Objective: To establish a rapid, accurate, and decentralized workflow for bacterial whole-genome sequencing (WGS) and risk profiling within the shelf-life of platelet concentrates, and to characterize the species, virulence, antimicrobial resistance (AMR), and immune evasion mechanisms of co-existing bacteria in qualified platelet products, thereby providing a scientific basis for transfusion safety assessment. Methods: Three units of platelet concentrates, which tested negative by routine bacterial screening, were collected from the Chengdu Blood Center between May and June 2025. Samples were enriched at 37℃under six aerobic and nine anaerobic conditions for 7 days. Using a culturomics strategy, aliquots were plated for isolation on days 1, 3, 5, and 7 to obtain cultivable isolates, with negative culture controls included to exclude contamination. High-molecular-weight genomic DNA was extracted via mechanical grinding, purified, and size-selected. Sequencing libraries were constructed and sequenced on the G-seq500 single-molecule nanopore sequencing platform. Genomes were assembled using Flye and polished with NextPolish, with quality evaluated by BUSCO and CheckM. Taxonomic identification was performed using GTDB-Tk. Functional annotation and database comparisons were conducted to analyze virulence factors, AMR genes, and genes related to immune evasion and environmental adaptation. Results: Viable bacteria were successfully isolated from all three qualified platelet units within their shelf life. The isolates were identified as Bacillus albus, Niallia taxi, and Staphylococcus warneri. Nanopore sequencing generated 92 227-109 813 reads (totaling 680-758 Mb) with an N50 of 7 625-8 584 bp and Q20/Q30 scores of 97%/93%, respectively. All three genomes were assembled into complete circular chromosomes with 1-3 plasmids, achieving >93% completeness. Functional analysis revealed that B. albus carried multiple hemolysins, metalloproteases, and multidrug resistance genes, indicating the highest potential pathogenicity and AMR risk. S. warneri exhibited a typical multidrug resistance profile and regulatory network characteristic of coagulase-negative staphylococci, suggesting intermediate virulence. N. taxi harbored few canonical virulence factors and lacked functional AMR determinants, presenting a "low-virulence, low-resistance" profile. Notably, all three strains were enriched in genes encoding antimicrobial peptide resistance systems (e.g., dltABCD, mprF, GraRS, BceAB) and antioxidant enzymes, suggesting a strong capacity to withstand immune stress in the blood environment. Conclusion: Viable bacteria can be recovered from qualified platelet concentrates that test negative by routine screening. Nanopore WGS enables rapid strain-level identification and comprehensive risk profiling of virulence, resistance, and immune adaptation traits. The functional repertoires of these "co-existing" isolates range from environmental adaptation to potential pathogenicity, representing an underappreciated risk for transfusion-transmitted infections in susceptible recipients.

