OBJECTIVE To screen and quantitatively analyze the quality marker （Q-Marker） associated with anti-renal fibrosis in Shenqi shenshuai mixture （SQSS）， so as to provide references for the analysis of pharmacodynamic substances and new drug transformation of SQSS. METHODS The chemical components of SQSS were characterized by untargeted metabolomics. Combined with network pharmacology， gene expression omnibus （GEO） and connectivity map （CMAP） databases， the anti-renal fibrosis Q-Markers of SQSS were screened. HPLC-MS/MS was applied to determine the contents of Q-Markers in 10 batches of SQSS. RESULTS A total of 1 319 compounds were identified from SQSS via untargeted metabolomics，and 84 active ingredients with anti-renal fibrosis activity were further screened out， such as formononetin. Nine anti-renal fibrosis Q-Markers were obtained by network pharmacology and GEO database， including berberine， quercetin， honokiol， nicotinamide， daidzein， coumarin， kaempferol， formononetin and amygdalin. The quantitative results showed that the average contents of the above components （excluding amygdalin） in 10 batches of SQSS were 2.523， 1.942， 26.848， 1.415， 0.692， 0.171， 0.374， 7.401 μg/mL， respectively. CONCLUSIONS Nine anti-renal fibrosis Q-Markers of SQSS were screened in this study， and the contents of eight among them were determined. The results can provide a basis for elucidating the pharmacodynamic material basis and promoting the new drug transformation of SQSS.

OBJECTIVE To screen and quantitatively analyze the quality marker （Q-Marker） associated with anti-renal fibrosis in Shenqi shenshuai mixture （SQSS）， so as to provide references for the analysis of pharmacodynamic substances and new drug transformation of SQSS. METHODS The chemical components of SQSS were characterized by untargeted metabolomics. Combined with network pharmacology， gene expression omnibus （GEO） and connectivity map （CMAP） databases， the anti-renal fibrosis Q-Markers of SQSS were screened. HPLC-MS/MS was applied to determine the contents of Q-Markers in 10 batches of SQSS. RESULTS A total of 1 319 compounds were identified from SQSS via untargeted metabolomics，and 84 active ingredients with anti-renal fibrosis activity were further screened out， such as formononetin. Nine anti-renal fibrosis Q-Markers were obtained by network pharmacology and GEO database， including berberine， quercetin， honokiol， nicotinamide， daidzein， coumarin， kaempferol， formononetin and amygdalin. The quantitative results showed that the average contents of the above components （excluding amygdalin） in 10 batches of SQSS were 2.523， 1.942， 26.848， 1.415， 0.692， 0.171， 0.374， 7.401 μg/mL， respectively. CONCLUSIONS Nine anti-renal fibrosis Q-Markers of SQSS were screened in this study， and the contents of eight among them were determined. The results can provide a basis for elucidating the pharmacodynamic material basis and promoting the new drug transformation of SQSS.

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.

This article reports a rare case of autoinflammatory disease presenting initially with skin induration and swelling after trauma as the initial manifestation, followed by progressive limb weakness. The patient was a middle-aged female who developed skin induration and swelling after trauma, which gradually progressed to limb weakness, dysarthria and bilateral facial paralysis, accompanied by livedo reticularis of the lower extremities, diffuse skin induration of the limbs, and beaded subcutaneous nodules in the right upper limb. The patient had a susceptibility to infection since childhood and a history of chronic livedo reticularis. Skin pathological examination revealed panniculitis. A comprehensive etiological screening for special infections and autoimmune diseases was completed with an unremarkable results, and whole-exome sequencing showed no abnormal findings. Following a multidisciplinary discussion combined with RNA sequencing results, the patient was diagnosed with an autoinflammatory disease, with a suspected type Ⅰ interferonopathy. Treatment with tofacitinib resulted in gradual improvement of clinical symptoms. This case highlights the importance of detailed medical history collection, systematic physical examination and multidisciplinary collaborative diagnosis and treatment, and underscores the pivotal role of molecular diagnosis in the confirmation of rare diseases. It can provide a reference for the clinical diagnosis and management of similar rare cases.

