Technical feasibility of automated blur detection in digital mammography using convolutional neural network.

Background: The presence of a blurred area, depending on its localization, in a mammogram can limit diagnostic accuracy. The goal of this study was to develop a model for automatic detection of blur in diagnostically relevant locations in digital mammography.

Methods: A retrospective dataset consisting of 152 examinations acquired with mammography machines from three different vendors was utilized.

Restoring the Multiple Sclerosis Associated Imbalance of Gut Indole Metabolites Promotes Remyelination and Suppresses Neuroinflammation.

In multiple sclerosis (MS) the circulating metabolome is dysregulated, with indole lactate (ILA) being one of the most significantly reduced metabolites. We demonstrate that oral supplementation of ILA impacts key MS disease processes in two preclinical models. ILA reduces neuroinflammation by dampening immune cell activation/ infiltration; and promotes remyelination and oligodendrocyte differentiation through the aryl hydrocarbon receptor (AhR).

Distinct plasma lipids predict axonal injury and multiple sclerosis activity.

Background: Lipids are of particular interest for the study of neuroinjury and neuroinflammation as structural lipids are major components of myelin, and a variety of lipid species modulate inflammation. In this study, we performed an in-depth lipidomics analysis to identify lipids associated with injury and disease activity.

Methods: Plasma samples were collected from paediatric-onset multiple sclerosis (MS) cases within 4 years of disease onset from 17 sites.

Peripheral inflammation is associated with brain atrophy and cognitive decline linked to mild cognitive impairment and Alzheimer's disease.

Inflammation is an important factor in Alzheimer's disease (AD). An NMR measurement in plasma, glycoprotein acetyls (GlycA), captures the overall level of protein production and glycosylation implicated in systemic inflammation. With its additional advantage of reducing biological variability, GlycA might be useful in monitoring the relationship between peripheral inflammation and brain changes relevant to AD.

ABCA1 and apoA-I dependent 12-hydroxyeicosatetraenoic acid efflux regulates macrophage inflammatory signaling.

Aberrant high-density lipoprotein (HDL) function is implicated in inflammation-associated pathologies. While HDL ABCA1-mediated reverse cholesterol and phospholipid transport are well described, the movement of pro-/anti-inflammatory lipids has not been explored. HDL phospholipids are the largest reservoir of circulating arachidonic acid-derived oxylipins.

Explainable Precision Medicine in Breast MRI: A Combined Radiomics and Deep Learning Approach for the Classification of Contrast Agent Uptake.

In DCE-MRI, the degree of contrast uptake in normal fibroglandular tissue, i.e., background parenchymal enhancement (BPE), is a crucial biomarker linked to breast cancer risk and treatment outcome.

Automatic Detection of Post-Operative Clips in Mammography Using a U-Net Convolutional Neural Network.

Background: After breast conserving surgery (BCS), surgical clips indicate the tumor bed and, thereby, the most probable area for tumor relapse. The aim of this study was to investigate whether a U-Net-based deep convolutional neural network (dCNN) may be used to detect surgical clips in follow-up mammograms after BCS.

Methods: 884 mammograms and 517 tomosynthetic images depicting surgical clips and calcifications were manually segmented and classified.

Serum Bile Acids Improve Prediction of Alzheimer's Progression in a Sex-Dependent Manner.

Sex disparities in serum bile acid (BA) levels and Alzheimer's disease (AD) prevalence have been established. However, the precise link between changes in serum BAs and AD development remains elusive. Here, authors quantitatively determined 33 serum BAs and 58 BA features in 4 219 samples collected from 1 180 participants from the Alzheimer's Disease Neuroimaging Initiative.

Oxylipin transport by lipoprotein particles and its functional implications for cardiometabolic and neurological disorders.

Lipoprotein metabolism is critical to inflammation. While the periphery and central nervous system (CNS) have separate yet connected lipoprotein systems, impaired lipoprotein metabolism is implicated in both cardiometabolic and neurological disorders. Despite the substantial investigation into the composition, structure and function of lipoproteins, the lipoprotein oxylipin profiles, their influence on lipoprotein functions, and their potential biological implications are unclear.

Generalizable attention U-Net for segmentation of fibroglandular tissue and background parenchymal enhancement in breast DCE-MRI.

