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 construct and evaluate a prognostic model for clear cell renal cell carcinoma(ccRCC)based on preoperative lipid ratios, cM0(i+)staging, and other clinical characteristics, so as to provide a precise tool for clinical prognosis assessment. Methods A retrospective analysis was conducted on the clinical data of 215 ccRCC patients treated in our hospital during May 2014 and May 2023. Lipid ratios were calculated using preoperative lipid data, and patients were divided into cM0(i+)stage or cM0 stage according to postoperative circulating tumor cells(CTCs)test results. The optimal lipid ratio and cutoff value were selected using receiver operating characteristic(ROC)curves and the X-tile method. Patients were subdivided into three groups based on the level of the low-density lipoprotein cholesterol to non-low-density lipoprotein cholesterol ratio(LNLR)and cM0(i+)staging:Group A [LNLR＞1.68 and diagnosed with cM0(i+)], Group B [LNLR＞1.68 or diagnosed with cM0(i+)], and Group C(LNLR ≤1.68 and diagnosed with cM0). Kaplan-Meier survival analysis was used to plot survival curves for patients in different groups. The log-rank test was employed to compare differences in recurrence-free survival(RFS)among the subgroups. Multivariate Cox regression analysis was conducted to identify the independent risk factors influencing RFS, and a nomogram prediction model was constructed based on these results. The predictive performance of the model was validated using ROC curves, calibration curves, and decision curves. Results ROC curves were plotted for lipid markers, and LNLR was identified as the most predictive for RFS. Its optimal cutoff point was 1. 68. Patients in Group A experienced a significantly shorter postoperative RFS. Multivariate Cox regression analysis identified preoperative LNLR, cM0(i+)staging, pathological grade, and stage as independent risk factors for RFS. A nomogram model was constructed based on these risk factors. The area under the ROC curve(AUC)for 1-, 3-, and 5-year RFS was 0.896(95% CI:0.8121-0.9627), 0.890(95%CI:0.7879-0.9641), and 0.870(95%CI:0.7697-0.9526), indicating good discriminatory ability and predictive performance. Calibration plots demonstrated good agreement between predicted and actual outcomes. Clinical decision curve analysis showed high clinical net benefit. Conclusion Preoperative LNLR level is an independent risk factor for RFS in ccRCC patients. The prognostic prediction model based on LNLR, cM0(i+)staging, patient pathological grade, and staging demonstrates good predictive performance for RFS and holds potential clinical application value.

This paper summarizes Professor LIU Fengbin's clinical experience in treating autoimmune liver disease （AILD） using the method of nourishing yin and removing stasis based on stage differentiation. He believes that the pathogenesis of AILD generally involves both deficiency in essence and excess in manifestation， with essence deficiency often presenting as liver and kidney yin deficiency， which may progress to spleen deficiency and yang deficiency over time. The excess manifestation commonly includes qi stagnation， blood stasis， damp-heat， and phlegm toxicity. Clinically， he advocates for the treatment principle of nourishing yin and removing stasis. On the foundation of nourishing liver and kidney yin， different pathological factors causing stasis are eliminated according to their nature. Treatment is also tailored to different stages of AILD. In the early and asymptomatic stages， liver qi stagnation and spleen deficiency are prominent， warranting a therapeutic approach of soothing the liver， regulating qi and strengthening the spleen. The modified Chaishao Qizhi Decoction （柴芍气滞汤） is used. During the symptomatic stage， pathogenic factors become more pronounced， often accompanied by a significant deficiency of vital qi， with damp-heat， water retention， and phlegm toxicity as key pathological features. The treatment should focus on strengthening the spleen and dispelling dampness， using modified Sijunzi Decoction （四君子汤） combined with Yinchen Wuling Powder （茵陈五苓散）. In the liver function decompensation stage， vital qi is severely deficient while pathogenic factors persist， with damp-heat， phlegm toxicity， and blood stasis obstructing the liver collaterals. Treatment should focus on nourishing blood， softening the liver， strengthening the spleen， and resolving stasis， using the modified Ruangan Yangxue Decoction （软肝养血汤）. Throughout the treatment process， emphasis is placed on tonifying the liver and kidneys while protecting yin fluids.

Objective:To study the risk factors of thyroid nodules in patients with type 2 diabetes.Methods:Data of patients with type 2 diabetes with normal thyroid function admitted to the Department of Endocrinology of Heze Municipal Hospital from January to June 2024 were collected. Binary logistic regression was used to analyze the influencing factors of thyroid nodules in patients with type 2 diabetes, and the receiver operating characteristic curve (ROC curve) was used to evaluate the diagnostic efficacy of each influencing factor.Results:Among 162 patients with type 2 diabetes, 96 had thyroid nodules, accounting for 59.3%. The incidence of thyroid nodules in women was significantly higher than that in men (χ 2 = 4.56, P = 0.034). Multivariate logistic regression analysis showed that age (≥50 years old), overweight and obesity [body mass index (BMI)≥24.0 kg/m 2], high glycated hemoglobin (≥10%), and high total cholesterol ( > 6.5 mmol/L) were independent risk factors for thyroid nodules in patients with type 2 diabetes ( OR = 1.83, 1.67, 1.08, 3.65, P < 0.05), and men was an independent protective factor ( OR = 0.63, P = 0.039). The ROC curve results showed that total cholesterol and total cholesterol combined with glycated hemoglobin could distinguish patients with thyroid nodules from those without thyroid nodules, with AUC = 0.64 and 0.68, respectively, and the differences were statistically significant ( P < 0.05). Conclusions:The incidence of thyroid nodules in patients with type 2 diabetes is relatively high. Age, overweight and obesity, high glycated hemoglobin, and high total cholesterol are independent risk factors for thyroid nodules in patients with type 2 diabetes, and total cholesterol has the ability to distinguish patients with thyroid nodules.

