Objective To investigate the effect of bone metabolic markers on sarcopenia in elderly patients with type 2 diabetes mellitus (T2DM). Methods A total of 412 patients with T2DM in the department of endocrinology of Nanjing Central Hospital from May 2020 to June 2025 were selected as the research subjects. According to Asian Working Group for Sarcopenia (AWGS) in 2019, these patients were evaluated for skeletal muscle mass index (ASMI), muscle strength, and muscle function, and were divided into a sarcopenia group (84 cases) and a non-sarcopenia group (328 cases). The glucolipid metabolic indexes were detected in both groups of patients, and the bone metabolic markers were evaluated, including procollagen type 1 N-terminal peptide (P1NP), beta-C-terminal telopeptide of type 1 collagen (β-CTX), and 25-hydroxy vitamin D [25-(OH)D]. The factors influencing the occurrence of sarcopenia in T2DM patients were analyzed by logistic regression analysis, and the diagnostic values of bone metabolic markers on sarcopenia in patients with T2DM were assessed by ROC curve. Results The levels of P1NP and 25-(OH)D were lower, while β-CTX level was higher in the sarcopenia group compared to the non-sarcopenia group, with statistical differences (P<0.05). After logistic correlation analysis, it was found that P1NP, β-CTX and 25-(OH)D were all influencing factors for the occurrence of sarcopenia in T2DM patients. ROC curve analysis suggested that combined detection of PINP, β-CTX, and 25-(OH)D had higher diagnostic value, with an area under the curve up to 0.805. Conclusion The abnormal expression of bone metabolic markers is associated with the increased risk of sarcopenia in patients with T2DM. The detection of serum bone metabolic markers expression level is of certain significance for the assessment of diabetes-related sarcopenia.

Objective To evaluate the efficacy and safety of CT-guided percutaneous radiofrequency ablation (RFA) as an alternative for video-assisted thoracoscopic surgery (VATS) in treating multiple pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of 113 patients with multiple pulmonary nodules admitted to Jiangsu Provincial Hospital of Traditional Chinese Medicine from October 2020 to October 2022. The patients were divided into the RFA group (n＝50) and the VATS group (n＝63) based on the treatment method. Perioperative indicators (operation time, intraoperative blood loss, postoperative length of hospital stay), oncological outcomes (recurrence-free survival [RFS], overall survival [OS]), and postoperative complication rates were compared between the two groups. Univariate and multivariate Cox regression analysis was performed to identify independent prognostic factors. Results The operation time in the RFA group was significantly shorter than that in the VATS group ([75.2±20.1] min vs [102.3±28.7]) min, P＜0.001). No statistically significant differences were observed in intraoperative blood loss and postoperative length of hospital stay. After follow-up of 24 (12, 30) months, no statistically significant differences were found in RFS (HR＝1.25, P＝0.445) or OS (HR＝1.42, P＝0.402) between the two groups. Mixed ground-glass nodules with high solid component and solid nodule were identified as independent risk factors for RFS (HR＝2.44, P＝0.023; HR＝2.97, P＝0.007) and OS (HR＝2.87, P＝0.022; HR＝3.43, P＝0.005) in patients with multiple pulmonary nodules. The total complication rate in the RFA group was lower than that in the VATS group (12.0% vs 34.9%, P＝0.009). Conclusions The efficacy of CT-guided RFA in treating multiple pulmonary nodules is comparable to that of VATS, with good safety, and it shows promise as an alternative to surgical treatment for multiple pulmonary nodules.

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.

ObjectivePhotoacoustic pump-probe imaging can effectively eliminate the interference of blood background signal in traditional photoacoustic imaging, and realize the imaging of weak phosphorescence molecules and their triplet lifetimes in deep tissues. However, background differential noise in photoacoustic pump-probe imaging often leads to large fitting results of phosphorescent molecule concentration and triplet lifetime. Therefore, this paper proposes a novel triplet lifetime fitting method for photoacoustic pump-probe imaging. By extracting the phase of the triplet differential signal and the background noise, the fitting bias caused by the background noise can be effectively corrected. MethodsThe advantages and feasibility of the proposed algorithm are verified by numerical simulation, phantom and in vivo experiments, respectively. ResultsIn the numerical simulation, under the condition of noise intensity being 10% of the signal amplitude, the new method can optimize the fitting deviation from 48.5% to about 5%, and has a higher exclusion coefficient (0.88>0.79), which greatly improves the fitting accuracy. The high specificity imaging ability of photoacoustic pump imaging for phosphorescent molecules has been demonstrated by phantom experiments. In vivo experiments have verified the feasibility of the new fitting method proposed in this paper for fitting phosphoometric lifetime to monitor oxygen partial pressure content during photodynamic therapy of tumors in nude mice. ConclusionThis work will play an important role in promoting the application of photoacoustic pump-probe imaging in biomedicine.

