types， the potential associations between pathomorphological features and TCM syndrome differentiation have been explored. The analysis revealed no statistically significant differences in the degree of inflammatory infiltration and thrombus formation among different syndrome types， suggesting a complex relationship between local pathological changes and systemic syndrome manifestations.

Objective To analyze the distribution status of the end digits of standardized blood pressure measurement recordings in the clinic and the effectiveness of standardized blood pressure measurement for community hypertension screening. Methods The first visit blood pressure measurement data from the Community Health Service Center in Jing'an District, Shanghai from June 2023 to May 2024 were collected and analyzed. According to different measurement methods, the data were divided into two groups: standardized blood pressure measurement and conventional blood pressure measurement. SPSS 19.0 software was used for data analysis. The differences in the distribution balance of the end digits of blood pressure values and the detection rate of blood pressure elevation between the two different groups were analyzed. Results The frequency range of the end digits of blood pressure recorded values in the standardized pressure measurement group was 9.42% to 10.83%, and the detection rate of elevated blood pressure was 24.89%. The conventional pressure measurement group had a preference of the end digit ^"0^", and the detection rate of elevated blood pressure was only 2.12%. The results of multiple logistic regression analysis showed that gender, age, season, and different blood pressure measurement modes were all influencing factors for the detection rate of elevated blood pressure. Conclusion The standardized blood pressure measurement mode in the clinic is suitable for community hypertension screening and pressure measurement, with higher data quality than the conventional pressure measurement mode.

ObjectiveTo investigate the mechanism by which adrenoceptor alpha 2A (Adra2a) regulates lipopolysaccharide (LPS)-induced inflammation in primary hepatocytes from lipopolysaccharide-binding protein (LBP) knockout mice (Lbp^-/-). MethodsPrimary hepatocytes from C57BL/6J and Lbp^-/- mice were isolated using a two-step perfusion method. An in vitro inflammatory model was established by LPS stimulation, and an in vivo inflammatory mouse model was established by intraperitoneal injection of LPS. The in vitro experiments were grouped as follows: Control group, LPS group, BRL+LPS group, OE-NC+LPS group, and OE-Adra2a+LPS group. The Control group served as the blank control. The LPS group involved stimulating primary hepatocytes with LPS. The BRL+LPS group involved pretreating primary hepatocytes with BRL-44408 maleate followed by LPS stimulation. The OE-NC+LPS group involved transfecting primary hepatocytes with an empty vector followed by LPS stimulation. The OE-Adra2a+LPS group involved transfecting primary hepatocytes with a lentivirus overexpressing Adra2a, followed by LPS stimulation. The in vivo experimental groups were divided into Control', LPS', BRL+LPS', OE-NC+LPS', and OE-Adra2a+LPS' groups. The Control' group served as the blank control. The LPS' group received intraperitoneal injection of LPS. The BRL+LPS' group received intraperitoneal injection of BRL-44408 maleate for pretreatment, followed by LPS injection. The OE-NC+LPS' group received intraperitoneal injection of empty vector for pretreatment, followed by LPS injection. The OE-Adra2a+LPS' group received intraperitoneal injection of a lentivirus overexpressing Adra2a for pretreatment, followed by LPS injection. Cell viability after Adra2a inhibition and overexpression was assessed via the Cell Counting Kit-8 (CCK-8) assay. RT-qPCR measured changes in gene expression levels of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and interleukin-1β (IL-1β) after Adra2a inhibition and overexpression. Western blotting was performed to detect Adra2a protein expression and phosphorylation levels of extracellular signal-regulated kinase 1/2 (ERK1/2), p38 mitogen-activated protein kinase, and c-Jun N-terminal kinase (JNK) following LPS stimulation. ResultsIn vitro experiments revealed that LPS stimulation significantly decreased Adra2a protein expression in primary hepatocytes from C57BL/6J mice compared to the Control group (P<0.05), whereas it increased in primary hepatocytes from Lbp^-/- mice (P<0.001). Compared to the LPS group, the BRL+LPS group exhibited significantly increased cell viability (P<0.01), reduced TNF-α, IL-6, and IL-1β gene transcription levels (P<0.01, P<0.001, P<0.001), and decreased phosphorylation levels of MAPK signaling pathway-related proteins ERK1/2, p38, and JNK (P<0.01, P<0.001, P<0.001). Compared with the OE-NC+LPS group, the OE-Adra2a+LPS group showed significantly decreased cell viability (P<0.001), increased gene transcription levels of TNF-α, IL-6, and IL-1β genes (P<0.001, P<0.01, P<0.001), and elevated phosphorylation levels of MAPK signaling pathway-related proteins ERK1/2, p38, and JNK (P<0.001, P<0.01, P<0.001). In vivo experiments showed that, compared with the LPS' group, the BRL+LPS' group exhibited significantly reduced phosphorylation levels of MAPK signaling pathway-related proteins ERK1/2, p38, and JNK (P<0.001, P<0.01, P<0.01). In the OE-Adra2a+LPS' group, the phosphorylation levels of ERK1/2, p38, and JNK were significantly elevated compared to the OE-NC+LPS' group (P<0.01, P<0.001, P<0.01). ConclusionLPS stimulation can cause a significant increase in Adra2a protein expression in primary hepatocytes of Lbp^-/- mice. Adra2a protein can regulate the level of LPS-induced inflammation in primary hepatocytes of Lbp^-/- mice through the MAPK signaling pathway.

