OBJECTIVE:Some studies have shown that physical exercise can effectively improve knee extensor strength and cardiorespiratory function in burn patients;some studies have also shown that physical exercise is not effective in improving respiratory function in burn patients.Improvement effects of physical exercise on physical functions(muscle function,walking function,cardiopulmonary function,and lean body mass)of burn patients were evaluated by a systematic evaluation and meta-analysis.METHODS:Based on databases including Web of Science,PubMed,Embase,Cochrane Library,CNKI,WanFang,and the Chinese Biomedical Database,literature on the improvement of physical function in burn patients through physical exercise was searched using subject headings and free terms.With muscle function,walking ability,cardiopulmonary function,and lean body mass as the primary outcome measures,a meta-analysis was conducted to compare the efficacy of physical exercise with traditional physical therapy or conventional care methods.RESULTS:A total of 38 papers were included,of which 26 papers were included in the meta-analysis,involving 1 658 patients.Meta-analysis results showed that:(1)Physical exercise significantly enhances the knee extensor strength of the dominant leg in burn patients(mean difference[MD]=8.34,95％confidence interval[CI]:6.95-9.72,P＜0.000 01),increases quadriceps strength,peak oxygen uptake,forced vital capacity and maximum ventilation volume in 1 second,and resting heart rate(standardized mean difference[SMD]=4.41,95％CI:2.52-6.30,P＜0.000 01;MD=4.91,95％CI:3.52-6.29,P＜0.000 01;MD=5.86,95％CI:0.09-11.63,P=0.05;MD=6.90,95％CI:2.93-10.87,P=0.000 7;MD=5.03,95％CI:1.45-8.61,P=0.006),and improves the 6-minute walking distance,gait parameters,and total lean body mass(MD=45.29,95％CI:24.7-65.89,P＜0.0001;SMD=7.84,95％CI:6.05-9.63,P＜0.000 01;MD=2.47,95％CI:2.01-2.93,P＜0.000 01).(2)The subgroup analysis results indicated that the improvement in knee extensor strength of the dominant leg may be better in children than in adults and better in the extra-heavy group than in the heavy group.Improvement in the 6-minute walking distance is better in children than in adults,and higher degree of burn indicates better improvement effects,with no difference from the control group for＜12 weeks.Peak oxygen uptake may be better in adults and severe burn groups than in children and moderate burn groups,resistance combined with aerobic exercise modalities may be better than aerobic exercise alone,and exercise duration＞60 minutes may be better than＜60 minutes.CONCLUSION:Physical activity is effective in improving physical function in burn patients,as evidenced by improvements in muscle strength,walking ability,cardiorespiratory fitness,and lean body mass.The quality of evidence recommended for all indicator results is moderate or below,with imprecision and inconsistency being the main factors for downgrading.Therefore,more high-quality randomized controlled trials are needed in the future to verify the reliability of the results.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

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.

Objective To summarize the clinical characteristics and analyze prognostic factors of neuroblastoma (NB) in infants (≤12 months) at a single center. Methods A retrospective analysis was conducted on the clinical data of infant patients (≤12 months) diagnosed with NB and treated between January 2014 and December 2022. Clinical features were analyzed, and comparisons between two sample rates were performed using the χ² test. Univariate prognostic analysis was conducted using the log-rank test, and survival outcomes were analyzed using the Kaplan-Meier method. Results A total of 42 infants (≤12 months) with NB were enrolled. Low-risk patients underwent surgical resection alone; intermediate-risk patients received surgery combined with chemotherapy with or without maintenance therapy; high-risk patients were treated with surgery and chemotherapy with or without maintenance therapy or radiotherapy. The 5-year event-free survival (EFS) rate was (92.7±4.9)%, and the 5-year overall survival rate was (95.2±3.6)%. Only two patients died because of tumor recurrence or progression. Univariate analysis identified MYCN amplification and the initial lactate dehydrogenase (LDH) level ≥ five times the upper limit of the normal were significantly associated with poor prognosis (5-year EFS: 33.3% vs. 97.4% and 60.0% vs. 97.3%, P<0.0001 and P=0.0035). Conclusion Infant NB has a favorable overall prognosis. MYCN amplification and markedly elevated initial LDH are associated with poor outcomes.

