BACKGROUND:The prevalence of osteoporosis is high in postmenopausal women,but muscle mass,grip strength,and how these factors affect osteoporosis are understudied,and the exact link between them has not been clarified.OBJECTIVE:To investigate the correlation between muscle mass,grip strength,appendicular skeletal muscle index and bone mineral density in postmenopausal women with osteoporosis and to assess the potential values of these indices in predicting and diagnosing postmenopausal osteoporosis.METHODS:Eighty-three postmenopausal women were collected from the outpatient clinic of the Third Affiliated Hospital of Guangzhou University of Chinese Medicine from February 2023 to January 2024.General data were collected.Bone mineral density was detected.T-value,muscle mass of each part,grip strength were recorded.The body mass index and appendicular skeletal muscle index were calculated.The patients were categorized into non-osteoporosis group(n=17)and postmenopausal osteoporosis group(n=66)according to T value and fracture history,and were statistically analyzed accordingly.RESULTS AND CONCLUSION:(1)The body mass,body mass index,bone mineral density of the overall lumbar spine,muscle mass and appendicular skeletal muscle index were higher in the non-osteoporosis group than the osteoporosis group(P＜0.05).(2)Muscle mass was positively correlated with bone mineral density of the overall lumbar spine and individual vertebrae(P＜0.05).(3)Multiple stepwise linear regression analysis showed that body mass and grip strength were linearly and positively correlated with muscle mass;body height and muscle mass were linearly and positively correlated with grip strength,and body mass was linearly and negatively correlated with grip strength.Body mass index was linearly and positively correlated with bone mineral density,and age was linearly and negatively correlated with bone mineral density.(4)Analysis by receiver operating characteristic curve showed that:muscle mass(the area under the curve,sensitivity,specificity and critical value of muscle mass were 0.744,76.50％,74.20％and 36.50 kg,respectively,with P=0.002)and appendicular skeletal muscle index(the area under the curve,sensitivity,specificity and critical value of appendicular skeletal muscle index were 0.739,82.40％,62.10％and 5.81 kg/m2,respectively,and P=0.002)had good predictive value for postmenopausal osteoporosis.To conclude,a reduction in muscle mass and appendicular skeletal muscle index can help to predict the risk of postmenopausal osteoporosis,and the possibility of osteoporosis should be taken into account in postmenopausal women when muscle mass is＜36.50 kg or appendicular skeletal muscle index is＜5.81 kg/m2,in order to prevent the occurrence of postmenopausal osteoporosis.

Objective To prepare Zanthoxylum alkaloid thermosensitive hydrogel, optimize the preparation process and conduct related performance studies. Methods Zanthoxylum alkaloids were obtained by reflux extraction, followed by enrichment and purification using macroporous adsorption resin. Poloxamer 407 and Poloxamer 188 were used as substrates to prepare the thermosensitive hydrogel of Zanthoxylum alkaloids, and the preparation process was optimized by orthogonal design. The quality of the hydrogel was systematically evaluated based on its gelation temperature, gelation time, Fourier transform infrared （FTIR） spectroscopy, scanning electron microscopy （SEM） images, mechanical properties, and in vitro release profile. Results The optimal preparation conditions for the Zanthoxylum alkaloid thermosensitive hydrogel were: 20% （g/ml） poloxamer 407, 2% （g/ml） poloxamer 188 and 100 μg/ml Zanthoxylum alkaloid. The gelation temperature was 32.6℃, and the average gelling time was 143.3 s. The hydrogel appeared as a transparent liquid at room temperature and was transformed into a semi-solid gel state when the temperature exceeded 33℃. Experimental results confirmed the successful preparation of poloxamer 407 and poloxamer 188 thermosensitive hydrogel loaded with Zanthoxylum alkaloids, which exhibited good bio adhesion, self-healing properties, and tensile strength. Conclusion The Zanthoxylum alkaloid thermosensitive hydrogel demonstrated favorable mechanical properties and a sustained-release effect, showing promising potential for further development and application.

