Trends in prescription opioid use in Europe: A DARWIN EU multinational cohort study including seven European countries.

Background: The opioid crisis has been a serious public health challenge in North America for decades, despite numerous efforts to mitigate its devastating consequences. As concerns grow about a similar situation developing in Europe, we evaluated the trends in opioid use and characterized prescribing indications across seven European countries.

Methods: We conducted a multinational cohort study using electronic health records from various healthcare settings: primary care [Clinical Practice Research Datalink (CPRD) GOLD (United Kingdom), Sistema d'Informació per al Desenvolupament de la Investigació en Atenció Primària (SIDIAP, Spain), and Integrated Primary Care Information Project (IPCI, the Netherlands)]; primary and outpatient specialist care [IQVIA Disease Analyzer (DA) Germany and IQVIA Longitudinal Patient Database (LPD) Belgium]; hospital care [Clinical Data Warehouse of Bordeaux University Hospital (CHUBX, France)]; and the Estonian Biobank (EBB).

UBE2N as a novel prognostic and therapeutic biomarker of lung adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) represents a significant global health burden. The absence of reliable biomarkers and the heterogeneity in treatment responses continue to hinder improvements in patient prognosis. This study aimed to identify novel biomarkers capable of predicting patient outcomes and therapeutic responsiveness, while also assessing their potential as intervention targets for LUAD.

Total neoadjuvant chemoradiotherapy plus anti PD-1 for mid-to-low locally advanced rectal cancer: study protocol of a prospective, single arm, phase II study (STARS - RC06).

Background: Neoadjuvant chemoradiotherapy has become the standard treatment for mid-to-low location LARC. Recently, total neoadjuvant therapy (TNT) has been used in patients with 'high-risk' or 'very high-risk' LARC according to ESMO guideline (2017). TNT not only increases the pathological complete response (pCR) rate, but also provides patients with more opportunities to preserve organ function.

MAT: Mixing Attention Transfer from Multiple Transformers for Medical Tasks.

Transformer has been widely used for image analysis tasks, but in medicine, it suffers from limited data availability. To overcome this challenge, we propose a novel approach specially designed for transformers to transfer knowledge from multiple sources to target medical tasks with limited data, named Mixing Attention Transfer (MAT). MAT aims to harness and merge knowledge from multiple source transformers at the token and layer level to improve the performance of target medical tasks.

TRAP1 Improves Diabetic Retinopathy by Preserving Mitochondrial Function.

Background: Recent studies have demonstrated that mitochondrial dysfunction is pivotal in early diabetic retinopathy (DR). Tumor necrosis factor-associated protein 1 (TRAP1), a mitochondrial chaperone regulating stress responses, remains unexplored in DR pathogenesis.

Methods: We established in vivo and in vitro models of DR.

Impact of climate change and extreme temperature on the incidence of infectious disease among children and adolescents in China: A nationwide case-crossover study with over 8.7 million cases between 2008 and 2019.

Background: The relationship between ambient temperature and infectious disease incidence lacks comprehensive documentation. Our study, therefore, sought to systematically determine the national association between temperature and the incidence of infectious diseases, categorized into respiratory, gastrointestinal and enterovirus, and vector-borne categories. We aimed to study the association between extreme cold and heat extreme temperature on infectious disease occurrence among children and teenagers, and to evaluate the secular trends in these diseases in relation to temperature extremes.

Optical Full Adder Based on Integrated Diffractive Neural Network.

Light has been intensively investigated as a computing medium due to its high-speed propagation and large operation bandwidth. Since the invention of the first laser in 1960, the development of optical computing technologies has presented both challenges and opportunities. Recent advances in artificial intelligence over the past decade have opened up new horizons for optical computing applications.

An adaptive AI-based virtual reality sports system for adolescents with excess body weight: a randomized controlled trial.