Immune-stimulating antibody drug conjugate (ISAC) can not only effectively solve the defects of stimulator of interferon genes (STING) agonists by coupling antibodies with STING agonists through the targeting of antibodies, but also play a synergistic role with antibodies to further improve the efficacy of STING agonists. This review first provides a concise overview of the current research landscape of ISACs and STING agonists, systematically elaborates on evolving trends in STING agonist development, and subsequently summarizes the mechanistic advances in STING ISAC research. Special emphasis is placed on representative STING ISAC candidates in preclinical/clinical development. Finally, the future directions of STING ISACs are critically discussed with perspectives and recommendations, aiming to provide theoretical insights and practical guidance for future investigations.

Objective: To compare the consistency between bioelectrical impedance analysis (BIA) and dual energy X ray absorptiometry (DXA) in measuring body composition among Tibetan children and adolescents and to explore the applicability of BIA in plateau region, so as to provide scientific and convenient body composition measurement support among children and adolescents. Methods: From May to June, 2022, a total of 344 Tibetan children and adolescents aged 6-17 years were selected from Golmud Municipal National Middle School and Changjiangyuan Nationality Primary School in Qinghai Province by cluster sampling method, and their fat mass, fat mass percentage and lean mass were measured by DXA and BIA. The consistency and correlation between the two methods were assessed by using the Wilcoxon rank-sum test, Spearman correlation analysis, intraclass correlation coefficient (ICC), and Bland-Altman analysis. Results: DXA measured fat mass and fat mass percentage were significantly higher than those obtained by BIA (6-12 years old: Z =9.91, 11.28; 13-17 years old: Z =9.02, 10.21), while lean mass and lean mass percentage were significantly lower than BIA results (6-12 years old: Z =-11.60, -11.30; 13-17 years old: Z =-10.77, -10.36) (all P < 0.05 ). The two methods showed strong correlations in fat mass and lean mass (all r >0.80, all ICC >0.90), but exhibited poor agreement in fat mass percentage and lean mass percentage (6-12 years old: Lin s CCC =0.64, 0.41; 13-17 years old: Lin s CCC = 0.79 , 0.35). Bland-Altman analysis showed that the difference between the two methods was negatively correlated with the average value in FM%(6-12 years old: r =-0.75, 13-17 years old: r =-0.79, both P <0.01). Conclusion BIA and DXA show high consistency in measuring body fat mass and lean body mass in Tibetan children and adolescents, although some bias is still present in certain individuals.

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.