Engineering Volumetric Tissue Analogs via Assembly of Endothelial Cell-Covered Spheroidal Microtissues.

Tissue engineering holds a significant promise for the development of bioartificial organs applicable to transplantation. However, the size of engineered tissues remains limited, primarily due to the challenge of establishing microvascular networks within tissue constructs. In this study, engineered tissues are fabricated and embedded with functional microvascular networks by assembling endothelial cell-covered spheroidal microtissues.

Novel Neuroactive Steroid Analogs and Voltage-Dependent Blockers of Ca3.2 Currents, B372 and YX23, Are Effective Anti-Nociceptives with Diminished Sedative Properties in Intact Female Mice.

Although opioids are effective in treating pain, they cause serious side effects. The use of regional anesthesia, although effective in the perioperative period, may not be suitable if mobility and lack of numbness is desired. Hence, there is a clear need for novel pain therapies.

Complications Following Percutaneous Epidural Neuroplasty: A Narrative Review of Clinical Evidence and the Rationale for Post-Procedural 6 h Inpatient Monitoring Amid Limited Systematic Data.

: Percutaneous epidural neuroplasty (PEN) and related adhesiolysis procedures are widely used for managing chronic spinal pain. Although generally safe, complications-ranging from minor to life-threatening-have been reported. This review aimed to estimate the incidence and characteristics of complications following PEN and to evaluate the medical rationale for post-procedural inpatient monitoring.

Toward Standardized Massive Transfusion Protocols: A Multicenter Evaluation of Practice Variability Within a National Trauma System.

: Hemorrhage remains a leading cause of early mortality in trauma patients, and timely transfusion guided by a structured massive transfusion protocol (MTP) is critical for improving outcomes. Although regional trauma centers have been established, standardized MTPs remain insufficiently developed in many settings. This study aimed to evaluate current MTP practices across five major trauma centers within a national trauma care system.

SiO-Based Anode Materials with High Si Content Achieved Through Uniform Nano-Si Dispersion for Li-Ion Batteries.

Silicon alloy-based materials are widely studied as high-capacity anode materials to replace commercial graphite in lithium-ion batteries (LIBs). Among these, silicon suboxide (SiO) offers superior cycling performance compared to pure Si-based materials. However, achieving a high initial Coulombic efficiency (ICE) remains a key challenge.

What is the Reason for the Trend Shift from Dynamic Hip Screw to Cephalomedullary Nailing for the Treatment of Intertrochanteric Fractures? A Comprehensive Retrospective Study in a Single Tertiary Referral Hospital.

Background: The prevalence of intertrochanteric fractures is increasing with the aging population. Two surgical treatments, cephalomedullary nailing (CMN) and dynamic hip screw (DHS), have been widely utilized; however, recent trends indicate growing preference for CMN. While several studies have compared these 2 surgical methods, there has been limited comprehensive analysis with a substantial sample size from a single medical center aimed at minimizing bias.

Prognostic Role of Pre-Cannulation Lactate in Trauma Patients Undergoing Venovenous Extracorporeal Membrane Oxygenation.

Although venovenous (VV) extracorporeal membrane oxygenation (ECMO) is a life-saving intervention for trauma patients with severe respiratory failure, its mortality rate is 27%, and optimal metabolic markers for its initiation remain uncertain. We investigate the prognostic value of pre-cannulation lactate in trauma patients receiving early VV ECMO. This retrospective cohort study (2015-2024) included trauma patients undergoing VV ECMO.

Machine Learning Techniques for Simulating Human Psychophysical Testing of Low-Resolution Phosphene Face Images in Artificial Vision.

To evaluate the quality of artificial visual percepts generated by emerging methodologies, researchers often rely on labor-intensive and tedious human psychophysical experiments. These experiments necessitate repeated iterations upon any major/minor modifications in the hardware/software configurations. Here, the capacity of standard machine learning (ML) models is investigated to accurately replicate quaternary match-to-sample tasks using low-resolution facial images represented by arrays of phosphenes as input stimuli.

Prediction of microsatellite-stable/epithelial-to-mesenchymal transition molecular subtype gastric cancer using CT radiomics and clinicopathologic factors.

Objectives: This study aimed to develop a predictive model for the microsatellite-stable (MSS)/epithelial-to-mesenchymal transition (EMT) subtype of gastric cancer (GC) using computed tomography (CT) radiomics and clinicopathological factors.

Materials And Methods: This retrospective study included 418 patients with GC who underwent primary resection and transcriptome analysis with microarray between October 1995 and May 2008. Using preoperative CT images, radiomic features from the volume of interest in the portal venous phase images were extracted.

The complete mitogenome dataset of the heptageniid mayfly (Ephemeroptera: Heptageniidae: Ecdyonurinae) from South Korea.

The Heptageniidae family stands out as one of the most abundant and widespread among mayflies, distinguished by its unique mitochondrial characteristics in intergenic spacers and duplication of transfer RNA (tRNA) genes. In this dataset, we present the complete mitochondrial genome sequence of (Navás, 1912), a member of the Heptageniidae family of mayflies. The total length of the mitogenome was determined to be 15,362 base pairs, encompassing 13 protein-coding genes (PCGs), 23 tRNA genes, and two ribosomal RNA genes.

Effect of the Chemical Structure of a Self-Assembled Monolayer on the Gas-Sensing Behavior of SnO Nanowires.

In this study, detailed investigations of the selective sensing capability of semiconducting metal oxide (SMO)-based gas sensors with self-assembled monolayer (SAM) functionalization were conducted. The selective gas-sensing behavior was improved by employing a simple and straightforward postmodification technique using functional SAM molecules. The chemical structure of the SAM molecules promoted interaction between the gas and SAM molecules, providing a gas selective sensing of SnO nanowires (NWs).

