ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

Objective To explore the correlation of bilateral knee joint strength asymmetry with balance,walking ability,and motor function in hemiplegic stroke patients,providing a reference for clinical assessment of stroke patients.Methods A total of 46 hemiplegic stroke patients admitted to the Rehabilitation Medicine Department of People's Hospital of Shijiazhuang from February to December 2023 were selected.According to the Berg Balance Scale(BBS)scores,patients were divided into Group A(BBS score≤20,n=23)and Group B(BBS score>20,n=23).The peak torque and differences of bilateral knee flexors and extensors were compared between two groups.Isokinetic technology was used to assess the differences in peak torque of bilateral knee joints at 60°/s and 120°/s.BBS,Functional Ambulation Classification(FAC),and Fugl-Meyer Assessment of Lower Extremity(FMA-LE)were used to evaluate patients'balance,walking ability,and lower limb motor function.The correlation between bilateral knee joint peak torque and its difference with the scores of three functional scales was analyzed.Results The peak torque of knee flexors and extensors at 60°/s in group A was significantly lower than that in group B(P<0.05).At both 60°/s and 120°/s the differences in peak torque between the healthy and affected sides of knee flexors and extensors were greater than those in group B(P<0.05).At 60°/s,the difference in peak torque of bilateral knee extensors in hemiplegic stroke patients was negatively correlated with the scores of BBS,FAC,and FMA-LE(r=-0.569,-0.582,-0.606,P<0.01),as did the knee flexors(r=-0.534,-0.386,-0.458,P<0.05).At 120°/s,similar negative correlations were observed for both knee extensors(r=-0.304,-0.304,-0.443,P<0.05)and flexors(r=-0.337,-0.349,-0.370,P<0.05).Conclusions Bilateral knee joint strength asymmetry in hemiplegic stroke patients is negatively correlated with balance and walking ability.The difference in strength between the two sides of knee joint may be one of the clinical indicators for evaluating the motor function of stroke patients.

Objective To investigate the expression of microRNA-508-3p(miR-508-3p)in epithelial ovarian cancer(EOC)tissue,its impact on the migration and invasion of ovarian cancer cells,and its regulatory relationship with zinc-finger E-box-binding homeobox 1(ZEB1).Methods The surgical resection of EOC cancer tissues and paired adjacent normal tissues were collected.SKOV3 cells were divided into the NC mimic group(transfected with NC mimic),miR-508-3p mimic group(transfected with miR-508-3p mimic),si-NC group(transfected with si-NC),si-ZEB1 group(transfected with si-ZEB1)and co-transfection group(co-transfected with si-ZEB1 and miR-508-3p mimic).The mRNA expression levels of miR-508-3p and ZEB1 in EOC cancer tissues,adjacent normal tissues and five groups of cells were measured by real-time quantitative polymerase chain reaction.The Transwell assay was used to detect the cell migration and invasion abilities.Results The relative expression levels of miR-508-3p in EOC tissues and adjacent normal tissues were 0.77±0.36 and 1.07±0.40,the relative expression levels of ZEB1 mRNA in EOC tissues and adjacent normal tissues were 2.10±1.21 and 1.29±0.95,and the differences were statistically significant(all P＜0.01).The migration cell number of the NC mimic,miR-508-3p mimic,si-NC,si-ZEB1 and co-transfection groups was 633.00±32.49,319.20±19.89,650.40±25.85,375.00±17.25 and 129.40±17.10;the invasion cell number was 527.20±25.01,288.60±16.68,520.00±25.83,293.40±18.37 and 76.60±8.76;the relative expression levels of miR-508-3p were 1.05±0.37,3.94±1.21,1.01±0.21,1.26±0.34 and 3.40±0.41;the relative expression levels of ZEB1 mRNA were 1.00±0.04,0.58±0.05,1.00±0.08,0.54±0.07 and 0.29±0.03,respectively.The above indicators showed statistically significant differences between the miR-508-3p mimic group and the NC mimic group,between the si-NC group and the co-transfection group(P＜0.01,P＜0.05).Conclusion MiR-508-3p is lowly expressed in EOC cancer tissue,and it may inhibit the migration and invasion of ovarian cancer cells by targeting ZEB1 expression.

