Browse Articles

The effects of 3-hydroxyflavone complexes with transition metal ions on the physicochemical and microbial properties of bacterial cell membranes

An optimal disc height changes for successful indirect decompression with OLIF

Tough talks COVID-19 (TT-C) digital health intervention: multistate randomized controlled trial

Long and short term fault prediction using the VToMe-BiGRU algorithm for electric drive systems

Identifying ovarian cancer with machine learning DNA methylation pattern analysis

DSNet enables feature fusion and detail restoration for accurate object detection in foggy conditions

Efficacy of nursing interventions based on the enhanced recovery after surgery (ERAS) in patients with lumbar disc herniation

The evolution of broad seascape utility and ontogenetic life history variation in lutjanids

Liver-related outcomes in patients with cirrhosis: The value of clinical and laboratory data and noninvasive tests

Background and Purpose Cirrhosis patients face high mortality risks from complications, emphasizing the need for prognostic tools to estimate risk of adverse liver outcomes based on cirrhosis etiology and hence improve disease management. This study aimed to evaluate the association between baseline clinical factors, lab values and noninvasive measurements and risk of adverse liver outcomes among patients with cirrhosis, and develop disease-specific associative models. Methods Using proportional hazards regression, we developed six associative models, categorized by cirrhosis etiology, after identifying significant predictors of 30-day risk of ascites, hepatic encephalopathy (HE), and variceal bleeding (VB) among cirrhosis patients, with measurements selected through LASSO regression. Results A total of 4045 adult patients with cirrhosis were included in the analysis from a single U.S. center retrospective cohort. The 5-year rates for ascites, HE, and VB were 31.6%, 22.9%, and 30.7%, respectively. Multivariable analyses showed that independent predictors in cirrhosis due to metabolic dysfunction-associated steatohepatitis (MASH) and viral hepatitis were: (a) ascites: albumin and international normalized ratio (INR); (b) HE: albumin, INR, total bilirubin, platelet count; (c) VB: albumin, platelet count, hemoglobin. No variables were significantly associated with outcomes in patients with alcohol-associated liver disease. Conclusions The newly developed models provided accurate estimates of the 30-day risks of ascites, HE, and VB in MASH or viral hepatitis-related cirrhosis using baseline variables, providing a reliable tool for identifying high-risk patients warranting intensified interventions.

Effect of synthesis methods, biocompatibility and photoluminescence of scheelite type sodium lanthanide double tungstates

Effect of perfusion pressure sensors on posterior capsule elevation in the porcine eye model with eyelid speculums

A spatially aware global and local perspective approach for few-shot incremental learning

Spatial correlations between summer ozone heatwave dual events and residents mental health in China

Determination of the oral carcinoma and sarcoma in contrast enhanced CT images using deep convolutional neural networks

Abstract Oral cancer is a hazardous disease and a major cause of morbidity and mortality worldwide. The purpose of this study was to develop the deep convolutional neural networks (CNN)-based multiclass classification and object detection models for distinguishing and detection of oral carcinoma and sarcoma in contrast-enhanced CT images. This study included 3,259 slices of CT images of oral cancer cases from the cancer hospital and two regional hospitals from 2016 to 2020. Multiclass classification models were constructed using DenseNet-169, ResNet-50, EfficientNet-B0, ConvNeXt-Base, and ViT-Base-Patch16-224 to accurately differentiate between oral carcinoma and sarcoma. Additionally, multiclass object detection models, including Faster R-CNN, YOLOv8, and YOLOv11, were designed to autonomously identify and localize lesions by placing bounding boxes on CT images. Performance evaluation on a test dataset showed that the best classification model achieved an accuracy of 0.97, while the best detection models yielded a mean average precision (mAP) of 0.87. In conclusion, the CNN-based multiclass models have a great promise for accurately determining and distinguishing oral carcinoma and sarcoma in CT imaging, potentially enhancing early detection and informing treatment strategies.

HPV cancer burden by anatomical site, country, and region in 2022

Copper only SOD repeat proteins likely act as an extracellular superoxide dismutase in oyster antioxidant defense

Age-related decline in behavior and reproductive health in male mice

The management of patients who self-harm in adult inpatient mental health settings: A policy analysis of English NHS mental health trusts

The management of self-harm is a critical focus for staff in inpatient mental health settings. This study aimed to better understand how staff are guided through policies to manage self-harm via the following objectives: 1) to assess the alignment of policies from English NHS Mental Health trusts with national guidelines, 2) identify which aspects of the national guidelines are most and least frequently reflected in these policies, and 3) determine whether trusts with dedicated self-harm policies better reflect national guidelines. We conducted a content analysis of self-harm-related policies across 50 English NHS mental health trusts against a framework of 20 standards created from National Institute for Health and Care Excellence self-harm guidelines. Our analysis revealed a significant difference (U = 36.50, p = .002) in the number of standards met by trusts with a specific self-harm policy (M = 11.44, SD = 3.00) compared to those without (M = 7.26, SD = 3.00), with the number of standards met ranging from zero to 15. Notably, trusts failed to meet the majority of standards (M = 11.69, SD = 3.30). The findings of this study highlight several new insights into NHS trust policy on self-harm: 1) trusts exhibit variability in how they organise information across their policies, 2) dedicated self-harm policies may support trusts to better meet guidance but risk complicating guidance for staff, 3) policy content varies across trusts, 4) the importance of patient voice is acknowledged but the facilitators of good participation are poorly supported in the same policies, 5) trusts rarely define self-harm and some trusts use definitions which do not reflect guidelines, and 6) harm-reduction remains underrepresented in policies, reflecting ongoing contention surrounding its implementation. Further research is needed to understand the role that policy and guidelines play in guiding staff practices when managing self-harm.

Mamba-fusion for privacy-preserving disease prediction

Gradual poisoning of a chest x-ray convolutional neural network with an adversarial attack and AI explainability methods