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.

Methods: Fifty patients who underwent UBE-TLIF and 50 patients who underwent W-TLIF, each with >2 years of follow-up, were retrospectively analyzed. Outcomes included operative parameters, time to postoperative mobilization, paravertebral muscle atrophy and fat infiltration rates, clinical scores (Visual Analog Scale [VAS], Oswestry Disability Index [ODI], Japanese Orthopaedic Association [JOA]), modified Macnab criteria, fusion rates, and complications. Results: Compared with W-TLIF, the UBE-TLIF group had significantly less intraoperative blood loss, shorter operative times, and lower postoperative drainage volumes (p <0.05). The UBE-TLIF group showed faster postoperative recovery and shorter hospital stays. At 6 months, 1 year, and 2 years, W-TLIF patients had higher multifidus and erector spinae atrophy, and greater paravertebral muscle fat infiltration (p <0.05). The UBE-TLIF group also had lower VAS and ODI scores at 1 year and 2 years (p <0.05) and fewer surgical complications (6% vs. 10%). Fusion rates (94% vs. 92%) and modified Macnab outcomes (88% vs. 86%) were comparable (p >0.05). Conclusions UBE-TLIF is associated with reduced intraoperative trauma, quicker recovery, and fewer complications. In the long-term, it better preserves paravertebral muscle integrity and provides superior pain and functional outcomes.

Objective To evaluate the efficacy of the manual cyclotorsion compensation method based on the obser-vation screen in the correction of with-the-rule astigmatism during small incision lenticule extraction(SMILE).Methods This prospective study enrolled 40 patients who underwent SMILE and another 40 patients who underwent Q-value-guided femtosecond laser-assisted laser in situ keratomileusis(FS-LASIK)at the Ophthalmology Center of the Second Affiliated Hospital of Nanchang University from April to September 2024.Through the random number method,one eye of each pa-tient who underwent SMILE was assigned to the manual cyclotorsion compensation group(the cyclotorsion group,40 eyes),while the contralateral eye was assigned to the non-cyclotorsion group(the non-cyclotorsion group,40 eyes).Meanwhile,one eye of each patient who underwent FS-LASIK was randomly selected for the FS-LASIK group(40 eyes).The age,uncorrected distance visual acuity(UDVA),spherical power,cylindrical power,spherical equivalent(SE),and corrected distance visual acuity(CDVA)were recorded before surgery and 3 months after surgery,respectively.Astigma-tism was subjected to Alpins vector analysis,and the indicators for assessing astigmatism included target-induced astigma-tism(TIA),surgically-induced astigmatism(SIA),difference vector(DV),correction index(CI),success index(IOS),angle of error(AE),and absolute value of angle of error(|AE|).Results Before surgery,there was no significant difference in age,spherical power,cylindrical power,SE,and CDVA among the cyclotorsion group,the non-cyclotorsion group,and the FS-LASIK group(all P＞0.05).At 3 months after surgery,the cyclotorsion group showed better UDVA and lower cylindrical power than the non-cyclotorsion group,with statistically significant differences(both P＜0.05);howev-er,there was no significant difference in CDVA,spherical power,and SE between the two groups(all P＞0.05).Besides,there was no significant difference in UDVA,CDVA,or refractive parameters between the cyclotorsion and FS-LASIK groups(all P＞0.05).The Alpins vector analysis of astigmatism 3 months after surgery revealed better SIA,CI,IOS,and|AE|in the cyclotorsion group compared with the non-cyclotorsion group,with statistically significant differences(all P＜0.05);however,there was no significant difference in TIA,DV,and AE between the two groups(all P＞0.05).No signifi-cant differences were found between the cyclotorsion and FS-LASIK groups in any astigmatism vector parameter(all P＞0.05).The linear regression analysis results indicated a high linear correlation between TIA and SIA in all groups.Conclu-sion The manual cyclotorsion compensation method based on the observation screen in the correction of with-the-rule astigmatism during SMILE is comparable to Q-value-guided FS-LASIK and superior to the conventional central tear film marking method in SMILE.

