Objective: To investigate the incidence, characteristics, and influencing factors of resolution discrepancies within the minipool (MP) testing model across Chinese blood station laboratories in 2024. Methods: A nationwide, multicenter, cross-sectional study was conducted, including 334 blood station laboratories that reported nucleic acid reactive data among enzyme immunoassay non-reactive samples. Of these, 296 laboratories adopted the pool resolution model, with a total of 12 536 273 samples tested. Systematic analysis was performed on resolution data, focusing on the MP-NAT reactivity rate, the pool resolution concordance rate, and the resolution discrepancy rate. Subgroup analyses were conducted based on reagent types, viral targets, and Ct values. Potential causes were further explored through laboratory surveys and re-examination of raw amplification curves. Results: In 2024, the national average MP-NAT reactivity rate was 0.15%. The overall pool resolution concordance rate was 57.86%, which showed a gradual decline as Ct values increased across all reagents. The national average resolution discrepancy rate was 0.081‱(102/12 536 273), with 17.91%(53/296) of laboratories reporting at least one discrepancy. Nine reagent types were associated with these events, exhibiting reagent-specific patterns. For Reagent A2, the predominant discrepancy was HBV reactive pools resolving as HIV (36.36%); for Reagent D1, HBV pools frequently resolved as HCV (38.89%); and for Reagent E, the most common pattern was HIV pools resolving as HBV (48.00%). These resolution discrepancies were strongly associated with high Ct values: the median pool Ct for HBV exceeded 38, while those for HCV and HIV both exceeded 40. Investigations across 16 laboratories revealed that most discrepant samples exhibited “tailing” amplification curves, with some cases linked to cross-contamination or reagent batch-specific issues. Conclusion: While the incidence of resolution discrepancies in the MP-NAT model remains low in China, variations exist across different reagents and laboratories. These discrepancies are closely associated with low viral load, reagent performance, and laboratory operational practices.

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.

From the theoretical perspective of "body fluids and blood stasis mixing"， environmental microplastics （MPs） are conceptualized as a "novel turbid-toxin". This study aims to elucidate the complete pathogenic pathway through which MPs act as a key driving force （the "crucible" of pathogenesis） in the initiation and progression of atherosclerosis （AS）. By tracing the classical theories in the Chapter The Occurrence of All Diseases of Miraculous Pivot （Ling Shu）， this paper clarifies the core connotations of "body fluids"-it not only refers to endogenous pathological fluids and lipid turbidity but also provides a theoretical basis for incorporating "exogenous turbid fluids"， thereby laying a logical foundation for conceptualizing MPs as a "novel turbid-toxin". Meanwhile， the implications of "blood" （encompassing both blood quality abnormalities and blood stasis） and the dynamic process of "mixing" are elucidated. Drawing upon modern toxicological evidence， this paper demonstrates the high homology between MPs and "exogenous turbid-fluids" from three aspects： Morphology， toxicity， and invasion routes. The micro/nano-scale particle morphology of MPs enables mobility within the bloodstream. The multiple exposure pathways of MPs correspond to the traditional Chinese medicine understanding of pathogens invading through the mouth， nose， and skin. The characteristics of accumulating in vivo while inducing oxidative stress and inflammatory responses of MPs fully embody the pathogenic features-adhesion， binding， and vessel damage-of "turbid-toxin". On this basis， the dynamic pathogenesis of MP-induced AS is systematically interpreted. Initially， MPs with the "turbid-toxin" nature impair nutrient-defense harmony and cause endothelial dysfunction. Subsequently， as the core of "mixing"， they interact with blood lipids and immune cells， generating heat and phlegm to form a major pathological hub of chronic inflammation. Ultimately， this process drives the coalescence of phlegm， stasis， and turbid-toxin into tangible plaques， evolving from stable lesions to vulnerable masses and accumulations. By integrating classical pathogenic model with contemporary environmental medicine， this study establishes an analytical framework that bridges macro-theory and micro-mechanisms for understanding the cardiovascular risks of MPs through an integrative Chinese-Western medicine lens.

Varicella, often referred to as chickenpox, is a widespread acute infectious condition triggered by the varicella-zoster virus (VZV). It manifests with systemic symptoms and distinct skin and mucosal eruptions, including macules, papules, and vesicles. Although it mainly affects children, the disease is typically more severe in teenagers and adults. Following the adoption of vaccine-based control measures in China, there has been a noticeable trend of varicella affecting older demographics, leading to an uptick in cases among teenagers and adults. This review synthesizes the latest research on the clinical symptoms, epidemiological trends, and immunization strategies for varicella in these age groups, both domestic and aboard. The goal is to enhance strategies for prevention and control, support the development of tailored immunization policies, and underscore the critical role of the varicella vaccine in comprehensive health management across all ages.

