Bovine milk consumption affects the transcriptome of porcine adipose stem cells: Do exosomes play any role?

The potential association of milk with childhood obesity has been widely debated and researched. Milk is known to contain many bioactive compounds as well as bovine exosomes rich in micro-RNA (miR) that can have effects on various cells, including stem cells. Among them, adipose stem cells (ASC) are particularly interesting due to their role in adipose tissue growth and, thus, obesity.

Liver magnetic resonance imaging, non-alcoholic fatty liver disease and metabolic syndrome risk in pre-pubertal Mexican boys.

Rising global pediatric obesity rates, increase non-alcoholic fatty liver disease (NAFLD) and metabolic syndrome (MetS) prevalence, with MetS being a NAFLD risk factor. NAFLD can be asymptomatic, with liver function tests insensitive to mild disease, and liver biopsy, risking complications. Thus, we investigated multiparametric MRI (mpMRI) metrics of liver fat (proton density fat fraction, PDFF) and disease activity (fibro-inflammation; iron-corrected T1, cT1), in a Hispanic pre-pubertal pediatric cohort, with increased risk of NAFLD.

Reference Range of Quantitative MRI Metrics Corrected T1 and Liver Fat Content in Children and Young Adults: Pooled Participant Analysis.

Background: Multiparametric MRI markers of liver health corrected T1 (cT1) and proton density fat fraction (PDFF) have shown utility in the management of various chronic liver diseases. We assessed the normal population reference range of both cT1 and PDFF in healthy child and adult volunteers without any known liver disease.

Methods: A retrospective multi-centre pooled analysis of 102 child and young adult (9.

MRI assessment of adipose tissue fatty acid composition in the UK Biobank and its association with diet and disease.

Objective: This study aimed to assess the fatty acid (FA) composition of abdominal subcutaneous and visceral adipose tissue (ASAT and VAT, respectively) in the UK Biobank imaging cohort (N = 33,823) using magnetic resonance imaging (MRI).

Methods: We measured the fractions of saturated, monounsaturated, and polyunsaturated FA (fSFA, fMUFA, and fPUFA, respectively) in ASAT and VAT from multiecho MRI scans. We selected a subcohort of participants who followed a vegan and an omnivore diet (N = 36) to validate the effect of diet on adipose tissue.

Differing genetic variants associated with liver fat and their contrasting relationships with cardiovascular diseases and cancer.

Background & Aims: The mechanisms underlying the association of steatotic liver disease with cardiovascular and cancer outcomes are poorly understood. We aimed to use MRI-derived measures of liver fat and genetics to investigate causal mechanisms that link higher liver fat to various health outcomes.

Methods: We conducted a genome-wide association study on 37,358 UK Biobank participants to identify genetic variants associated with liver fat measured from MRI scans.

The Association of Cardiometabolic, Diet and Lifestyle Parameters With Plasma Glucagon-like Peptide-1: An IMI DIRECT Study.

Context: The role of glucagon-like peptide-1 (GLP-1) in type 2 diabetes (T2D) and obesity is not fully understood.

Objective: We investigate the association of cardiometabolic, diet, and lifestyle parameters on fasting and postprandial GLP-1 in people at risk of, or living with, T2D.

Methods: We analyzed cross-sectional data from the two Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohorts, cohort 1 (n = 2127) individuals at risk of diabetes; cohort 2 (n = 789) individuals with new-onset T2D.

Genetic Evidence for Distinct Biological Mechanisms That Link Adiposity to Type 2 Diabetes: Toward Precision Medicine.

We aimed to unravel the mechanisms connecting adiposity to type 2 diabetes. We used MR-Clust to cluster independent genetic variants associated with body fat percentage (388 variants) and BMI (540 variants) based on their impact on type 2 diabetes. We identified five clusters of adiposity-increasing alleles associated with higher type 2 diabetes risk (unfavorable adiposity) and three clusters associated with lower risk (favorable adiposity).

Quantifying the effect of nutritional interventions on metabolic resilience using personalized computational models.

