Unified Analysis of Viscoelasticity and Viscoplasticity Using the Onsager Variational Principle.

This study is the application of the Onsager variational principle to viscoelasticity and viscoplasticity with the minimization of the assumptions which are popularly used in conventional approaches. The conventional approaches assume Kröner-Lee decomposition, incompressible plastic deformation, flowing rule, stress equation and so on. These assumptions have been accumulated by many researchers for a long time and have shown many successful cases.

Calponin 3 Regulates Myoblast Proliferation and Differentiation Through Actin Cytoskeleton Remodeling and YAP1-Mediated Signaling in Myoblasts.

An actin-binding protein, known as Calponin 3 (CNN3), modulates the remodeling of the actin cytoskeleton, a fundamental process for the maintenance of skeletal muscle homeostasis. Although the roles of CNN3 in actin remodeling have been established, its biological significance in myoblast differentiation remains largely unknown. This study investigated the functional significance of CNN3 in myogenic differentiation, along with its effects on actin remodeling and mechanosensitive signaling in C2C12 myoblasts.

Age-Dependent Effects of Butyl Benzyl Phthalate Exposure on Lipid Metabolism and Hepatic Fibrosis in Mice.

Endocrine-disrupting chemicals (EDCs), including phthalates, have been implicated in the development of non-alcoholic fatty liver disease (NAFLD) and hepatic fibrosis. This study investigates the age-dependent effects of butyl benzyl phthalate (BBP) exposure on lipid metabolism in the livers of young and aged mice. Young (2-month-old) and aged (20-month-old) male C57BL/6 mice were exposed to BBP through drinking water at a dose of 169 μg/kg/day for 6 and 4 months, respectively.

Neuroprotective Efficacy of in Ischemic Stroke: Antioxidant and Anti-Inflammatory Mechanisms.

Stroke affects over 12 million people annually, leading to high mortality, long-term disability, and substantial healthcare costs. Although East Asian herbal medicines are widely used for stroke treatment, the pathways of operation they use remain poorly understood. Our study investigates the neuroprotective properties of (AM) in acute ischemic stroke using photothrombotic (PTB) and transient middle cerebral artery occlusion (tMCAO) mouse models, as well as an oxygen-glucose deprivation (OGD) model.

Immune Gene Expression Profiling in Individuals with Turner Syndrome, Graves' Disease, and a Healthy Female by Single-Cell RNA Sequencing: A Comparative Study.

Turner syndrome (TS) can be determined by karyotype analysis, marked by the loss of one X chromosome in females. However, the genes involved in autoimmunity in TS patients remain unclear. In this study, we aimed to analyze differences in immune gene expression between a patient with TS, a healthy female, and a female patient with Graves' disease using single-cell RNA sequencing (scRNA-seq) analysis of antigen-specific CD4(+) T cells.

Molecular Mechanisms of Alzheimer's Disease Induced by Amyloid-β and Tau Phosphorylation Along with RhoA Activity: Perspective of RhoA/Rho-Associated Protein Kinase Inhibitors for Neuronal Therapy.

Amyloid-β peptide (Aβ) is a critical cause of Alzheimer's disease (AD). It is generated from amyloid precursor protein (APP) through cleavages by β-secretase and γ-secretase. γ-Secretase, which includes presenilin, is regulated by several stimuli.

Modulation of Second Messenger Signaling in the Brain Through PDE4 and PDE5 Inhibition: Therapeutic Implications for Neurological Disorders.

Phosphodiesterase (PDE) enzymes regulate intracellular signaling pathways crucial for brain development and the pathophysiology of neurological disorders. Among the 11 PDE subtypes, PDE4 and PDE5 are particularly significant due to their regulation of cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP) signaling, respectively, which are vital for learning, memory, and neuroprotection. This review synthesizes current evidence on the roles of PDE4 and PDE5 in neurological health and disease, focusing on their regulation of second messenger pathways and their implications for brain function.

Anti-Inflammatory Effects of Cannabigerol In Vitro and In Vivo Are Mediated Through the JAK/STAT/NFκB Signaling Pathway.

Cannabinoid compounds have potential as treatments for a variety of conditions, with cannabigerol (CBG) being known for its anti-inflammatory properties. In this study, we investigated the effects of CBG in a cellular model of 1-chloro-2,4-dinitrobenzene (DNCB)-induced atopic dermatitis (AD). In the cellular model, we confirmed the cytotoxicity of CBG and downregulated the expression of inflammatory markers , , , and ( < 0.

