Extracts Exert Anti-Melanogenic Properties via the CREB/MAPK Pathway in B16F10 Cells.

, a salt-tolerant plant, has demonstrated antioxidant effects, the ability to prevent prostate enlargement, antifungal properties, and skin moisturizing benefits. This study aimed to explore the anti-melanogenic potential of the 70% ethanol extract of (TME) along with its ethyl acetate (TME-EA) and water (TME-A) fractions. TME (10-200 µg/mL), TME-EA (1-15 µg/mL), and TME-A (100-1000 µg/mL) were prepared and applied to B16F10 cells with or without α-MSH for 72 h.

Spherical Shell Bioprinting to Produce Uniform Spheroids with Controlled Sizes.

Conventional cell spheroid production methods are largely manual, leading to variations in size and shape that compromise consistency and reliability for use in cell-based therapeutic applications. To enhance spheroid production, a spherical shell bioprinting system was implemented, enabling the high-throughput generation of uniform cell spheroids with precisely controlled sizes. The system encapsulates cells within thin alginate hydrogel shells formed through bioprinting and ion crosslinking reactions.

CXCL11 reprograms M2-biased macrophage polarization to alleviate pulmonary fibrosis in mice.

Background: In understanding the pathophysiology of pulmonary fibrosis (PF), macrophage plasticity has been implicated with a crucial role in the fibrogenic process. Growing evidence indicates that accumulation of M2 macrophages correlates with the progression of PF, suggesting that targeted modulation of molecules that influence M2 macrophage polarization could be a promising therapeutic approach for PF. Here, we demonstrated a decisive role of C-X-C motif chemokine ligand 11 (CXCL11) in driving M1 macrophage polarization to alleviate PF in the bleomycin-induced murine model.

as a Prognostic Biomarker: Linking Copy Number Variation to EMT and Survival in Colon Cancer.

The role of biomarkers in cancer treatment varies significantly depending on the cancer stage. Thus, in clinical practice, tailoring biomarkers to meet the specific needs and challenges of each cancer stage can increase the precision of treatment. Because they reflect underlying genetic alterations that influence cancer progression, copy number variation (CNV) biomarkers can play crucial prognostic roles.

Radiographic Analysis of Scoliosis Using Convolutional Neural Network in Clinical Practice.

Purpose: To assess the reliability and accuracy of an automated Cobb angle measurement (ACAM) using a convolutional neural network (CNN) for scoliosis evaluation and to compare measurement times.

Materials And Methods: ACAM was applied to spine radiographs in 411 patients suspected of scoliosis. Observer 1 (consensus of two musculoskeletal radiologists) and observer 2 (a radiology resident) measured Cobb angle (CA).

Multipartite network analysis to identify environmental and genetic associations of metabolic syndrome in the Korean population.

Network analysis has become a crucial tool in genetic research, enabling the exploration of associations between genes and diseases. Its utility extends beyond genetics to include the assessment of environmental factors. Unipartite network analysis is commonly used in genomics to visualize initial insights and relationships among variables.

A comprehensive multi-task deep learning approach for predicting metabolic syndrome with genetic, nutritional, and clinical data.

Metabolic syndrome (MetS) is a complex disorder characterized by a cluster of metabolic abnormalities, including abdominal obesity, hypertension, elevated triglycerides, reduced high-density lipoprotein cholesterol, and impaired glucose tolerance. It poses a significant public health concern, as individuals with MetS are at an increased risk of developing cardiovascular diseases and type 2 diabetes. Early and accurate identification of individuals at risk for MetS is essential.

Gene-gene interaction analysis for age at onset of bipolar disorder in a Korean population.

Background: Multiple genes might interact to determine the age at onset of bipolar disorder. We investigated gene-gene interactions related to age at onset of bipolar disorder in the Korean population, using genome-wide association study (GWAS) data.

Methods: The study population consisted of 303 patients with bipolar disorder.

Deep learning framework for bovine iris segmentation.

Iris segmentation is an initial step for identifying the biometrics of animals when establishing a traceability system for livestock. In this study, we propose a deep learning framework for pixel-wise segmentation of bovine iris with a minimized use of annotation labels utilizing the BovineAAEyes80 public dataset. The proposed image segmentation framework encompasses data collection, data preparation, data augmentation selection, training of 15 deep neural network (DNN) models with varying encoder backbones and segmentation decoder DNNs, and evaluation of the models using multiple metrics and graphical segmentation results.

Oxidative Stress and DNA Damage in by the Dinoflagellate .

is a common species of red tide dinoflagellate that causes the mass mortality of marine fauna in coastal waters of Republic of Korea. Despite continuous studies on the ecophysiology and toxicity of , the underlying molecular mechanisms remain poorly understood. Red sea bream, is a high-value aquaculture fish species, and the coastal aquaculture industry of red sea bream has been increasingly affected by red tides.

A comparative study of epidemiological characteristics, treatment outcomes, and mortality among patients undergoing hemodialysis by health insurance types: data from the Korean Renal Data System.

Background: The prevalence of end-stage renal disease (ESRD) requiring dialysis has progressively increased. Therefore, to achieve financial stability by managing the increasing numbers of patients undergoing hemodialysis (HD), a fixed-payment system was introduced in 2001 for medical aid (MA) beneficiaries receiving HD in Korea.

Methods: We identified patients in the Korean Renal Data System that received HD between 2001 and 2017 and stratified them into the following two groups: the National Health Insurance (NHI) and MA groups.

