Spatial Gene Expression of Human Coronary Arteries Revealed the Molecular Features of Diffuse Intimal Thickening in Explanted Hearts.

Diffuse intimal thickening (DIT) is a pre-clinical stage of atherosclerosis characterized by thickened intima. The molecular basis of its susceptibility to atherogenesis is unknown, and mechanistic investigations cannot be performed in commonly used mouse models, in which DIT does not exist. Vascular smooth muscle cells (SMCs) are the predominant cell type that occupies the intima and media of DIT.

Advancing Sleep Disorder Diagnostics: A Transformer-based EEG Model for Sleep Stage Classification and OSA Prediction.

Sleep disorders, particularly Obstructive Sleep Apnea (OSA), have a considerable effect on an individual's health and quality of life. Accurate sleep stage classification and prediction of OSA are crucial for timely diagnosis and effective management of sleep disorders. In this study, we develop a sequential network that enhances sleep stage classification by incorporating self-attention mechanisms and Conditional Random Fields (CRF) into a deep learning model comprising multi-kernel Convolutional Neural Networks (CNNs) and Transformer-based encoders.

Neddylation of RhoA impairs its protein degradation and promotes renal interstitial fibrosis progression in diabetic nephropathy.

Diabetic nephropathy (DN) is a common and serious complication of diabetes, characterized by chronic fibro-inflammatory processes with an unclear pathogenesis. Renal fibrosis plays a significant role in the development and progression of DN. While recent research suggests that the neddylation pathway may influence fibrotic processes, its specific dysregulation in DN and the underlying mechanisms remain largely unexplored.

Deep learning based prediction of depression and anxiety in patients with type 2 diabetes mellitus using regional electronic health records.

Background: Depression and anxiety are prevalent mental health conditions among individuals with type 2 diabetes mellitus (T2DM), who exhibit unique vulnerabilities and etiologies. However, existing approaches fail to fully utilize regional heterogeneous electronic health record (EHR) data. Integrating this data can provide a more comprehensive understanding of depression and anxiety in T2DM patients, leading to more personalized treatment strategies.

Development and Validation of a Nomogram-Based Model to Predict Primary Hypertension Within the Next Year in Children and Adolescents: Retrospective Cohort Study.

Background: Primary hypertension (PH) poses significant risks to children and adolescents. Few prediction models for the risk of PH in children and adolescents currently exist, posing a challenge for doctors in making informed clinical decisions.

Objective: This study aimed to investigate the incidence and risk factors of PH in Chinese children and adolescents.

Clinical surveillance of split renal function in kidney transplant recipients using Tc-diethylenetriamine-pentaacetic acid (DTPA) dynamic renal scintigraphy: preliminary findings and novel insights.

Background: En bloc kidney transplantation (EBKT) involves transplantation of two kidneys, the aorta, and inferior vena cava from a deceased pediatric donor into an adult recipient. Recent articles have shown that EBKT is associated with excellent long-term allograft performance and patient survival. Developmental differences exist between the two transplanted kidneys after EBKT, and it is crucial to assess split renal function.

Development and research status of intelligent ophthalmology in China.

This paper analyzes the current status, technological developments, academic exchange platforms, and future challenges and solutions in the field of intelligent ophthalmology (IO) in China. In terms of technology, significant progress has been made in various areas, including diabetic retinopathy, fundus image analysis, quality assessment of medical artificial intelligence products, clinical research methods, technical evaluation, and industry standards. Researchers continually enhance the safety and standardization of IO technology by formulating a series of clinical application guidelines and standards.

Comprehensive analysis of chromosome abnormalities by chromosome conformation based karyotyping (C-MoKa) in patients with conception failure and pregnancy loss.

Background: Chromosome abnormalities are a leading cause of conception failure and pregnancy loss. While traditional cytogenetics technologies like karyotyping have been helpful in identifying structural variations (SVs), they face challenges in detecting complex rearrangements and cryptic structures. In this study, we developed a new method called chromosome conformation based karyotyping (C-MoKa) to comprehensively detect different types of chromosomal abnormalities in patients with conception failure and pregnancy loss.

