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.

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 study the molecular biological mechanism for a case of ABO blood group B subtype, and perform three-dimensional modeling of the mutant enzyme. [Methods] The ABO phenotype was identified by the tube method and microcolumn gel method; the ABO gene of the proband was detected by sequence-specific primer polymerase chain reaction (PCR-SSP), and the exon 6 and 7 of the ABO gene were sequenced and analyzed. Homologous modeling of Bw.03 glycosyltransferase (GT) was carried out by Modeller and analyzed by PyMOL2.5.0 software. [Results] The weakening B antigen was detected in the proband sample by forward typing, and anti-B antibody was detected by reverse typing. PCR-SSP detection showed B, O gene, and the sequencing results showed c.721 C>T mutation in exon 7 of the B gene, resulting in p. Arg 241 Trp. Compared with the wild type, the structure of Bw.03GT was partially changed, and the intermolecular force analysis showed that the original three hydrogen bonds at 241 position disappeared. [Conclusion] Blood group molecular biology examination is helpful for the accurate identification of ambiguous blood group. Homologous modeling more intuitively shows the key site for the weakening of Bw.03 GT activity. The intermolecular force analysis can explain the root cause of enzyme activity weakening.

Objective:To evaluate the effectiveness of fosaprepitant in preventing postoperative nausea and vomiting (PONV) following gynecological laparoscopic surgery.Methods:In this randomized parallel-controlled trial, 100 American Society of Anesthesiologists Physical Status classification Ⅰ or Ⅱ patients, aged 18-64 yr, undergoing elective gynecological laparoscopic surgery under general anesthesia at the First Affiliated Hospital of Zhengzhou University, were selected and divided into 2 groups ( n=50 each) in a ratio of 1∶1 using blocked randomization: fosaprepitant group (group F) and tropisetron group (group T). At 30 min before anesthesia induction, fosaprepitant 150 mg was intravenously infused in group F, and tropisetron 5 mg was intravenously infused in group T, both diluted in 150 ml of normal saline. Anesthesia was induced by intravenous injection of midazolam, etomidate, sufentanil and cisatracurium. Anesthesia was maintained by intravenous infusion of remifentanil and propofol. Patient-controlled intravenous analgesia was performed with hydromorphone at the end of operation until 48 h after operation. Metoclopramide was given as rescue antiemetic. The PONV, requirement for antiemetic drugs and related adverse reactions were recorded within 24 h after surgery. Results:The incidence of PONV (10% vs 30%), the incidence of vomiting(2% vs 16%) and the rescue rate of antiemetic drugs(2% vs 12%)were significantly lower in group F than in group T ( P<0.05). There was no significant difference in the incidence of related adverse reactions between the two groups ( P>0.05). Conclusions:Intravenous infusion of fosaprepitant 150 mg at 30 min before anesthesia induction effectively prevents PONV in patients undergoing gynecological laparoscopic surgery, and the efficacy is superior to that of the conventional use of tropisetron.

