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.

Chronic mucocutaneous candidiasis (CMC) is an infectious phenotype characterized by recurrent or persistent infections caused by Candida species that affect the skin, nails, oral, and genital mucosae for a duration exceeding six months. Current research suggests that CMC is an immunodeficiency disease with a complex pathogenesis. Patients with CMC have various defects in nonspecific and/or specific immunity against Candida infection, resulting in the inability of patients to defend themselves against Candida infection. CMC can be stratified into primary CMC and secondary CMC based on etiology. Primary CMC is often associated with genetic mutations leading to immunodeficiencies in T helper cell 17 and interleukin-17, whereas secondary CMC is frequently linked to factors such as human immunodeficiency virus infection, diabetes mellitus, and immunosuppressive therapy. Primary CMC typically manifests as Candida infections, with distinct genetic mutations often correlating to varied concomitant symptoms. Secondary CMC may present with not only superficial mucosal Candida infections and manifestations of the underlying primary disease but also with invasive fungal infections. Diagnosing CMC requires an integration of medical history and clinical presentation, supplemented by the outcomes of auxiliary diagnostic procedures, including microscopic examination of fungal smear, fungal culture, immunological testing, and genetic sequencing and analysis. Furthermore, confirming primary CMC requires exclusion of the aforementioned secondary factors. At present, antifungal drugs such as triazoles, echinocandins, and polyenes are the main treatment for CMC. Moreover, immunotherapy with biologics such as Janus kinase (JAK) inhibitors provides more options for the clinical treatment of patients with CMC. Gene therapy also has potential clinical application value. In this review, we discuss the etiologies, pathogenesis, clinical manifestations, diagnosis, and treatments of CMC, aiming to provide a reference for the clinical diagnosis and treatment of CMC.

Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

OBJECTIVE T o explore the long-term effect of multidimensional evidence-based interventions based on i-PARIHS theoretical framework on reduction of incidence of central line-associated bloodstream infections(CLABSI)in pediatric intensive care units(PICU)of pediatrics department and evaluate the impact on nurses'compliance to taking the interventions and use intensity of catheters.METHODS By means of quasi-experimental design,the multidimensional intervention system covering multidisciplinary collaboration,standardized operation procedures,information system optimization and hierarchical training was established and staged for implementa-tion of 5 years(from T0 baseline stage to T3 maintenance stage).The variations in implementation rates of cathe-ter maintenance(daily maintenance,dressings change,catheter removal)were analyzed by Chi-square test,and the change of incidence of CLABSI was monitored with the use of statistical process control U chart.RESULTS The nurses'compliance to operations was remarkably improved(P＜0.05)o The implementation rate of dressings change continuously increased from 52.91％in T0 to81.62％in T3(x2=72.444,P＜0.001),the implementa-tion rate of catheter removal increased from 48.72％to 79.31％(x2=8.179,P=0.042).The incidence rate of CLABSI decreased from 1.92％0 in 2019 to 0.5％0 in 2022,and the control chart showed that most of the months fluctuated within control limits.CONCLUSIONS The multidimensional evidence-based interventions can achieve a long term control of CLABSI by raising the nurses' compliance to operations.The information monitoring and closed-loop management are crucial to maintenance of the interventional effect,and the risk early warning system should be optimized with the combination of artificial intelligence technology.

Objective To construct and preliminary verify a postoperative pulmonary rehabilitation nursing programme for children with double lung transplantation,aiming to promote early recovery and provide references for clinical nursing practice.Methods A convenience sampling approach was employed to select 25 cases pediatric patients who underwent bilateral lung transplantation at a tertiary teaching hospital in Hangzhou between January 2020 and September 2024,and they were divided into an experimental group and a control group according to the time of admission to the hospital.The experimental group received the newly developed post-transplant rehabilitation nursing program,which encompassed fluid management,mechanical ventilation,sequential oxygen therapy,pulmonary function training,exercise management,and process facilitation.In contrast,the control group received the standard post-lung transplantation rehabilitation protocol.Key outcomes,including mechanical ventilation duration,ICU stay,total hospitalization time,activity level,pulmonary function,incidence of adverse events and rehabilitation adherence,were compared between the 2 groups.Results Finally,24 cases completed the study,including 11 cases in the experimental group and 13 cases in the control group.After the intervention,the experimental group exhibited significantly shorter mechanical ventilation time compared to it in the control group(P=0.009).Additionally,at discharge,the intervention group demonstrated higher activity levels and better rehabilitation compliance(P＜0.05).Conclusion The pulmonary rehabilitation nursing program for children with double lung transplantation is scientifically sound,safe,and feasible.The implementation of this program is beneficial for the early discontinuation of mechanical ventilation,improving postoperative mobility,and enhancing compliance with pulmonary rehabilitation.

A method for determination and targeted screening of diflorasone components in health products using ultra performance liquid chromatography-quadrupole time of flight mass spectrometry(UPLC-Q-TOF/MS)was established.Four representative diflorasone and esters(diflorasone,diflorasone diacetate,diflorasone-17-propionate,and diflorasone-21-propionate)were selected to optimize the pretreatment conditions,and 10 mL of extraction solvent dosage,15 min of extraction time and 5 g of salting-out agent as the optimal conditions were selected by response surface methodology.The results showed that the four analytes exhibited good linearity within the concentration range of 2.0?100 μg/L with the chromatographic peak area,and the correlation coefficients(R2)were all greater than 0.9990,while the results of recovery and relative standard deviation could satisfy the requirements of determination.The common characteristic ions of diflorasone and esters werem/z121 andm/z335,and their specific structures were obtained by analyzing the cleavage pathway based on the optimized determination conditions.A targeted screening method for other esters of diflorasone based on characteristic ions guidance strategy was established.This method had many advantages such as high efficiency,high sensitivity and good reproducibility,and could be used for targeted screening of diflorasone and esters in health products.The developed characteristic ion guided strategy could be employed to construct mass spectral databases for various glucocorticoids,enabling comprehensive targeted screening across a broad range of compounds.