In 2022， Hainan provincial government launched the project for the prevention and control of viral hepatitis with the goals of a hepatitis B screening rate of 90%， a diagnostic rate of 90%， and a treatment rate of 80% among people aged 18 years and above by the year 2025， and the main intervention measures include population-based prevention， case screening， antiviral therapy， and health management. As of December 31， 2024， a total of 6.875 million individuals in the general population had been screened for hepatitis B， with a screening rate of 95.6%. A total of 184 710 individuals with positive HBsAg were identified， among whom 156 772 were diagnosed through serological reexamination， resulting in a diagnostic rate of 84.9%. A total of 50 742 patients with chronic hepatitis B were identified， among whom 42 921 had hepatitis B-specific health records established for health management， with a file establishment rate of 84.6%. A total of 31 553 individuals received antiviral therapy， with a treatment rate of 62.2%. A total of 2.503 million individuals at a high risk of hepatitis C were screened， among whom 4 870 tested positive for HCV antibody and 3 858 underwent HCV RNA testing， resulting in a diagnostic rate of 79.2%， and 1 824 individuals with positive HCV RNA were identified， among whom 1 194 received antiviral therapy， with a treatment rate of 65.5%. In addition， 159 301 individuals with negative HBsAg and anti-HBs and an age of 20 — 40 years were inoculated with hepatitis B vaccine free of charge. Through the implementation of the project for the prevention and control of viral hepatitis， a large number of hepatitis patients have been identified， treated， and managed in the province within a short period of time， which significantly accelerates the efforts to eliminate the crisis of viral hepatitis.

Obsessive-compulsive disorder （OCD） is a highly disabling mental disorder that impairs patients' social function and quality of life， and impose a substantial economic burden. Intolerance of uncertainty （IU） refers to a cognitive bias in perceiving， interpreting and responding to uncertain situations or events. IU is closely associated with the cognitive patterns of OCD patients. Based on magnetic resonance imaging （MRI）， this paper discusses the research progress of the relationship between IU and psychopathological characteristics of OCD， and put forward the research direction， aims to provide evidence-based references for the development of optimized therapeutic interventions for OCD.

ObjectiveTo optimize the processing technology of honey bran-fried Rosae Laevigatae Fructus（h-RLF）， formulate relevant quality standards， and explore its improving effect and mechanism on mice with ulcerative colitis（UC） induced by dextran sodium sulfate（DSS）. MethodsTaking the content of polysaccharides and water-soluble extract as the indexes， L₉（3⁴） orthogonal test was used to optimize parameters of the amount of honey bran， frying time and frying temperature. The quality of 15 batches of h-RLF decoction pieces was evaluated according to the optimized process， and the inspection limit standard was preliminarily drawn up. Eighty SPF male Kunming mice were randomly divided into 8 groups， including the blank group， model group， mesalazine group（0.13 g·kg^-1）， RLF group（3.77 g·kg^-1）， bran-fried RLF group（3.77 g·kg^-1）， h-RLF low， medium and high dose groups（1.89， 3.77， 7.54 g·kg^-1）， with 10 mice in each group. The mice in the blank group were free to drink pure water， and the other groups were free to drink 3% DSS solution for 7 days to prepare UC mouse model. Each treatment group was given corresponding drugs by intragastric administration， and the blank and model groups were given equal volume of normal saline. The body weight of mice was recorded daily and the disease activity index（DAI） was calculated. After the administration， the colon tissues of mice were collected to observe the pathological changes by hematoxylin-eosin（HE） staining. The levels of tumor necrosis factor（TNF）-α， interleukin（IL）-1β， IL-6 and IL-10 in the colon of mice were detected by enzyme-linked immunosorbent assay（ELISA）. Western blot was used to detect the expression levels of phosphorylation nuclear transcription factor-κB p65（p-NF-κB p65）， Toll-like receptor 4（TLR4）， p-p38 mitogen-activated protein kinase（p-p38 MAPK）， p-extracellular signal-regulated kinase（p-ERK） and p-c-Jun N-terminal kinase（p-JNK） proteins in colon tissues. ResultsThe optimum processing technology of h-RLF was 20 g honey bran per 100 g RLF， and stir-frying at 200 ℃ for 8 min. The limit standard under the examination of h-RLF was preliminarily formulated as follows：the polysaccharide content should not be less than 25% based on anhydrous glucose（C₆H₁₂O₆）， the content of water-soluble extract should not be less than 38%， the moisture content should not be more than 12.0%， the total ash content should not be more than 5.0%， and the acid-insoluble ash content should not be more than 1.0%. The cluster heat map analysis showed that the quality of RLF from Huanggang， Hubei province was better. Animal experiments showed that compared with the blank group， the DAI score of the model group was significantly increased， the levels of TNF-α， IL-1β and IL-6 in the colon tissue were significantly increased， the IL-10 level was significantly decreased， the colonic mucosa was seriously damaged， accompanied by a large number of inflammatory cell infiltration， tissue congestion and a significant reduction in glands， and the expression levels of p-NF-κB p65， TLR4， p-p38 MAPK， p-ERK and p-JNK proteins were significantly increased（P<0.01）. Compared with the model group， each administration group could alleviate the symptoms of colonic ulcer， the structure of colonic crypt was basically intact， and the glands were arranged in an orderly manner. Among them， the high-dose group of h-RLF had a better effect， which could significantly reduce the DAI score and the levels of TNF-α， IL-1β and IL-6 in colon tissue（P<0.01）， and significantly increase the level of IL-10（P<0.01）， alleviate the colonic mucosal injury， and effectively inhibit the expression levels of p-NF-κB p65， TLR4， p-p38 MAPK， p-ERK and p-JNK proteins（P<0.01）. ConclusionThe key parameters of the processing technology of h-RLF are determined， and the optimized technology is stable and feasible. The established quality standard is simple and reliable， and can be used for the quality control. h-RLF can effectively alleviate DSS-induced UC， and its mechanism may be related to inhibiting the activation of NF-κB/TLR4/MAPK pathway.