Deep Learning-Based Precision Analysis for Acrosome Reaction by Modification of Plasma Membrane in Boar Sperm.

The analysis of AR is widely used to detect loss of acrosome in sperm, but the subjective decisions of experts affect the accuracy of the examination. Therefore, we develop an ARCS for objectivity and consistency of analysis using convolutional neural networks (CNNs) trained with various magnification images. Our models were trained on 215 microscopic images at 400× and 438 images at 1000× magnification using the ResNet 50 and Inception-ResNet v2 architectures.

MXene-Embedded Electrospun Polymeric Nanofibers for Biomedical Applications: Recent Advances.

Recently MXenes has gained immense attention as a new and exciting class of two-dimensional material. Due to their unique layered microstructure, the presence of various functional groups at the surface, earth abundance, and attractive electrical, optical, and thermal properties, MXenes are considered promising candidates for various applications such as energy, environmental, and biomedical. The ease of dispersibility and metallic conductivity of MXene render them promising candidates for use as fillers in polymer nanocomposites.

Transcriptomic Changes Induced by Low and High Concentrations of Heavy Metal Exposure in .

The impact of sewage and wastewater pollution on marine ecosystems is of increasing concern due to the rapid accumulation of heavy metals in seaweeds inhabiting near-shore environments. Seaweeds can be severely damaged by heavy metals throughout their life cycles. Although the physiological and ecological effects of heavy metal exposure have been studied, there is limited research on their molecular responses.

Comparison of cancer subtype identification methods combined with feature selection methods in omics data analysis.

Background: Cancer subtype identification is important for the early diagnosis of cancer and the provision of adequate treatment. Prior to identifying the subtype of cancer in a patient, feature selection is also crucial for reducing the dimensionality of the data by detecting genes that contain important information about the cancer subtype. Numerous cancer subtyping methods have been developed, and their performance has been compared.

Novel Materials in Perovskite Solar Cells: Efficiency, Stability, and Future Perspectives.

Solar energy is regarded as the finest clean and green energy generation method to replace fossil fuel-based energy and repair environmental harm. The more expensive manufacturing processes and procedures required to extract the silicon utilized in silicon solar cells may limit their production and general use. To overcome the barriers of silicon, a new energy-harvesting solar cell called perovskite has been gaining widespread attention around the world.

Nanoarchitectonics of Three-Dimensional Carbon Nanofiber-Supported Hollow Copper Sulfide Spheres for Asymmetric Supercapacitor Applications.

Three-dimensional carbon nanofiber (3D-CNF)-supported hollow copper sulfide (HCuS) spheres were synthesized by the facile hydrothermal method. The morphology of the as-synthesized HCuS@3D-CNF composite clearly revealed that the 3D-CNFs act as a basement for HCuS spheres. The electrochemical performance of as-synthesized HCuS@3D-CNFs was evaluated by cyclic voltammetry (CV) tests, gravimetric charge-discharge (GCD) tests, and Nyquist plots.

CFP1 governs uterine epigenetic landscapes to intervene in progesterone responses for uterine physiology and suppression of endometriosis.

Progesterone (P) is required for the preparation of the endometrium for a successful pregnancy. P resistance is a leading cause of the pathogenesis of endometrial disorders like endometriosis, often leading to infertility; however, the underlying epigenetic cause remains unclear. Here we demonstrate that CFP1, a regulator of H3K4me3, is required for maintaining epigenetic landscapes of P-progesterone receptor (PGR) signaling networks in the mouse uterus.

Electrospun Nanofibers for Dura Mater Regeneration: A Mini Review on Current Progress.

Dural defects are a common problem in neurosurgical procedures and should be repaired to avoid complications such as cerebrospinal fluid leakage, brain swelling, epilepsy, intracranial infection, and so on. Various types of dural substitutes have been prepared and used for the treatment of dural defects. In recent years, electrospun nanofibers have been applied for various biomedical applications, including dural regeneration, due to their interesting properties such as a large surface area to volume ratio, porosity, superior mechanical properties, ease of surface modification, and, most importantly, similarity with the extracellular matrix (ECM).

Suppression of triple-negative breast cancer aggressiveness by LGALS3BP via inhibition of the TNF-α-TAK1-MMP9 axis.

Transforming growth factor-β-activated kinase 1 (TAK1), which is highly expressed and aberrantly activated in triple-negative breast cancer (TNBC), plays a pivotal role in metastasis and progression. This makes it a potential therapeutic target for TNBC. Previously, we reported lectin galactoside-binding soluble 3 binding protein (LGALS3BP) as a negative regulator of TAK1 signaling in the inflammatory response and inflammation-associated cancer progression.

The use of virtual reality in screening for preclinical Alzheimer's disease: A scoping review protocol.

Introduction: Preclinical Alzheimer's disease (AD) represents the earliest phase of AD, often years before the onset of mild cognitive impairment (MCI). There is a pressing focus on identifying individuals in the preclinical AD phase to alter the trajectory or impact of the disease potentially. Increasingly, Virtual Reality (VR) technology is being used to support a diagnosis of AD.

MP-LASSO chart: a multi-level polar chart for visualizing group LASSO analysis of genomic data.

Penalized regression has been widely used in genome-wide association studies for jointanalyses to find genetic associations. Among penalized regression models, the least absolute shrinkage and selection operator (Lasso) method effectively removes some coefficientsfrom the model by shrinking them to zero. To handle group structures, such as genes andpathways, several modified Lasso penalties have been proposed, including group Lasso andsparse group Lasso.