The manifestation of metabolic deteriorations that accompany overweight and obesity can differ greatly between individuals, giving rise to a highly heterogeneous population. This inter-individual variation can impede both the provision and assessment of nutritional interventions as multiple aspects of metabolic health should be considered at once. Here, we apply the Mixed Meal Model, a physiology-based computational model, to characterize an individual's metabolic health A population of 342 personalized models were generated using data for individuals with overweight and obesity from three independent intervention studies, demonstrating a strong relationship between the model-derived metric of insulin resistance (ρ = 0.

The use of NADH anisotropy to investigate mitochondrial cristae alignment.

Life may be expressed as the flow of electrons, protons, and other ions, resulting in large potential difference. It is also highly photo-sensitive, as a large proportion of the redox capable molecules it relies on are chromophoric. It is thus suggestive that a key organelle in eukaryotes, the mitochondrion, constantly adapt their morphology as part of the homeostatic process.

Ultra weak photon emission-a brief review.

Cells emit light at ultra-low intensities: photons which are produced as by-products of cellular metabolism, distinct from other light emission processes such as delayed luminescence, bioluminescence, and chemiluminescence. The phenomenon is known by a large range of names, including, but not limited to, biophotons, biological autoluminescence, metabolic photon emission and ultraweak photon emission (UPE), the latter of which shall be used for the purposes of this review. It is worth noting that the photons when produced are neither 'weak' nor specifically biological in characteristics.

Precision MRI phenotyping of muscle volume and quality at a population scale.

Magnetic resonance imaging (MRI) enables direct measurements of muscle volume and quality, allowing for an in-depth understanding of their associations with anthropometric traits, and health conditions. However, it is unclear which muscle volume measurements: total muscle volume, regional measurements, measurements of muscle quality: intermuscular adipose tissue (IMAT) or proton density fat fraction (PDFF), are most informative and associate with relevant health conditions such as dynapenia and frailty. We have measured image-derived phenotypes (IDPs) including total and regional muscle volumes and measures of muscle quality, derived from the neck-to-knee Dixon images in 44,520 UK Biobank participants.

Liver shape analysis using statistical parametric maps at population scale.

Background: Morphometric image analysis enables the quantification of differences in the shape and size of organs between individuals.

Methods: Here we have applied morphometric methods to the study of the liver by constructing surface meshes from liver segmentations from abdominal MRI images in 33,434 participants in the UK Biobank. Based on these three dimensional mesh vertices, we evaluated local shape variations and modelled their association with anthropometric, phenotypic and clinical conditions, including liver disease and type-2 diabetes.

Kidney shape statistical analysis: associations with disease and anthropometric factors.

Background: Organ measurements derived from magnetic resonance imaging (MRI) have the potential to enhance our understanding of the precise phenotypic variations underlying many clinical conditions.

Methods: We applied morphometric methods to study the kidneys by constructing surface meshes from kidney segmentations from abdominal MRI data in 38,868 participants in the UK Biobank. Using mesh-based analysis techniques based on statistical parametric maps (SPMs), we were able to detect variations in specific regions of the kidney and associate those with anthropometric traits as well as disease states including chronic kidney disease (CKD), type-2 diabetes (T2D), and hypertension.

Near-Infrared Light Exposure Triggers ROS to Downregulate Inflammatory Cytokines Induced by SARS-CoV-2 Spike Protein in Human Cell Culture.

The leading cause of mortality from SARS-CoV-2 is an exaggerated host immune response, triggering cytokine storms, multiple organ failure and death. Current drug- and vaccine-based therapies are of limited efficacy against novel viral variants. Infrared therapy is a non-invasive and safe method that has proven effective against inflammatory conditions for over 100 years.

Non-chemical signalling between mitochondria.

A wide variety of studies have reported some form of non-chemical or non-aqueous communication between physically isolated organisms, eliciting changes in cellular proliferation, morphology, and/or metabolism. The sources and mechanisms of such signalling pathways are still unknown, but have been postulated to involve vibration, volatile transmission, or light through the phenomenon of ultraweak photon emission. Here, we report non-chemical communication between isolated mitochondria from MCF7 (cancer) and MCF10A (non-cancer) cell lines.