Objective To establish a central cutting two-dimensional liquid chromatography for the determination of lamotrigine in human plasma. Methods External standard method was used. The first dimensional chromatographic column: SNCB（T）-1A（silica gel, 4.6 mm×50 mm, 5 μm）, mobile phase A:VCV-1D mobile phase, flow rate: 0.4 ml/min; mobile phase B: water, flow rate: 1.0 ml/min; second dimensional chromatographic column: Symmetry C₁₈ （4.6 mm×250 mm, 5 μm）, mobile phase: acetonitrile-10 mmol/L ammonium acetate solution（V/V=25∶75）, flow rate: 1.0 ml/min；Intermediate column: SBX 4-MA（resin, 3.0 mm×10 mm, 5µm）. The UV detection wavelength：306 nm, the column temperature：45 ℃, and the injection volume：200 μl. Results The linear range of lamotrigine was 1.24-39.50 μg/ml, the lower limit of quantification was 1.24 μg/ml, the detection limit was 0.02 μg/ml, the intra-day precision RSD was less than 5%, the day-to-day precision RSD was less than 10%, the variation of intra-day accuracy ranged from 102.17% to 111.17%, and the daytime accuracy variation ranged from 99.80% to 107.31% the recovery RSD was less than 5%, and the variation range was 89.95% -96.16%. After 24 hours storage at room temperature, repeated freezing and thawing for 3 times and storage at −40 ℃ for 2 weeks, the ratio of the measured value/labeled value ranged from 87.01% to 115.88%. Conclusion In this study, a method with simple operation, good stability, high sensitivity and good reproducibility was established, which could be suitable for clinical monitoring of blood concentration of lamotrigine and provide reliable monitoring data support for clinical individualized medication guidance.

Objective To explore the role of resilience and stress in childhood maltreatment and adolescent depression and anxiety symptoms, and to provide a basis for adolescent psychological intervention. Methods From September to October 2022, a total of 11 217 students from four middle schools in Changsha were selected by multistage stratified sampling, and the Childhood Trauma Questionnaire, Depression–Anxiety–Stress Scales and the Resilience Scale for Chinese Adolescents were used to carry out online questionnaire survey. Results The detection rate of depressive symptoms and anxiety symptoms in adolescent was 19.43% (2 179) and 28.7% (3 224). The direct effect of childhood maltreatment on depressive symptoms was significant (β =0.09), Childhood maltreatment is a negative prediction of resilience (β = -0.57) and a positive prediction of pressure (β =0.06); Resilience can negatively predict stress (β = -0.61) and depressive symptoms (β = -0.25) (all P values <0.001); The direct effect of childhood maltreatment on anxiety symptoms was significant (β =0.03), resilience negatively predicts anxiety symptoms (β = -0.08) (all P values <0.01). Resilience and stress have a partially mediating role between childhood maltreatment and depressive symptoms, the mediation effect value was 0.39, accounting for 81.25% of the total effect. The effect values of the three pathways accounted for 29.17%, 8.33% and 43.75% of the total effect, respectively. Resilience and stress have a partial mediating effect between childhood abuse and anxiety symptoms, and the mediating effect was 0.36, accounting for 92.31% of the total effect, and the effect values of the three pathways accounted for 12.82%, 10.26% and 69.23% of the total effect, respectively. Conclusion Childhood maltreatment could affect adolescents’ depression and anxiety through the chain mediating effect of resilience and stress.

Intervertebral disc degeneration (IVDD) is the predominant pathological contributor to chronic low back pain, a pervasive musculoskeletal condition affecting over 630 million people globally and imposing tremendous socioeconomic and public health burdens. The etiopathogenesis of IVDD is remarkably complex and multifactorial, involving intricate crosstalk among chronic inflammatory responses, extracellular matrix (ECM) catabolism, cellular senescence, aberrant programmed cell death (including apoptosis, pyroptosis, and ferroptosis), mitochondrial dysfunction, and oxidative damage. Compelling evidence indicates that the inflammatory microenvironment acts as a decisive driving force throughout the entire degenerative course of IVDD. Among the diverse inflammatory mediators, interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) serve as core pro-inflammatory cytokines that initiate and perpetuate the degenerative cascade. These two pivotal cytokines collectively activate an array of canonical intracellular signaling pathways, including nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) inflammasome, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) cascade. Such interconnected signaling networks trigger a self-reinforcing positive feedback loop, which exacerbates inflammatory reactions, disrupts the anabolic-catabolic homeostasis of the ECM, promotes oxidative stress and mitochondrial injury, induces multiple forms of disc cell death, and ultimately