Ultra-sensitive DNA detection with single-base mismatch resolution using a tapered thin-diameter photonic crystal fiber interferometer.

A tapered thin-diameter photonic crystal fiber interferometer (TTD-PCFI) biosensor is proposed and demonstrated for DNA hybridization detection with an ultra-low limit of detection (LoD) and high specificity. The TTD-PCFI is fabricated by arc-discharged melting and adiabatic tapering, with a lower loss and stronger evanescent optical field. The fabricated TTD-PCFI with a diameter of 8.

Designing orthopaedic seat cushion made of rattan using quality function deployment approach.

Using ergonomic orthopaedic chairs can address spinal issues, particularly HNP, due to their flexible and elastic properties. By achieving optimal ergonomic design, various positive aspects can be achieved, such as increasing work quality productivity and reducing the cost of injuries or accidents. This research demonstrates diverse product design approaches to enhance posture health ergonomics, address specific musculoskeletal disorder issues, and consider local needs and available materials.

Cohort profile: the Nanjing Diabetes Cohort database - a population-based surveillance cohort.

Purpose: To study epidemiology, complications, risk factors, clinical course and treatment patterns of diabetes, the Nanjing Diabetes Cohort (NDC) was established using anonymised electronic health records from 650 hospitals and primary care since 2020. This cohort provides valuable data for researchers and policy-makers focused on diabetes management and public health strategies.

Participants: Diabetes was defined as having inpatient or outpatient encounters with a diagnosis of diabetes International Classification of Diseases-9/10 codes, any use of insulin or oral hypoglycaemic drugs, or one encounter with haemoglobin A1C >4.

Features and Differences in Core Symptom Clusters in Home-Based Hospice Patients With Advanced Cancer: A Network Analysis.

Introduction: Patients with terminal-stage cancer frequently experience multiple symptoms simultaneously. Little is known about how core symptom clusters differ in advanced-cancer patients with different survival expectancies receiving hospice care. To identify the core symptom clusters of hospice-care cancer patients with different survival expectancies and compare the features of their symptom networks.

A fundus vessel segmentation method based on double skip connections combined with deep supervision.

Background: Fundus vessel segmentation is vital for diagnosing ophthalmic diseases like central serous chorioretinopathy (CSC), diabetic retinopathy, and glaucoma. Accurate segmentation provides crucial vessel morphology details, aiding the early detection and intervention of ophthalmic diseases. However, current algorithms struggle with fine vessel segmentation and maintaining sensitivity in complex regions.

Multi-omics PGT: re-evaluation of euploid blastocysts for implantation potential based on RNA sequencing.

Study Question: In addition to chromosomal euploidy, can the transcriptome of blastocysts be used as a novel predictor of embryo implantation potential?

Summary Answer: This retrospective analysis showed that based on differentially expressed genes (DEGs) between euploid blastocysts which resulted and did not result in a clinical pregnancy, machine learning models could help improve implantation rates by blastocyst optimization.

What Is Known Already: Embryo implantation is a multifaceted process, with implantation loss and pregnancy failure related not only to blastocyst euploidy but also to the intricate dialog between blastocyst and endometrium. Although in vitro studies have revealed the characteristics of trophectoderm (TE) differentiation in implanted blastocysts and the function of TE placentation at the implantation site, the precise molecular mechanisms of embryo implantation and their clinical application remain to be fully elucidated.

Simultaneously Enhancing the Efficiency and Stability of Perovskite Solar Cells by Using P3HT/PEDOT:PSS as a Double Hole Transport Layer.

The stability issue of perovskite solar cells (PSCs) has long been of concern to researchers. Poly (3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) is commonly used as a hole transport layer (HTL) in the inverted PSCs to achieve efficient and stable performance. However, PEDOT:PSS can corrode ITO, affecting device efficiency.

Personalized embryo transfer guided by rsERT with hourly precision improves pregnancy outcomes in patients with a receptive window of implantation: a pilot study.

