feed-forward

BACKGROUND: In recent years, research has determined that impaired sensorimotor integration is a contributor to the formation of voice symptoms and voice disorders. A scoping review is undertaken to explore the current state of scientific research regarding behavioral examinations of sensorimotor integration impairments in patients. SUMMARY: Following the guidelines of the PRISMA Extension for Scoping Reviews, five online databases identified papers published 2000-2023, from which 17 publications were selected that used sensorimotor integration paradigms with voice-related acoustics as an outcome variable in individuals diagnosed with a voice disorder...

Esophageal cancer (EC) remains a significant health challenge globally, with increasing incidence and high mortality rates. Despite advances in treatment, there remains a need for improved diagnostic methods and understanding of disease progression. This study addresses the significant challenges in the automatic classification of EC, particularly in distinguishing its primary subtypes: adenocarcinoma and squamous cell carcinoma, using histopathology images. Traditional histopathological diagnosis, while being the gold standard, is subject to subjectivity and human error and imposes a substantial burden on pathologists...

UNLABELLED: A lab-scale continuous ohmic heating (COH) system was developed, and its performance was studied for pineapple juice heating as a model sample. The effect of independent parameters [°Brix/Acid (unstandardized, 18, 22, 26) and flow rate (80-120 mL/min) of juice and electric field strength (EFS: 25-45 V/cm)] were analysed for responses viz. come-up-time, heating rate (HR) and system performance coefficient (SPC). The full factorial experimental design was used for this study...

COVID-19's effects on the human brain reveal a multifactorial impact on cognition and the potential to inflict lasting neuronal damage. Type I interferon signaling, a pathway that represents our defense against pathogens, is primarily affected by COVID-19. Type I interferon signaling, however, is known to mediate cognitive dysfunction upon its dysregulation following synaptopathy, microgliosis and neuronal damage. In previous studies, we proposed a model of outside-in dysregulation of tonic IFN-I signaling in the brain following a COVID-19...

UNLABELLED: The ability to express transgenes at specified levels is critical for understanding cellular behaviors, and for applications in gene and cell therapy. Transfection, viral vectors, and other gene delivery methods produce varying protein expression levels, with limited quantitative control, while targeted knock-in and stable selection are inefficient and slow. Active compensation mechanisms can improve precision, but the need for additional proteins or lack of tunability have prevented their widespread use...

A longstanding challenge in gene therapy is expressing a dosage-sensitive gene within a tight therapeutic window. For example, loss of MECP2 function causes Rett syndrome, while its duplication causes MECP2 duplication syndrome. Viral gene delivery methods generate variable numbers of gene copies in individual cells, creating a need for gene dosage-invariant expression systems. Here, we introduce a compact miRNA-based, incoherent feed-forward loop circuit that achieves precise control of Mecp2 expression in cells and brains, and improves outcomes in an AAV-based mouse model of Rett syndrome gene therapy...

BACKGROUND: Mounting evidence suggests a role for the gastro-intestinal microbiome as a determinant of peripheral immunity and central neurodegeneration, but the local disease mechanisms remain unknown. Given its potential relevance for early diagnosis and therapeutic intervention, we set out to map the pathogenic changes induced by bacterial amyloids in the gastro-intestinal tract and its enteric nervous system. METHODS: To examine the early response, we challenged primary murine myenteric networks with curli, the prototypic bacterial amyloid, and performed shotgun RNA sequencing and multiplex ELISA...

The threat posed by forged video technology has gradually grown to include individuals, society, and the nation. The technology behind fake videos is getting more advanced and modern. Fake videos are appearing everywhere on the internet. Consequently, addressing the challenge posed by frequent updates in various deepfake detection models is imperative. The substantial volume of data essential for their training adds to this urgency. For the deepfake detection problem, we suggest a cascade network based on spatial and channel reconstruction convolution (SCConv) and vision transformer...

Machine condition monitoring is used in a variety of industries as a very efficient strategy for equipment maintenance. This paper presents a study on monitoring a pneumatic system using a feed-forward backpropagation neural network as a classifier and compares the results obtained with different sensor signals and associated extracted features as input for classification. The vibrations of the body of a pneumatic cylinder are acquired using both common industrial sensors and low-cost sensors integrated into an Arduino board...

This observational study investigated the potential of radiomics as a non-invasive adjunct to CT in distinguishing COVID-19 lung nodules from other benign and malignant lung nodules. Lesion segmentation, feature extraction, and machine learning algorithms, including decision tree, support vector machine, random forest, feed-forward neural network, and discriminant analysis, were employed in the radiomics workflow. Key features such as Idmn, skewness, and long-run low grey level emphasis were identified as crucial in differentiation...

