Machine learning-derived gut microbiome signature predicts fatty liver disease in the presence of insulin resistance

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Clustering in education, particularly in large-scale online environments like MOOCs, is essential for understanding and adapting to diverse student needs. However, the effectiveness of clustering depends on its interpretability, which becomes challenging w ...

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Obesity represents a significant public health concern and is linked to various comorbidities and cognitive impairments. Previous research indicates that elevated body mass index (BMI) is associated with structural changes in white matter (WM). However, a ...

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Background: There is increasing evidence that children or young adults having acquired liver disease in childhood display neurocognitive impairment which may become more apparent as they grow older. The molecular, cellular and morphological underpinnings o ...

Type C hepatic encephalopathy (HE) is a severe neuropsychiatric complication of chronic liver disease, for which the prognosis is poor in the absence of liver transplantation. Cirrhosis in type C HE leads to a toxic accumulation of ammonia in the blood, wh ...

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

Brain edema is considered as a common feature associated with hepatic encephalopathy (HE). However, its central role as cause or consequence of HE and its implication in the development of the neurological alterations linked to HE are still under debate. I ...

Herein, machine learning (ML) models using multiple linear regression (MLR), support vector regression (SVR), random forest (RF) and artificial neural network (ANN) are developed and compared to predict the output features viz. specific capacitance (Csp), ...

With a growing emphasis on indoor air quality (IAQ) in educational environments, CO2 monitoring in classrooms has become commonplace. CO2 data can be used to estimate outdoor air change rate (ACH) based on the mass balance principle, which can be further l ...

Hepatocytes are the main workers in the hepatic factory, managing metabolism of nutrients and xenobiotics, production and recycling of proteins, and glucose and lipid homeostasis. Division of labor between hepatocytes is critical to coordinate complex comp ...

Epilepsy is one of the most prevalent brain disorders that disrupts the lives of millions worldwide. For patients with drug-resistant seizures, there exist implantable devices capable of monitoring neural activity, promptly triggering neurostimulation to r ...

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

The Euclid Space Telescope will provide deep imaging at optical and near-infrared wavelengths, along with slitless near-infrared spectroscopy, across similar to 15 000deg(2) of the sky. Euclid is expected to detect similar to 12 billion astronomical source ...

Machine learning models have been shown to leak sensitive information about their training datasets. Models are increasingly deployed on devices, raising concerns that white-box access to the model parameters increases the attack surface compared to black- ...

BSEP (ABCB11) is an ATP-binding cassette transporter that is expressed in hepatocytes and extrudes bile salts into the canaliculi of the liver. BSEP dysfunction, caused by mutations or induced by drugs, is frequently associated with severe cholestatic live ...

Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

This study presents a self-supervised Bayesian Neural Network (BNN) framework using air-borne Acoustic Emission (AE) to identify different Laser Powder Bed Fusion (LPBF) process regimes such as Lack of Fusion, conduction mode, and keyhole without ground-tr ...

Introduction Type C hepatic encephalopathy (HE) is a decompensating event of chronic liver disease leading to severe motor and cognitive impairment. The progression of type C HE is associated with changes in brain metabolite concentrations measured by 1H m ...

Machine learning-derived gut microbiome signature predicts fatty liver disease in the presence of insulin resistance

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Diffusion of brain metabolites highlights altered brain microstructure in type C hepatic encephalopathy: a 9.4 T preliminary study