leads to progressive structural collapse and functional deterioration of the intervertebral disc. Conventional therapeutic strategies, dominated by nonsteroidal anti-inflammatory drugs and surgical interventions, are limited by systemic adverse reactions, suboptimal long-term efficacy, and the risk of adjacent segment degeneration. In contrast, traditional Chinese medicine (TCM) exhibits prominent advantages in the prevention and treatment of IVDD by virtue of its holistic regulation, syndrome differentiation, and multi-component, multi-target, multi-pathway pharmacological properties. This review systematically elucidates the molecular mechanisms by which inflammation-associated signaling pathways modulate disc cell fate and ECM metabolic homeostasis, and comprehensively summarizes the experimental progress over the past five years on TCM monomers and compound formulas for intervening in IVDD. Accumulating studies have confirmed that numerous natural active ingredients isolated from herbal medicines (ferulic acid, mangiferin, paeonol, astragaloside IV) and representative TCM compound prescriptions (Bushen Huoxue Formula, Shensuitongzhi Formula, Fuzi Decoction) exert synergistic protective effects by coordinately targeting core signaling hubs. These TCM agents demonstrate potent anti-inflammatory, antioxidant, anti-apoptotic, anti-pyroptotic, anti-ferroptotic, ECM-protective, and autophagy-regulating bioactivities, thereby effectively decelerating the pathological progression of IVDD. Despite remarkable progress, current investigations are still confronted by several critical limitations. Most studies are restricted to validating the regulatory effects of single TCM components on individual signaling pathways, leaving the systematic, dynamic, and synergistic mechanisms of TCM compound formulas within multi-pathway regulatory networks largely unexplored. Furthermore, clinical translation of TCM is severely hampered by the lack of efficient targeted drug delivery systems, unclear pharmacokinetic profiles, suboptimal local bioavailability, and incomplete long-term safety assessments. Therefore, future research should adopt an interdisciplinary paradigm integrating multi-omics technologies, artificial intelligence, organoid models, and organ-on-chip systems to systematically decipher the scientific basis of TCM against IVDD. Concurrently, the development of intelligent, site-specific delivery systems (hydrogels, nanoparticles, exosome-based carriers) is urgently needed to enhance the local accumulation and sustained release of TCM ingredients. By deepening mechanistic exploration and accelerating translational research, TCM is expected to evolve into safe, effective, and personalized precision therapeutic regimens for IVDD, offering novel and reliable solutions for the clinical management of chronic low back pain.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveTo analyze the comorbidity patterns of chronic metabolic diseases and their influencing factors among residents aged 35‒75 years old in Nantong City of Jiangsu Province, and to provide theoretical support for the prevention and control of comorbidities. MethodsThe permanent residents aged 35‒75 years from the Comprehensive Prevention and Control Project of Cardiovascular and Cerebrovascular Diseases in Nantong City from 2021 to 2024 were selected as the research subjects. Clustering analysis and association rule were used to investigate the comorbidity patterns of chronic metabolic diseases, and their influencing factors were identified through logistic regression analyses. ResultsThe prevalence of comorbidity of chronic metabolic diseases among residents aged 35‒75 years in Nantong City was 47.40%. Among comorbidity patterns based on disease counts, the prevalence of hypertension+dyslipidemia was highest in binary comorbidity patterns (6.25%), while that of hypertension+dyslipidemia+obesity was highest in ternary comorbidity patterns (4.01%). Association rules showed that in both binary and ternary comorbidity patterns, the confidence level was highest for obesity+hypertension (72.70%) and obesity+dyslipidemia+hypertension (74.54%). Renal insufficiency formed an independent cluster in cluster analyses. Logistic regression analyses revealed that, compared with the non-comorbidity group, males (OR=2.22, 95%CI: 1.69‒2.91), advanced age (45‒54 years, OR=1.38, 95%CI: 1.02‒1.88; 55‒64 years, OR=1.59, 95%CI: 1.14‒2.23; 65‒75 years, OR=2.34, 95%CI: 1.58‒3.47), and low physical activity (OR=1.26, 95%CI: 1.10‒1.65) were influencing factors for metabolic disease comorbidity. ConclusionIn the comorbidity patterns of chronic metabolic diseases among residents aged 35‒75 years in Nantong City, hypertension, diabetes mellitus, and dyslipidemia interact with each other. Individuals with obesity are more prone to diseases such as hypertension and dyslipidemia. Prevention and control of chronic metabolic diseases should be strengthened for males, individuals with low physical activity and advanced age.

