Myosteatosis is one of the common complications in patients with end-stage liver disease, which is significantly associated with poor outcomes after liver transplantation. Currently, diagnostic criteria of myosteatosis have not been established, and CT is the most commonly used for diagnosis. The pathogenesis of myosteatosis is multifactorial, and the pathophysiological mechanisms linking it to end-stage liver disease are not fully understood. An increasing number of scholars have recognized that the severity of myosteatosis is closely related to its clinical consequences, but there are no effective treatment options available. This article reviews the pathophysiological mechanisms and diagnostic methods of myosteatosis, and its impact on the prognosis of liver transplant recipients, and discusses current treatment strategies to provide references for the perioperative management of liver transplant recipients.

Oral squamous cell carcinoma (OSCC) is a common head and neck malignancy. Approximately 50% to 60% of patients with OSCC are diagnosed at a locally advanced stage (clinical staging III-IVa). Even with comprehensive and sequential treatment primarily based on surgery, the 5-year overall survival rate remains below 50%, and patients often suffer from postoperative functional impairments such as difficulties with speaking and swallowing. Programmed death receptor-1 (PD-1) inhibitors are increasingly used in the neoadjuvant treatment of locally advanced OSCC and have shown encouraging efficacy. However, clinical practice still faces key challenges, including the definition of indications, optimization of combination regimens, and standards for efficacy evaluation. Based on the latest research advances worldwide and the clinical experience of the expert group, this expert consensus systematically evaluates the application of PD-1 inhibitors in the neoadjuvant treatment of locally advanced OSCC, covering combination strategies, treatment cycles and surgical timing, efficacy assessment, use of biomarkers, management of special populations and immune related adverse events, principles for immunotherapy rechallenge, and function preservation strategies. After multiple rounds of panel discussion and through anonymous voting using the Delphi method, the following consensus statements have been formulated: 1) Neoadjuvant therapy with PD-1 inhibitors can be used preoperatively in patients with locally advanced OSCC. The preferred regimen is a PD-1 inhibitor combined with platinum based chemotherapy, administered for 2-3 cycles. 2) During the efficacy evaluation of neoadjuvant therapy, radiographic assessment should follow the dual criteria of Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 and immune RECIST (iRECIST). After surgery, systematic pathological evaluation of both the primary lesion and regional lymph nodes is required. For combination chemotherapy regimens, PD-L1 expression and combined positive score need not be used as mandatory inclusion or exclusion criteria. 3) For special populations such as the elderly (≥ 70 years), individuals with stable HIV viral load, and carriers of chronic HBV/HCV, PD-1 inhibitors may be used cautiously under the guidance of a multidisciplinary team (MDT), with close monitoring for adverse events. 4) For patients with a poor response to neoadjuvant therapy, continuation of the original treatment regimen is not recommended; the subsequent treatment plan should be adjusted promptly after MDT assessment. Organ transplant recipients and patients with active autoimmune diseases are not recommended to receive neoadjuvant PD-1 inhibitor therapy due to the high risk of immune related activation. Rechallenge is generally not advised for patients who have experienced high risk immune related adverse events such as immune mediated myocarditis, neurotoxicity, or pneumonitis. 5) For patients with a good pathological response, individualized de escalation surgery and function preservation strategies can be explored. This consensus aims to promote the standardized, safe, and precise application of neoadjuvant PD-1 inhibitor strategies in the management of locally advanced OSCC patients.

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.