ObjectiveTo explore the interaction and competitive binding of Homo sapiens long intergenic non-protein-coding RNA 1134 （LINC01134） to CCCTC-binding factor CTCF， affecting the transcription of cyclin-dependent kinase inhibitor （p21） and influencing the proliferation of A549 cells， in order to investigate the possible mechanism of Astragali Radix and Hedyotis diffusa （A-H） in inhibiting A549 proliferation by regulating this axis. MethodsRNA-binding protein immunoprecipitation （RIP） assays were conducted to examine the interaction between LINC01134 and CTCF， and chromatin immunoprecipitation （ChIP） assays were used to study the effect of LINC01134 overexpression on the interaction between CTCF and p21. Stable A549 cell lines （oe-NC and oe-LINC01134） were established using lentiviral transfection， and each group was treated with 10% A-H drug-containing serum. Real-time PCR and Western blot analyses were performed to detect the effects of A-H on the expression of LINC01134， CTCF， and p21 in A549 cells. Cell counting kit-8 （CCK-8） and colony formation assays were used to assess the effects of A-H on A549 cell proliferation via LINC01134. Flow cytometry was employed to evaluate the effects of A-H on the A549 cell cycle through LINC01134， and Western blot was used to detect changes in cell cycle proteins. ResultsCompared with the IgG group， the oe-CTCF group showed a significantly increased abundance of LINC01134 aggregates （P0.01）. Compared with the oe-Vector group， p21 abundance in CTCF complexes was significantly reduced in the oe-LINC01134 group （P0.01）. Compared with the 10% blank + oe-LINC01134 group， the 10% A-H + oe-LINC01134 group reversed the expression of LINC01134 and p21 （P0.05）， but had no significant regulatory effect on CTCF. Compared with the 10% blank + oe-LINC01134 group， the 10% A-H + oe-LINC01134 group reversed cell viability at 72 h （P0.05）， inhibited malignant proliferation （P0.05）， and reversed the proportions of cells in the G₀/G₁ and S phases （P0.01）. Furthermore， compared with the 10% blank + oe-LINC01134 group， the 10% A-H + oe-LINC01134 group reversed the expression of Cyclin D₁， CDK4， Cyclin E， CDK2， phosphorylated retinoblastoma protein （p-Rb）， and E2F transcription factor 3 （E2F3） （P0.01）. ConclusionA-H regulates the LINC01134-CTCF-p21 axis to block the G₁/S phase transition of A549 cell cycle， accelerate cellular senescence， and inhibit malignant proliferation.

ObjectiveTo explore the interaction and competitive binding of Homo sapiens long intergenic non-protein-coding RNA 1134 （LINC01134） to CCCTC-binding factor CTCF， affecting the transcription of cyclin-dependent kinase inhibitor （p21） and influencing the proliferation of A549 cells， in order to investigate the possible mechanism of Astragali Radix and Hedyotis diffusa （A-H） in inhibiting A549 proliferation by regulating this axis. MethodsRNA-binding protein immunoprecipitation （RIP） assays were conducted to examine the interaction between LINC01134 and CTCF， and chromatin immunoprecipitation （ChIP） assays were used to study the effect of LINC01134 overexpression on the interaction between CTCF and p21. Stable A549 cell lines （oe-NC and oe-LINC01134） were established using lentiviral transfection， and each group was treated with 10% A-H drug-containing serum. Real-time PCR and Western blot analyses were performed to detect the effects of A-H on the expression of LINC01134， CTCF， and p21 in A549 cells. Cell counting kit-8 （CCK-8） and colony formation assays were used to assess the effects of A-H on A549 cell proliferation via LINC01134. Flow cytometry was employed to evaluate the effects of A-H on the A549 cell cycle through LINC01134， and Western blot was used to detect changes in cell cycle proteins. ResultsCompared with the IgG group， the oe-CTCF group showed a significantly increased abundance of LINC01134 aggregates （P0.01）. Compared with the oe-Vector group， p21 abundance in CTCF complexes was significantly reduced in the oe-LINC01134 group （P0.01）. Compared with the 10% blank + oe-LINC01134 group， the 10% A-H + oe-LINC01134 group reversed the expression of LINC01134 and p21 （P0.05）， but had no significant regulatory effect on CTCF. Compared with the 10% blank + oe-LINC01134 group， the 10% A-H + oe-LINC01134 group reversed cell viability at 72 h （P0.05）， inhibited malignant proliferation （P0.05）， and reversed the proportions of cells in the G₀/G₁ and S phases （P0.01）. Furthermore， compared with the 10% blank + oe-LINC01134 group， the 10% A-H + oe-LINC01134 group reversed the expression of Cyclin D₁， CDK4， Cyclin E， CDK2， phosphorylated retinoblastoma protein （p-Rb）， and E2F transcription factor 3 （E2F3） （P0.01）. ConclusionA-H regulates the LINC01134-CTCF-p21 axis to block the G₁/S phase transition of A549 cell cycle， accelerate cellular senescence， and inhibit malignant proliferation.