Efficient Isolation of Cellulose Nanocrystals from Seaweed Waste via a Radiation Process and Their Conversion to Porous Nanocarbon for Energy Storage System.

This article presents an efficient method for isolating cellulose nanocrystals (CNcs) from seaweed waste using a combination of electron beam (E-beam) irradiation and acid hydrolysis. This approach not only reduces the chemical consumption and processing time, but also improves the crystallinity and yield of the CNcs. The isolated CNcs were then thermally annealed at 800 and 1000 °C to produce porous nanocarbon materials, which were characterized using scanning electron microscopy, X-ray diffraction, Raman spectroscopy, and X-ray photoelectron spectroscopy to assess their structural and chemical properties.

Sustained BMP-2 delivery via alginate microbeads and polydopamine-coated 3D-Printed PCL/β-TCP scaffold enhances bone regeneration in long bone segmental defects.

Background/objective: Repair of long bone defects remains a major challenge in clinical practice, necessitating the use of bone grafts, growth factors, and mechanical stability. Hence, a combination therapy involving a 3D-printed polycaprolactone (PCL)/β-tricalcium phosphate (β-TCP) scaffold coated with polydopamine (PDA) and alginate microbeads (AM) for sustained delivery of bone morphogenetic protein-2 (BMP-2) was investigated to treat long bone segmental defects.

Methods: Several in vitro analyses were performed to evaluate the scaffold osteogenic effects in vitro such as PDA surface modification, namely, hydrophilicity and cell adhesion; cytotoxicity and BMP-2 release kinetics using CCK-8 assay and ELISA, respectively; osteogenic differentiation in canine adipose-derived mesenchymal stem cells (Ad-MSCs); formation of mineralized nodules using ALP staining and ARS staining; and mRNA expression of osteogenic differentiation markers using RT-qPCR.

The Fibrotic Phenotype of Human Precision-Cut Lung Slices Is Maintained after Cryopreservation.

Human precision-cut lung slices (hPCLS) prepared from fibrotic lungs recapitulate the pathophysiological hallmarks of fibrosis. These hallmark features can also be induced by treating non-fibrotic hPCLS with a fibrotic cocktail (FC). As a result, the fibrotic and fibrosis-induced hPCLS are rapidly emerging as preferred models for disease modeling and drug discovery.

Efficient data labeling strategies for automated muscle segmentation in lower leg MRIs of Charcot-Marie-Tooth disease patients.

We aimed to develop efficient data labeling strategies for ground truth segmentation in lower-leg magnetic resonance imaging (MRI) of patients with Charcot-Marie-Tooth disease (CMT) and to develop an automated muscle segmentation model using different labeling approaches. The impact of using unlabeled data on model performance was further examined. Using axial T1-weighted MRIs of 120 patients with CMT (60 each with mild and severe intramuscular fat infiltration), we compared the performance of segmentation models obtained using several different labeling strategies.

Prognostic Role of Pre-Treatment Body Composition Parameters in Patients Undergoing First-Line Immunotherapy for Metastatic Renal Cell Carcinoma.

Purpose: We investigated the relationship between body mass index (BMI), radiological body composition, and survival outcomes in patients with metastatic renal cell carcinoma (mRCC) underwent first-line immune checkpoint inhibitor (ICI)-based therapy.

Methods: Analyzing data from 102 patients treated between November 2019 and March 2023, pre-treatment computed tomography (CT) scans assessed fat and muscle areas. BMI and body composition indices were examined, including skeletal muscle index, subcutaneous fat index (SFI), visceral fat index, and total fat index.

Deep Cascade of Convolutional Neural Networks for Quantification of Enlarged Perivascular Spaces in the Basal Ganglia in Magnetic Resonance Imaging.

In this paper, we present a cascaded deep convolution neural network (CNN) for assessing enlarged perivascular space (ePVS) within the basal ganglia region using T2-weighted MRI. Enlarged perivascular spaces (ePVSs) are potential biomarkers for various neurodegenerative disorders, including dementia and Parkinson's disease. Accurate assessment of ePVS is crucial for early diagnosis and monitoring disease progression.

Comprehensive deep learning-based assessment of living liver donor CT angiography: from vascular segmentation to volumetric analysis.

Background: Precise preoperative assessment of liver vasculature and volume in living donor liver transplantation is essential for donor safety and recipient surgery. Traditional manual segmentation methods are being supplemented by deep learning (DL) models, which may offer more consistent and efficient volumetric evaluations.

Methods: This study analyzed living liver donors from Samsung Medical Center using preoperative CT angiography data between April 2022 and February 2023.

Elucidating the interaction between stretch and stiffness using an agent-based spring network model of progressive pulmonary fibrosis.

Pulmonary fibrosis is a deadly disease that involves the dysregulation of fibroblasts and myofibroblasts, which are mechanosensitive. Previous computational models have succeeded in modeling stiffness-mediated fibroblasts behaviors; however, these models have neglected to consider stretch-mediated behaviors, especially stretch-sensitive channels and the stretch-mediated release of latent TGF-β. Here, we develop and explore an agent-based model and spring network model hybrid that is capable of recapitulating both stiffness and stretch.

3D auto-segmentation of biliary structure of living liver donors using magnetic resonance cholangiopancreatography for enhanced preoperative planning.

Background: This study aimed to develop an automated segmentation system for biliary structures using a deep learning model, based on data from magnetic resonance cholangiopancreatography (MRCP).

Materials And Methods: Living liver donors who underwent MRCP using the gradient and spin echo technique followed by three-dimensional modeling were eligible for this study. A three-dimensional residual U-Net model was implemented for the deep learning process.