Objective Based on the national drug sampling inspection program,this study aims to comprehensively and systematically evaluate the quality of Xuanmai Ganjie preparations,analyze existing quality issues,and provide references and suggestions for quality control of this variety.Methods A total of 237 batches of Xuanmai Ganjie preparations were tested using legal standards,and methods were established for detecting adulteration of Ophiopogon japonicus with counterfeit varieties,paclobutrazol residue levels,and determining the content of platycodin D in Xuanmai Ganjie preparations.These methods were applied to the quality control and evaluation of Xuanmai Ganjie preparations.Results Through statutory inspection,one batch of Xuanmai Ganjie granules was found non-compliant.Specific batches were identified to contain the following irregularities:adulteration of Ophiopogon japonicus with counterfeit varieties,paclobutrazol residue levels exceeding proposed limits,and platycodin D content below the established threshold.Conclusion The overall quality of Xuanmai Ganjie granules was average,while the overall quality of Xuanmai Ganjie capsules and lozenges was relatively good.Manufacturing enterprises should strengthen their sense of primary responsibility and enhance control over the entire drug production process.

BACKGROUND:The cryopreservation technology enables tissues/cells to be stored for a long time in a low-temperature environment while maintaining the integrity of their activity and function,which is of great significance for the construction of cell therapy,tissue engineering and biological sample banks.Cryoprotective agents often contain dimethyl sulfoxide and serum.To avoid the toxic side effects of dimethyl sulfoxide,the complexity of serum components and immune responses,although some finished cryoprotective agents have been marketed,they are faced with many difficulties such as high cost and limited application.Therefore,there is an urgent need to develop a cryoprotective agent with clear components and the ability to solve the above problems.OBJECTIVE:To evaluate the effects of a novel cryoprotectant on cryopreservation efficiency of different tissue and cell sources.METHODS:By applying the novel cryoprotectant as an experimental group with the commercially available and widely used cryoprotectant(control group)to umbilical cord Wharton's jelly tissue,umbilical cord mesenchymal stem cells,umbilical cord blood/peripheral blood mononuclear cells,NK and CIK cells,comparative analyses were conducted in terms of cell morphology,number,viability,surface markers,differentiation potential,and cell-killing toxicity assay before cryopreservation and after resuscitation thawing.We confirmed the cryopreservation effect of the new cryoprotectant and its potential application value.RESULTS AND CONCLUSION:(1)The novel cryoprotectant facilitated the normal growth of cryopreserved Wharton's jelly tissue upon recovery,exhibiting mesenchymal stem cell morphology.No significant differences were observed between the experimental and control groups in terms of cell recovery rate,surface markers,and differentiation potential.(2)There was no significant difference in the number and viability of cells between the experimental group and the control group after cryopreservation of cord blood/peripheral blood mononuclear cells,and the cryo-resuscitated cell numbers and viability of derived NK cells/CIK cells did not show significant difference between the experimental and control groups.(3)For NK cells derived and differentiated from cord blood/peripheral blood mononuclear cells,there was no significant difference in the proportion of CD56+CD16+cell subpopulations between the experimental group and the control group.For CIK cells derived and differentiated from cord blood/peripheral blood mononuclear cells,there was no significant difference in the proportions of CD3+CD8+and CD3+CD56+cell subpopulations between the experimental group and the control group.(4)In terms of cytotoxicity testing,when the effective-target ratio of immune cells and melanoma cell line Mel624 was 20:1,whether it was NK cells/CIK cells derived from cord blood or peripheral blood mononuclear cells,there was no significant difference in the tumoricidal activity of cells between the experimental group and the control group.These findings suggest that the novel cryoprotectant can replace existing commercially available and widely used cryoprotectants,and is applicable to Wharton's jelly tissue,umbilical cord mesenchymal stem cells,umbilical cord blood/peripheral blood mononuclear cells,as well as NK and CIK cells,providing a solid technical foundation for the scaling,standardization,and commercialization of universal cryoprotectants.

OBJECTIVE T o explore the long-term effect of multidimensional evidence-based interventions based on i-PARIHS theoretical framework on reduction of incidence of central line-associated bloodstream infections(CLABSI)in pediatric intensive care units(PICU)of pediatrics department and evaluate the impact on nurses'compliance to taking the interventions and use intensity of catheters.METHODS By means of quasi-experimental design,the multidimensional intervention system covering multidisciplinary collaboration,standardized operation procedures,information system optimization and hierarchical training was established and staged for implementa-tion of 5 years(from T0 baseline stage to T3 maintenance stage).The variations in implementation rates of cathe-ter maintenance(daily maintenance,dressings change,catheter removal)were analyzed by Chi-square test,and the change of incidence of CLABSI was monitored with the use of statistical process control U chart.RESULTS The nurses'compliance to operations was remarkably improved(P＜0.05)o The implementation rate of dressings change continuously increased from 52.91％in T0 to81.62％in T3(x2=72.444,P＜0.001),the implementa-tion rate of catheter removal increased from 48.72％to 79.31％(x2=8.179,P=0.042).The incidence rate of CLABSI decreased from 1.92％0 in 2019 to 0.5％0 in 2022,and the control chart showed that most of the months fluctuated within control limits.CONCLUSIONS The multidimensional evidence-based interventions can achieve a long term control of CLABSI by raising the nurses' compliance to operations.The information monitoring and closed-loop management are crucial to maintenance of the interventional effect,and the risk early warning system should be optimized with the combination of artificial intelligence technology.