High levels of proinflammatory cytokines induce neurotoxicity and catalyze inflammation-driven neurodegeneration, but the specific release mechanisms from microglia remain elusive. Here we show that secretory autophagy (SA), a non-lytic modality of autophagy for secretion of vesicular cargo, regulates neuroinflammation-mediated neurodegeneration via SKA2 and FKBP5 signaling. SKA2 inhibits SA-dependent IL-1β release by counteracting FKBP5 function. Hippocampal Ska2 knockdown in male mice hyperactivates SA resulting in neuroinflammation, subsequent neurodegeneration and complete hippocampal atrophy within six weeks...

INTRODUCTION: Deep learning models can assess the quality of images and discriminate among abnormalities in small bowel capsule endoscopy (CE), reducing fatigue and the time needed for diagnosis. They serve as a decision support system, partially automating the diagnosis process by providing probability predictions for abnormalities. METHODS: We demonstrated the use of deep learning models in CE image analysis, specifically by piloting a bowel preparation model (BPM) and an abnormality detection model (ADM) to determine frame-level view quality and the presence of abnormal findings, respectively...

Visual inspection is the typical way for evaluating burns, due to the rising occurrence of burns globally, visual inspection may not be sufficient to detect skin burns because the severity of burns can vary and some burns may not be immediately apparent to the naked eye. Burns can have catastrophic and incapacitating effects and if they are not treated on time can cause scarring, organ failure, and even death. Burns are a prominent cause of considerable morbidity, but for a variety of reasons, traditional clinical approaches may struggle to effectively predict the severity of burn wounds at an early stage...

Skin cancer is one of the most fatal skin lesions, capable of leading to fatality if not detected in its early stages. The characteristics of skin lesions are similar in many of the early stages of skin lesions. The AI in categorizing diverse types of skin lesions significantly contributes to and helps dermatologists to preserve patients' lives. This study introduces a novel approach that capitalizes on the strengths of hybrid systems of Convolutional Neural Network (CNN) models to extract intricate features from dermoscopy images with Random Forest (Rf) and Feed Forward Neural Networks (FFNN) networks, leading to the development of hybrid systems that have superior capabilities early detection of all types of skin lesions...

The feed-forward loop between the transcription factors Ppar-gamma and C/ebp-alpha is critical for lineage commitment during adipocytic differentiation. Ppar-gamma interacts with epigenetic cofactors to activate C/ebp-alpha and the downstream adipocytic gene expression program. Therefore, knowledge of the epigenetic cofactors associated with Ppar-gamma, is central to understanding adipocyte differentiation in normal differentiation and disease. We found that Prmt6 is present with Ppar-gamma on the Ppar-gamma and C/ebp-alpha promoter...

Background Hypertension, or high blood pressure, is a common medical condition that affects a significant portion of the global population. It is a major risk factor for cardiovascular diseases (CVD), stroke, and kidney disorders. Objective The objective of this study is to create and validate a model that combines bootstrapping, ordered logistic regression, and multilayer feed-forward neural networks (MLFFNN) to identify and analyze the factors associated with hypertension patients who also have dyslipidemia...

The transformation from perception to action requires a set of neuronal decisions about the nature of the percept, identification and selection of response options and execution of the appropriate motor response. The unfolding of such decisions is mediated by distributed representations of the decision variables-evidence and intentions-that are represented through oscillatory activity across the cortex. Here we combine magneto-electroencephalography and linear ballistic accumulator models of decision-making to reveal the impact of Parkinson's disease during the selection and execution of action...

OBJECTIVE: Cardiovascular diseases (CVDs) account for a high fatality rate worldwide. Heart murmurs can be detected from phonocardiograms (PCGs) and may indicate CVDs. Still, they are often overlooked as their detection and correct clinical interpretation require expert skills. In this work, we aim to predict the presence of murmurs and clinical outcomes from multiple PCG recordings employing an explainable multitask model. APPROACH: Our approach consists of a two-stage multitask model...

Condensing the many physical variables defining a chemical system into a fixed-size array poses a significant challenge in the development of chemical Machine Learning (ML). Atom Centered Symmetry Functions (ACSFs) offer an intuitive featurization approach by means of a tedious and labor-intensive selection of tunable parameters. In this work, we implement an unsupervised ML strategy relying on a Gaussian Mixture Model (GMM) to automatically optimize the ACSF parameters. GMMs effortlessly decompose the vastness of the chemical and conformational spaces into well-defined radial and angular clusters, which are then used to build tailor-made ACSFs...

INTRODUCTION: Thyroid carcinoma is the most frequent malignancy in different endocrine-related tumours. In this study, we demonstrated a long non-coding RNA LINC00092-associated molecular mechanism in promoting the progression of papillary thyroid carcinoma (PTC). MATERIAL AND METHODS: The expression of LINC00092 was analysed in the The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA) patient cohorts and further determined by q-PCR. (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide) (MTT) assay, and wound healing assay confirmed the function of LINC00092 in migration and proliferation...