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.

ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by the selective loss of dopaminergic neurons in the substantia nigra pars compacta and the pathological accumulation ofα‑synuclein. Although extensive progress has been made in elucidating its pathogenesis, current therapeutic approaches remain largely symptomatic, and effective disease-modifying treatments are still unavailable. Increasing evidence indicates that PD is driven by the interaction of multiple pathological processes, including neuroinflammation, iron homeostasis dysregulation and ferroptosis, endoplasmic reticulum (ER) stress, mitochondrial dysfunction, oxidative stress, and impaired protein homeostasis, which together contribute to neuronal vulnerability and degeneration. Fibroblast growth factors (FGFs) comprise a family of 22 ligands that play important roles in neural development, stress responses, metabolic regulation, and the maintenance of nervous system homeostasis. Recent studies have shown that several FGF family members, such as FGF1, FGF2, FGF9, and FGF21, exert neuroprotective effects in cellular and animal models of PD. These effects include the regulation of inflammatory responses, oxidative stress, iron homeostasis, cellular stress adaptation, and neuronal survival. Compared with therapeutic strategies targeting a single pathogenic pathway, FGFs appear to influence multiple disease-related processes, suggesting their potential relevance to the complex pathophysiology of PD. Experimental evidence indicates that altered FGF signaling may contribute to dopaminergic neuron dysfunction through the coordinated regulation of several interconnected mechanisms. FGFs have been reported to modulate neuroinflammation by affecting the activation of microglia and astrocytes, thereby influencing the inflammatory environment in the central nervous system. In addition, FGFs are involved in the regulation of iron homeostasis and ferroptosis, partly through antioxidant signaling pathways associated with NRF2, SLC7A11, and GPX4. Moreover, FGFs can alleviate ER stress and mitochondrial dysfunction by activating intracellular signaling pathways such as PI3K/AKT, AMPK-PGC-1α, as well as SIRT1-dependent programs, which support cellular energy metabolism and redox balance. Recent advances in single-cell and spatial transcriptomic studies further suggest that FGF signaling is not limited to neuron-intrinsic mechanisms but also involves interactions among different glial cell types. Altered FGF ligand-receptor communication between astrocytes and oligodendrocytes has been observed in PD models and is associated with increased susceptibility of dopaminergic neurons to oxidative stress and ferroptosis. These findings indicate that the biological effects of FGFs are influenced by cell type and disease stage and may vary under different pathological conditions. In this review, we summarize recent progress in understanding the roles of FGF family members in PD, with a focus on their involvement in iron homeostasis dysregulation and ferroptosis, neuroinflammation, cellular stress responses, and neuronal protection and regeneration. By integrating current evidence, this review aims to provide a clearer understanding of how FGFs participate in PD pathogenesis and to offer a theoretical basis for future studies exploring their potential value in disease-modifying therapeutic strategies.

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.

Objective To analyze personal external exposure dose monitoring results of pet hospital radiation workers in Beijing from 2022 to 2024, and to provide scientific evidence for developing effective monitoring protocols, standardizing radiological practices in pet hospitals, and protecting the health of both workers and the public. Methods Personal dose equivalents, H_p(10), were measured using GR-200A thermoluminescent dosimeters. Monitoring included radiation workers at 286 pet hospitals across all 16 districts of Beijing from 2022 to 2024. Each monitoring cycle lasted no more than 90 days. Annual effective doses were calculated by summing the results of four consecutive quarterly cycles. Data were processed and analyzed using Access and TLPS 6.41 software. All evaluations complied with national laws, regulations, and technical standards. Results A total of 1,579 person-time measurements were recorded. Only 51.87% of workers completed the full four-cycle annual monitoring schedule. Over the study period, the mean annual effective dose was 0.29 mSv, and the median dose was 0.14 mSv. The collective effective dose was 238.34 man-mSv. Notably, 94.26% of workers had annual effective doses below 1.0 mSv, and only 0.12% had doses at or above 5 mSv. Dose levels showed a statistically significant downward trend (P<0.05). Both independent and chain-branded clinics had a median annual effective dose of 0.14 mSv. In independent clinics, the proportion of workers with doses below 1.0 mSv increased from 80.77% in 2022 to 98.82% in 2024. In chain-branded clinics, this proportion rose from 96.88% to 98.11% over the same period. Conclusion Radiation exposure among pet hospital workers in Beijing remains at low levels, well below regulatory limits, and shows an overall declining trend. The disparity in personal doses between independent and chain-branded pet hospitals has diminished over time. Nevertheless, the industry still faces challenges such as high staff turnover and low monitoring completion rates. Expanding monitoring coverage and harmonizing protection standards would provide a scientific basis for precise, nationwide regulation.

Objective:To explore the changes in the whole transcriptome gene expression profile affected by EPB41L4A-AS,and to reveal its potential mechanisms that influence the progression of AD.Methods:U251 cells with stable low expression of EPB41L4A-AS1 were constructed using shRNA technology.Transcriptome sequencing was performed to screen for transcripts regulated by EPB41L4A-AS1.KEGG pathway and GO analysis were used to explore the related signaling pathways and biological processes regulated by EPB41L4A-AS1.Immunofluorescence assay was used to investigate the effects of EPB41L4A-AS1 on the activity of glial cells with antibodies against GFAP.Results:Knocking down the expression of EPB41L4A-AS1 in U251 cells significantly influenced the levels of multiple transcripts,with 626 upregulated and 949 downregulated.Further analysis revealed that the downregulated transcripts are related to AD,activation and proliferation of glial cells,and formation of amyloid fibers,and close to multiple signaling pathways that are involved in the glial cells-mediated Aβ clearance.Cellular experiments have shown that EPB41L4A-AS1 regulated the synapses length and activity of glial cells.Conclusions:EPB41L4A-AS1 may influence the glial cells-mediated Aβ clearance through multiple signaling pathways.