Objective To delineate the current research landscape,emerging hotspots,and frontiers re-garding the relationship between the oral microbiome and digestive system diseases.Methods We retrieved publications from the Web of Science Core Collection database using topic-specific queries on"oral microbi-ome"and"digestive diseases."Bibliometric analysis was performed using VOSviewer,CiteSpace,and the"bibliometrix"package in R for data mining and visualization.Results A total of 1228 eligible articles were included.Analysis revealed that research on the correlation between oral microbiota and digestive system diseases will remain a global hotspot.Academic institutions dominated the publications,with centralized institutional distribution and team-based collaboration,though overall collaboration networks remained fragmented.Geo-graphically,the United States emerged as the leading contributor,followed by China and the United Kingdom.While China-U.S.collaborations were prominent,China's engagement with other regions remained limited.Current research hotspots focus on the interplay between oral microbiota and gut microbiota,inflam-matory bowel disease(IBD),and digestive system tumors.Conclusions Research in this field demonstrates high activity and diversity.Studies on the associations of oral microbiota with gut microbiota,IBD,and diges-tive system tumors(particularly esophageal,gastric,pancreatic,and colorectal cancers)remain prominent.Future studies should prioritize elucidating underlying mechanisms and innovating in biomarker discovery and application.However,insufficient collaboration and resource-sharing among institutions currently hinder pro-gress in this field.

Objective:To investigate the changes in N100, P300, and N400 of event-related potential(ERP) in children with obstructive sleep apnea (OSA), and provide the basis for evaluating cognitive and neurological impairment in pediatric OSA.Methods:Totally 108 children aged 5-10 years who visited the Sleep Center of Beijing Children's Hospital due to snoring or mouth breathing were recruited from June to September, 2023, and ultimately 90 children were included in the study.According to the obstructive sleep apnea hypopnea index (OAHI) in their polysomnography (PSG) results, children with OAHI>1 time/h were classified as OSA group ( n=74), and children with OAHI ≤ 1 time/h were classified as non-OSA group ( n=16).All participants completed the auditory oddball and Peabody image vocabulary test tasks, and the EEG data collected through ERP technology were compared between the two groups.SPSS 26.0 software was used for statistical analysis, and independent samples t-test or non parametric test was used for comparison between the two groups. Results:The P300 latency of OSA children in lead Fz was significantly longer than that of non OSA children (330.00(308.00, 396.00) ms, 309.00(294.50, 337.50)ms), and the difference was statistically significant ( Z=-2.143, P=0.032). The latency of P300 was positively correlated with apnea hypopnea index(AHI)(Fz lead: r=0.332, Cz lead: r=0.239, Pz lead: r=0.213, all P<0.05). There was no statistically significant difference in P300 latency between Cz and Pz leads ( Z=-1.615, P=0.106; Z=-1.055, P=0.291). There was no statistically significant difference in the amplitude of P300 among the leads (all P>0.05). There was no statistically significant difference in the amplitude and latency of N100 and N400 (both P>0.05). Conclusion:The latency of P300 in OSA children is significantly longer than that in non-OSA children, indicating impaired cognitive function. The latency of auditory P300 might serve as an early neuroelectrophysiological biomarker for identifying cognitive impairment in OSA children.

Aim To study the mechanism of salidro-side combined with rosavin in rats with ischemic stroke.Methods The MCAO rats was established by using thread-embolic method.The rats were divided into the sham group,MCAO group,salidroside com-bined with rosavin group,and positive control group;the drug was given continuously for seven days.Western blot was used to detect apoptosis indicators.Proteomics was used to analyse differential proteins(DEPs).STEP receptor inhibitor was injected into the lateral ventricles,the rats were administered for seven days,then the apoptosis indicators were detected.Re-sults Salidroside combined with rosavin could reduce neurological function scores in MCAO rats and inhibit cell apoptosis.Quantitative proteomics identified 496 DEPs in brain tissue and discovered core proteins STEP,p38,and CRTC1.Salidroside combined with rosavin could promote the STEP and CRTC1 while in-hibiting p38 protein.After treatment with STEP inhibi-tor,those effects were reversed.Conclusion Salidro-side combined with rosavin can inhibit cell apoptosis in MCAO rats,which is closely related to the regulation of the STEP/p38/CRTC1 signaling pathway.