Role of Hypothalamus in Acupuncture's Effects.

The significant correlation between ancient medicinal practices and brain function marks a revolutionary frontier in the field of neuroscience. Acupuncture, a traditional oriental medicine, can affect brain regions, such as the hypothalamus, anterior cingulate, posterior cingulate, and hippocampus, and produces specific therapeutic effects, such as pain relief, suppression of hypertension, and alleviation of drug addiction. Among the brain regions, the hypothalamus, a small yet critical region in the brain, plays a pivotal role in maintaining homeostasis by regulating a wide array of physiological processes, including stress responses, energy balance, and pain modulation.

Diagnostic Errors in the Acutely Dizzy Patient-Lessons Learned.

Acute vertigo or dizziness is a frequent presentation to the emergency department (ED), making up between 2.1% and 4.4% of all consultations.

The Stress and Adversity Inventory for Adults (Adult STRAIN) in Korean: Initial Validation and Associations with Psychiatric Disorders.

Background/objectives: Stressors occurring across the life course are considered to have a cumulative impact on health, but there is no instrument for assessing lifetime stressor exposure in Korea. Therefore, we validated the Stress and Adversity Inventory (Adult STRAIN) in Korean.

Methods: We translated the Adult STRAIN into Korean and examined its concurrent, predictive, and comparative predictive validity in 218 Korean adults (79 men, 139 women; = 29.

Estimating the Impact of Aging on Visual Function Using Useful Field of View (UFOV) with a Focus on the Population of Gangwon-do in Korea.

Background/objectives: There is a need in Korea for research estimating the impact of aging using the Useful Field Of View (UFOV) test, which can evaluate visual function for elderly drivers.

Methods: This observational study involved young people in their twenties and thirties, later-middle-aged people in their fifties or older, and elderly people 65 or older recruited from the Gangwon-do region. UFOV testing was conducted on the participants where the participants completed a questionnaire about general and driving-related characteristics.

E46K α-Synuclein Mutation Fails to Promote Neurite Outgrowth by Not Inducing Cdc42EP2 Expression, Unlike Wild-Type or A53T α-Synuclein in SK-N-SH Cells.

Background/objectives: α-Synuclein (α-syn) protein is a major pathological agent of familial Parkinson's disease (PD), and its levels and aggregations determine neurotoxicity in PD pathogenesis. Although the pathophysiological functions of α-syn have been extensively studied, its biological functions remain elusive, and there are reports of wild-type (WT) α-syn and two missense mutations of α-syn (A30P and A53T) inducing protective neuritogenesis through neurite outgrowth. However, the function of another α-syn mutation, E46K, has not been fully elucidated.

Emerging Strategies for Revascularization: Use of Cell-Derived Extracellular Vesicles and Artificial Nanovesicles in Critical Limb Ischemia.

Critical limb ischemia (CLI) poses a substantial and intricate challenge in vascular medicine, necessitating the development of innovative therapeutic strategies to address its multifaceted pathophysiology. Conventional revascularization approaches often fail to adequately address the complexity of CLI, necessitating the identification of alternative methodologies. This review explores uncharted territory beyond traditional therapies, focusing on the potential of two distinct yet interrelated entities: cell-derived extracellular vesicles (EVs) and artificial nanovesicles.

Automated Audit and Self-Correction Algorithm for Seg-Hallucination Using MeshCNN-Based On-Demand Generative AI.

Recent advancements in deep learning have significantly improved medical image segmentation. However, the generalization performance and potential risks of data-driven models remain insufficiently validated. Specifically, unrealistic segmentation predictions deviating from actual anatomical structures, known as a Seg-Hallucination, often occur in deep learning-based models.

Targeting Chondrocyte Hypertrophy as Strategies for the Treatment of Osteoarthritis.

Osteoarthritis (OA) is a common joint disease characterized by pain and functional impairment, which severely impacts the quality of life of middle-aged and elderly individuals. During normal bone development, chondrocyte hypertrophy is a natural physiological process. However, in the progression of OA, chondrocyte hypertrophy becomes one of its key pathological features.

LightweightUNet: Multimodal Deep Learning with GAN-Augmented Imaging Data for Efficient Breast Cancer Detection.

Breast cancer ranks as the second most prevalent cancer globally and is the most frequently diagnosed cancer among women; therefore, early, automated, and precise detection is essential. Most AI-based techniques for breast cancer detection are complex and have high computational costs. Hence, to overcome this challenge, we have presented the innovative LightweightUNet hybrid deep learning (DL) classifier for the accurate classification of breast cancer.

