BACKGROUND:Collagen combined with microneedling therapy has gradually become an important means of improving skin photoaging.OBJECTIVE:To summarize and explore the main mechanism and clinical application status of collagen combined with microneedle therapy.METHODS:PubMed,China National Knowledge Infrastructure,and ScienceDirect databases were searched for Chinese and English literature published before August 2024.Chinese and English search terms were"ultraviolet radiation,photoaging,collagen,microneedling,clinical applications."Finally,74 articles were included for summary.RESULTS AND CONCLUSION:Collagen treats skin photoaging through mechanisms such as inhibiting matrix metalloproteinase expression,retaining skin moisture,and reducing melanin formation.Microneedles can better promote the penetration of collagen into deep layers of the skin,breaking down the skin's barrier and increasing the absorption rate.Collagen combined with microneedles has various beneficial effects for treating skin photoaging,such as whitening,anti-wrinkle,improving skin elasticity,shrinking pores,and repairing skin barriers.It also has the advantages of easy operation,significant effects,and high safety.Currently,the research on collagen combined with microneedling therapy is still in its early stages,and achieving clinical application may become a key research direction in the future.The clinical application of collagen combined with microneedles for the treatment of photoaging still faces many challenges,such as exploring the optimal mechanical structure and materials of microneedles,selecting appropriate microneedle types,and insufficient clinical evidence that collagen combined with microneedles can further delay the treatment of skin photoaging.

BACKGROUND:Several observational studies have found a strong association between thyroid function and its related disorders and osteoporosis,but the causal relationship is unclear.OBJECTIVE:To ascertain the causal relationship between genetically predicted thyroid function and its associated disorders,as well as osteoporosis,through the Mendelian randomization analysis with extensive pooled genetic data.METHODS:Pooled data from genome-wide association studies were employed to investigate the causal relationship between thyroid function and its associated disorders and osteoporosis.This was achieved through the utilization of the inverse variance weighting method as the primary Mendelian randomization analysis method,in conjunction with the MR-Egger method,weighted median method,simple model method,and weighted model method.A two-step mediated Mendelian randomization analysis was used to calculate the mediating effect of drug-mediated thyroid dysfunction on osteoporosis and the mediating proportion.Subsequently,sensitivity analyses were conducted using the MR-Egger intercept test and MR-PRESSO to detect multiplicity,Cochran's Q test to detect heterogeneity,and leave-one-out to perform sensitivity analyses.RESULTS AND CONCLUSION:(1)The results of the inverse variance weighting method showed that thyroid function had an effect on bone mineral density,and that thyrotropin,free triiodothyronine on bone mineral density,free thyroxine,and subclinical hyperthyroidism all had a causal effect on bone mineral density.(2)In addition,mediation analyses revealed a potential mediating effect of carbimazole in the causal relationship between hyperthyroidism and the risk of developing osteoporosis,as well as a potential mediating effect of levothyroxine sodium in the causal relationship between hypothyroidism and the risk of developing osteoporosis.(3)In conclusion,thyrotropin,which is high in the normal range,has been demonstrated to increase bone mineral density.Conversely,free triiodothyronine and free thyroxine,which are also high within the normal range,as well as subclinical hyperthyroidism,have been shown to decrease bone mineral density.The risk of developing osteoporosis is partially mediated by the pathway of taking the therapeutic medication in the context of pharmacologic treatment of thyroid dysfunction.(4)The present study primarily focuses on European population data.However,given the commonality of the genetic background and the generalizability of genome-wide data analysis methods,it is of significant importance to explore the pathogenesis of osteoporosis in the Chinese population,develop effective interventions,and provide genetic counseling.

BACKGROUND:Epidemiological studies indicate that individuals with neurodegenerative diseases exhibit a comparatively lower risk of developing the majority of cancers.Although the precise mechanisms underlying this inverse correlation remain unclear,it is noteworthy that aberrant glucose metabolism,a pathological factor common to both conditions,may significantly contribute to this association.OBJECTIVE:To review the potential relationship between cancers and neurodegenerative diseases in glucose metabolism.METHODS:PubMed was searched for relevant literature using the search terms of"cancer,neurodegenerative diseases,Alzheimer's disease,Parkinson's disease,metabolic reprogramming,glucose metabolism,aerobic glycolysis,neuroprotection,aging,"and 136 articles were finally included for analysis.RESULTS AND CONCLUSION:Cancer and neurodegenerative diseases exhibit a profound pathological correlation at the level of glucose metabolism imbalance associated with aging.Cancer cells promote uncontrolled proliferation,invasion,and metastasis through the persistent activation of aerobic glycolysis,whereas neurodegenerative diseases are characterized by a reduction in aerobic glycolysis.Restoring aerobic glycolysis may confer neuroprotective effects and delay disease progression.The key nodes of glucose metabolism demonstrate a bidirectional regulatory pattern:metabolic regulators,which are significantly upregulated or aberrantly activated in cancer,are inhibited or functionally inactivated in neurodegenerative diseases.Mitochondria play a crucial role in mediating the aging process through the regulation of reactive oxygen species homeostasis and mitochondrial autophagy.They establish regulatory networks that connect cancer and neurodegenerative diseases,and maintaining their functional homeostasis is of paramount importance for disease prevention and treatment.