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 effect of Sanet Vision Integrator (SVI)-based visuomotor integration training on the severity of neglect symptoms, upper limb motor function and activities of daily living (ADL) in patients with post-stroke unilateral spatial neglect (USN). MethodsFrom July, 2023 to September, 2025, 41 patients with post-stroke USN in Beijing Bo'ai Hospital were enrolled and randomly assigned to control group (n = 20) and experimental group (n = 21). Both groups received conventional rehabilitation and visual scanning training, while the experimental group received supplementary SVI-based visuomotor integration training, including saccadic, rotation and hand-eye coordination training, for eight weeks. They were assessed with Chinese Behavioral Inattention Test-Hong Kong version (CBIT-HK), Fugl-Meyer Assessment-Upper Extremities (FMA-UE) and modified Barthel Index (MBI) before and after treatment. ResultsAfter treatment, all the scores significantly improved in both groups (|t| > 4.004, P < 0.001), and the total scores of CBIT-HK and the core visual search sub-items (star cancellation, line crossing and letter cancellation), FMA-UE and MBI were better in the experimental group than in the control group (t > 2.096, P < 0.05). ConclusionSVI-based visuomotor training can effectively alleviate the USN symptoms, broaden the span of visual attention, facilitate the functional recovery of the affected upper extremity, and improve ADL in patients after stroke.

Objective To investigate the effect of diet and lifestyle on cardiovascular comorbidity in elderly diabetic patients in community. Methods A total of 437 elderly patients with diabetes mellitus in a community of Huai'an City were divided into comorbidity group and non-comorbidity group according to the presence or absence of cardiovascular comorbidity. Dietary and lifestyle data were collected by self-designed questionnaires. The differences between the two groups were compared. Multivariate logistic regression was used to analyze the influencing factors of comorbidity of diabetes mellitus with cardiovascular disease. Results Among the surveyed patients, 184 (42.11%) had at least one comorbidity of cardiovascular disease, with the most common diseases being hypertension in 93 patients (21.28%), coronary heart disease in 71 patients (16.25%), and stroke in 42 patients (9.61%). Multivariate logistic regression analysis showed that: the risk of comorbidity in the male group was 1.528 times higher than that in the female group; the risk of comorbidity among individuals with inadequate carbohydrate intake was 1.520 times higher than that of individuals with adequate carbohydrate intake; the risk of comorbidity in the group with smoking history > 30 years was 1.299 times higher than that in the group ≤ 30 years; the risk of comorbidity was 49.80% lower in the group with tea preference than that in the group without tea preference; and the risk of comorbidity in the group not meeting the standard for exercise was 1.492 times higher than that in the group meeting the standard for exercise. All these differences were statistically significant (P<0.05). Conclusion The comorbidity of cardiovascular disease in elderly diabetic patients in community should not be ignored, and targeted dietary and lifestyle interventions are helpful for the prevention and control of comorbidity.

Objective: To investigate the influencing factors for kinesiophobia among elderly patients with chronic obstructive pulmonary disease (COPD), so as to provide the reference for alleviating kinesiophobia among COPD patients. Methods: From December 2023 to July 2024, COPD patients aged 60 years and above who sought medical treatment at a tertiary grade-a hospital in Guiyang City were selected. Demographic information was collected through questionnaire surveys. Kinesiophobia, exercise self-efficacy, social support, type D personality and coping styles were assessed using the Chinese version of Tampa Scale for Kinesiophobia, the Chinese version of the Self-Efficacy for Exercise Scale, Social Support Rating Scale, Type D Personality Scale and Chinese version of the Medical Coping Modes Questionnaire, respectively. Factors affecting kinesiophobia among elderly patients with COPD were analyzed using a multiple linear regression model. Results: A total of 300 COPD patients were surveyed, including 238 males (79.33%) and 62 females (20.67%). The majority of patients had a disease duration of less than 5 years, with 130 cases (43.33%). The average kinesiophobia score was (48.01±7.74) points. The average exercise self-efficacy score was (3.39±1.01) points. The average social support score was (34.42±6.76) points. There were 280 patients (93.33%) with type D personality. The average scores of the confrontation, avoidance, and resignation dimensions of coping styles were (17.42±5.00), (13.76±1.91), and (11.81±2.95) points, respectively. Multiple linear regression analysis showed that age (70-<80 years, β'=0.124; ≥80 years, β'=0.205), educational level (primary school and below, β'=0.228; junior high school, β'=0.182), household monthly income per capita (<3 000 yuan, β'=0.234; 3 000~<5 000 yuan, β'=0.165), social support (β'=0.294), type D personality (β'= 0.170), and coping styles (confrontation dimension, β'=-0.140; avoidance dimension, β'=0.154; resignation dimension, β'=0.175) statistically associated with kinesiophobia among elderly patients with COPD. Conclusion Kinesiophobia among elderly patients with COPD is associated with age, educational level, household monthly income per capita, social support, type D personality and coping styles.

