Outcomes following hospitalization for diabetic ketoacidosis in patients with cardiovascular disease.

Introduction: Diabetic ketoacidosis (DKA) is a serious complication in patients with diabetes. This study compares the outcomes of hospitalized DKA patients with and without cardiovascular disease (CVD). In addition, we assess outcomes between DKA and hyperosmolar hyperglycemic syndrome (HHS) in diabetes patients with CVD, and between those who developed DKA and those who did not.

Association Between Age of Onset of Hypertension and Risk of CKD: Cohort Study Based on the UK Biobank.

Background: The onset age of hypertension has decreased significantly due to lifestyle changes over the years. However, the link between hypertension onset age and subsequent incidence of chronic kidney disease (CKD) remains unclear.

Methods: Individual-level data were obtained from the UK Biobank.

Brønsted bases promote interfacial proton transfer for enhanced biomass electrocatalysis.

Efficient electrooxidation of 5-hydroxymethylfurfural (HMF) is essential for the production of valuable chemicals from biomass. However, the sluggish interfacial proton transfer kinetics during the reaction significantly hinder its progress. This study proposes that the introduction of Brønsted bases on cobalt-based catalysts can enhance HMF oxidation by modulating interfacial proton transfer kinetics.

The role of 8-OxoG and its repair systems in liver diseases progression: responsible mechanisms and promising natural products.

The accumulation of deoxyribonucleic acid (DNA) oxidative damage mediated by reactive oxygen species (ROS) is closely associated with liver diseases. 8-Oxoguanine (8-OxoG), a prevalent DNA oxidation product, plays a significant role in liver disease progression. The base excision repair (BER) pathway, comprising over 30 proteins including 8-OxoG DNA glycosylase1 (OGG1), MutY homolog (MUTYH), and MutT homolog protein 1 (MTH1), is responsible for the clearance and mismatch repair of 8-OxoG.

Next app prediction based on graph neural networks and self-attention enhancement.

Next mobile app prediction aims to recommend the apps that users will most likely to use next based on their historical usage behavior. It is critical for optimizing app preloading strategies and personalized recommendations, enhancing the user experience on mobile devices. However, it faces fundamental challenges such as interactions sparsity, rapid expansion of the app ecosystem and long-term interest neglect.

Targeting USP18 overcomes acquired resistance in hepatocellular carcinoma by regulating NCOA4 deISGylation and ferroptosis.

Targeted therapy resistance has become a major challenge for hepatocellular carcinoma (HCC) treatment. Triggering ferroptosis emerges as a promising strategy to overcome therapeutic resistance. Here, we have identified ubiquitin-specific protease 18 (USP18), a member of the deubiquitinating enzyme family, contributing to HCC resistance by inhibiting sorafenib-induced ferroptosis.

Complementary Hydrogen─Bonded Functionalized Mixed Conducting Terpolymers for High-Performance n-type Organic Electrochemical Transistors and Healable Inverters.

High-performing n-type organic electrochemical transistors (OECTs), crucial for integrated circuits in wearable bioelectronics, demand organic mixed ion-electron conductors (OMIECs) that exhibit efficient mixed conduction and biological functionality for practical applications. However, the development of self-healing OMIECs has not yet been achieved due to the lack of suitable synthetic strategies. Here, we present a design concept through incorporating dynamic cross-linked hydrogen-bonded in the polymer backbone for the first demonstration of self-healing polymeric mixed conductors, enabling high-performing OECTs and high gain, self-healing inverters.

Medical image translation with deep learning: Advances, datasets and perspectives.

Traditional medical image generation often lacks patient-specific clinical information, limiting its clinical utility despite enhancing downstream task performance. In contrast, medical image translation precisely converts images from one modality to another, preserving both anatomical structures and cross-modal features, thus enabling efficient and accurate modality transfer and offering unique advantages for model development and clinical practice. This paper reviews the latest advancements in deep learning(DL)-based medical image translation.

Visual analysis of research status and development trends in the field of postgraduate nursing education.

Aim: The purpose of this study was to systematically analyze the research status and development trends in the field of postgraduate education in nursing through visual analysis.

Methods: We conducted a comprehensive online search of English literature via citation index extensions in the Web of Science Core Collection Database. Chinese literature was searched online via the CNKI, Wanfang, VIP and China Medical Biobank Databases.

Identification and characterization of tubulin as Ga(III)-binding protein in T24 cells.

Gallium-based metallic drugs and agents have been widely applied for the diagnosis and treatment of diseases such as non-Hodgkin's lymphoma (NHL), but there are few reports on the potential Ga(III)-binding proteins and the related cytotoxic mechanisms for Ga(III). Herein, by using human urinary bladder cancer T24 cells as a model, we identify and report that tubulin is a Ga(III)-binding protein target in T24 cells. Our analyses, including the employment of a series of methods based on immobilized metal affinity chromatography (IMAC), cellular thermal shift assay (CETSA), and immunofluorescence experiments, collectively explained this finding.

Multi-Scale Dynamic Sparse Attention UNet for Medical Image Segmentation.

Transformers have recently gained significant attention in medical image segmentation due to their ability to capture long-range dependencies. However, the presence of excessive background noise in large regions of medical images introduces distractions and increases the computational burden on the fine-grained self-attention (SA) mechanism, which is a key component of the transformer model. Meanwhile, preserving fine-grained details is essential for accurately segmenting complex, blurred medical images with diverse shapes and sizes.

Smoking is associated with adverse clinical outcomes after thyroidectomy: a 5-year retrospective analysis.