Objective:To investigate the changes in N100, P300, and N400 of event-related potential(ERP) in children with obstructive sleep apnea (OSA), and provide the basis for evaluating cognitive and neurological impairment in pediatric OSA.Methods:Totally 108 children aged 5-10 years who visited the Sleep Center of Beijing Children's Hospital due to snoring or mouth breathing were recruited from June to September, 2023, and ultimately 90 children were included in the study.According to the obstructive sleep apnea hypopnea index (OAHI) in their polysomnography (PSG) results, children with OAHI>1 time/h were classified as OSA group ( n=74), and children with OAHI ≤ 1 time/h were classified as non-OSA group ( n=16).All participants completed the auditory oddball and Peabody image vocabulary test tasks, and the EEG data collected through ERP technology were compared between the two groups.SPSS 26.0 software was used for statistical analysis, and independent samples t-test or non parametric test was used for comparison between the two groups. Results:The P300 latency of OSA children in lead Fz was significantly longer than that of non OSA children (330.00(308.00, 396.00) ms, 309.00(294.50, 337.50)ms), and the difference was statistically significant ( Z=-2.143, P=0.032). The latency of P300 was positively correlated with apnea hypopnea index(AHI)(Fz lead: r=0.332, Cz lead: r=0.239, Pz lead: r=0.213, all P<0.05). There was no statistically significant difference in P300 latency between Cz and Pz leads ( Z=-1.615, P=0.106; Z=-1.055, P=0.291). There was no statistically significant difference in the amplitude of P300 among the leads (all P>0.05). There was no statistically significant difference in the amplitude and latency of N100 and N400 (both P>0.05). Conclusion:The latency of P300 in OSA children is significantly longer than that in non-OSA children, indicating impaired cognitive function. The latency of auditory P300 might serve as an early neuroelectrophysiological biomarker for identifying cognitive impairment in OSA children.

Objective To delineate the current research landscape,emerging hotspots,and frontiers re-garding the relationship between the oral microbiome and digestive system diseases.Methods We retrieved publications from the Web of Science Core Collection database using topic-specific queries on"oral microbi-ome"and"digestive diseases."Bibliometric analysis was performed using VOSviewer,CiteSpace,and the"bibliometrix"package in R for data mining and visualization.Results A total of 1228 eligible articles were included.Analysis revealed that research on the correlation between oral microbiota and digestive system diseases will remain a global hotspot.Academic institutions dominated the publications,with centralized institutional distribution and team-based collaboration,though overall collaboration networks remained fragmented.Geo-graphically,the United States emerged as the leading contributor,followed by China and the United Kingdom.While China-U.S.collaborations were prominent,China's engagement with other regions remained limited.Current research hotspots focus on the interplay between oral microbiota and gut microbiota,inflam-matory bowel disease(IBD),and digestive system tumors.Conclusions Research in this field demonstrates high activity and diversity.Studies on the associations of oral microbiota with gut microbiota,IBD,and diges-tive system tumors(particularly esophageal,gastric,pancreatic,and colorectal cancers)remain prominent.Future studies should prioritize elucidating underlying mechanisms and innovating in biomarker discovery and application.However,insufficient collaboration and resource-sharing among institutions currently hinder pro-gress in this field.

Aim To study the mechanism of salidro-side combined with rosavin in rats with ischemic stroke.Methods The MCAO rats was established by using thread-embolic method.The rats were divided into the sham group,MCAO group,salidroside com-bined with rosavin group,and positive control group;the drug was given continuously for seven days.Western blot was used to detect apoptosis indicators.Proteomics was used to analyse differential proteins(DEPs).STEP receptor inhibitor was injected into the lateral ventricles,the rats were administered for seven days,then the apoptosis indicators were detected.Re-sults Salidroside combined with rosavin could reduce neurological function scores in MCAO rats and inhibit cell apoptosis.Quantitative proteomics identified 496 DEPs in brain tissue and discovered core proteins STEP,p38,and CRTC1.Salidroside combined with rosavin could promote the STEP and CRTC1 while in-hibiting p38 protein.After treatment with STEP inhibi-tor,those effects were reversed.Conclusion Salidro-side combined with rosavin can inhibit cell apoptosis in MCAO rats,which is closely related to the regulation of the STEP/p38/CRTC1 signaling pathway.