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.

Objective To analyze the effect of releasing the lower pulmonary ligament on right residual lung expansion after right upper lobe resection under different body mass index (BMI) levels. Methods The clinical data of patients who underwent thoracoscopic right upper lobe resection in the First Affiliated Hospital with Nanjing Medical University from 2021 to 2022 were retrospectively analyzed. Patients were divided into a group A (17 kg/m2＜BMI≤23 kg/m2), a group B (23 kg/m2＜BMI≤29 kg/m2) and a group C (BMI＞29 kg/m2) according to BMI. The presence of residual cavity was judged by chest X-ray at 7-10 days after operation, the degree of compensation change of the right main bronchus angle was measured, and the changes in lung volume were determined by CT three-dimensional reconstruction. Results A total of 157 patients who underwent thoracoscopic right upper lobe resection were included, including 71 males and 86 females, with an average age of (59.7±11.2) years. There were 50 patients in the group A, 75 patients in the group B, and 32 patients in the group C. In the group A, compared with those without releasing the lower pulmonary ligament, patients with releasing had a lower incidence of postoperative residual cavity (P=0.016), greater changes in bronchus angle (P<0.001), and smaller changes in lung volume (P<0.001). In the group B and C, there was no significant effect of releasing the lower pulmonary ligament on postoperative residual cavity, bronchus angle, and lung volume changes (P>0.05). Conclusion For patients with thin and long body shape and low BMI, releasing the lower pulmonary ligament is helpful to promote the expansion of the residual lung after right upper lobe resection and reduce the occurrence of postoperative residual cavity in patients.

Background: High-mobility group box protein 1 (HMGB1) is a chromatin-binding protein involved in arthritis, ischemia, sepsis, atherosclerosis, neurodegenerative disorders, meningitis, and cancer. HMGB1 exhibits dual roles in cancer, acting as either a tumor suppressor or oncoprotein depending on context. Objective: This research aimed to elucidate HMGB1’s functional significance in cutaneous squamous cell carcinoma (cSCC). Methods: We overexpressed HMGB1 in cSCC cell lines using recombinant adenovirus and examined its effects on cell proliferation, colony formation, and cell migration. Results: Immunohistochemical analysis revealed elevated HMGB1 expression levels in cSCC tissue relative to normal epidermis. To assess the influence of HMGB1, we employed recombinant adenoviruses expressing HMGB1 to transduce SCC cell lines (SCC12 and SCC13). Enhanced HMGB1 expression significantly promoted cellular proliferation and colony formation capacity.Notably, HMGB1 overexpression elevated the levels of proliferation regulators, including P63, SOX2, CDK4 and CDK6. Furthermore, HMGB1 overexpression substantially enhanced tumor invasiveness, accompanied by upregulation of epithelial-mesenchymal transition (EMT) biomarkers. Mechanistically, overexpression of HMGB1 enhanced transforming growth factor-β signaling by increasing phosphorylation of SMAD2/3, the key mediators of EMT. Conclusion These data imply that HMGB1 acts as a tumor-promoting factor in cSCC.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

This study was aimed at preliminarily assessing the prevalence of latent tuberculosis infection(LTBI)among cattle farming and slaughterhouse workers across Wuxue,Xianning,and Yichang Cities in Hubei Province,and exploring associated risk factors.Data on cattle farming and slaughterhouse workers were gathered via a questionnaire.LTBI detection was performed with a tu-berculin skin test and interferon-gamma release assay,and influencing factors were subsequently analyzed.The LTBI prevalence among cattle farming and slaughterhouse personnel in the three cities was 30.50%,and a higher rate was observed in slaughterhouse workers(39.01%)than cattle farmers(21.63%)(P<0.01).Multifactor analysis indicated that working in slaughterhouses(95%CI:1.582-3.878),having a history of tuberculosis(95%CI:1.377-25.057)or BCG vaccination(95%CI:1.229-3.285),and having a college education or above(95%CI:0.303-0.859)were significant factors influencing LTBI positivity in these personnel.Having more than 30 years of work experience(95%CI:1.303-18.782)was a risk factor for personnel at cattle breeding farms.Among slaugh-terhouse personnel,having a college education or above(95%CI:0.164-0.894),11-20 years of work experience(95%CI:0.122-0.994),or a history of tuberculosis(95%CI:1.661-64.397);performing logistics work(95%CI:3.234-126.424);and working in slaughter-related positions(95%CI:1.209-19.639)were associated with LTBI positivity.Therefore,the slaughterhouse workers in the three cities had higher LTBI rates than the cattle farming workers,thus underscoring the need for increased attention to personnel in logistics and slaughter-related positions.