Objective: Tobacco use has been confirmed to be a risk factor for postoperative complications, but the impact of smoking on adverse outcomes following thyroidectomy remains largely unknown.

Methods: Using data spanning 2016-2020 from the National Inpatient Sample, patients aged ≥ 18 years who underwent thyroidectomy for thyroid malignancy or other thyroid disorders were identified and classified into two groups: current smokers and non-smokers. We compared outcome variables between the two groups via univariate analysis and adjusted multivariate logistic regression.

The role of GPT in promoting inclusive higher education for people with various learning disabilities: a review.

The generative pre-trained transformer (GPT) is a notable breakthrough in the field of artificial intelligence, as it empowers machines to effectively comprehend and engage in interactions with humans. The GPT exhibits the capacity to enhance inclusivity and accessibility for students with learning disabilities in the context of higher education, hence potentially facilitating substantial advancements in the field. GPT can provide personalized and diverse solutions that successfully cater to the distinct requirements of students with learning disabilities.

Tooth Instance Segmentation and Disease Detection With Uncertainty-Aware Contrastive Learning and Cross-Scale Attention.

Recent years have witnessed the increasing applications of artificial intelligence for tooth treatment, among which tooth instance segmentation and disease detection are two important research directions. Advanced algorithms have been proposed, however, two challenging issues remain unsolved, i.e.

Imine-Based Polymeric Mixed Ionic-Electronic Conductors Featuring Degradability and Biocompatibility for Transient Bioinspired Electronics.

Degradable features are highly desirable to advance next-generation organic mixed ionic-electronic conductors (OMIECs) for transient bioinspired artificial intelligence devices. It is highly challenging that OMIECs exhibit excellent mixed ionic-electronic behavior and show degradability simultaneously. Specially, in OMIECs, doping is often a tradeoff between structural disorder and charge carrier mobilities.

Lumbar intervertebral disc calcification with massive herniation: a case report.

An 18-year-old female patient presented with a 1-month history of low back pain, which had worsened and was accompanied by radiating pain in the right lower limb for half a month. She was admitted to our hospital with computed tomography and magnetic resonance imaging findings suggesting calcification of the L3/4 disc and a large intraspinal mass at the L2-4 level. The patient's symptoms did not improve with conservative treatment, and her muscle strength rapidly declined.

Artificial Fine-Tuned van Hove Singularity in Twisted Bilayer and Double-Twist Trilayer Graphene with Enhanced Absorption for Photodetection and Photoemission in the Near-Infrared II Range.

Optical responses of twisted bilayer graphene at targeted wavelengths can be amplified by leveraging energy levels of van Hove singularities (VHS) via tuning periods of moiré superlattices. Therefore, precise control of twist angles as well as the moiré superlattices is necessary for fabricating integrated optoelectronic devices such as photodetectors and emitters. Although recent advances in twist angle control help the observation of correlated states in twisted magic-angle graphene structures, the impact of such precise control on enhanced optical absorption is still under investigation.

Scalable Synthesis of 2D ErOCl with Sub-meV Narrow Emissions at Telecom Band.

Van der Waals (vdWs) materials are promising candidates for hetero-integration with silicon photonics toward miniaturization and integration. VdWs materials like molybdenum telluride and black phosphorus, despite being prominent, exhibit air sensitivity, and their room temperature emissions can be significantly broadened by tens of meV. Here, a self-encapsulation strategy is developed to scalably synthesize robust 2D vdWs ErOCl with sub-meV narrow emissions at the telecom C-band.

Long noncoding RNA FAM111A-DT promotes aggressiveness of papillary thyroid cancer via activating NF-κB signaling.

Purpose: Long noncoding RNAs (lncRNAs) play crucial regulatory roles in the tumorigenesis and progression of various cancers. However, the functional roles of lncRNAs in papillary thyroid cancer (PTC) remain unclear. In this study, we investigated the functional role of the lncRNA FAM111A-DT in PTC progression and the underlying mechanisms.

Machine learning based predictive modeling and risk factors for prolonged SARS-CoV-2 shedding.

Background: The global outbreak of the coronavirus disease 2019 (COVID-19) has been enormously damaging, in which prolonged shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, previously 2019-nCoV) infection is a challenge in the prevention and treatment of COVID-19. However, there is still incomplete research on the risk factors that affect delayed shedding of SARS-CoV-2.

Methods: In a retrospective analysis of 56,878 hospitalized patients in the Fangcang Shelter Hospital (National Convention and Exhibition Center) in Shanghai, China, we compared patients with the duration of SARS-CoV-2 viral shedding > 12 days with those days < 12 days.

TGFBR3 inhibits progression of papillary thyroid cancer by inhibiting the PI3K/AKT pathway and EMT.

Background: Transforming growth factor beta receptor III (TGFBR3) has been shown to play a tumor-suppressive role in a variety of cancers. However, its role in papillary thyroid cancer (PTC) remains unknown.

Method: TGFBR3 expression levels in PTC were analyzed utilizing The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases.

Single ambipolar OECT-based inverter with volatility and nonvolatility on demand.

Organic electrochemical transistor (OECT)-based inverter introduces new prospects for energy-efficient brain-inspired artificial intelligence devices. Here, we report single-component OECT-based inverters by incorporating ambipolar p(gDPP-V). Notably, p(gDPP-V) shows state-of-the-art ambipolar OECT performances in both conventional (p/n-type mode transconductance of 29/25 S cm) and vertical (transconductance of 297.