Poorly differentiated and advanced thyroid cancers are characterized by high malignan-cy,progress rapidly,and resistance to radiotherapy and chemotherapy.These characteristics pose sig-nificant challenges,severely limiting effective treat-ment options.Various kinase inhibitors have been used in the treatment of refractory thyroid cancer were used accompanying by the carcinogenic mechanisms'studies investigating in thyroid cancer,such as Dabrafenib(BRAF inhibitor),Trametinib(MEK inhibitor),Vandetanib(RET inhibitor),Lenva-tinib(VEGF inhibitor),and multi-target kinase inhib-itors.However,drug resistance remains an inevita-ble issue,significantly limiting the efficacy and ap-plication of kinase inhibitors.Therapeutic approach-es such as immunotherapy,redifferentiation strate-gies for thyroid cancer,radiopharmaceutical conju-gates,and the application of nanotechnology are currently in the clinical research stage,requiring further clarification of their efficacy.Comprehen-sive understanding of therapeutic strategies and available treatment combinations for refractory thy-roid cancer is of paramount importance in the diag-nosis and treatment of thyroid cancer.Therefore,this article reviews technologies and methods for treating refractory thyroid cancer,focusing on che-motherapy,molecular targeted therapy,immuno-therapy,and radiopharmaceutical therapy,aiming to provide a reference for selecting treatment strat-egies for refractory thyroid cancer.

Objective:To investigate anxiety symptoms and associated factors in relocated elderly residents of new townships,and to provide evidence for prevention interventions.Methods:A cross-sectional study was conduc-ted in relocated elderly residents in new townships of three urban areas in Shandong Province from 2021 to 2023.The study instruments included Ascertain Dementia-8,Generalized Anxiety Disorder-7,self-administered de-mographic characteristics information questionnaire.Multivariate analysis of factors associated with anxiety symp-toms in elderly residents was performed using multivariate logistic regression.Results:The prevalence rate of mild anxiety symptoms was 5.8％,and the rate of moderate-to-severe anxiety symptoms was 1.3％in 3 313 resi-dents.Multivariate analysis found that self-assessed general psychological condition(OR=0.52),good family envi-ronment(OR=0.34),no self-perceived cognitive impairment(OR=0.31),no chronic diseases(OR=0.42),and only one chronic disease(OR=0.61)were protective factors for mild anxiety symptoms,and very good dietary structure(OR=2.15)and fair dietary structure(OR=2.39)were risk factors for those.Very good family environ-ment(OR=0.11)and average family environment(OR=0.16),and no self-perceived cognitive impairment(OR=0.14)were protective factors for moderate-to-severe anxiety symptoms,and 0-3 years(OR=3.24)and 4-6 years(OR=3.28)of relocation were risk factors for those.Conclusion:Family environment,dietary structure,and duration since relocation are key factors associated with anxiety symptoms among relocated elderly residents in new townships.Targeted interventions should be implemented to address their mental health needs.

Objective:To investigate the self-perceived cognitive decline status in the community population,and to explore the association between different dietary habits and self-perceived cognitive decline.Methods:A cross-sectional study was carried out in 11 879 community residents in the three regions of Weifang,Jining,and Zoucheng in Shandong Province.The Ascertain Dementia-8 and dietary habits information questionnaire were used to assess self-perceived cognitive decline and dietary habits,and their association were analyzed using single factor and multivariate logistic regression.Results:The detection rate of self-perceived cognitive decline was 21.4％.Lo-gistic regression showed that smoking in the past was positively associated with self-perceived cognitive decline(OR=1.40,95％CI:1.14-1.73).However,intake of fruits(often,OR=0.70,95％CI:0.52-0.94;everyday,OR=0.60,95％CI:0.44-0.81),nuts(daily,OR=0.62,95％CI:0.44-0.88),mushrooms(often,OR=0.74,95％CI:0.57-0.92)and high tryptophan foods(sometimes,OR=0.79,95％CI:0.68-0.91;everyday,OR=0.54,95％CI:0.34-0.87)were negatively associated with self-perceived cognitive decline.Conclusion:Smoking history might be a risk factor for self-perceived cognitive decline,and high frequency intake of fruits,nuts,mush-rooms,and high tryptophan foods might protective factors for it.