Objective To investigate the risk factors of hemodynamic instability after carotid artery stenting by meta-analysis.Methods Ten databases were searched:PubMed,ProQuest,ScienceDirect,Embase,Cochrane Library,Web of Science,China Knowledge Network,Wanfang Data,VIP Information Database,and China Biomedical Database.The search date was from inception until 2 February 2024,and meta-analysis was performed using Stata 16.0 statistical software.Results A total of 27 studies with 4199 subjects and 22 influencing factors were included.The studies showed a 37.4％(95％CI 30.3％-44.8％)incidence of haemodynamic instability after carotid stenting,Meta-analysis determined that age＞60 years(P＜0.001),hypertension(P＜0.001),calcified plaque(P＜0.001),stenosis＞70％(P=0.008),eccentric plaque(P=0.002),distance from the largest stenosis to the carotid bifurcation≤ 10 mm(P＜0.001),stenosis involvement of the balloon or bifurcation(P＜0.001),balloon post-dilation(P=0.003),open-loop stenting(P＜0.001),dilated balloon diameter≥5 mm(P=0.002),repeat balloon dilation(P=0.011)and balloon dilation pressure≥8 atm(P＜0.001)are risk factors for intraoperative and postoperative haemodynamic instability in patients undergoing carotid artery stenting surgery.Statin use was a protective factor(P＜0.001).Conclusions Medical staff working in the clinic should assess the patient's condition preoperatively,identify risk factors that may lead to haemodynamic instability,and avoid unnecessary intraoperative stimulation of patients who are already in a high-risk state.Reduce postoperative clinical complications in patients with carotid artery stenosis and improve patient recovery.

Objective To analyze the related factors of long-term prognosis of patients with localized renal cell carcinoma after laparoscopic partial nephrectomy.Method Clinical data of 110 patients with localized renal cell carcinoma who underwent laparoscopic partial nephrectomy from January 2020 to January 2021 were retrospectively analyzed.According to whether the patients died within 3 years after operation,they were divided into death group(n=19)and survival group(n=91).The related factors of long-term prognosis of the two groups were compared.Results Compared with the survival group,the proportion of hyperlipidemia,diabetes,hypertension,sarcomatoid differentiation,clear cell type,T1b～T3a stage and American Society of Anesthesiologists(ASA)grade Ⅲ～Ⅵ in the death group increased(P＜0.05),the maximum diameter of tumor increased(P＜0.05),score of Mayo adhesive probability(MAP)and perirenal fat density increased(P＜0.05),the operation time and indwelling drainage tube time prolonged(P＜0.05),and the levels of blood urea nitrogen(BUN),creatinine(Cr),hypersensitive C-reactive protein(Hs-CRP),total cholesterol(TC)and microalbuminuria(MAU)increased(P＜0.05).Sarcomatoid differentiation(OR=1.737,95％CI:1.074～2.807),T stage of T1b～T3a(OR=1.627,95％CI:1.182～2.240)and level of Cr≥91.27 μmol/L(OR=1.923,95％CI:1.064～3.476)were risk factors for long-term prognosis of patients with localized renal cell carcinoma after laparoscopic partial nephrectomy(P＜0.05).Conclusion The mortality rate of patients with localized renal cell carcinoma within 3 years after laparoscopic partial nephrectomy is high.Sarcomatoid differentiation,T stage of T1b～T3a and level of Cr ≥ 91.27 μmol/L are related to the long-term prognosis of patients with localized renal cell carcinoma after laparoscopic partial nephrectomy.Clinical interventions could be taken for high-risk patients.

Objective:To test the validity and reliability of the Chinese version of the Peer Mental Health Stig-matization Scale-Revised(PMHSS-R)in middle school students.Methods:A total of 1 099 middle school students were selected and randomly divided into Sample 1(n=549)and Sample 2(n=550)for exploratory factor analysis and confirmatory factor analysis,respectively.The total sample(n=1 099)was used to measure internal consisten-cy,and 87 of them were retested two weeks later.A total of 259 middle school students(Sample 3)was selected for the criterion validity test with the Depression Stigma Scale(DSS)and the Attitudes toward Seeking Professional Psychological Help Scale-Short Form(ATSPPH-SF).Results:Exploratory factor analysis identified 2 common fac-tors,namely stigma awareness and stigma agreement,with a cumulative variance contribution rate of 66.86％.The confirmatory factor analysis showed that the two-factor structure model fit was adequate(x2/df=3.70,CFI=0.97,TLI=0.96,SRMR=0.03,RMSEA=0.07).The PMHSS-R Chinese version scores were positively correlated with the DDS scores(ICC=0.58,P＜0.01)and negatively correlated with the ATSPPH-SF scores(ICC=-0.40,P＜0.01).The Cronbach α coefficients of the total scores and the two-factor scores were 0.90,0.92,0.85,respective-ly.The test-retest reliability coefficients(ICC)were 0.84,0.76,0.78,respectively.Conclusion:The Chinese ver-sion of the Peer Mental Health Stigmatization Scale-Revised(PMHSS-R)demonstrates good validity and reliability in assessing mental health stigma among middle school students.