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.

ObjectiveTo investigate the mechanisms by which Huanglian Jiedutang （HLJDT） modulates microglial （MG） phenotypes through the sialic acid-binding Ig-like lectin 2 （SIGLEC2/CD22）/Src-homology-2-domain-containing protein tyrosine phosphatase-1 （SHP-1）/phosphorylated protein kinase B （p-Akt） signaling pathway， thereby promoting myelin repair and alleviating agitation-like behaviors in vascular dementia （VAD）. MethodsSixty C57BL/6J mice were randomly assigned to a sham （normal） group， model group， HLJDT low-， medium-， and high-dose groups （2.5， 5， and 10 g·kg^-1·d^-1）， and a risperidone group （2 mg·kg^-1·d^-1）， with 10 mice per group. VAD was induced by bilateral common carotid artery stenosis （BCAS）. From day 42， mice received drug interventions for 2 weeks. Agitation-like behaviors were assessed using the resident-intruder test. After behavioral testing， ventrolateral part of the ventromedial hypothalamus （VMHvl） tissues were collected. Western blot was used to measure protein levels of myelin oligodendrocyte glycoprotein （MOG）， myelin basic protein （MBP）， proteolipid protein （PLP）， inducible nitric oxide synthase （iNOS）， arginase-1 （Arg1）， CD86， CD206， and CD22， SHP-1， and p-Akt. Immunofluorescence was used to evaluate myelin-associated glycoprotein （MAG） intensity and the proportion of iNOS⁺/ionized calcium-binding adapter molecule 1 （Iba1）⁺ cells. ELISA was used to detect tumor necrosis factor-α （TNF-α）， interleukin （IL）-6， and IL-1β. ResultsCompared with the normal group， the model group exhibited markedly increased biting and aggressive behaviors and shortened attack latency （P<0.01）. MOG， MBP， and PLP protein levels and MAG fluorescence intensity were significantly reduced （P<0.05， P<0.01）. INOS and CD86 expression and TNF-α， IL-6， and IL-1β levels were significantly elevated （P<0.01）. CD22 and SHP-1 expression increased significantly （P<0.01）， whereas p-Akt expression decreased （P<0.01）. Compared with the model group， the medium- and high-dose HLJDT groups and the risperidone group showed markedly reduced biting and aggression （P<0.05， P<0.01） and prolonged attack latency （P<0.01）. MOG， MBP， and PLP levels and MAG fluorescence intensity were significantly increased （P<0.05， P<0.01）. INOS， CD86， TNF-α， IL-6， and IL-1β levels decreased significantly （P<0.05， P<0.01）. CD22 and SHP-1 expression decreased， while p-Akt expression increased significantly （P<0.05， P<0.01）. ConclusionHLJDT may modulate CD22/SHP-1/p-Akt signaling in the VMHvl， promote the shift of MG toward an anti-inflammatory and phagocytic phenotype， enhance myelin repair， and improve agitation-like behaviors in VAD mice.

Zoledronic acid (ZA), a nitrogen-containing bisphosphonate with established clinical utility in osteoporosis management, exhibits emerging antitumor potential in estrogen receptor-positive breast cancer. However, the molecular mechanisms underlying its nonapoptotic anticancer effects remain poorly characterized. This study revealed that ZA induced ferroptosis in ER+ breast cancer cells through dual suppression of cystine-glutamate antiporter SLC7A11 and glutathione peroxidase 4 (GPX4), key repressors of ferroptosis. Pharmacological inhibition of ferroptosis using Ferrostatin-1 significantly attenuated ZA-induced cytotoxicity, while combinatorial treatment with the GPX4 inhibitor RSL3 synergistically enhanced lipid peroxidation and cell death. Mechanistically, ZA activated the Hippo-YAP signaling pathway, promoting YAP phosphorylation, proteasomal degradation, and cytoplasmic retention, thereby silencing SLC7A11 and GPX4. We established a novel metabolic vulnerability in hormone-responsive malignancies.These findings position ZA as a bifunctional ferroptosis inducer in ER+ breast cancer, offering a promising strategy to overcome endocrine resistance.