This narrative review examines the challenges, strategies, and future directions in the development of young teachers within the pathophysiology departments of Chinese medical colleges. A thorough review of 49 studies published between 2013 and 2024 was carried out using PubMed, Web of Science, and various Chinese databases. The primary challenges identified include teaching innovation (cited in 84.2% of the studies), research pressure (91.2%), disciplinary characteristics (87.7%), and career development (80.7%). Medical schools have responded by enhancing training systems (94.7%), innovating teaching methods (93.0%), and bolstering research support (96.5%). Looking ahead, trends are shifting toward the application of new technologies, interdisciplinary integration, and international collaboration. The focus on cultivating young teachers is increasingly geared towards personalization and diversification, which are essential for advancing education in pathophysiology. High-quality young teachers are pivotal in raising teaching standards, fostering research innovation, and facilitating interdisciplinary exchanges. Based on these insights, we recommend several practical measures to enhance the quality of pathophysiology education in China. These include establishing comprehensive training programs that integrate teaching innovation and research skills; developing structured mentorship systems with clear pathways for career advancement; creating platforms that support technology-enhanced teaching and international collaboration; and implementing systematic evaluation mechanisms to assess teaching effectiveness. These targeted interventions will require a coordinated effort from department heads, educational institutions, and policymakers to ensure a sustained improvement in the quality of pathophysiology education.

This narrative review examines the challenges, strategies, and future directions in the development of young teachers within the pathophysiology departments of Chinese medical colleges. A thorough review of 49 studies published between 2013 and 2024 was carried out using PubMed, Web of Science, and various Chinese databases. The primary challenges identified include teaching innovation (cited in 84.2% of the studies), research pressure (91.2%), disciplinary characteristics (87.7%), and career development (80.7%). Medical schools have responded by enhancing training systems (94.7%), innovating teaching methods (93.0%), and bolstering research support (96.5%). Looking ahead, trends are shifting toward the application of new technologies, interdisciplinary integration, and international collaboration. The focus on cultivating young teachers is increasingly geared towards personalization and diversification, which are essential for advancing education in pathophysiology. High-quality young teachers are pivotal in raising teaching standards, fostering research innovation, and facilitating interdisciplinary exchanges. Based on these insights, we recommend several practical measures to enhance the quality of pathophysiology education in China. These include establishing comprehensive training programs that integrate teaching innovation and research skills; developing structured mentorship systems with clear pathways for career advancement; creating platforms that support technology-enhanced teaching and international collaboration; and implementing systematic evaluation mechanisms to assess teaching effectiveness. These targeted interventions will require a coordinated effort from department heads, educational institutions, and policymakers to ensure a sustained improvement in the quality of pathophysiology education.

This narrative review examines the challenges, strategies, and future directions in the development of young teachers within the pathophysiology departments of Chinese medical colleges. A thorough review of 49 studies published between 2013 and 2024 was carried out using PubMed, Web of Science, and various Chinese databases. The primary challenges identified include teaching innovation (cited in 84.2% of the studies), research pressure (91.2%), disciplinary characteristics (87.7%), and career development (80.7%). Medical schools have responded by enhancing training systems (94.7%), innovating teaching methods (93.0%), and bolstering research support (96.5%). Looking ahead, trends are shifting toward the application of new technologies, interdisciplinary integration, and international collaboration. The focus on cultivating young teachers is increasingly geared towards personalization and diversification, which are essential for advancing education in pathophysiology. High-quality young teachers are pivotal in raising teaching standards, fostering research innovation, and facilitating interdisciplinary exchanges. Based on these insights, we recommend several practical measures to enhance the quality of pathophysiology education in China. These include establishing comprehensive training programs that integrate teaching innovation and research skills; developing structured mentorship systems with clear pathways for career advancement; creating platforms that support technology-enhanced teaching and international collaboration; and implementing systematic evaluation mechanisms to assess teaching effectiveness. These targeted interventions will require a coordinated effort from department heads, educational institutions, and policymakers to ensure a sustained improvement in the quality of pathophysiology education.