Objective To investigate the causal relationship between metabolic syndrome and breast cancer by using a bidirectional two-sample Mendelian randomization (MR) approach. Methods Genome-wide association study (GWAS) summary statistics for metabolic syndrome and breast cancer were acquired from the Integrative Epidemiology Unit GWAS database and the GWAS Catalog, with populations encompassing the United States and East Asia. A bidirectional causal design was employed: a forward analysis with metabolic syndrome as the exposure and breast cancer as the outcome, followed by a reverse analysis wherein their roles were interchanged. The inverse-variance weighting (IVW) method was primarily used for effect estimation, supplemented by MR-Egger regression, the weighted median method, the simple mode method, and the weighted mode method. Instrument variable strength was screened using the F-statistic (F>10). Robustness of the results was assessed through heterogeneity tests, horizontal pleiotropy tests, forest plots, and leave-one-out sensitivity analyses. Results The IVW analysis indicated no significant causal relationship between metabolic syndrome and breast cancer (OR=1.00, 95%CI: 0.97-1.03), P>0.05). Sensitivity analyses yielded consistent results, suggesting the good robustness of the study findings. Conclusion This study found no evidence to support a causal relationship, either positive or negative, between metabolic syndrome and breast cancer.

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.

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.

Hypertension ranks among the most prevalent chronic non-communicable diseases worldwide, with its prevalence rising steadily and exerting substantial impacts on the demographic composition of voluntary blood donors and the safety of blood supply. The eligibility of hypertensive individuals for safe blood donation and the relevant screening and management strategies have long remained controversial in transfusion medicine. This article systematically reviews the epidemiological characteristics of hypertension, donation-related physiological alterations and underlying risk mechanisms. By synthesizing evidence from international multicenter studies and regulatory practices across major nations, it conducts a comprehensive analysis of blood donation safety and donor admission criteria for hypertensive patients. Available evidence demonstrates that for hypertensives with well-stabilized blood pressure and no severe cardiac, cerebral or renal complications or target organ damage, the overall incidence of adverse reactions following blood donation is comparable to that in healthy donors, and no definitive correlation has been identified between blood pressure levels and vasovagal responses. Current mainstream international management frameworks are gradually shifting from screening reliant on a single blood pressure cutoff value toward an integrated strategy combining stratified risk classification and individualized dynamic assessment, with core focus on long-term blood pressure control, consistency of medication regimens and complication status. Meanwhile, emerging technologies including artificial intelligence, ambulatory blood pressure monitoring and wearable devices have opened innovative avenues for blood donation risk evaluation and full-cycle donor management. In light of existing clinical evidence, future efforts should further refine the multi-dimensional risk stratification system, facilitate the implementation of intelligent screening and continuous monitoring technologies, and scale up health education and follow-up management for hypertensive populations. Such measures aim to appropriately expand the pool of eligible blood donors while safeguarding donation safety, ultimately achieving coordinated improvement in blood safety and blood supply capacity.