OBJECTIVE: To identify prognostic genes associated with lysosome-dependent cell death (LDCD) in patients with gastric cancer (GC). METHODS: Differentially expressed genes (DEGs) were identified using The Cancer Genome Atlas - Stomach Adenocarcinoma. Weighted gene co-expression network analysis was performed to identify the key module genes associated with LDCD score. Candidate genes were identified by DEGs and key module genes. Univariate Cox regression analysis, and least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were performed for the selection of prognostic genes, and risk module was established. Subsequently, key cells were identified in the single-cell dataset (GSE183904), and prognostic gene expression was analyzed. Cell proliferation and migration were assessed using the Cell Counting Kit-8 assay and the wound healing assay. RESULTS: A total of 4,465 DEGs, 95 candidate genes, and 4 prognostic genes, including C19orf59, BATF2, TNFAIP2, and TNFSF18, were identified in the analysis. Receiver operating characteristic curves indicated the excellent predictive power of the risk model. Three key cell types (B cells, chief cells, and endothelial/pericyte cells) were identified in the GSE183904 dataset. C19orf59 and TNFAIP2 exhibited predominant expression in macrophage species, whereas TNFAIP2 evolved over time in endothelial/pericyte cells and chief cells. Functional experiments confirmed that interfering with C19orf59 inhibited proliferation and migration in GC cells. CONCLUSION C19orf59, BATF2, TNFAIP2, and TNFSF18 are prognostic genes associated with LDCD in GC. Furthermore, the risk model established in this study showed robust predictive power.
Stomach Neoplasms/pathology* ; Humans ; Prognosis ; Lysosomes/physiology* ; RNA-Seq ; Cell Death ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Cell Proliferation ; Single-Cell Gene Expression Analysis

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Case 1: A 19-day-old male infant presented with poor feeding and decreased activity for 2 weeks, worsening with poor responsiveness for 3 days. At 5 days old, he developed poor feeding and poor responsiveness, was hospitalized, and was found to have elevated blood ammonia and thrombocytopenia. Whole-genome genetic analysis revealed a pathogenic homozygous mutation in the PCCA gene, NM-000282.4: c.1834-1835del (p.Arg612AspfsTer44), leading to a diagnosis of propionic acidemia. Case 2: A 4-day-old male infant presented with poor responsiveness and feeding difficulties since birth, with elevated blood ammonia for 1 day. He showed weak sucking and deteriorating responsiveness, with blood ammonia >200 µmol/L. Genetic testing identified two heterozygous mutations in the MMUT gene: NM_000255.4: c.1677-1G>A and NM_000255.4: ex.5del, confirming methylmalonic acidemia. Case 3: A 20-day-old male infant presented with poor feeding for 15 days and skin petechiae for 8 days. He developed feeding difficulties at 5 days old and lower limb petechiae at 12 days old, with blood ammonia measured at 551.6 µmol/L. Genetic analysis found two heterozygous mutations in the PCCA gene: NM_000282.4: c.1118T>A (p.Met373Lys) and NM_000282.4: ex.16-18del, confirming propionic acidemia. In the first two cases, continuous hemodiafiltration was performed for 30 hours and 20 hours, respectively, before administering carglumic acid. In the third case, carglumic acid was administered orally without continuous hemodiafiltration, resulting in a decrease in blood ammonia from 551.6 µmol/L to 72.0 µmol/L within 6 hours, with a reduction rate of approximately 20-25 µmol/(kg·h), similar to the first two cases. Carglumic acid was effective in all three cases, suggesting it may help optimize future treatment protocols for organic acidemia.
Humans ; Male ; Infant, Newborn ; Propionic Acidemia/drug therapy* ; Amino Acid Metabolism, Inborn Errors/genetics* ; Mutation ; Methylmalonyl-CoA Decarboxylase/genetics* ; Citrates/administration & dosage* ; Carbon-Carbon Ligases/genetics* ; Glutamates

Objective:To understand the coverage and information consistency rate of National Immunization Program (NIP) vaccines among children born during 2020-2021 in Zhejiang Province, Chongqing City, and Shanxi Province (3 provinces) of China .Methods:A simple random sampling method was used to randomly select 3 counties (districts) from each of the 3 provinces, 5 townships from each county (district), and 5 villages from each township. Vaccination information for seven NIP vaccines was collected for children born between 2020 and 2021 in each village. The vaccination coverage, timely coverage, and consistency rates between the survey data and the Immunization Planning Information System data were analyzed.Results:A total of 1 117 children were investigated. The vaccination coverage for each dose of NIP vaccine ranged from 99.10% to 100.00%, with those in Zhejiang Province, Chongqing City, and Shanxi Province ranging from 99.19% to 100.00%, 98.92% to 100.00%, and 99.20% to 100.00%, respectively. The timely coverage of each dose of NIP vaccine ranged from 89.79% to 99.82%, with those in Zhejiang Province, Chongqing City, and Shanxi Province ranging from 94.09% to 99.73%, 89.52% to 99.73%, and 78.55% to 100.00%, respectively. The consistency rate of information on each dose of NIP vaccine ranged from 94.36% to 99.91%, with those in Zhejiang Province, Chongqing City, and Shanxi Province ranging from 97.85% to 99.73%, 98.92% to 100.00%, and 86.06% to 100.00%, respectively.Conclusions:Coverage of NIP vaccines was generally high among children born during 2020-2021 in the 3 provinces of China, but there were regional differences in the timely coverage of some vaccine doses and the vaccination information consistency rate. It is necessary to strengthen the timely vaccination of children's vaccine booster doses and optimize the management of vaccination services.