AIM:To observe the changes of atrial fibrillation susceptibility,and the remodeling of atrial myo-cyte action potential,ultrarapid activation delayed rectifier potassium current(IKur)and transient outward potassium cur-rent(Ito)in elderly mice,and to explore the mechanism of atrial fibrillation from the single cell electrophysiological level.METHODS:The C57BL/6J mice were divided into old group(20 months old)and young group(4 months old).Atrial fi-brillation was induced by esophageal atrial pacing.The atrial myocytes were isolated,and action potential and ion currents were recorded with patch-clamp technique.The associated proteins were detected by Western blot technique.RE-SULTS:(1)Compared with young mice,the total incidence of atrial fibrillation was significantly increased in old mice(20.0%at 4 months old vs 60.0%at 20 months old,P<0.01).(2)The action potential duration of atrial myocytes in aged mice was shortened,and more significantly after stimulation.(3)The density of Ito and IKur in atrial myocytes of aged mice increased significantly,from(12.6±1.4)pA/pF to(21.7±1.1)pA/pF,and from(7.5±1.5)pA/pF to(13.3±2.1)pA/pF,respectively(P<0.01).After stimulation,the current increased more significantly,especially in older atrial cells.Compared with the young mice,the steady-state activation curve of Ito in the atrial myocytes of the aged mice shifted towards the depolarization,suggesting that activation of Ito channels in the aged mice increased at the same voltage stimula-tion.(4)Compared with young group,the expression of KV4.2(generating Ito)and KV1.5(generating IKur)proteins in the atrial tissue of the mice in old group was significantly increased,and the expression of caveolin-3 and end-binding protein 1(EB1)was up-regulated,suggesting that the increases in KV4.2 and KV1.5 total channel proteins and effective proteins in the cell membrane might contribute to the increase in the remodeling of potassium currents in the elderly atrial myo-cytes.CONCLUSION:The incidence of atrial fibrillation in elderly mice is significantly augmented,which may be related to the increases in Ito and IKur in atrial myocytes.The remodeling of potassium currents in elderly atrial myocytes is one of the electrophysiological bases leading to the shortening of action potential duration and the occurrence of atrial fibrillation.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Intestinal failure(IF)is defined as a severe impairment of intestinal function requiring prolonged intravenous supplementation to maintain health or growth.Chronic intestinal failure(CIF)refers to stable metabolic dependence on parenteral support for months or years.IF is associated with life-threatening complications,and recent advances in its diagnosis and management have deepened the understanding of this condition,facilitating personalized and precision treatment strategies.This review synthesizes current knowledge on CIF,including its definition,classification,diagnostic criteria,and therapeutic approaches and its complications.

Objective To investigate the protective effect and mechanism of heat acclimation(HA)on electromagnetic field(EMF)induced hippocampus neuron injury in mice.Methods Forty healthy BALB/c male mice(18～22 g,7 weeks old)were randomly divided into 4 groups(n=10):Control group(Con),HA group(34℃,30 d),EMF group(2 450 MHz,20 min/d,4 weeks)and HA+EMF group(HA preconditioning+EMF).Sucrose preference test was performed to evaluate sucrose preference levels of mice in each group.Tail suspension test and forced swimming test were utilized to observe the immobility time.Morris water maze test was conducted to determine the learning and memory capabilities.Pathological changes in the hippocampus were observed with HE staining.Immunohistochemical assay for Iba1(marker of microglia),CD68(marker of pro-inflammatory phenotype)and CD206(marker of anti-inflammatory phenotype)were used to detect the number and activation phenotype of microglia in the hippocampus.ELISA was applied to measure the levels of TNF-α,IL-1β,TGF-β and IL-10 in the hippocampus of each group.Western blotting was performed to determine the protein levels of HSP70 in the hippocampus.Results As compared with the Con group,the EMF group showed a decreased preference for sucrose(P<0.05),prolonged immobile time in the tail suspension test(P<0.01)as well as in the forced swimming test(P<0.01),extented escape latency on the 7th day(P<0.01),and a decreased time of crossing the platform(P<0.05).EMF exposure resulted in that the hippocampal neurons were in disordered arrangement,loose structure and irregular morphology,with swollen cytoplasm and condensed nuclei,swollen and more microglial cells in the hippocampus(P<0.01),and enhanced relative fluorescence intensity of CD68(P<0.01),but not in CD206 fluorescence intensity(P=0.885).All these findings suggested that activated microglia predominantly exhibited a pro-inflammatory M1 phenotype during this phase.In the hippocampus,the levels of TNF-α and IL-1β were significantly increased,while the levels of IL-10 and TGF-β were significantly decreased(P<0.01).HA treatment reversed the conditions induced by EMF exposure,including better preference for sucrose(P<0.01),shorten immobile time in tail suspension test(P<0.05)and forced swimming test(P<0.01),less escape latency on the 7th day(P<0.01),and improved hippocampal cell injuries.Compared with the Con group,there were more microglial cells in the hippocampus in the HA+EMF group,with increased relative fluorescence intensity of M2 phenotype marker CD206(P<0.01)and decreased CD68 fluorescence intensity(P<0.01).HA treatment also significantly decreased the expression of TNF-α and IL-1β levels(P<0.01),increased the expression of IL-10 and TGF-β(P<0.01),and elevated the protein level of HSP70(P<0.01)when compared with the EMF group.Conclusion HA may ameliorate EMF-induced hippocampus neurons injury in mice by altering the phenotype of activated microglia and inhibiting inflammatory responses.