A joint model for lesion segmentation and classification of MS and NMOSD.

Introduction: Multiple sclerosis (MS) and neuromyelitis optic spectrum disorder (NMOSD) are mimic autoimmune diseases of the central nervous system with a very high disability rate. Their clinical symptoms and imaging findings are similar, making it difficult to diagnose and differentiate. Existing research typically employs the T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) MRI imaging technique to focus on a single task in MS and NMOSD lesion segmentation or disease classification, while ignoring the collaboration between the tasks.

Impaired olfactory identification in dementia-free individuals is associated with the functional abnormality of the precuneus.

Objective: Olfactory dysfunction indicates a higher risk of developing dementia. However, the potential structural and functional changes are still largely unknown.

Methods: A total of 236 participants were enrolled, including 45 Alzheimer's disease (AD) individuals and 191dementia-free individuals.

2.5D transfer deep learning model for segmentation of contrast-enhancing lesions on brain magnetic resonance imaging of multiple sclerosis and neuromyelitis optica spectrum disorder.

Background: Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are the two mimic autoimmune diseases of the central nervous system, which are rare in East Asia. Quantitative detection of contrast-enhancing lesions (CELs) on contrast-enhancing T1-weighted magnetic resonance (MR) images is of great significance for assessing the disease activity of MS and NMOSD. However, it is challenging to develop automatic segmentation algorithms due to the lack of data.

[Titin: structure, isoforms and functional regulation].

Titin, the largest known protein in the body expressed in three isoforms (N2A, N2BA and N2B), is essential for muscle structure, force generation, conduction and regulation. Since the 1950s, muscle contraction mechanisms have been explained by the sliding filament theory involving thin and thick muscle filaments, while the contribution of cytoskeleton in force generation and conduction was ignored. With the discovery of insoluble protein residues and large molecular weight proteins in muscle fibers, the third myofilament, titin, has been identified and attracted a lot of interests.

Two case reports and a systematic review of the literature on adult cerebral cortical encephalitis with anti-myelin oligodendrocyte glycoprotein antibody.

Background And Purpose: Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) has gained recognition in recent years as an immune-mediated inflammatory demyelinating disease of the central nervous system. The clinical features and prognosis of MOGAD adult cerebral cortical encephalitis (adult CCE) have not been fully elucidated. This study aims to further characterize the clinical symptoms, magnetic resonance imaging (MRI) findings, and prognosis of CCE with anti-MOG antibody.

Local Brain Network Alterations and Olfactory Impairment in Alzheimer's Disease: An fMRI and Graph-Based Study.

Alzheimer's disease (AD) is associated with the abnormal connection of functional networks. Olfactory impairment occurs in early AD; therefore, exploring alterations in olfactory-related regions is useful for early AD diagnosis. We combined the graph theory of local brain network topology with olfactory performance to analyze the differences in AD brain network characteristics.

[Effects of alternate-day modified fasting combined exercise on fat reducing and the FNDC5/Irisin-UCP1 pathway].

Objective: The effects of Alternate-day modified fasting combined exercise on fat mass, muscle mass, and serum Irisin, FNDC5 and UCP1 proteins were investigated in rats with 4 weeks of aerobic exercise and modified alternate-day fasting intervention.

Methods: Thirty-two healthy 8-week-old SPF male SD rats were randomly divided into control group, exercise group, alternate-day modified fasting and alternate-day modified fasting combined with exercise group, 8 rats in each group. The exercise group performed treadmill exercise with moderate exercise intensity(60 min/d,5 d/w), the alternate-day modified fasting group alternated between fasting and free feeding every other day, and fed 25% basal energy feed on fasting days, and the alternate-day modified fasting combined exercise group received two combined interventions.

Dual Semi-Supervised Learning for Classification of Alzheimer's Disease and Mild Cognitive Impairment Based on Neuropsychological Data.

Deep learning has shown impressive diagnostic abilities in Alzheimer's disease (AD) research in recent years. However, although neuropsychological tests play a crucial role in screening AD and mild cognitive impairment (MCI), there is still a lack of deep learning algorithms only using such basic diagnostic methods. This paper proposes a novel semi-supervised method using neuropsychological test scores and scarce labeled data, which introduces difference regularization and consistency regularization with pseudo-labeling.

Clinical characteristics of late-onset neuromyelitis optica spectrum disorder.

Background: Anti-aquaporin-4 (AQP-4) immunoglobulin G (IgG) is a major autoimmune antibody that contributes to the pathogenesis of neuromyelitis optica spectrum disorder (NMOSD). NMOSD often presents as disability, severe sensory impairment, and sleep disorders, which can cause anxiety and depression and further affect the quality of life. The age of onset is a key factor influencing the prognosis of NMOSD.

Ensemble learning supervision augmentation for white matter hyperintensity segmentation.

Since the ambiguous boundary of the lesion and inter-observer variability, white matter hyperintensity segmentation annotations are inherently noisy and uncertain. On the other hand, the high capacity of deep neural networks (DNN) enables them to overfit labels with noise and uncertainty, which may lead to biased models with weak generalization ability. This challenge has been addressed by leveraging multiple annotations per image.

Energy Transfer Assisted Fast X-ray Detection in Direct/Indirect Hybrid Perovskite Wafer.

Metal halide perovskite scintillators encounter unprecedented opportunities in indirect ionizing radiation detection due to their high quantum yields. However, the long scintillation lifetime of microseconds upon irradiation, known as the afterglow phenomenon, obviously limits their fast development. Here, a new type of hybrid X-ray detector wafer combining direct methylamine lead iodide (MAPbI ) semiconductor and indirect zero-dimensional cesium copper iodide (Cs Cu I ) scintillator through low-cost fast tableting processes is reported.