Adolescents with obesity face numerous health risks and encounter barriers that lead to physical inactivity. We developed a virtual reality sports system, named REVERIE (Real-World Exercise and VR-Based Exercise Research in Education), which used deep reinforcement learning to train transformer-based virtual coaching agents, offering immersive and effective sports guidance, with biomechanical performance comparable to real-world physical sports. We integrated REVERIE into a randomized controlled trial involving an 8-week intervention in adolescents with excess body weight (n = 227).

A deep learning system for detecting silent brain infarction and predicting stroke risk.

Current brain imaging to detect silent brain infarctions (SBIs) is not feasible for the general population. Here, to overcome this challenge, we developed a retinal image-based deep learning system, DeepRETStroke, to detect SBI and refine stroke risk. We use 895,640 retinal photographs to pretrain the DeepRETStroke system, which encodes a domain-specific foundation model for representing eye-brain connections.

Use of Machine Learning to Compare Disease Risk Scores and Propensity Scores Across Complex Confounding Scenarios: A Simulation Study.

Purpose: The surge of treatments for COVID-19 in the second quarter of 2020 had a low prevalence of treatment and high outcome risk. Motivated by that, we conducted a simulation study comparing disease risk scores (DRS) and propensity scores (PS) using a range of scenarios with different treatment prevalences and outcome risks.

Method: Four methods were used to estimate PS and DRS: logistic regression (reference method), least absolute shrinkage and selection operator (LASSO), multilayer perceptron (MLP), and XgBoost.

Acid-activated mitochondria-targeting nanoprodrug for reactive oxygen species (ROS)-tolerant cancer therapy via antioxidant defense inhibition.

The intracellular balance of reactive oxygen species (ROS) is crucial for cancer cell survival and tumor development, with mitochondria playing a key role in maintaining this balance through antioxidant defenses. Despite the efficacy of ROS-modulating strategies in many tumors, certain ROS-tolerant malignancies, such as HepG2 cells, pose significant therapeutic challenges due to their robust antioxidant systems and unique redox microenvironments. In this work, we have developed a self-amplifying nanoprodrug (nCACT) designed to target ROS-tolerant tumor cells.

Grapevine adaptation to cold and heat stress.

Temperature plays a pivotal role in modulating growth, development, and distribution of plants. Grapevine (Vitis spp.), a perennial plant, must withstand changes in both low and high temperatures due to its sessile nature.

Immunity Debt for Seasonal Influenza After the COVID-19 Pandemic and as a Result of Nonpharmaceutical Interventions: An Ecological Analysis and Cohort Study.

Non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic significantly reduced influenza transmission. This study explores the hypothesis of "immunity debt" which suggests increased vulnerability to influenza following reduced exposure during the pandemic. World Health Organization aggregated data on influenza from 116 countries and its association with NPI intensity as measured by the COVID-19 Stringency Index is analyzed.

Insights into the itaconate family: Immunomodulatory mechanisms and therapeutic potentials.

The itaconate family, comprising itaconate derivatives, endogenous isomers, and other related compounds, has demonstrated substantial immunoregulatory properties. These compounds exhibit significant therapeutic potential in various disease models by modulating metabolic pathways, signal transduction cascades, and post-translational modifications. In this review, we delineate the structural characteristics and biological functions of the members of the itaconate family and elucidate their immunomodulatory mechanisms.

Deep-Learning-Based Analysis of Electronic Skin Sensing Data.

E-skin is an integrated electronic system that can mimic the perceptual ability of human skin. Traditional analysis methods struggle to handle complex e-skin data, which include time series and multiple patterns, especially when dealing with intricate signals and real-time responses. Recently, deep learning techniques, such as the convolutional neural network, recurrent neural network, and transformer methods, provide effective solutions that can automatically extract data features and recognize patterns, significantly improving the analysis of e-skin data.

AG73-GelMA/AlgMA hydrogels provide a stable microenvironment for the generation of pancreatic progenitor organoids.