Objectives: Development of automated segmentation models enabling standardized volumetric quantification of fibroglandular tissue (FGT) from native volumes and background parenchymal enhancement (BPE) from subtraction volumes of dynamic contrast-enhanced breast MRI. Subsequent assessment of the developed models in the context of FGT and BPE Breast Imaging Reporting and Data System (BI-RADS)-compliant classification.

Methods: For the training and validation of attention U-Net models, data coming from a single 3.

Tai Chi exercise reduces circulating levels of inflammatory oxylipins in postmenopausal women with knee osteoarthritis: results from a pilot study.

Background: Tai Chi (TC) controls pain through mind-body exercise and appears to alter inflammatory mediators. TC actions on lipid biomarkers associated with inflammation and brain neural networks in women with knee osteoarthritic pain were investigated.

Methods: A single-center, pre- and post-TC group (baseline and 8 wk) exercise pilot study in postmenopausal women with knee osteoarthritic pain was performed.

Integration of plasma and CSF metabolomics with CSF proteomic reveals novel associations between lipid mediators and central nervous system vascular and energy metabolism.

Integration of the omics data, including metabolomics and proteomics, provides a unique opportunity to search for new associations within metabolic disorders, including Alzheimer's disease. Using metabolomics, we have previously profiled oxylipins, endocannabinoids, bile acids, and steroids in 293 CSF and 202 matched plasma samples from AD cases and healthy controls and identified both central and peripheral markers of AD pathology within inflammation-regulating cytochrome p450/soluble epoxide hydrolase pathway. Additionally, using proteomics, we have identified five cerebrospinal fluid protein panels, involved in the regulation of energy metabolism, vasculature, myelin/oligodendrocyte, glia/inflammation, and synapses/neurons, affected in AD, and reflective of AD-related changes in the brain.

Diet high in linoleic acid dysregulates the intestinal endocannabinoid system and increases susceptibility to colitis in Mice.

Inflammatory bowel disease (IBD) is a multifactorial disease with increasing incidence in the U.S. suggesting that environmental factors, including diet, are involved.

Automatic and standardized quality assurance of digital mammography and tomosynthesis with deep convolutional neural networks.

Objectives: The aim of this study was to develop and validate a commercially available AI platform for the automatic determination of image quality in mammography and tomosynthesis considering a standardized set of features.

Materials And Methods: In this retrospective study, 11,733 mammograms and synthetic 2D reconstructions from tomosynthesis of 4200 patients from two institutions were analyzed by assessing the presence of seven features which impact image quality in regard to breast positioning. Deep learning was applied to train five dCNN models on features detecting the presence of anatomical landmarks and three dCNN models for localization features.

Several serum lipid metabolites are associated with relapse risk in pediatric-onset multiple sclerosis.

Background: The circulating metabolome is altered in multiple sclerosis (MS), but its prognostic capabilities have not been extensively explored. Lipid metabolites might be of particular interest due to their multiple roles in the brain, as they can serve as structural components, energy sources, and bioactive molecules. Gaining a deeper understanding of the disease may be possible by examining the lipid metabolism in the periphery, which serves as the primary source of lipids for the brain.

Diagnostic accuracy of automated ACR BI-RADS breast density classification using deep convolutional neural networks.

Objectives: High breast density is a well-known risk factor for breast cancer. This study aimed to develop and adapt two (MLO, CC) deep convolutional neural networks (DCNN) for automatic breast density classification on synthetic 2D tomosynthesis reconstructions.

Methods: In total, 4605 synthetic 2D images (1665 patients, age: 57 ± 37 years) were labeled according to the ACR (American College of Radiology) density (A-D).

Detection of microcalcifications in photon-counting dedicated breast-CT using a deep convolutional neural network: Proof of principle.

Objective: In this study, we investigate the feasibility of a deep Convolutional Neural Network (dCNN), trained with mammographic images, to detect and classify microcalcifications (MC) in breast-CT (BCT) images.

Methods: This retrospective single-center study was approved by the local ethics committee. 3518 icons generated from 319 mammograms were classified into three classes: "no MC" (1121), "probably benign MC" (1332), and "suspicious MC" (1065).

