Molecular signatures associated with venous thromboembolism in children with acute lymphoblastic leukemia.

Background: Venous thromboembolism (VTE) is a frequent complication of childhood acute lymphoblastic leukemia (ALL).

Objectives: We aimed to identify molecular markers and signatures of leukemia microenvironment associated with VTE in childhood ALL, by dual-omics approach of gene expression (GEP) and DNA-methylation profiling.

Patients/methods: Eligible children were aged 1-21 years old with newly diagnosed ALL enrolled on the Dana Farber Cancer Institute 16-001 trial with available RNA sequencing data from bone marrow at diagnosis.

Acquired thrombotic thrombocytopenic purpura of unidentified pathophysiology in patients with severe disease: completing the landscape of thrombotic thrombocytopenic purpura.

Not available.

ProPickML: Advancing Clinical Diagnostics with Automated Peak Picking in Label-Free Targeted Proteomics.

In targeted proteomics utilizing Selected Reaction Monitoring (SRM), the precise detection of specific peptides within complex mixtures remains a significant challenge, particularly due to noise and interference in chromatograms. Existing methodologies, such as isotopic labeling and scoring algorithms, offer partial solutions but are constrained by high run times and elevated false discovery rates. To address these limitations, we have developed ProPickML a machine learning-based tool designed to accurately identify peptide peaks across diverse data sets, independent of the assumed presence of the peptide.

LC-SRM Combined With Machine Learning Enables Fast Identification and Quantification of Bacterial Pathogens in Urinary Tract Infections.

Urinary tract infections (UTIs) are a worldwide health problem. Fast and accurate detection of bacterial infection is essential to provide appropriate antibiotherapy to patients and to avoid the emergence of drug-resistant pathogens. While the gold standard requires 24 h to 48 h of bacteria culture prior to MALDI-TOF species identification, we propose a culture-free workflow, enabling bacterial identification and quantification in less than 4 h using 1 ml of urine.

Methotrexate versus conventional disease-modifying antirheumatic drugs in the treatment of non-anterior sarcoidosis-associated uveitis.

Aims: To compare the safety and efficacy of methotrexate (MTX), mycophenolate mofetil (MMF) and azathioprine (AZA) in non-anterior sarcoidosis-associated uveitis.

Methods: Retrospective study including non-anterior sarcoidosis-associated uveitis according to the revised International Workshop on Ocular Sarcoidosis criteria. The primary outcome was defined as the median time to relapse or occurrence of serious adverse events leading to treatment discontinuation.

Optimizing hybrid ensemble feature selection strategies for transcriptomic biomarker discovery in complex diseases.

Biomedical research takes advantage of omic data, such as transcriptomics, to unravel the complexity of diseases. A conventional strategy identifies transcriptomic biomarkers characterized by expression patterns associated with a phenotype by relying on feature selection approaches. Hybrid ensemble feature selection (HEFS) has become increasingly popular as it ensures robustness of the selected features by performing data and functional perturbations.

Target repositioning using multi-layer networks and machine learning: The case of prostate cancer.

The discovery of novel therapeutic targets, defined as proteins which drugs can interact with to induce therapeutic benefits, typically represent the first and most important step of drug discovery. One solution for target discovery is target repositioning, a strategy which relies on the repurposing of known targets for new diseases, leading to new treatments, less side effects and potential drug synergies. Biological networks have emerged as powerful tools for integrating heterogeneous data and facilitating the prediction of biological or therapeutic properties.

A Machine Learning Approach to Identify Key Residues Involved in Protein-Protein Interactions Exemplified with SARS-CoV-2 Variants.

Human infection with the coronavirus disease 2019 (COVID-19) is mediated by the binding of the spike protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the human angiotensin-converting enzyme 2 (ACE2). The frequent mutations in the receptor-binding domain (RBD) of the spike protein induced the emergence of variants with increased contagion and can hinder vaccine efficiency. Hence, it is crucial to better understand the binding mechanisms of variant RBDs to human ACE2 and develop efficient methods to characterize this interaction.

3D microscopic reconstruction of pearls using combined optical microscopy and photogrammetry.

In this study, we introduce an affordable and accessible method that combines optical microscopy and photogrammetry to reconstruct 3D models of Tahitian pearls. We present a novel device designed for acquiring microscopic images around a sphere using translational displacement stages and outline our method for reconstructing these images. We successfully created 3D models of two individual pearl rings, each representing 6.

Combined transcriptomics and proteomics unveil the impact of vitamin C in modulating specific protein abundance in the mouse liver.

Background: Vitamin C (ascorbate) is a water-soluble antioxidant and an important cofactor for various biosynthetic and regulatory enzymes. Mice can synthesize vitamin C thanks to the key enzyme gulonolactone oxidase (Gulo) unlike humans. In the current investigation, we used Gulo mice, which cannot synthesize their own ascorbate to determine the impact of this vitamin on both the transcriptomics and proteomics profiles in the whole liver.

BERNN: Enhancing classification of Liquid Chromatography Mass Spectrometry data with batch effect removal neural networks.

Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful method for profiling complex biological samples. However, batch effects typically arise from differences in sample processing protocols, experimental conditions, and data acquisition techniques, significantly impacting the interpretability of results. Correcting batch effects is crucial for the reproducibility of omics research, but current methods are not optimal for the removal of batch effects without compressing the genuine biological variation under study.

SARS-CoV-2 infection modifies the transcriptome of the megakaryocytes in the bone marrow.

Megakaryocytes (MKs), integral to platelet production, predominantly reside in the bone marrow (BM) and undergo regulated fragmentation within sinusoid vessels to release platelets into the bloodstream. Inflammatory states and infections influence MK transcription, potentially affecting platelet functionality. Notably, COVID-19 has been associated with altered platelet transcriptomes.

DENTALMODELSEG: FULLY AUTOMATED SEGMENTATION OF UPPER AND LOWER 3D INTRA-ORAL SURFACES.

In this paper, we present a deep learning-based method for surface segmentation. This technique consists of acquiring 2D views and extracting features from the surface such as the normal vectors. The rendered images are analyzed with a 2D convolutional neural network, such as a UNET.

Potential efficacy of T and B lymphocyte-targeted therapies on articular involvement of patients with rheumatoid arthritis and systemic sclerosis overlap syndrome. Results from a 2-centre series of 19 cases.

Objectives: To analyse in routine practice the efficacy of targeted therapies on joint involvement of patients with rheumatoid arthritis/systemic sclerosis (RA/SSc) overlap syndrome.

Methods: This was a retrospective analysis of medical records of two academic centres over a 10-year period. Joint response to targeted therapies was measured according to EULAR criteria based on Disease Activity Score (DAS)-28.

Structural interhemispheric connectivity defects in mouse models of BBSOAS: Insights from high spatial resolution 3D white matter tractography.

White matter (WM) tract formation and axonal pathfinding are major processes in brain development allowing to establish precise connections between targeted structures. Disruptions in axon pathfinding and connectivity impairments will lead to neural circuitry abnormalities, often associated with various neurodevelopmental disorders (NDDs). Among several neuroimaging methodologies, Diffusion Tensor Imaging (DTI) is a magnetic resonance imaging (MRI) technique that has the advantage of visualizing in 3D the WM tractography of the whole brain non-invasively.

Judgments of relevance in preschoolers: a study of training and transfer of self-cueing strategies.

Introduction: When facing a task, children must analyze it precisely to fully identify what its goal is. This is particularly difficult for young children, who mainly rely on environmental cues to get there. Research suggests that training children to look for the most relevant perceptual cues is promising.

SlicerSALT: From Medical Images to Quantitative Insights of Anatomy.

Three-dimensional (3D) shape lies at the core of understanding the physical objects that surround us. In the biomedical field, shape analysis has been shown to be powerful in quantifying how anatomy changes with time and disease. The Shape AnaLysis Toolbox (SALT) was created as a vehicle for disseminating advanced shape methodology as an open source, free, and comprehensive software tool.

BioDiscViz: A visualization support and consensus signature selector for BioDiscML results.

Machine learning (ML) algorithms are powerful tools to find complex patterns and biomarker signatures when conventional statistical methods fail to identify them. While the ML field made significant progress, state of the art methodologies to build efficient and non-overfitting models are not always applied in the literature. To this purpose, automatic programs, such as BioDiscML, were designed to identify biomarker signatures and correlated features while escaping overfitting using multiple evaluation strategies, such as cross validation, bootstrapping and repeated holdout.

Predictive model for vitamin C levels in hyperinsulinemic individuals based on age, sex, waist circumference, low-density lipoprotein, and immune-associated serum proteins.

Vitamin C (ascorbic acid) is an important water-soluble antioxidant associated with decreased oxidative stress in type 2 diabetes (T2D) patients. A previous targeted plasma proteomic study has indicated that ascorbic acid is associated with markers of the immune system in healthy subjects. However, the association between the levels of ascorbic acid and blood biomarkers in subjects at risk of developing T2D is still unknown.

Impact of automatic tools for detecting new lesions on therapeutic strategies offered to patients with MS by neurologists.

Background: Automatic tools for detecting new lesions in patients with MS between two MRI scans are now available to clinicians. They have been assessed from the radiologist's point of view, but their impact on the therapeutic strategies that neurologists offer their patients has not yet been documented.

Objectives: To compare neurologist's decisions according to whether a lesion detection support system had been used and describe variability between neurologists on decision-making for the same clinical cases.

Developing a cluster-based approach for deciphering complexity in individuals with neurodevelopmental differences.

Objective: Individuals with neurodevelopmental disorders such as global developmental delay (GDD) present both genotypic and phenotypic heterogeneity. This diversity has hampered developing of targeted interventions given the relative rarity of each individual genetic etiology. Novel approaches to clinical trials where distinct, but related diseases can be treated by a common drug, known as basket trials, which have shown benefits in oncology but have yet to be used in GDD.