Patient specific induced pluripotent stem cells (iPSCs) derived β cells represent an effective means for disease modeling and autologous diabetes cell replacement therapy. In this study, an AG73-5%gelatin methacryloyl (GelMA) /2% alginate methacrylate (AlgMA) hydrogel was employed to generate pancreatic progenitor (PP) organoids and improve stem cell-derived β (SC-β) cell differentiation protocol. The laminin-derived homolog AG73, which mimics certain cell‒matrix interactions, facilitates AKT signaling pathway activation to promote PDX1/NKX6.

Prevalence, numbers and mortality risk of hypertensive patients with depressive symptom in China.

Background: China is currently grappling with the escalating burden of hypertension and depression. This study aimed to assess the prevalence and number of hypertensive patients with depressive symptom, and to evaluate their risk of all-cause mortality.

Methods: Data from the China Health and Retirement Longitudinal Study (CHARLS) were utilized to estimate the prevalence of individuals with both hypertension and depressive symptom, the recommendation rate for antihypertensive medications, the blood pressure control rate, and the corresponding population size.

Development of an evaluation index system for inappropriate hospital admissions after colorectal cancer surgery in the context of enhanced recovery after surgery.

Background: Colorectal cancer (CRC) is one of the most prevalent cancers globally, and its treatment has garnered significant attention. The promotion and application of the Enhanced Recovery After Surgery (ERAS) concept have notably reduced postoperative hospital stay durations for CRC patients and improved recovery efficiency. However, there exist significant discrepancies in the discharge criteria for CRC patients, with a lack of uniformity and specificity in the evaluation standards for postoperative hospital days across different regions and healthcare institutions.

Effect of intermittent urethral catheter clamping combined with active urination training (ICCAUT) strategy on postoperative urinary dysfunction after radical rectal cancer surgery: single-centre randomised controlled trial (ICCAUT -1) study protocol.

Background: Urinary catheter placement is routinely performed after proctectomy. However, there is uncertainty regarding the need for bladder training before catheter removal. This trial aims to examine the effect of intermittent catheter clamping combined with active urination training (ICCAUT) on urinary retention and secondary catheterisation after proctectomy.

Global, regional, and national trends in colorectal cancer burden from 1990 to 2021 and projections to 2040.

Background: Colorectal cancer (CRC) is a common malignancy with notable recent shifts in its burden distribution. Current data on CRC burden can guide screening, early detection, and treatment strategies for efficient resource allocation.

Methods: This study utilized data from the latest Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study.

ColorNet: An AI-based framework for pork freshness detection using a colorimetric sensor array.

Pork freshness is crucial for flavour, nutrition and consumer health. The current colorimetric sensor array (CSA) detection systems face challenges related to high sensor development costs, low recognition accuracy and limitations in the platform use. Herein, we developed a CSA and ColorNet framework to detect pork freshness.

Intermittent catheter clamping combined with active urination training (ICCAUT) to reduce the risk of urinary dysfunction in patients after proctectomy: a single-center cohort study.

Background: Intermittent urethral catheter clamping is widely used to reduce secondary catheterization in patients after proctectomy; however, its effectiveness is unclear.

Materials And Methods: This study investigated the effects of intermittent catheter clamping combined with active urination training (ICCAUT) on postoperative urinary dysfunction in patients after proctectomy. This retrospective cohort study analyzed data on patients who underwent laparoscopic/robotic-assisted proctectomy at a single medical center in China between July 2023 and January 2024.

Non-invasive techniques for wound assessment: A comprehensive review.

Efficient wound assessment is essential for healthcare teams to facilitate prompt diagnosis, optimize treatment plans, reduce workload, and enhance patients' quality of life. In recent years, non-invasive techniques for aiding wound assessment, such as digital photography, 3D modelling, optical imaging, fluorescence and thermography, as well as artificial intelligence, have been gradually developed. This paper aims to review the various methods of measurement and diagnosis based on non-invasive wound imaging, and to summarize their application in wound monitoring and assessment.