Triclosan (TCS) and triclocarban (TCC) are widely used synthetic broad-spectrum antibacterial agents that can enter the human body through the skin, gastrointestinal tract, and other pathways. More and more studies have found that exposure to TCS and TCC can affect human health, but currently, review reports on the health effects of human exposure to TCS and TCC are limited. Therefore, this study reviewed population studies on the relationship between TCS and TCC exposure and health effects by searching the PubMed database, summarized the associated health outcomes, and elucidated the biological mechanisms. A total of 56 studies were retrieved, among which cross-sectional studies (25 studies, 44.64%) and cohort studies (25 studies, 44.64%) accounted for a relatively large proportion, while case-control studies (6 studies, 10.72%) were relatively few. Studies on TCS exposure (48 studies, 85.71%) were far more prevalent than those on TCC exposure (2 studies, 3.57%). The remaining 6 studies involved both TCS and TCC exposure. The research results revealed that TCS exposure was associated with male and female abnormal reproductive functions, fetal growth restriction, abnormal behavior development in children, obesity, gestational diabetes mellitus (GDM), and immune-related diseases. Although the results of different studies show significant differences, they have indicated that exposure to TCS is a potential risk factor for these health problems. Due to the limited number of studies, the evidence for the relationship between TCC exposure and most of the aforementioned health effects is insufficient. Population studies and in vitro and in vivo studies have shown that exposure to TCS and TCC can interfere with the microbial homeostasis, the endocrine system, oxidative stress and immune function of the body, which are potential mechanisms causing adverse health effects. In the future, large-scale prospective cohort studies, as well as in vivo and in vitro studies, are still needed to further clarify the associations between TCS and TCC exposure and health effects, and to deeply explore its mechanism of action. These efforts will provide references for clarifying the human health hazards of TCS and TCC exposure and formulating targeted prevention and control strategies.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

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 incidence and spatiotemporal distribution of typhus fever in Baoshan City, Yunnan Province from 2005 to 2023, to identify high-risk populations and regions, so as to provide a scientific basis for optimizing the allocation of local prevention and control resources and developing targeted intervention measures. MethodsData of typhus fever cases in Baoshan City from 2005 to 2023 were obtained from the Infectious Disease Information Management System of the Chinese Center for Disease Control and Prevention. Descriptive epidemiological methods were used to analyze the temporal, spatial and demographic distribution of typhus fever cases. Spatial clustering was assessed using spatial dynamic window scan statistics (circular and elliptical windows), flexible spatial scan statistics, and local spatial autocorrelation methods (including local Moran’s I, local Geary’s C, and Getis-Ord G_i*). Retrospective spatiotemporal scan statistics were employed to detect spatiotemporal clusters. ResultsA total of 1 099 typhus fever cases were reported in Baoshan City from 2005 to 2023. The incidence rate peaked at 6.31/ 100 000 in 2007, followed by a decline until reaching its lowest level at 0.21/100 000 in 2015 , and subsequently rebounded during 2016‒2023. The highest proportion of cases was among children under 10 years of age (31.12%), and the top three occupations of cases were farmers, students, and children, accounting for 88.62% of all cases. Cases occurred predominantly between June and September each year. The incidence was relatively high in Jiucheng Town (62.58/100 000), Yaoguan Town (57.15/100 000), and Dianyang Town (46.81/100 000) of Shidian County. Spatial clustering analyses indicated that high-risk areas were mainly located in the southern part of Baoshan City, showing a south-to-north trend. Spatiotemporal scan analyses identified five clusters, with the most likely cluster centered around Yaoguan Town, covering ten towns (subdistricts) during the period 2007‒2010. ConclusionThe incidence of typhus fever in Baoshan City exhibits a clear seasonal and spatial clustering pattern, with peak incidence occurring in summer and autumn. Spatially, cases are primarily distributed in the southern part of Baoshan City, and high-risk clusters exhibit a south-to-north trend. Farmers, students, and children are the high-risk groups.