OBJECTIVE To explore the efficacy and influencing factors of intravitreal injection of ranibizumab in the treatment of macular edema （ME） secondary to retinal vein obstruction （RVO） with different optical coherence tomography （OCT） subtypes. METHODS A retrospective study was conducted on 150 patients with ME secondary to RVO treated at Dept. of Ocular Trauma of Tianjin Eye Hospital between January 1， 2021 and January 1， 2024. According to OCT findings， patients were classified into the diffuse retinal thickening （DRT） group （48 cases）， cystoid macular edema （CME） group （83 cases）， and serous retinal detachment （SRD） group （19 cases）. The best corrected visual acuity （BCVA） and central macular thickness （CMT） were compared before and at 1， 3 and 6 months after treatment. Clinical efficacies of 3 groups were compared based on CMT and fluorescein fundus angiography （FFA） findings before and after treatment. Adverse events and the number of additional injections of ranibizumab during treatment were compared among 3 groups. Using “ineffectiveness” in clinical outcomes at 6 months post- treatment as the dependent variable and patients’ baseline data as the independent variables， a multivariate Logistic regression analysis was conducted to identify risk factors influencing the clinical efficacy of ranibizumab. RESULTS The proportion of branch RVO was significantly higher in the CME and SRD groups than in the DRT group （P＜0.05）， while central RVO （CRVO） was more frequent in the DRT group than in the CME and SRD groups （P＜0.05）. The proportion of patients with ischemia was highest in the SRD group， followed by the CME and DRT groups （P＜0.05）， while the proportion of patients with ischemia in the CME group was significantly higher than that in the DRT group （P＜0.05）. Before treatment， the BCVA and CMT showed no significant differences among the 3 groups （P＞0.05）. After treatment， BCVA and CMT in all 3 groups were significantly reduced compared to those before treatment （P＜0.05）. At different treatment time points， patients in the CME group and SRD group consistently showed significantly higher BCVA and CMT values compared to those in the DRT group （P＜0.05）. Six months after treatment， the differences in clinical efficacy among the 3 groups were statistically significant （P＜0.05）， with the proportion of non-responders in the SRD group being significantly higher than that in the DRT group and the CME group （P＜0.05）. The number of additional injections of ranibizumab in patients from the CME group and the SRD group was significantly more than that in the DRT group （P＜0.05）. The incidence of adverse reactions did not differ significantly among 3 groups （P＞0.05）. Multivariate Logistic regression revealed that CRVO and ischemic type were common risk factors affecting the clinical efficacy of ranibizumab in all 3 groups， while longer disease duration was an independent risk factor for the clinical efficacy of ranibizumab in patients from the DRT group. CONCLUSIONS The therapeutic efficacy of ranibizumab varies among different OCT phenotypes of ME secondary to RVO. DRT patients achieve the best visual improvement， SRD patients have the highest non-response rate， and CME/SRD patients require more additional injections of ranibizumab. CRVO and ischemia are shared adverse prognostic factors for poor prognosis in various subtypes of ME secondary to RVO. Individualized treatment and follow-up strategies should be developed based on OCT patterns and risk factors.

Objective To investigate the alterations of cerebral blood flow(CBF)in type 2 diabetic mellitus(T2DM) patients without cognitive impairment by using arterial spin labeling(ASL)technique.Methods A total of 23 T2DM patients without cognitive impairment and 23 healthy controls(HC)matched by age,sex,and education attainment were recruited.Their clinical data were collected,and neuropsychological tests and cerebral magnetic resonance imaging were performed.Then,the outcomes of clinical features,neuropsychological tests,and global and regional CBF were compared between the two groups.The significant regional zCBF(z-transformed relative CBF)values were extracted and correlated with clinical data and neuropsychological scores in T2DM patients,controlling age,sex,and education.Results No significant difference was found in whole brain CBF between the two groups(P=0.155),while significantly higher CBF was identified in the left superior temporal gyrus and left insula in the T2DM group(Gaussian random field correction,initial threshold P < 0.001,cluster level P < 0.05).No correlation was observed between the significant regional zCBF values and the clinical data or the neuropsychological scores in T2DM patients(all P>0.05).Conclusion Alterations in cerebral hemodynamics may precede cognitive function changes in T2DM,suggesting that the ASL technique is promising for early monitoring of cerebral hemodynamic changes associated with cognitive impairment in patients with T2DM.
Humans ; Diabetes Mellitus, Type 2/physiopathology* ; Cerebrovascular Circulation ; Middle Aged ; Male ; Female ; Magnetic Resonance Imaging ; Case-Control Studies ; Cognitive Dysfunction ; Neuropsychological Tests ; Aged

Listeria brainstem encephalitis with myelitis is extremely rare in clinical practice.Since the clinical manifestations are non-specific,MRI is helpful for diagnosis.Positive cerebrospinal fluid culture is considered the gold standard for diagnosis.This article reports a case of an immunocompetent individual with listeria brainstem encephalitis with myelitis,aiming to enhance the awareness of this condition.
Humans ; Brain Stem/pathology* ; Diagnostic Errors ; Encephalitis/complications* ; Encephalomyelitis, Acute Disseminated/diagnosis* ; Listeriosis/complications* ; Myelitis/complications*