Objective To analyze the therapeutic effect of ultrasound combined with external application of Chinese medicine in the treatment of temporomandibular disorders(TMD).Methods A total of 72 patients with TMD and treated in our hospital from January 2022 to December 2023 were randomly divided into the control group and the treatment group,with 36 cases in each group.The control group was treated with ultrasound,and the treatment group was treated with ultrasound combined with traditional Chinese medicine.Then the pain VAS score,maximum mouth opening degree,joint click and clinical effect were observed before and after treatment.Re-sults The VAS score of the treatment group was lower than that of the control group(P＜0.05).There were more patients with maxi-mum mouth opening greater than 3.7 cm in the treatment group than in the control group(P＜0.05).There was no statistical significance in the number of patients with joint click between the two groups(P＞0.05).The significant efficiency of treatment group was higher than that of control group(P＜0.05).The effective rate of treatment group was higher than that of control group,but the difference was not statistically significant(P＞0.05).Conclusion Ultrasound combined with external application of traditional Chinese medicine in the treatment of TMD,compared with single ultrasound treatment,can significantly improve the clinical symptoms and promote the clin-ical therapeutic effect.

Objective:To analyze the clinical and ultrasonic features of breast invasive ductal carcinoma in young women patients,and improve the accuracy of ultrasonic diagnosis of breast invasive ductal carcinoma in young patients.Methods:A retrospective study was conducted on patients with invasive ductal carcinoma who underwent surgery in the Second Hospital of Shandong University from December 2015 to June 2023,with complete clinical data,preopera-tive ultrasonography and postoperative pathology.All patients were divided into two groups:young group(≤35 year-old)and control group(>35 year-old).Univariate t-test and multivariate Logistic regression analyses were used to assess the factors.Results:There was a statistical difference between the young group and the control group in the accuracy of ultrasound diagnosis(young group 81%vs control group 94%,χ2=13.082,P=0.001).Compared with the control group,the young group had a shorter disease history,a higher proportion of multiple masses,posterior echo changes and hypo-vascular lesions(P<0.05).However,there was no statistical difference in family history of breast cancer,other cancer family history,clinical symptoms,size,lesion classification,palpation,location,aspect ratio,focus echo,shape,edge per-formance,bright ring sign,calcification characteristics,ER,PR,HER-2 and Ki67(P>0.05).Conclusion:The incidence rate of young breast IDC is low,while the misdiagnosis rate of ultrasound is relatively high.More attention should be paid when the patient has a short history,multiple masses,changes in the posterior echo and less lesion blood supply.

Schizophrenia is a chronic and debilitating mental disorder.Around 20%to 40%of patients do not respond well to normal antipsychotic medication,and are ultimately diagnosed with treatment-resistant schizophrenia(TRS),representing the most severe and challenging form of schizophrenia.Currently,clozapine is the standard treatment for TRS.Early identification and standardized treatment can be beneficial to patients with TRS by controlling acute-phase symptoms as soon as possible,reducing suicidal rate and improving their quality of life.Under the guidance of the Steering Committee,this consensus was formed after multiple discussions by 30 psychiatric experts and anonymous Delphi surveys including 17 consensus opinions on treatment-resistant schizophrenia,which cover risk factors and prevention,diagnosis and evaluation,standardized clozapine treatment and management of adverse reactions,treatment regimens for clozapine resistance and intolerance,and psychosocial intervention,etc.The consensus-making process also incorporated evidence-based medicine to help standardize and guide diagnosis and treatment for adults with TRS in China.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.