BACKGROUND:Collagen combined with microneedling therapy has gradually become an important means of improving skin photoaging.OBJECTIVE:To summarize and explore the main mechanism and clinical application status of collagen combined with microneedle therapy.METHODS:PubMed,China National Knowledge Infrastructure,and ScienceDirect databases were searched for Chinese and English literature published before August 2024.Chinese and English search terms were"ultraviolet radiation,photoaging,collagen,microneedling,clinical applications."Finally,74 articles were included for summary.RESULTS AND CONCLUSION:Collagen treats skin photoaging through mechanisms such as inhibiting matrix metalloproteinase expression,retaining skin moisture,and reducing melanin formation.Microneedles can better promote the penetration of collagen into deep layers of the skin,breaking down the skin's barrier and increasing the absorption rate.Collagen combined with microneedles has various beneficial effects for treating skin photoaging,such as whitening,anti-wrinkle,improving skin elasticity,shrinking pores,and repairing skin barriers.It also has the advantages of easy operation,significant effects,and high safety.Currently,the research on collagen combined with microneedling therapy is still in its early stages,and achieving clinical application may become a key research direction in the future.The clinical application of collagen combined with microneedles for the treatment of photoaging still faces many challenges,such as exploring the optimal mechanical structure and materials of microneedles,selecting appropriate microneedle types,and insufficient clinical evidence that collagen combined with microneedles can further delay the treatment of skin photoaging.

BACKGROUND:Several observational studies have found a strong association between thyroid function and its related disorders and osteoporosis,but the causal relationship is unclear.OBJECTIVE:To ascertain the causal relationship between genetically predicted thyroid function and its associated disorders,as well as osteoporosis,through the Mendelian randomization analysis with extensive pooled genetic data.METHODS:Pooled data from genome-wide association studies were employed to investigate the causal relationship between thyroid function and its associated disorders and osteoporosis.This was achieved through the utilization of the inverse variance weighting method as the primary Mendelian randomization analysis method,in conjunction with the MR-Egger method,weighted median method,simple model method,and weighted model method.A two-step mediated Mendelian randomization analysis was used to calculate the mediating effect of drug-mediated thyroid dysfunction on osteoporosis and the mediating proportion.Subsequently,sensitivity analyses were conducted using the MR-Egger intercept test and MR-PRESSO to detect multiplicity,Cochran's Q test to detect heterogeneity,and leave-one-out to perform sensitivity analyses.RESULTS AND CONCLUSION:(1)The results of the inverse variance weighting method showed that thyroid function had an effect on bone mineral density,and that thyrotropin,free triiodothyronine on bone mineral density,free thyroxine,and subclinical hyperthyroidism all had a causal effect on bone mineral density.(2)In addition,mediation analyses revealed a potential mediating effect of carbimazole in the causal relationship between hyperthyroidism and the risk of developing osteoporosis,as well as a potential mediating effect of levothyroxine sodium in the causal relationship between hypothyroidism and the risk of developing osteoporosis.(3)In conclusion,thyrotropin,which is high in the normal range,has been demonstrated to increase bone mineral density.Conversely,free triiodothyronine and free thyroxine,which are also high within the normal range,as well as subclinical hyperthyroidism,have been shown to decrease bone mineral density.The risk of developing osteoporosis is partially mediated by the pathway of taking the therapeutic medication in the context of pharmacologic treatment of thyroid dysfunction.(4)The present study primarily focuses on European population data.However,given the commonality of the genetic background and the generalizability of genome-wide data analysis methods,it is of significant importance to explore the pathogenesis of osteoporosis in the Chinese population,develop effective interventions,and provide genetic counseling.