ObjectiveTo investigate the mechanism of modified Si Junzitang and Shashen Maidong Tang ［Yiqi Yangyin Jiedu prescription （YQYYJD）］ in enhancing the sensitivity of cisplatin in epidermal growth factor receptor tyrosine kinase inhibitor （EGFR-TKI）-resistant lung adenocarcinoma cells based on aerobic glycolysis. MethodsThe effects of different concentrations of YQYYJD （0， 2， 3， 4， 5， 6， 7， 8 g·L^-1） and cisplatin （0， 3， 6， 9， 12， 15， 18， 21， 24， 27 mg·L^-1） on the proliferation and activity of PC9/GR cells were detected by the cell counting kit-8 （CCK-8） assay after 24 hours of intervention. The half-maximal inhibitory concentration （IC₅₀） for PC9/GR cells was calculated to determine the concentrations used in subsequent experiments. PC9/GR cells were divided into blank group （complete medium）， YQYYJD group （5 g·L^-1）， cisplatin group （12 mg·L^-1）， and combined group （YQYYJD 5 g·L^-1 + cisplatin 12 mg·L^-1）. After 24 hours of intervention， cell viability was measured using CCK-8 assay. Cell proliferation was assessed by colony formation assay， and cell migration was evaluated by scratch and Transwell assays. Glucose consumption， lactate production， and adenosine triphosphate （ATP） levels were measured by colorimetric assays. The expression levels of glycolysis-related proteins， including hexokinase 2 （HK2）， phosphofructokinase P （PFKP）， pyruvate kinase M2 （PKM2）， lactate dehydrogenase A （LDHA）， glucose transporter 1 （GLUT1）， and monocarboxylate transporter 4 （MCT4）， were determined by Western blot. ResultsBoth YQYYJD and cisplatin inhibited the viability of PC9/GR cells in a concentration-dependent manner. The IC₅₀ of PC9/GR cells for YQYYJD and cisplatin were 5.15 g·L^-1 and 12.91 mg·L^-1， respectively. In terms of cell proliferation， compared with the blank group， the cell survival rate and the number of colonies formed in the YQYYJD group， cisplatin group， and combined group were significantly decreased （P<0.01）. Compared with the YQYYJD and cisplatin groups， the combined group showed a further significant reduction in cell survival rate and colony formation （P<0.01）. In terms of cell migration， compared with the blank group， the cell migration rate and the number of cells passing through the Transwell membrane in the YQYYJD group， cisplatin group， and combined group were significantly decreased （P<0.01）. Compared with the YQYYJD and cisplatin groups， the combined group exhibited a further significant reduction in cell migration rate and the number of cells passing through the Transwell membrane （P<0.01）. In terms of glycolysis， compared with the blank group， glucose consumption， lactate production， and ATP levels in the YQYYJD group， cisplatin group， and combined group were significantly decreased （P<0.01）. Compared with the YQYYJD and cisplatin groups， the combined group showed a further significant reduction in glucose consumption， lactate production， and ATP levels （P<0.05）. Compared with the blank group， the protein expression levels of HK2， PFKP， PKM2， and LDHA in the YQYYJD， cisplatin， and combined groups were significantly decreased （P<0.01）. The combined group showed a further significant reduction in the expression levels of these proteins compared with the YQYYJD and cisplatin groups （P<0.01）. No significant differences were observed in the protein expression levels of GLUT1 and MCT4 among the groups. ConclusionYQYYJD can synergistically inhibit the proliferation and migration of PC9/GR cells and enhance their sensitivity to cisplatin. The mechanism may be related to the downregulation of the expression of glycolysis-related rate-limiting enzymes， including HK2， PFKP， PKM2， and LDHA， thereby inhibiting glycolysis.

[Objective] To investigate the factors influencing the detection of HLA-C expression by flow cytometry. [Methods] A total of 12 hematopoietic stem cell suspension samples from peripheral hematopoietic stem cell volunteer donors were randomly collected after CD34⁺ cell counting detection. The influence of detecting different number of nucleated cell (500 000, 50 000 and 5 000), sequential order of red blood cell lysis and antibody incubation, and the HLA-C antibody with varied remaining time from the expiration date on the detection results of HLA-C expression by flow cytometry were investigated, respectively. The significance of differences between different groups was analyzed through Student t test. [Results] There was no significant difference in the proportion of HLA-C positive cells and mean fluorescence intensity (MFI) among the three groups with different nucleated cell numbers detected (500 000, 50 000 and 5 000) (P>0.05). The sequential order of red blood cell lysis and antibody incubation had no influence on the proportion of HLA-C positive cells (P>0.05), but HLA-C MFI value was significantly lower when antibody incubation was performed after red blood cell lysis than that when antibody incubation was performed before red blood cell lysis (P<0.05). The proportion of HLA-C positive cells and MFI value detected by HLA-C antibody remaining 24 months from the expiration date were significantly higher than those detected by HLA-C antibody remaining only 5 months from the expiration date (P<0.05). [Conclusion] The present study has investigated the factors of influencing HLA-C expression level by flow cytometry, the results have important reference and application value for standardizing the experimental operation of HLA-C expression and improving the accuracy and comparability of detection results.

Background: The association of changes in metabolic syndrome (MetS) with cognitive function remains unclear. We explored this association using prospective and Mendelian randomization (MR) studies. Methods: MetS components including high-density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), waist circumference (WC), fasting plasma glucose (FPG), and triglycerides were measured at baseline and two follow-ups, constructing a MetS index. Immediate, delayed memory recall, and cognitive function along with its dimensions were assessed by immediate 10- word recall test (IWRT) and delayed 10-word recall test (DWRT), and mini-mental state examination (MMSE), respectively, at baseline and follow-ups. Linear mixed-effect model was used. Additionally, the genome-wide association study (GWAS) of MetS was conducted and one-sample MR was performed to assess the causality between MetS and cognitive function. Results: Elevated MetS index was associated with decreasing annual change rates (decrease) in DWRT and MMSE scores, and with decreases in attention, calculation and recall dimensions. HDL-C was positively associated with an increase in DWRT scores, while SBP and FPG were negatively associated. HDL-C showed a positive association, whereas WC was negatively associated with increases in MMSE scores, including attention, calculation and recall dimensions. Interaction analysis indicated that the association of MetS index on cognitive decline was predominantly observed in low family income group. The GWAS of MetS identified some genetic variants. MR results showed a non-significant causality between MetS and decrease in DWRT, IWRT, nor MMSE scores. Conclusion Our study indicated a significant association of MetS and its components with declines in memory and cognitive function, especially in delayed memory recall.