Background: Adrenocortical hormones, particularly 11-oxygenated androgens, are pivotal in female reproductive health and fertility. Standardized detection kits and population-specific reference intervals are lacking in China, hindering related clinical applications. Methods: A HPLC-tandem mass spectrometry (HPLC-MS/MS) pipeline was developed, rigorously validated, and applied to simultaneously quantify corticosterone, cortisone, cortisol, 18-OH cortisol, androstenedione (A4), 11β-hydroxyandrostenedione (11-OH A4), dehydroepiandrosterone, and dehydroepiandrosterone sulfate in serum samples from 455 reproductive-aged women (18–45 yrs) in Guangxi, China. Age-dependent concentration trends were analyzed, and reference intervals stratified by age (2.5th to 97.5th percentiles) were established. Correlations with body-composition metrics, ethnicity, and the menstrual cycle were investigated. Results: The HPLC-MS/MS method demonstrated high precision (intra- and inter-assay CVs < 15%), accuracy, and sensitivity. All eight hormones exhibited significant age-related declines (P < 0.001 for seven hormones; P = 0.001 for 11-OH A4). Notably, 11-OH A4 levels were significantly lower in the 35–45-yr (3.05 nmol/L) and 25–34-yr (3.09 nmol/L) age groups than in the 18–24-yr (3.57 nmol/L) age group, whereas no significant difference was observed between the 35–45-yr and 25–34-yr age groups. Weak negative correlations were observed between the body mass index and corticosterone and cortisone levels, whereas ethnicity and the menstrual cycle showed no significant associations with hormone levels. Conclusions We developed an HPLC-MS/MS-based method for simultaneously quantifying eight adrenocortical hormones, including 11-OH A4, and defined age-specific reference intervals for reproductive-aged Chinese women. These findings advance the clinical utility of adrenocortical hormones in diagnosing and managing reproductive disorders.

OBJECTIVE:Some studies have shown that physical exercise can effectively improve knee extensor strength and cardiorespiratory function in burn patients;some studies have also shown that physical exercise is not effective in improving respiratory function in burn patients.Improvement effects of physical exercise on physical functions(muscle function,walking function,cardiopulmonary function,and lean body mass)of burn patients were evaluated by a systematic evaluation and meta-analysis.METHODS:Based on databases including Web of Science,PubMed,Embase,Cochrane Library,CNKI,WanFang,and the Chinese Biomedical Database,literature on the improvement of physical function in burn patients through physical exercise was searched using subject headings and free terms.With muscle function,walking ability,cardiopulmonary function,and lean body mass as the primary outcome measures,a meta-analysis was conducted to compare the efficacy of physical exercise with traditional physical therapy or conventional care methods.RESULTS:A total of 38 papers were included,of which 26 papers were included in the meta-analysis,involving 1 658 patients.Meta-analysis results showed that:(1)Physical exercise significantly enhances the knee extensor strength of the dominant leg in burn patients(mean difference[MD]=8.34,95％confidence interval[CI]:6.95-9.72,P＜0.000 01),increases quadriceps strength,peak oxygen uptake,forced vital capacity and maximum ventilation volume in 1 second,and resting heart rate(standardized mean difference[SMD]=4.41,95％CI:2.52-6.30,P＜0.000 01;MD=4.91,95％CI:3.52-6.29,P＜0.000 01;MD=5.86,95％CI:0.09-11.63,P=0.05;MD=6.90,95％CI:2.93-10.87,P=0.000 7;MD=5.03,95％CI:1.45-8.61,P=0.006),and improves the 6-minute walking distance,gait parameters,and total lean body mass(MD=45.29,95％CI:24.7-65.89,P＜0.0001;SMD=7.84,95％CI:6.05-9.63,P＜0.000 01;MD=2.47,95％CI:2.01-2.93,P＜0.000 01).(2)The subgroup analysis results indicated that the improvement in knee extensor strength of the dominant leg may be better in children than in adults and better in the extra-heavy group than in the heavy group.Improvement in the 6-minute walking distance is better in children than in adults,and higher degree of burn indicates better improvement effects,with no difference from the control group for＜12 weeks.Peak oxygen uptake may be better in adults and severe burn groups than in children and moderate burn groups,resistance combined with aerobic exercise modalities may be better than aerobic exercise alone,and exercise duration＞60 minutes may be better than＜60 minutes.CONCLUSION:Physical activity is effective in improving physical function in burn patients,as evidenced by improvements in muscle strength,walking ability,cardiorespiratory fitness,and lean body mass.The quality of evidence recommended for all indicator results is moderate or below,with imprecision and inconsistency being the main factors for downgrading.Therefore,more high-quality randomized controlled trials are needed in the future to verify the reliability of the results.