Objective:To investigate the relationship between lipid levels and cognitive impairment in the elderly Chinese population using prospective cohort data.Methods:Based on the China-PAR (Prediction for Atherosclerotic Cardiovascular Disease Risk in China) cohort, this study included 24 380 individuals aged ≥60 years who participated in the cognitive function follow-up survey from 2018 to 2019. Cognitive function was assessed using the Mini-Mental State Examination (MMSE), with cognitive impairment defined according to different educational levels: MMSE ≤17 for illiterate individuals, MMSE ≤20 for those with primary education and MMSE ≤24 for those with secondary education or above. Multivariable linear regression and logistic regression models were employed to examine the associations between six baseline lipid indicators and cognitive scores, as well as cognitive impairment. Additionally, restricted cubic splines were used to explore the exposure-dose relationship between lipid levels and cognitive function.Results:The study population had a median follow-up time of 11.6 years, with a baseline age of (59.7±6.8) years. Among the participants, 9 510 (39.0%) were males, and the mean MMSE score was 24.7±6.8. A total of 3 887 individuals (15.9%) were identified as cognitively impaired. The results of multivariable linear regression and logistic regression indicated that total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and non-high-density lipoprotein cholesterol (non-HDL-C) levels were not only significantly positively associated with cognitive scores but also significantly associated with a lower risk of cognitive impairment. Each 1 mmol/L increase in these lipid levels corresponded to β values (95% CI) of 0.267 (0.173-0.361), 0.385(0.271-0.499) and 0.331(0.231-0.431), respectively. Each 1 mmol/L increase in these lipid levels corresponded to odds ratio ( OR) (95% CI) values of 0.915 (0.876-0.956), 0.875 (0.830-0.923) and 0.886 (0.848-0.927), respectively. The dose-response curve demonstrated that the negative association was primarily observed within the guideline-recommended optimal lipid level range. Specifically, when LDL-C was less than 3.4 mmol/L and non-HDL-C was less than 4.1 mmol/L, the corresponding OR (95% CI) values were 0.859 (0.796-0.926) and 0.876 (0.818-0.939). Conclusion:Lipid levels exhibit a certain linear negative association with cognitive impairment in elderly Chinese adults, with LDL-C and non-HDL-C demonstrating a stronger effect, particularly within the guideline-recommended optimal range.

(rsFC)and their relationship with negative symptoms in schizophrenia patients with predominant negative symptoms(PNS).Methods Fifty-four schizophrenia patients with PNS and sixty-one healthy controls underwent resting-state functional magnetic resonance imaging(fMRI)scans.Data were collected on general demographic information,the Positive and Negative Syndrome Scale(PANSS),the Scale for the Assessment of Negative Symptoms(SANS),and the Temporal Experience of Pleasure Scale(TEPS).Twelve striatal subregions were selected as regions of interest(ROIs)to analyze the rsFC between each ROI and whole-brain voxels.The rsFC values of areas with significant differences were extracted for Pearson correlation analysis with negative symptoms.Results Compared with healthy controls,schizophrenia patients with PNS exhibited decreased rsFC between the right dorsal caudal putamen(DCP)and right insula,left middle frontal gyrus(MFG),right median cingulate and paracingulate gyri(MCC);between the left DCP and right putamen,left insula,left MFG;between the right dorsal rostral putamen(DRP)and bilateral MFG,left insula,right MCC;between the left DRP and right insula,left rolandic operculum;between the right ventral rostral putamen(VRP)and bilateral putamen,left MFG,right MCC;between the left VRP and right insula,left putamen,bilateral MFG,right MCC,left inferior parietal gyrus,excluding supramarginal and angular gyri.Decreased rsFC was also observed between the left ventral caudate/nucleus accumbens(inferior)and right insula,left anterior cingulate cortex,supracallosal,bilateral precuneus(a threshold of P<0.001 in voxel-level with P<0.05 in cluster-lever,corrected for family-wise error,PFWE<0.05/12=0.004).No regions showed increased rsFC in schizophrenia patients with PNS relative to healthy controls.And no significant correlations were found between striatal rsFC and negative symptoms(PBonferroni>0.05).Conclusion Schizophrenia patients with PNS exhibited widespread cortical-striatal functional connectivity abnormalities,particularly reduced rsFC between the putamen and the MFG,MCC and insula.