The 1985 version of WHO G6PD variation classification is no longer suitable for the development of modern medicine, and it has been revised by the WHO G6PD Technical Advisory Group. According to the genetic variation classification of G6PD by WHO in 2024, G6PD deficiency is divided into four categories: Class A: enzyme activity < 20% with chronic hemolytic anemia; Class B: enzyme activity < 45% in association with acute hemolysis caused by inducement; Class C: enzyme activity > 60%, no hemolysis; Class U: for those with incomplete clinical phenotypic information, and will be classified again with new clinical evidence obtained. The clinical implications of the new classification include: (1) To guide the prevention and treatment of G6PD deficiency; (2) To better understand the pathological and non-pathological status of G6PD deficiency, which lays a foundation for re-determining the birth defect rate in China; (3) To guide the safe use of anti-malarial drugs and related oxidizing drugs in G6PD deficient patients; (4) To promote the hierarchical health management of G6PD deficient individuals throughout their life cycle; (5) To guide the pathogenicity rating of G6PD gene variation; (6) To unify the diagnostic criteria for global G6PD deficiency, promote the homogenization, comparability and data sharing of global relevant data, and lay the foundation for the application of artificial intelligence.
Humans ; Glucosephosphate Dehydrogenase Deficiency/diagnosis* ; Glucosephosphate Dehydrogenase/genetics* ; Genetic Variation ; World Health Organization ; China

Respiratory syncytial virus(RSV)infection is a major respiratory disease threatening the health of infants and immuno-compromised populations worldwide,with no specific therapeutic drugs available.Traditional Chinese medicine(TCM)has shown unique advantages of multi-target and multi-pathway in the prevention and treatment of RSV infection,and its mechanism is closely re-lated to the regulation of cellular signaling pathways.This article systematically reviews the research progress of TCM including mono-mer components and compound prescriptions in intervening RSV infection through nuclear factor-κB(NF-κB),Janus kinase/signal transducer and activator of transcription(JAK/STAT),phosphatidylinositol 3-kinase/protein kinase B(PI3K/Akt),mitogen-activated protein kinase(MAPK),nuclear factor E2-related factor 2/heme oxygenase-1(Nrf2/HO-1)and other signaling pathways.Current re-search still has problems such as insufficient analysis of pathway synergy mechanisms,unclear material basis of compounds,and single technical means.Future studies should focus on cross-talk of multiple pathways,identification of active component groups of TCM,and research on"syndrome-type-pathway"association,combined with cutting-edge technologies such as network pharmacology and or-ganoid models,so as to provide a scientific basis for the mechanism and clinical transformation of TCM against RSV infection.

Background Exposure to air pollutants increases the risk of diseases in multiple systems, including respiratory and cardiovascular systems, yet its association with neurological diseases remains unclear. Objective To quantitatively evaluate the association between short-term exposure to air pollutants and outpatient and emergency visits for neurological diseases, identify potential susceptible populations, and quantify associated disease burden. Methods Daily 24-hour average concentrations of fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO), daily maximum 8-hour average concentration of ozone (O₃), daily meteorological data (24-hour average temperature, 24-hour average relative humidity), and data on daily outpatient and emergency department visits for neurological diseases from two hospitals in Conghua District, Guangzhou, China, were collected from 2015 to 2022. A time-stratified case-crossover design was adopted, and a conditional Poisson regression model was constructed to analyze the association between air pollution exposure and neurological disease visits. Two-pollutant models and sensitivity analysis were used to validate model stability. Stratified analyses by season (cold season: from November to March; warm season: from April to October), sex (male, female), and age (≤45 years, 46–60 years, ≥61 years) were performed to identify vulnerable group. Additionally, the number and proportion of neurological disease visits attributable to short-term air pollutant exposure were calculated. Results A total of 72 673 outpatient and emergency department visits for neurological diseases were included during the study period. Most of the patients were middle-aged and elderly individuals (69.89% were over 45 years old) and females (60.25%). The results of single-pollutant models showed that for each interquartile range (IQR) increase in exposure to PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃, the risk of outpatient and emergency department visits for neurological diseases increased by 7.54% (95%CI: 4.69%, 10.46%), 6.66% (95%CI: 3.92%, 9.46%), 16.72% (95%CI: 10.58%, 23.19%), 8.12% (95%CI: 4.82%, 11.53%), 5.60% (95%CI: 2.34%, 8.97%), and 6.11% (95%CI: 2.91%, 9.40%), respectively. The results of the two-pollutant model showed that the association between PM_2.5 and SO₂ exposure and outpatient and emergency department visits for neurological diseases were relatively stable. The stratified analyses showed that the effect of SO₂ was stronger in the cold season. It was estimated that 8.32% (95%CI: 5.55%, 10.96%) and 6.65% (95%CI: 4.27%, 8.96%) of the outpatient and emergency department visits were attributable to short-term exposure to SO₂ and PM_2.5, respectively. Conclusion Exposure to PM_2.5 and SO₂ is associated with increased risks of outpatient and emergency visits for neurological diseases. SO₂ shows stronger effects during the cold season, and exposure to air pollution contributes to up to 8.32% of neurological disease visits.