BACKGROUND:Epidemiological studies indicate that individuals with neurodegenerative diseases exhibit a comparatively lower risk of developing the majority of cancers.Although the precise mechanisms underlying this inverse correlation remain unclear,it is noteworthy that aberrant glucose metabolism,a pathological factor common to both conditions,may significantly contribute to this association.OBJECTIVE:To review the potential relationship between cancers and neurodegenerative diseases in glucose metabolism.METHODS:PubMed was searched for relevant literature using the search terms of"cancer,neurodegenerative diseases,Alzheimer's disease,Parkinson's disease,metabolic reprogramming,glucose metabolism,aerobic glycolysis,neuroprotection,aging,"and 136 articles were finally included for analysis.RESULTS AND CONCLUSION:Cancer and neurodegenerative diseases exhibit a profound pathological correlation at the level of glucose metabolism imbalance associated with aging.Cancer cells promote uncontrolled proliferation,invasion,and metastasis through the persistent activation of aerobic glycolysis,whereas neurodegenerative diseases are characterized by a reduction in aerobic glycolysis.Restoring aerobic glycolysis may confer neuroprotective effects and delay disease progression.The key nodes of glucose metabolism demonstrate a bidirectional regulatory pattern:metabolic regulators,which are significantly upregulated or aberrantly activated in cancer,are inhibited or functionally inactivated in neurodegenerative diseases.Mitochondria play a crucial role in mediating the aging process through the regulation of reactive oxygen species homeostasis and mitochondrial autophagy.They establish regulatory networks that connect cancer and neurodegenerative diseases,and maintaining their functional homeostasis is of paramount importance for disease prevention and treatment.

Objective To investigate the post-discharge exercise behavior and factors influencing moderate to vigorous intensity physical activity (MVPA) in patients undergoing lung surgery. Methods A total of 2874 patients from the large prospective, observational perioperative lung symptom study cohort (CN-PRO-Lung 3) in the Department of Thoracic Surgery at Sichuan Cancer Hospital between April 7, 2021, and January 31, 2024, were selected as the survey subjects. A survey was conducted using the Investigation of Exercise Behavior after Lung Surgery questionnaire and the International Physical Activity Questionnaire-Short Form (IPAQ-SF) among patients who underwent lung surgery. Binary logistic regression was used to analyze the factors influencing patients’ engagement in MVPA. Results A total of 702 patients were surveyed, including 252 males and 450 females, with an average age of (52.4±10.2) years. Patients with lung cancer accounted for 85.9%. Only 36.0% of the patients had regular exercise habits, while 42.3% did not engage in any physical activity. The three main barriers for postoperative exercise were physical discomfort (pain, coughing, shortness of breath, etc, 54.7%), lack of professional guidance (41.7%), and concerns about the surgical wound (28.9%). The proportions of patients engaging in vigorous, moderate, and low-intensity physical activity were 5.7%, 28.2%, and 66.1%, respectively. Multivariate analysis showed that patients with a personal annual income ≥50000 yuan (OR=1.52, 95%CI 1.01-2.29, P=0.044), high school education or above (OR=1.92, 95%CI 1.33-2.76, P<0.001), and lobectomy (OR=1.44, 95%CI 1.02-2.03, P=0.037) engaged in more MVPA. Conclusion Patients undergoing lung surgery have inadequate physical activity after discharge, particularly lacking in MVPA. Patients with higher income, higher educational levels, and lobectomy are more frequently engaged in MVPA. Measures such as symptom control, providing exercise guidance, and enhancing education on wound care may potentially improve the inadequate physical activity in lung surgery patients after discharge.

In recent years， the incidence of depression among adolescents has increased significantly， becoming a serious global public health problem. There is a close relationship between adolescent depression and lipid metabolism abnormalities. However， the mechanisms underlying this association have not been fully elucidated. This article provides a review of the mechanisms and interventions linking adolescent depression and lipid metabolism abnormalities， aiming to offer new ideas for interventions in adolescent depression. Using computerized searches of the China National Knowledge Infrastructure （CNKI）， Wanfang Data， PubMed， and Web of Science， studies on the mechanisms and interventions related to adolescent depression and lipid metabolism were collected， with the search period extending up to October 10， 2025. Two researchers independently conducted literature screening and extracted basic information from the included studies. A total of 12 original studies were included. The results indicate that adolescent depression is associated with certain lipid metabolites. Neurobiological factors， immune inflammation， oxidative stress， and gut microbiota imbalance play important roles in this association. In addition， lipid metabolites such as omega-3 polyunsaturated fatty acids （ω-3 PUFAs） have a significant ameliorating effect on adolescent depression. ［Funded by Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties （number， SZGSP013）； Shenzhen Science and Technology Program （number， 20210617155253001）］

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.

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.