Objective:To analyze the epidemiological and clinical characteristics of pertussis in children and the antimicrobial resistance pattern of Bordetella pertussis isolates in Anhui province in 2024. Methods:Prospective observational study. The demographic information of 4 233 cases of pertussis confirmed by nucleic acid testing in Anhui Provincial Children′s Hospital in 2024 and the clinical data of hospitalized cases were collected. The annual epidemic trend of pertussis in children, the clinical characteristics of hospitalized cases, and the vaccination status were analyzed. Bordetella pertussis isolates were recovered from nasopharyngeal swabs obtained from hospitalized children and their family caregivers during the outbreak period and antimicrobial susceptibility was tested. Results:Among the 4 233 children, 2 330 were male and 1 903 were female. A total of 4 059 cases (95.9%) occurred from March to September, with the peak of the disease from April to July (3 364 cases (79.5%)).There were 4 075 cases (96.3%) aged 9 years and under, among which 718 cases (17.0%) were under 1 year old and 2 494 cases (58.9%) were aged 4 to 7 years. During the outbreak period, there were a total of 301 hospitalized children (7.1%), with an average age of 4.4 (2.8, 16.5) months. Among them, 61 cases (20.3%) received the full course of vaccination (4 doses), 64 cases (21.3%) received partial doses of the vaccine, and 176 cases (58.5%) were unvaccinated. Among the unvaccinated children, 79.6% (172/216) were under 1 year old, 8.7% (2/23) were between 1 and 3 years old, and 3.2% (2/62) were 3 years old or older. None of the 20 cases (6.6%) of severe pertussis received pertussis vaccine.Among the 301 hospitalized children, 298 cases (99.0%) presented with typical paroxysmal spasmodic cough, 94 cases (31.2%) had vomiting after coughing, 82 cases (27.2%) had whooping sounds, and 54 cases (17.9%) had cyanotic attacks. There were 228 cases (75.7%) complicated with pneumonia and 5 cases (1.7%) with pertussis encephalopathy. The infection rate among the accompanying family members who underwent screening was 77.1% (371/481). Based on the minimum inhibitory concentration testing of 186 Bordetella pertussis isolates, the minimum inhibitory concentration 90 of azithromycin and trimethoprim-sulfamethoxazole were >256.000 and 0.050 mg/L, respectively. Conclusions:The peak of pertussis cases in Anhui region in 2024 occurred from April to July. Children aged ≤9 years were the major affected population. Infants and preschool children were most susceptible to pertussis. The intrafamily transmission rate of pertussis is high. Empirical use of macrolides for the treatment of pertussis is not recommended. Trimethoprim-sulfamethoxazole can be used as the preferred antibiotic for pertussis in children aged 2 months and above.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Objective:The purpose of this study was to analyze the epidemiological characteristics of hand, foot, and mouth disease (HFMD) among individuals aged 6 years and above in Guangzhou from 2010 to 2023, with the intention that a scientific basis be provided for effective prevention and control measures in older age groups.Methods:Data on HFMD incidence among individuals aged 6 years and above in Guangzhou from 2010 to 2023 were collected and analyzed. Descriptive epidemiological methods were used to analyze the distributions and pathogen components of HFMD cases in Guangzhou residents aged 6 years and above. Spatial autocorrelation analysis and Getis-Ord Gi* analysis were conducted to identify the spatial clustering patterns of HFMD at the street town level. Results:From 2010 to 2023, the gender ratio of HFMD cases in persons aged 6 and above was 1.49∶1 in Guangzhou. The average annual incidence rate of HFMD among individuals aged 6 years and above in Guangzhou was 25.75 per 100 000. Furthermore, the reported incidence rate indicated an increased tendency. The annual incidence showed a bimodal distribution, with the main peak occurring from May to July and the secondary peak from September to October. HFMD incidence rates vary by townships, with hotspots clustered in urban and urban-rural regions. The dominant pathogen shifts from year to year. Enterovirus 71 (EV71) was the prevalent strain in 2010, followed by other enteroviruses and Coxsackievirus (CV)-A16 from 2011 to 2016. Since 2017, CV-A6 has steadily become the major pathogen.Conclusions:The incidence of HFMD cases among individuals aged 6 years and above in Guangzhou increased generally from 2010 to 2023, with hotspots localized in urban and urban-rural areas. The pathogen composition altered dramatically, with the proportion of EV71 dropping overall, while CV-A6 eventually became the dominating strain. Therefore, it is imperative to focus on the prevention and control of HFMD in this age group, especially by strengthening measures in areas with high prevalence.

Objective To describe the application related to mobile health(mHealth)technology in cognitive rehabilitation of stroke patients,aiming to identify the types of mHealth technologies,intervention content,and outcome measures,so as to provide references for future research.Methods According to the methodological framework of the scoping review,we systematically searched relevant studies in Chinese and English databases.The retrieval time was from establishment of databases to February 16,2025.Data extraction and meta-analysis were performed on the included literature.Results Totally 28 studies were finally included,involving 5 intervention types,including APP,VR combined with APP,the internet platform,VR integrated with the internet platform and telerehabilitation system.The content elements of the intervention included cognitive training,remote cognitive assessment,monitoring and reminders and health guidance.Conclusion The intervention types based on mHealth technology are diverse and the intervention strategies are rich,which can effectively improve the cognitive function of patients.It is necessary to conduct large-sample,high-quality and long-term follow-up studies to provide higher quality evidence support for this field in the future.

Owing to the insidious onset and limited awareness of early screening,many patients with esophageal squamous cell carcinoma(ESCC)are diagnosed at an advanced stage.Immunochemotherapy is the current standard first-line treatment for advanced ESCC;however,survival outcomes remain suboptimal.Radiotherapy,with its precise local control and potential immunomodulatory effects,is anticipated to act synergistically with immunochemotherapy,offering a novel direction for overcoming survival limitations.This review systematically sum-marizes the progress in the use of radiotherapy as a first-line treatment for advanced ESCC and discusses the synergistic mechanisms,clinical applications,and challenges associated with its combination with immunochemotherapy.