Purpose: To investigate whether personalized embryo transfer (pET) predicted by a modified RNA-sequencing-based endometrial receptivity test (rsERT) model can improve intrauterine pregnancy rate (IPR) in patients with a receptive window of implantation (WOI).

Design: A retrospective pilot study was conducted in the Center for Reproductive Medicine, Central South University, from January 2018 to December 2023. A total of 524 patients with receptive WOI results from rsERT were assigned into two groups based on whether they underwent conventional embryo transfer (conventional ET) or pET.

NCME-Net: Nuclear cataract mask encoder network for intelligent grading using self-supervised learning from anterior segment photographs.

Cataracts are a leading cause of blindness worldwide, making accurate diagnosis and effective surgical planning critical. However, grading the severity of the lens nucleus is challenging because deep learning (DL) models pretrained using ImageNet perform poorly when applied directly to medical data due to the limited availability of labeled medical images and high interclass similarity. Self-supervised pretraining offers a solution by circumventing the need for cost-intensive data annotations and bridging domain disparities.

Mechanisms of Postischemic Stroke Angiogenesis: A Multifaceted Approach.

Ischemic stroke constitutes a significant global health care challenge, and a comprehensive understanding of its recovery mechanisms is imperative for the development of innovative therapeutic strategies. Angiogenesis, a pivotal element of ischemic tissue repair, facilitates the restoration of blood flow to damaged regions, thereby promoting neuronal regeneration and functional recovery. Nevertheless, the mechanisms underlying postischemic stroke angiogenesis remain incompletely elucidated.

Unveiling the Evolution of Virtual Reality in Medicine: A Bibliometric Analysis of Research Hotspots and Trends over the Past 12 Years.

Background: Virtual reality (VR), widely used in the medical field, may affect future medical training and treatment. Therefore, this study examined VR's potential uses and research directions in medicine.

Methods: Citation data were downloaded from the Web of Science Core Collection database (WoSCC) to evaluate VR in medicine in articles published between 1 January 2012 and 31 December 2023.

Dual role of dissolved black carbon in sensitized ofloxacin photooxidation: Mechanism and influential factors.

Dissolved black carbon (DBC) is the more photoactive component of dissolved organic matter (DOM) pool, which plays a dual role in the photoconversion of aquatic contaminants, acting as both a photosensitizer and an inhibitor. However, little is known about the more systematic mechanism by which DBC exhibits a dual effect, which is closely related to the structure composition of DBC. In this study, the differences in characteristics of DBC obtained from 300 °C and 500 °C were compared via UV-vis absorption spectrum, Fluorescence excitation emission matrix spectra (3D-EEM), Fourier transform infrared (FT-IR), and X-ray photoelectron spectroscopy (XPS), and evaluated the promoting and inhibiting effects of DBC on ofloxacin (OFL) photodegradation.

Automatic height measurement of central serous chorioretinopathy lesion using a deep learning and adaptive gradient threshold based cascading strategy.

Accurately quantifying the height of central serous chorioretinopathy (CSCR) lesion is of great significance for assisting ophthalmologists in diagnosing CSCR and evaluating treatment efficacy. The manual measurement results dominated by single optical coherence tomography (OCT) B-scan image in clinical practice face the dilemma of weak reference, poor reproducibility, and experience dependence. In this context, this paper constructs two schemes: Scheme Ⅰ draws on the idea of ensemble learning, namely, integrating multiple models for locating starting key point in the height direction of lesion in the inference stage, which appropriately improves the performance of a single model.

Emerging Drug Delivery Vectors: Engineering of Plant-Derived Nanovesicles and Their Applications in Biomedicine.

Extracellular vesicles can transmit intercellular information and transport biomolecules to recipient cells during various pathophysiological processes in the organism. Animal cell exosomes have been identified as potential nanodrugs delivery vehicles, yet they have some shortcomings such as high immunogenicity, high cytotoxicity, and complicated preparation procedures. In addition to exosomes, plant-derived extracellular vesicles (PDVs), which carry a variety of active substances, are another promising nano-transport vehicles emerging in recent years due to their stable physicochemical properties, wide source, and low cost.