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 analyze the trends and research hotspots in English publications from China′s anesthesiology discipline in international journals from 2000 to 2023 using the bibliometric analysis.Methods:Based on the results retrieved from the Science Citation Index Expanded database covering English publications from China′s anesthesiology discipline in international journals from January 2000 to December 2023, CiteSpace 6.3.R1 and VOSviewer 1.6.20.0 were employed to analyze the annual publication counts, institutions, authors, co-cited references, and keywords, etc. with knowledge graph generated.Results:A total of 53, 039 articles published in English from January 2000 to December 2023 were included. The annual number of articles published in English showed an overall increasing trend year by year. Basic research articles exhibited a phase of slow growth during 2000-2007, entered a period of accelerated growth from 2008, and demonstrated a slightly decreased trend by 2023. The number of clinical research articles increased rapidly since 2008, was equivalent to the basic research articles by 2020, surpassed basic research articles by 2023 and became the mainstream research direction of anesthesiology discipline. Among clinical research publications, case series studies predominated from 2000 to 2022, and cohort studies exceeded case series for the first time in 2023, ranking second only to the randomized controlled trials. Research hotspots in anesthesiology discipline predominantly focused on the relationship of neuropsychiatry to anesthesia, pain management, cardiovascular surgery and organ injury, COVID-19 pandemic and patient safety. In terms of journals, Medicine was the journal with the largest number of publications, with 1, 345 publications in 2023 and an impact factor of 1.3. American journals dominated the top 15 highly productive journals, and Anesthesiology had the highest h-index (60) and g-index (98) with an impact factor of 9.1. In terms of domestic high-yield institutions, Shanghai Jiao Tong University topped the list, publishing about 1, 200 papers between 2000 and 2023, followed by Sichuan University (about 850) and Capital Medical University (about 720). Conclusions:China′s anesthesiology research has demonstrated a meteoric rise in both the number of papers published and cited frequency, reflecting ascending scientific academic levels and innovation capacity in the the international arena. While acknowledging this quantitative expansion, recognition is warranted that enhancing research quality and international impact remains imperative to narrow the gap with advanced nations and gradually achieve advancement.

(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 evaluate the efficacy and safety of once-daily tacrolimus extended-release capsules (OD-TAC) in pediatric liver transplant recipients after conversion from twice-daily tacrolimus (TD-TAC).Methods:A retrospective analysis was performed on pediatric liver transplant recipients at Tianjin First Center Hospital between January 2014 and December 2020 who were converted from TD-TAC to OD-TAC with a follow-up of at least 12 months. After conversion, all patients received OD-TAC monotherapy. The daily dose conversion ratio from TD-TAC to OD-TAC ranged from 2∶1 to 1∶2. Clinical data including demographics, tacrolimus dosage, trough concentrations, liver function, and adverse events were collected. Continuous variables with normal distribution were expressed as Mean±SD and compared using independent-samples t-test or ANOVA; non-normally distributed variables were expressed as median ( Q1, Q3) and compared using Mann-Whitney U or Kruskal-Wallis H tests. Categorical variables were expressed as frequency and percentage, and compared using χ 2 test or Fisher's exact test. P<0.05 was considered statistically significant. Results:A total of 290 children were enrolled, including 140 males (48.3%) and 150 females (51.7%). The median age at transplantation was 7.34 (6.03, 12.34) months, and the median time to conversion was 36 (29, 48) months post-transplant. Tacrolimus daily doses at 3, 6, and 12 months after conversion were slightly higher than before conversion, but without statistical significance (all P>0.05). Trough tacrolimus levels at 6 and 12 months after conversion were 2.34±1.02 μg/L and 2.23±1.07 μg/L, respectively, both lower than pre-conversion (2.77±1.43 μg/L), with statistical significance ( P=0.02 and P<0.01). Serum creatinine levels at 6 and 12 months post-conversion were 2.63±0.63 mmol/L and 2.76±0.68 mmol/L, respectively, both higher than before conversion (2.57±1.90 mmol/L, P<0.05). Triglyceride level at 12 months post-conversion was 0.87±0.25 mmol/L, significantly lower than pre-conversion (1.05±0.55 mmol/L, P<0.05). Two patients developed transient bilirubin elevation at 3 months, and another two developed transient triglyceride elevation at 6 months; all recovered without intervention. No new-onset diabetes was observed during follow-up. Thirteen patients experienced acute rejection. One patient (0.3%) died three years after conversion due to hepatic venous outflow obstruction, while all others survived. Conclusion:In pediatric liver transplant recipients, OD-TAC provides comparable efficacy and safety to TD-TAC.