Metabolite patterns associated with individual response to supervised exercise therapy in patients with intermittent claudication.

Objective: Supervised exercise therapy (SET) is the first line treatment for intermittent claudication owing to peripheral arterial disease. Despite multiple randomized controlled trials proving the efficacy of SET, there are large differences in individual patient's responses. We used plasma metabolomics to identify potential metabolic influences on the individual response to SET.

Potential Cardioprotective Effects and Lipid Mediator Differences in Long-Chain Omega-3 Polyunsaturated Fatty Acid Supplemented Mice Given Chemotherapy.

Many commonly used chemotherapies induce mitochondrial dysfunction in cardiac muscle, which leads to cardiotoxicity and heart failure later in life. Dietary long-chain omega-3 polyunsaturated fatty acids (LC n-3 PUFA) have demonstrated cardioprotective function in non-chemotherapy models of heart failure, potentially through the formation of LC n-3 PUFA-derived bioactive lipid metabolites. However, it is unknown whether dietary supplementation with LC n-3 PUFA can protect against chemotherapy-induced cardiotoxicity.

Blood Levels of Endocannabinoids, Oxylipins, and Metabolites Are Altered in Hemodialysis Patients.

Hemodialysis patients (HDPs) have higher blood pressure, higher levels of inflammation, a higher risk of cardiovascular disease, and unusually low plasma n-3 polyunsaturated fatty acid (PUFA) levels compared to healthy subjects. The objective of our investigation was to examine the levels of endocannabinoids (eCBs) and oxylipins (OxLs) in female HDPs compared to healthy matched female controls, with the underlying hypothesis that differences in specific PUFA levels in hemodialysis patients would result in changes in eCBs and OxLs. Plasma phospholipid fatty acids were analyzed by gas chromatography.

Linoleate-Rich Safflower Oil Diet Increases Linoleate-Derived Bioactive Lipid Mediators in Plasma, and Brown and White Adipose Depots of Healthy Mice.

Polyunsaturated fats are energy substrates and precursors to the biosynthesis of lipid mediators of cellular processes. Adipose tissue not only provides energy storage, but influences whole-body energy metabolism through endocrine functions. How diet influences adipose-lipid mediator balance may have broad impacts on energy metabolism.

BI-RADS-Based Classification of Mammographic Soft Tissue Opacities Using a Deep Convolutional Neural Network.

The aim of this study was to investigate the potential of a machine learning algorithm to classify breast cancer solely by the presence of soft tissue opacities in mammograms, independent of other morphological features, using a deep convolutional neural network (dCNN). Soft tissue opacities were classified based on their radiological appearance using the ACR BI-RADS atlas. We included 1744 mammograms from 438 patients to create 7242 icons by manual labeling.

Radiomics in photon-counting dedicated breast CT: potential of texture analysis for breast density classification.

Background: We investigated whether features derived from texture analysis (TA) can distinguish breast density (BD) in spiral photon-counting breast computed tomography (PC-BCT).

Methods: In this retrospective single-centre study, we analysed 10,000 images from 400 PC-BCT examinations of 200 patients. Images were categorised into four-level density scale (a-d) using Breast Imaging Reporting and Data System (BI-RADS)-like criteria.

Lipoxins reduce obesity-induced adipose tissue inflammation in 3D-cultured human adipocytes and explant cultures.

Adipose tissue inflammation drives obesity-related cardiometabolic diseases. Enhancing endogenous resolution mechanisms through administration of lipoxin A, a specialized pro-resolving lipid mediator, was shown to reduce adipose inflammation and subsequently protects against obesity-induced systemic disease in mice. Here, we demonstrate that lipoxins reduce inflammation in 3D-cultured human adipocytes and adipose tissue explants from obese patients.

Detecting Abnormal Axillary Lymph Nodes on Mammograms Using a Deep Convolutional Neural Network.

The purpose of this study was to determine the feasibility of a deep convolutional neural network (dCNN) to accurately detect abnormal axillary lymph nodes on mammograms. In this retrospective study, 107 mammographic images in mediolateral oblique projection from 74 patients were labeled to three classes: (1) "breast tissue", (2) "benign lymph nodes", and (3) "suspicious lymph nodes". Following data preprocessing, a dCNN model was trained and validated with 5385 images.