Immunization represents the most effective strategy for the prevention and control of diseases. Nevertheless, some people may still get infected and contract the disease even after being fully vaccinated, which is known as a "breakthrough case." The presence of breakthrough cases shows that although vaccines significantly lower the rates of disease and death, they do not entirely eliminate the risk of illness.Addressing breakthrough cases, comprehending their epidemiological characteristics, and identifying the associated factors carry substantial public health implications for vaccine development, the optimization of vaccination strategies, and the implementation of intervention efforts. This review aims to provide a scientific reference for enhancing the prevention and control of vaccine-preventable diseases by summarizing the definitions, epidemiological characteristics, and relevant factors related to breakthrough infection cases across various diseases.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To explore the efficacy of goal management training(GMT)on core symptoms and mental status in college students with attention deficit hyperactivity disorder(ADHD)inattentive type.Methods Delphi method was used to construct a GMT program for college students with inattentive ADHD.Then,totally 68 college students with inattentive ADHD were recruited through advertisements published by hospitals and universities(Second Affiliated Hospital of Army Medical University,and 3 universities in Chongqing from March to June 2024.The subjects were randomly divided into an intervention group(n=34)and a control group(n=34).The intervention group received GMT for 2 h,once a week,for 7 weeks,and the control group did not receive training for the time being.The 2 groups were evaluated within 1 week before and in 7 weeks after intervention by using Adult ADHD Self-Report Scale(ASRS),Dysregulation of Emotions Rating Scale(DERS),Generalized Anxiety Disorde-7(GAD-7),Patient Health Questionnaire-9(PHQ-9),Self-Compassion Scale(SCS),and Satisfaction with Life Scale(SWLS).Results ① The expert authority coefficient(Cr)of 2 rounds of expert consultation was 0.83,with a questionnaire recovery rate of 100%and 95%,respectively,the Kendall's coordination coefficient was 0.081(P<0.01)and 0.226(P<0.01),and the coefficient of variation was<0.3,indicating the results of the expert consultation were reliable.The constructed GMT program includes 1 first-level indicator,7 second-level indicators,and 20 third-level indicators.② After 7 weeks of GMT intervention,the interaction between the 2 groups and time showed that the experimental group obtained significant improvements than the control group in terms of inattention symptoms(Wald Chi-square=28.35,P<0.001),dysregulation of emotions(Wald Chi-square=23.81,P<0.001),anxiety(Wald Chi-square=22.79,P<0.001),depression(Wald Chi-square=20.52,P<0.001),self-compassion(Wald Chi-square=9.36,P<0.01),and life satisfaction(Wald Chi-square=3.97,P<0.05).Conclusion GMT intervention can significantly improve the core symptoms of college students with inattentive ADHD,reduce anxiety and depression levels,enhance their emotion regulation and self-compassion abilities,and improve their life satisfaction.

OBJECTIVE: To distinguish the ambiguous genotyping results of human leukocyte antigen (HLA), identify a novel HLA-B allele and analyze the nucleotide sequence. METHODS: A total of 2 076 umbilical core blood samples from the Zhejiang Cord Blood Bank in 2022 were detected using the next generation sequencing technology (NGS) based on the Ion Torrent S5 platform. Among these a rare HLA-B allele with ambiguous combination result containing a base mutation was identified, and was further confimed by the third-generation sequencing (TGS) based on the nanopore technology. RESULTS: The NGS typing result of HLA-B locus showed HLA-B* 46:18, 54:06 or HLA-B*46:01, 54:XX (including a base mutation), and nanopore sequencing confirmed the typing as HLA-B*46:01, 54:XX (including a base mutation). Compared with HLA-B*54:01:01:01, the HLA-B*54:XX allele showed one single nucleotide substitution at position 1014 T>C in exon 6, with no amino acid change. The nucleotide sequence of the novel HLA-B*54:XX has been submitted to the GenBank nucleotide sequence database and the accession number OP853532 was assigned. CONCLUSION A ambiguous genotyping of the HLA-B Locus detected by NGS was distinguished by nanopore sequencing and a new HLA-B allele was successfully identified, which was officially named as HLA-B*54:01:11 by the World Health Organization Nomenclature Committee for Factors of the HLA System.
Humans ; High-Throughput Nucleotide Sequencing ; Alleles ; HLA-B Antigens/genetics* ; Genotype ; Mutation ; Sequence Analysis, DNA ; Base Sequence

Although cancer immunotherapy has made great strides in the clinic, it is still hindered by the tumor immunosuppressive microenvironment (TIME). The stimulator of interferon genes (STING) pathway which can modulate TIME effectively has emerged as a promising therapeutic recently. However, the delivery of most STING agonists, specifically cyclic dinucleotides (CDNs), is performed intratumorally due to their insufficient pharmacological properties, such as weak permeability across cell membranes and vulnerability to nuclease degradation. To expand the clinical applicability of CDNs, a novel pH-sensitive polycationic polymer-modified lipid nanoparticle (LNP-B) system was developed for intravenous delivery of CDNs. LNP-B significantly extended the circulation of CDNs and enhanced the accumulation of CDNs within the tumor, spleen, and tumor-draining lymph nodes compared with free CDNs thereby triggering the STING pathway of dendritic cells and repolarizing pro-tumor macrophages. These events subsequently gave rise to potent anti-tumor immune reactions and substantial inhibition of tumors in CT26 colon cancer-bearing mouse models. In addition, due to the acid-sensitive property of the polycationic polymer, the delivery system of LNP-B was more biocompatible and safer compared with lipid nanoparticles formulated with an indissociable cationic DOTAP (LNP-D). These findings suggest that LNP-B has great potential in the intravenous delivery of CDNs for tumor immunotherapy.