Objective To investigate the association between birth weight and dementia risk and the mediating roles of chronic diseases,and to assess potential biological pathways underlying the birth weight-associated dementia risk based on large-scale proteomics.Methods We used data from 279 743 participants aged 40 to 69 years enrolled in the UK Biobank.Birth weight was categorized into low birth weight(≤2 500 g),normal birth weight(2 500-3 999 g),and macrosomia(≥4 000 g).Multivariable Cox proportional hazards regression models were used to assess the associations between birth weight categories and all-cause dementia and its subtypes(Alzheimer's disease and vascular dementia).Proteomics analyses were conducted to identify proteins and the potential pathways involved.Results Low birth weight was associated with higher risks for all-cause dementia and its subtypes.The hazard ratios were 1.18(95%CI,1.08-1.30)for all-cause dementia,1.14(95%CI,1.00-1.31)for Alzheimer's disease,and 1.22(95%CI,1.01-1.48)for vascular dementia.A non-linear relationship was observed between birth weight and dementia risk(P for nonlinearity<0.001).Certain cardiometabolic diseases in middle-aged adults,such as diabetes,stroke,hypertension,and dyslipidemia,played a significant mediating role in the relationship between low birth weight and dementia risk,with the mediation proportion being 6.3%to 15.8%.Proteomic analyses identified 21 proteins linked to both low birth weight and all-cause dementia risk,which were significantly enriched in the pathways for viral protein interaction with cytokines and cytokine receptors,adipocytokine signaling,and cytokine-cytokine receptor interaction.Conclusion Low birth weight is positively associated with dementia risk.Cardiometabolic diseases in middle-aged adults may mediate the relationship between low birth weight and dementia risk.A number of proteins and the associated pathways underscore the relationship between low birth weight and dementia risk.

ObjectiveTo evaluate the efficacy and safety of transcutaneous electrical acupoint stimulation (TEAS) for muscle atrophy in patients with immobilization after surgical fixation of foot and ankle fractures.MethodsThis was a two-arm randomized controlled trial wherein 80 patients were recruited and divided into control (n = 40) and intervention (n = 40) groups. The control group received conventional orthopedic treatment, whereas the intervention group received TEAS and conventional treatment. The intervention group received TEAS 3 times a week for 30 min each time for 8 weeks. The primary outcomes were muscle thickness (MT) and cross-sectional area (CSA) of the rectus femoris and gastrocnemius muscles, whereas the secondary outcome measure was echo intensity (EI). Data were collected before the fixation operations (baseline assessment) and 4 and 8 weeks after intervention.ResultsCompared with baseline, the MT and CSA were reduced in both groups by the end of treatment, whereas EI increased in both groups. At week 4, the reduction in the rectus femoris CSA in the intervention group was significantly lower than that in the control group (P = .02); however, the between-group differences in the MT and EI (all P .05) were not significant. No serious adverse events were observed in either group.ConclusionOur study showed that TEAS can improve muscle atrophy by attenuating the decline in the muscle CSA. Because this was only a pilot trial, subsequent studies will need longer follow-ups and larger sample sizes.