Improving segmentation reliability of multi-scanner brain images using a generative adversarial network.

Background: Magnetic resonance (MR) images generated by different scanners generally have inconsistent contrast properties, making it difficult to perform a combined quantitative analysis of images from a range of scanners. In this study, we aimed to develop an automatic brain image segmentation model to provide a more reliable analysis of MR images taken with different scanners.

Methods: The spatially localized atlas network tiles-27 (SLANT-27) deep learning model was used to train the automatic segmentation module, based on a multi-center dataset of 1,917 three-dimensional (3D) T1-weighted MR images.

Effect of Tai Chi combined with Kinesio taping on posture control of football players with FAI: protocol for a randomized controlled trial.

Background: Functional ankle instability (FAI) of college football players is an important risk factor affecting their training and competition. Physical therapy and appropriate sports intervention can improve the stability of FAI patients. Previous studies have shown that Tai Chi (TC) and Kinesio taping (KT) can improve the posture control ability of FAI patients.

Oriented 2D Perovskite Wafers for Anisotropic X-ray Detection through a Fast Tableting Strategy.

2D perovskite single crystals have emerged as excellent optoelectronic materials owing to their unique anisotropic properties. However, growing large 2D perovskite single crystals remains challenging and time-consuming. Here, a new composition of lead-free 2D perovskite-4-fluorophenethylammonium bismuth iodide [(F-PEA) BiI ] is reported.

Fine-control-valve of halide perovskite single crystal quality for high performance X-ray detection.

Halide perovskite single crystals (HPSCs) provide a unique platform to study the optoelectronic properties of such emerging semiconductor materials, while the temperature induced crystal growth method often has an increased solute integration speed and/or unavoidable solute consumption, resulting in a soaring or slumping crystal growth rate of HPSCs. Here, we developed a universal and facile solvent-volatilization-limited-growth (SVG) strategy to finely control the crystal growth rate by the fine-control-valve for high quality crystal grown through solution processes. The grown HPSCs by SVG method exhibited a record low trap density of 2.

[Effect of 4-week electroacupuncture intervention on "Browning" of white fat in rats and its mechanism].

To investigate the effects of 4-week electroacupuncture intervention on "Browning" of white fat in rats, and to explore its molecular mechanisms. Twenty-four 8-week-old male SD rats were randomly divided into sedentary group (Sed), aerobic exercise group (Exe) and electroacupuncture group (ElA), 8 rats in each group. Exe group used 65% Max oxygen uptake intensity treadmill exercise, 1 h/d,6 d/w, while the ElA group used electric acupuncture to stimulate "zusanli" and "tianshu" points, 20 min/d,6 d/w, and the weight of rats was recorded every week.

3D Compressed Convolutional Neural Network Differentiates Neuromyelitis Optical Spectrum Disorders From Multiple Sclerosis Using Automated White Matter Hyperintensities Segmentations.

Background: Magnetic resonance imaging (MRI) has a wide range of applications in medical imaging. Recently, studies based on deep learning algorithms have demonstrated powerful processing capabilities for medical imaging data. Previous studies have mostly focused on common diseases that usually have large scales of datasets and centralized the lesions in the brain.

SOX2 Regulates lncRNA CCAT1/MicroRNA-185-3p/FOXP3 Axis to Affect the Proliferation and Self-Renewal of Cervical Cancer Stem Cells.

It has been presented the role of long non-coding RNAs (lncRNAs) in cervical cancer (CC). We aim to discuss the effect of sex-determining region Y-box 2 (SOX2)/lncRNA colon cancer-associated transcript-1 (CCAT1)/microRNA-185-3p (miR-185-3p)/forkhead box protein 3 (FOXP3) on the proliferation and self-renewal ability of CC stem cells. MiR-185-3p, SOX2, CCAT1 and FOXP3 expressions were tested in CC tissues and cells.

Gene regulation by long non-coding RNAs and its biological functions.

Evidence accumulated over the past decade shows that long non-coding RNAs (lncRNAs) are widely expressed and have key roles in gene regulation. Recent studies have begun to unravel how the biogenesis of lncRNAs is distinct from that of mRNAs and is linked with their specific subcellular localizations and functions. Depending on their localization and their specific interactions with DNA, RNA and proteins, lncRNAs can modulate chromatin function, regulate the assembly and function of membraneless nuclear bodies, alter the stability and translation of cytoplasmic mRNAs and interfere with signalling pathways.

Cancer genotypes prediction and associations analysis from imaging phenotypes: a survey on radiogenomics.

In this paper, we present a survey on the progress of radiogenomics research, which predicts cancer genotypes from imaging phenotypes and investigates the associations between them. First, we present an overview of the popular technology modalities for obtaining diagnostic medical images. Second, we summarize recently used methodologies for radiogenomics analysis, including statistical analysis, radiomics and deep learning.

Mechanisms of Long Noncoding RNA Nuclear Retention.

Long noncoding RNAs (lncRNAs) are crucial regulators in diverse cellular contexts and biological processes. The subcellular localization of lncRNAs determines their modes of action. Compared to mRNAs, however, many mRNA-like lncRNAs are preferentially localized to the nucleus where they regulate chromatin organization, transcription, and different nuclear condensates.

Distortion correction of single-shot EPI enabled by deep-learning.

Purpose: A distortion correction method for single-shot EPI was proposed. Point-spread-function encoded EPI (PSF-EPI) images were used as the references to correct traditional EPI images based on deep neural network.

Theory And Methods: The PSF-EPI method can obtain distortion-free echo planar images.