Informing the Cannabis Conjecture: From Life's Beginnings to Mitochondria, Membranes and the Electrome-A Review.

Before the late 1980s, ideas around how the lipophilic phytocannabinoids might be working involved membranes and bioenergetics as these disciplines were "in vogue". However, as interest in genetics and pharmacology grew, interest in mitochondria (and membranes) waned. The discovery of the cognate receptor for tetrahydrocannabinol (THC) led to the classification of the endocannabinoid system (ECS) and the conjecture that phytocannabinoids might be "working" through this system.

Diet-induced Weight Loss and Phenotypic Flexibility Among Healthy Overweight Adults: A Randomized Trial.

Background: The capacity of an individual to respond to changes in food intake so that postprandial metabolic perturbations are resolved, and metabolism returns to its pre-prandial state, is called phenotypic flexibility. This ability may be a more important indicator of current health status than metabolic markers in a fasting state.

Aim: In this parallel randomized controlled trial study, an energy-restricted healthy diet and 2 dietary challenges were used to assess the effect of weight loss on phenotypic flexibility.

Abdominal imaging associates body composition with COVID-19 severity.

The main drivers of COVID-19 disease severity and the impact of COVID-19 on long-term health after recovery are yet to be fully understood. Medical imaging studies investigating COVID-19 to date have mostly been limited to small datasets and post-hoc analyses of severe cases. The UK Biobank recruited recovered SARS-CoV-2 positive individuals (n = 967) and matched controls (n = 913) who were extensively imaged prior to the pandemic and underwent follow-up scanning.

Artifact-free fat-water separation in Dixon MRI using deep learning.

Unlabelled: Chemical-shift encoded MRI (CSE-MRI) is a widely used technique for the study of body composition and metabolic disorders, where derived fat and water signals enable the quantification of adipose tissue and muscle. The UK Biobank is acquiring whole-body Dixon MRI (a specific implementation of CSE-MRI) for over 100,000 participants. Current processing methods associated with large whole-body volumes are time intensive and prone to artifacts during fat-water separation performed by the scanner, making quantitative analysis challenging.

Bioelectric Fields at the Beginnings of Life.

The consensus on the origins of life is that it involved organization of prebiotic chemicals according to the underlying principles of thermodynamics to dissipate energy derived from photochemical and/or geochemical sources. Leading theories tend to be chemistry-centric, revolving around either metabolism or information-containing polymers first. However, experimental data also suggest that bioelectricity and quantum effects play an important role in biology, which might suggest that a further factor is required to explain how life began.

Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium.

Understanding Long COVID; Mitochondrial Health and Adaptation-Old Pathways, New Problems.

Many people infected with the SARS-CoV-2 suffer long-term symptoms, such as "brain fog", fatigue and clotting problems. Explanations for "long COVID" include immune imbalance, incomplete viral clearance and potentially, mitochondrial dysfunction. As conditions with sub-optimal mitochondrial function are associated with initial severity of the disease, their prior health could be key in resistance to long COVID and recovery.

Quantifying the contribution of triglycerides to metabolic resilience through the mixed meal model.

Despite the pivotal role played by elevated circulating triglyceride levels in the pathophysiology of cardio-metabolic diseases many of the indices used to quantify metabolic health focus on deviations in glucose and insulin alone. We present the Mixed Meal Model, a computational model describing the systemic interplay between triglycerides, free fatty acids, glucose, and insulin. We show that the Mixed Meal Model can capture deviations in the post-meal excursions of plasma glucose, insulin, and triglyceride that are indicative of features of metabolic resilience; quantifying insulin resistance and liver fat; validated by comparison to gold-standard measures.

Improving the accuracy of fatty liver index to reflect liver fat content with predictive regression modelling.

Background: The fatty liver index (FLI) is frequently used as a non-invasive clinical marker for research, prognostic and diagnostic purposes. It is also used to stratify individuals with hepatic steatosis such as non-alcoholic fatty liver disease (NAFLD), and to detect the presence of type 2 diabetes or cardiovascular disease. The FLI is calculated using a combination of anthropometric and blood biochemical variables; however, it reportedly excludes 8.