Objective:To investigate clinical efficacy and safety of dupilumab in the treatment of moderate to severe atopic dermatitis (AD) complicated with asthma.Methods:A self-controlled study before and after treatment was conducted to retrospectively analyze 45 patients with moderate to severe atopic dermatitis combined with asthma who received dupilumab in the respiratory allergy clinic of North Theater Command General Hospital from January 2021 to May 2024, which age ≥12 years, including 27 males, 18 females. The treatment period was 4 to 12 months. All patients were treated with dupilumab combined with inhaled glucocorticoids and long-acting beta2-receptor agonists, as well as symptomatic drugs for atopic dermatitis. Analyze the clinical data of the patients before and after treatment, including lung function, asthma and AD-related assessment scales. Generalized estimation equation was used to analyze the simple effect of time on the repeated measurement data following non-normal distribution, and Wilcoxon signed rank test was used to compare the differences of each observation index before and after treatment.Results:Among 45 patients with moderate to severe atopic dermatitis complicated with asthma, after treatment with dupilumab, the FEV 1 increased from 2.39 (1.87, 2.83) L at baseline to 2.50 (1.84, 2.97) L 3 months after treatment ( Z=2.417, P=0.016), 2.60 (1.95, 3.14) L 6 months after treatment ( Z=2.896, P=0.004); the FEV 1pred% increased from 74.10% (67.70%, 78.75%) at baseline to 77.09% (68.40%, 80.24%) at 3 months after treatment ( Z=2.574, P=0.010), and 77.20% (71.10%, 80.72%) at 6 months after treatment ( Z=2.861, P=0.004). Meanwhile, there were statistically significant differences in the ACT and Mini-AQLQ scales at 3, 6, and 12 months after treatment compared with those before treatment (ACT score Z=3.170, 4.216, 5.723; Mini-AQLQ score Z=3.231, 4.133, 5.826; all P<0.05). The EASI scale decreased from baseline 25.90 (18.95, 33.45) to 6.20 (1.15, 8.35) at 4 months after treatment ( Z=5.842, P<0.05) and 4.90 (2.75, 8.35) at 6 months after treatment ( Z=5.841, P<0.05), 4.00 (3.15, 5.05) at 12 months after treatment ( Z=5.841, P<0.05); The scores of each scale of IGA, NRS and DLQI decreased significantly compared with the baseline after 4 months, 6 months and 12 months of treatment, and this trend became more obvious with the extension of treatment time. The differences were statistically significant (IGA score Z=6.247, 6.070, 5.946; NRS score Z=5.960, 5.893, 5.879; DLQI score Z=5.880, 5.850, 5.848; all P<0.05). During treatment, 1 patient had local adverse reactions at the injection site and 1 patient had conjunctivitis. Conclusion:Dupilumab may have a positive effect on improving the clinical efficacy of patients with moderate to severe atopic dermatitis complicated with asthma. During the 12-month observation period, this biological agent generally demonstrated good safety characteristics.