Enhanced Detection Performance of Acute Vertebral Compression Fractures Using a Hybrid Deep Learning and Traditional Quantitative Measurement Approach: Beyond the Limitations of Genant Classification.

Objective: This study evaluated the applicability of the classical method, height loss ratio (HLR), for identifying major acute compression fractures in clinical practice and compared its performance with deep learning (DL)-based VCF detection methods. Additionally, it examined whether combining the HLR with DL approaches could enhance performance, exploring the potential integration of classical and DL methodologies.

Methods: End-to-End VCF Detection (EEVD), Two-Stage VCF Detection with Segmentation and Detection (TSVD_SD), and Two-Stage VCF Detection with Detection and Classification (TSVD_DC).

Accessible AI Diagnostics and Lightweight Brain Tumor Detection on Medical Edge Devices.

The timely and accurate detection of brain tumors is crucial for effective medical intervention, especially in resource-constrained settings. This study proposes a lightweight and efficient RetinaNet variant tailored for medical edge device deployment. The model reduces computational overhead while maintaining high detection accuracy by replacing the computationally intensive ResNet backbone with MobileNet and leveraging depthwise separable convolutions.

Deep Temporal Clustering of Pathological Gait Patterns in Post-Stroke Patients Using Joint Angle Trajectories: A Cross-Sectional Study.

Rehabilitation of gait function in post-stroke hemiplegic patients is critical for improving mobility and quality of life, requiring a comprehensive understanding of individual gait patterns. Previous studies on gait analysis using unsupervised clustering often involve manual feature extraction, which introduces limitations such as low accuracy, low consistency, and potential bias due to human intervention. This cross-sectional study aimed to identify and cluster gait patterns using an end-to-end deep learning approach that autonomously extracts features from joint angle trajectories for a gait cycle, minimizing human intervention.

Effects of an Avatar Control on VR Embodiment.

The motion control of the virtual avatar enhances a sense of embodiment in a virtual reality (VR). Yet, the detailed relationship between motion control, assigned tasks, and the sense of embodiment remains unclear. We aim to investigate the relationships between degrees of control on a full-body avatar and three elements of the sense of embodiment: the sense of self-location, agency, and ownership in standalone and interaction tasks.

Plant-Scale Circular Economy Using Biological Reuse of Electrolyte Residues in the Amino Acid Industry.

The amino acid industry generates significant amounts of electrolyte residues, such as ammonium sulfate, acetic acid, and phosphoric acid, which cause challenges to sustainability. This short article investigates the feasibility of implementing a plant-scale circular economy through the recycling and biological reuse of these electrolyte residues. Scenario analyses of L-lysine (LYS) HCl, L-methionine (MET), and L-cysteine (CYS) HCl production highlight the environmental and economic benefits of the plant-scale circular economy.

Automated Measurements of Tooth Size and Arch Widths on Cone-Beam Computerized Tomography and Scan Images of Plaster Dental Models.

Measurements of tooth size for estimating inter-arch tooth size discrepancies and inter-tooth distances, essential for orthodontic diagnosis and treatment, are primarily done using traditional methods involving plaster models and calipers. These methods are time-consuming and labor-intensive, requiring multiple steps. With advances in cone-beam computerized tomography (CBCT) and intraoral scanning technology, these processes can now be automated through computer analyses.

External Validation of Deep Learning Models for Classifying Etiology of Retinal Hemorrhage Using Diverse Fundus Photography Datasets.

Retinal hemorrhage (RH) is a significant clinical finding with various etiologies, necessitating accurate classification for effective management. This study aims to externally validate deep learning (DL) models, specifically FastVit_SA12 and ResNet18, for distinguishing between traumatic and medical causes of RH using diverse fundus photography datasets. A comprehensive dataset was compiled, including private collections from South Korea and Virginia, alongside publicly available datasets such as RFMiD, BRSET, and DeepEyeNet.

The Potential Clinical Utility of the Customized Large Language Model in Gastroenterology: A Pilot Study.

The large language model (LLM) has the potential to be applied to clinical practice. However, there has been scarce study on this in the field of gastroenterology. Aim: This study explores the potential clinical utility of two LLMs in the field of gastroenterology: a customized GPT model and a conventional GPT-4o, an advanced LLM capable of retrieval-augmented generation (RAG).