Objective To evaluate the diagnostic value of transrectal contrast-enhanced ultrasound (CEUS) for rectal cancer with intestinal stenosis caused by tumors. Methods Forty-nine patients with rectal cancer underwent transrectal CEUS and magnetic resonance imaging (MRI) before surgery.Intraoperative tumor localization and postoperative pathological results were taken as the gold standard for diagnosis.The differences in T stage,localization,and tumor length of rectal cancer were compared between the two methods. Results The total accuracy rates of transrectal CEUS and MRI in diagnosing T stage were 75.5% (36/49) and 67.3% (33/49),which had no significant difference (χ²=0.8,P=0.371).The total accuracy rates of transrectal CEUS and MRI in judging tumor localization were 79.5% (39/49) and 77.5% (38/49),which had no significant difference (χ²=0.061,P=0.806).The measurement results of tumor length in pathological examination had no significant difference from the transrectal CEUS results (t=1.42,P=0.162) but a significant difference from the MRI results (t=3.38,P=0.001).Furthermore,transrectal CEUS detected 8 (16.3%) cases of colonic polyps among the 49 patients,while MRI did not detect colon lesions. Conclusions Transrectal CEUS has good consistency with MRI in T staging and localization judgement of rectal cancer with intestinal stenosis,and this method can more accurately evaluate the tumor length and simultaneously evaluate whether there is a lesion in the entire colon at the proximal end of stenosis.It can be used as a supplementary examination before rectal cancer treatment in clinical practice.
Humans ; Rectal Neoplasms/complications* ; Male ; Middle Aged ; Female ; Aged ; Contrast Media ; Ultrasonography ; Adult ; Magnetic Resonance Imaging ; Constriction, Pathologic/diagnostic imaging* ; Aged, 80 and over ; Intestinal Obstruction/etiology*

Objective To evaluate the diagnostic value of intestinal ultrasound (IUS) for organic lesions in the intestines of patients with chronic abdominal pain or diarrhea. Methods The IUS signs in 263 patients with chronic abdominal pain or diarrhea were retrospectively analyzed.With the endoscopic examination results as the gold standard,comparison was performed for the IUS signs between the groups with positive and negative endoscopic results,as well as between the inflammatory bowel disease group and the non-specific intestinal inflammation group of positive cases.Furthermore,the detection rates of IUS in different intestinal segments were analyzed to evaluate the accuracy of IUS in the diagnosis and localization of intestinal lesions. Results Among the 263 patients,194 (73.8%) and 69 (26.2%) patients were in the groups with positive and negative endoscopic results,respectively.The diagnosis sensitivity,specificity,and accuracy of IUS were 82.0%,71.0%,and 79.1%,respectively.The proportions of positive IUS signs in the group with positive endoscopic results were higher than that in the group with negative endoscopic results (all P<0.001).The proportions of positive IUS signs in the inflammatory bowel disease group were higher than those in the non-specific bowel inflammation group (all P<0.001).When the lesion was located in the ileum,ileocecal region,and colon,IUS demonstrated good consistency with endoscopic results in locating the lesion (kappa=0.642,0.686,and 0.601,respectively),with sensitivity and specificity of 82.7% (95%CI=75.4%-88.6%) and 81.5% (95%CI=73.5%-87.9%),73.7% (95%CI=62.3%-83.1%) and 93.0% (95%CI=88.4%-96.2%),and 68.9% (95%CI=58.3%-78.2%) and 89.6% (95%CI=84.1%-93.7%),respectively. Conclusions IUS can be used for screening the patients with chronic abdominal pain or diarrhea to detect organic lesions in the intestines. Moreover,it can effectively locate the affected intestinal segment,which is helpful for the monitoring and follow-up of intestinal diseases.
Humans ; Diarrhea/diagnostic imaging* ; Female ; Male ; Abdominal Pain/diagnostic imaging* ; Middle Aged ; Adult ; Ultrasonography ; Retrospective Studies ; Aged ; Young Adult ; Intestines/diagnostic imaging* ; Adolescent ; Chronic Disease ; Sensitivity and Specificity ; Aged, 80 and over