Intervertebral disc degeneration (IVDD) is the predominant pathological contributor to chronic low back pain, a pervasive musculoskeletal condition affecting over 630 million people globally and imposing tremendous socioeconomic and public health burdens. The etiopathogenesis of IVDD is remarkably complex and multifactorial, involving intricate crosstalk among chronic inflammatory responses, extracellular matrix (ECM) catabolism, cellular senescence, aberrant programmed cell death (including apoptosis, pyroptosis, and ferroptosis), mitochondrial dysfunction, and oxidative damage. Compelling evidence indicates that the inflammatory microenvironment acts as a decisive driving force throughout the entire degenerative course of IVDD. Among the diverse inflammatory mediators, interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) serve as core pro-inflammatory cytokines that initiate and perpetuate the degenerative cascade. These two pivotal cytokines collectively activate an array of canonical intracellular signaling pathways, including nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) inflammasome, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) cascade. Such interconnected signaling networks trigger a self-reinforcing positive feedback loop, which exacerbates inflammatory reactions, disrupts the anabolic-catabolic homeostasis of the ECM, promotes oxidative stress and mitochondrial injury, induces multiple forms of disc cell death, and ultimately leads to progressive structural collapse and functional deterioration of the intervertebral disc. Conventional therapeutic strategies, dominated by nonsteroidal anti-inflammatory drugs and surgical interventions, are limited by systemic adverse reactions, suboptimal long-term efficacy, and the risk of adjacent segment degeneration. In contrast, traditional Chinese medicine (TCM) exhibits prominent advantages in the prevention and treatment of IVDD by virtue of its holistic regulation, syndrome differentiation, and multi-component, multi-target, multi-pathway pharmacological properties. This review systematically elucidates the molecular mechanisms by which inflammation-associated signaling pathways modulate disc cell fate and ECM metabolic homeostasis, and comprehensively summarizes the experimental progress over the past five years on TCM monomers and compound formulas for intervening in IVDD. Accumulating studies have confirmed that numerous natural active ingredients isolated from herbal medicines (ferulic acid, mangiferin, paeonol, astragaloside IV) and representative TCM compound prescriptions (Bushen Huoxue Formula, Shensuitongzhi Formula, Fuzi Decoction) exert synergistic protective effects by coordinately targeting core signaling hubs. These TCM agents demonstrate potent anti-inflammatory, antioxidant, anti-apoptotic, anti-pyroptotic, anti-ferroptotic, ECM-protective, and autophagy-regulating bioactivities, thereby effectively decelerating the pathological progression of IVDD. Despite remarkable progress, current investigations are still confronted by several critical limitations. Most studies are restricted to validating the regulatory effects of single TCM components on individual signaling pathways, leaving the systematic, dynamic, and synergistic mechanisms of TCM compound formulas within multi-pathway regulatory networks largely unexplored. Furthermore, clinical translation of TCM is severely hampered by the lack of efficient targeted drug delivery systems, unclear pharmacokinetic profiles, suboptimal local bioavailability, and incomplete long-term safety assessments. Therefore, future research should adopt an interdisciplinary paradigm integrating multi-omics technologies, artificial intelligence, organoid models, and organ-on-chip systems to systematically decipher the scientific basis of TCM against IVDD. Concurrently, the development of intelligent, site-specific delivery systems (hydrogels, nanoparticles, exosome-based carriers) is urgently needed to enhance the local accumulation and sustained release of TCM ingredients. By deepening mechanistic exploration and accelerating translational research, TCM is expected to evolve into safe, effective, and personalized precision therapeutic regimens for IVDD, offering novel and reliable solutions for the clinical management of chronic low back pain.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Purpose: Metastatic rectal cancer (mRC) is a highly lethal and complex disease that demands a multidisciplinary treatment approach. However, the clinical effectiveness of radiotherapy (RT) for de novo mRC remains controversial and uncertain. Methods: This retrospective cohort study examined medical records from Kaohsiung Chang Gung Memorial Hospital for patients with histologically confirmed de novo mRC diagnosed between January 2015 and December 2020. All patients received standard systemic therapy and radical surgery when feasible. The primary outcome, overall survival (OS), was assessed using the Kaplan-Meier method. Multivariable analysis was performed using a Cox regression model. Results: Among 271 patients included in the analysis, 117 received RT and 154 did not. The median OS was significantly longer in the RT group compared with the non-RT group (27.8 months vs. 21.9 months; P=0.046). Multivariate analysis identified several independent predictors of OS: age ≥65 years (hazard ratio [HR], 1.69; 95% confidence interval [CI], 1.26–2.27; P=0.001), primary tumor resection (HR, 2.62; 95% CI, 1.90–3.61; P<0.001), M1b or M1c disease (HR, 1.97; 95% CI, 1.44–2.69; P<0.001), and receipt of RT (HR, 1.41; 95% CI, 1.02–1.94; P=0.036). Conclusion RT significantly improves OS in patients with mRC, underscoring its role in treatment strategies. These findings support its inclusion in therapeutic protocols and highlight the need for larger, multicenter trials to confirm and extend these results.