MG‐PE3 bioinspired nanoparticle treatment for clearing amyloid with no toxicity.

Background: Impaired Aβ clearance plays a key role in the common, late‐onset AD. Anti‐Aβ immunotherapies are controversial, in part because of high rates of serious side effects including edema, microhemorrhages, and siderosis, highlighting the importance of the development of alternative Aβ clearance strategy. Here, we introduce a bioinspired nanoparticle named MG‐PE3 crossing the human blood‐brain barrier (BBB) and clearing Aβ with no adverse effect.

Effects of Postural Changes Using a Standing Desk on the Craniovertebral Angle, Muscle Fatigue, Work Performance, and Discomfort in Individuals with a Forward Head Posture.

Forward head posture is common among office workers who sit for long periods of time and is one of the main causes of neck pain. This study aimed to assess the effects of utilizing a standing desk on the craniovertebral angle, muscle fatigue, work performance, and discomfort in individuals with forward head posture. Twenty-four participants meeting the inclusion criteria were randomly assigned to either a traditional desk group ( = 12) or a standing desk group ( = 12).

Omnigene-Gut ensures fecal microbiome stability in the pediatric population.

Increasing evidence exists that the gut microbiome influences toxicity as well as outcomes in a variety of cancers. To investigate the role of the gut microbiome in pediatric neuro-oncology, microbiome analysis has been included in multiple prospective pediatric neuro-oncology clinical trials (NCT05009992, NCT04732065, NCT04775485). In these trials, the OMNIgene-GUT preservation tubes are used for the collection of the feces.

Robust self-supervised learning strategy to tackle the inherent sparsity in single-cell RNA-seq data.

Single-cell RNA sequencing (scRNA-seq) is a powerful tool for elucidating cellular heterogeneity and tissue function in various biological contexts. However, the sparsity in scRNA-seq data limits the accuracy of cell type annotation and transcriptomic analysis due to information loss. To address this limitation, we present scRobust, a robust self-supervised learning strategy to tackle the inherent sparsity of scRNA-seq data.

Comprehensive Symptom Prediction in Inpatients With Acute Psychiatric Disorders Using Wearable-Based Deep Learning Models: Development and Validation Study.

Background: Assessing the complex and multifaceted symptoms of patients with acute psychiatric disorders proves to be significantly challenging for clinicians. Moreover, the staff in acute psychiatric wards face high work intensity and risk of burnout, yet research on the introduction of digital technologies in this field remains limited. The combination of continuous and objective wearable sensor data acquired from patients with deep learning techniques holds the potential to overcome the limitations of traditional psychiatric assessments and support clinical decision-making.

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.

Identifying clinical and proteomic markers for early diagnosis and prognosis prediction of major psychiatric disorders.

Background: To clarify if blood proteins can predict disease progression among individuals at clinical high-risk of severe mental illness (CHR-SMI), we developed a statistical model incorporating clinical and blood protein markers to distinguish the transition group (who developed severe mental illness) (CHR-SMI-T) and from non-transition group (CHR-SMI-NT) at baseline.

Methods: Ninety individuals (74 at CHR-SMI: 16 patients) were monitored for ≤4 years and were the focus of predictive models. Three predictive models (1 [100 clinical variables], 2 [158 peptides], and 3 [100 clinical variables +158 peptides]) were evaluated using area under the receiver operating characteristic (AUROC) values.

WO Nanofibers Functionalized with Graphene as a Selective Sensing of NO Gas at Room Temperature.

Recent trends in two-dimensional (2D) graphene have demonstrated significant potential for gas-sensing applications with significantly enhanced sensitivity even at room temperature. Herein, this study presents fabrication of distinctive gas sensor based on one-dimensional (1D) WO nanofibers decorated 2D graphene, specifically coated on copper (Cu)-based interdigitated electrodes formed by DC sputtering, which can selectively detect NO gas at room temperature. The sensor device fabricated using WO/Gr1.

Complete genome sequence of candidate probiotic KUFM407.

It has been reported that the administration of alleviates diseases such as osteoporosis and colitis. In this study, we report the complete genome sequence of KUFM407, a probiotic strain of LAB isolated from Korean traditional fermented food, Kimchi. Whole genome sequencing of KUFM407 was performed on the Illumina MiSeq and Oxford Nanopore MinION platform.

A Development of a Sound Recognition-Based Cardiopulmonary Resuscitation Training System.

The objective of this study was to develop a sound recognition-based cardiopulmonary resuscitation (CPR) training system that is accessible, cost-effective, easy-to-maintain and provides accurate CPR feedback. Beep-CPR, a novel device with accordion squeakers that emit high-pitched sounds during compression, was developed. The sounds emitted by Beep-CPR were recorded using a smartphone, segmented into 2-second audio fragments, and then transformed into spectrograms.

Molecular epidemiology and virulence factors of group B Streptococcus in South Korea according to the invasiveness.

Background: Group B Streptococcus (GBS) causes invasive infections in newborns and elderly individuals, but is a noninvasive commensal bacterium in most immunocompetent people. Recently, the incidence of invasive GBS infections has increased worldwide, and there is growing interest in the molecular genetic characteristics of invasive GBS strains. Vaccines against GBS are expected in the near future.

DeepPIG: deep neural network architecture with pairwise connected layers and stochastic gates using knockoff frameworks for feature selection.

Selecting relevant feature subsets is essential for machine learning applications. Among the feature selection techniques, the knockoff filter procedure proposes a unique framework that minimizes false discovery rates (FDR). However, employing a deep neural network architecture for a knockoff filter framework requires higher detection power.