Publications by authors named "Caiment F"

Article Synopsis
  • Gene expression biomarkers can help identify both genotoxic and non-genotoxic carcinogens, which could reduce the need for animal testing.
  • In August 2022, a workshop reviewed current methods for using transcriptomic profiling to detect genotoxic chemicals, examining 1341 papers to find reliable biomarkers.
  • The analysis identified two promising in vivo biomarkers and three in vitro biomarkers that show over 92% predictive accuracy and can be adapted for various testing conditions, with support from workshop participants for their regulatory adoption.
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As a part of the International Workshop on Genotoxicity Testing (IWGT) in 2022, a workgroup was formed to evaluate the level of validation and regulatory acceptance of transcriptomic biomarkers that identify genotoxic substances. Several such biomarkers have been developed using various molecular techniques and computational approaches. Within the IWGT workgroup on transcriptomic biomarkers, bioinformatics was a central topic of discussion, focusing on the current approaches used to process the underlying molecular data to distill a reliable predictive signal; that is, a gene set that is indicative of genotoxicity and can then be used in later studies to predict potential DNA damaging properties for uncharacterized chemicals.

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  • MASLD is often asymptomatic and underdiagnosed, creating a need for non-invasive diagnostic tools to assess liver fat.
  • The study identified and validated specific miRNAs from liver and serum samples that correlate with liver steatosis, using techniques like miRNA sequencing and RT-qPCR.
  • A predictive model was developed using five key miRNAs, demonstrating a low error rate for estimating hepatic steatosis, making it a practical and cost-effective diagnostic method.
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Recent advances in cancer therapy have substantially increased survival rates among patients, yet the prolonged effect of current treatment regimens with anthracyclines (ACs) often include severe long-term complications, notably in the form of anthracycline-induced cardiotoxicity (AIC). Despite known associations between AC treatment and AIC, a comprehensive understanding of the underlying molecular pathways remains elusive. This gap is highlighted by the scarcity of reliable therapeutic interventions, with dexrazoxane being the sole FDA-approved drug to mitigate AIC risks.

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Introduction: Endocrine disruptors are compounds of manmade origin able to interfere with the endocrine system and constitute an important environmental concern. Indeed, detrimental effects on thyroid physiology and functioning have been described. Differences exist in the susceptibility of human sexes to the incidence of thyroid disorders, like autoimmune diseases or cancer.

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  • Parkinson's disease (PD) is a complicated brain disorder that can be affected by genes and environmental things like chemicals.
  • The study looked at how a chemical called PCB-180, which can harm brain cells, impacts specific types of brain cells called dopaminergic neurons.
  • Researchers discovered that PCB exposure changes important brain functions and links to other harmful substances, suggesting that PCBs might play a role in diseases like Parkinson's.
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The blood-brain barrier consists of tightly connected endothelial cells protecting the brain's microenvironment from the periphery. These endothelial cells are characterized by specific tight junction proteins such as Claudin-5 and Occludin, forming the endothelial barrier. Disrupting these cells might lead to blood-brain barrier dysfunction.

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Article Synopsis
  • Biomedicine research utilizes high-throughput technologies to analyze large datasets, and pathway analysis helps in understanding how experimental conditions affect biological pathways through statistical methods.
  • The study presents a new variable selection method called cluster PLS (c-PLS) that evaluates the collective impact of biologically relevant variable groups on model performance using datasets from liver tissue biopsies.
  • c-PLS enhances the analysis of biological processes by focusing on interrelated variable clusters, improving predictive understanding and prioritizing factors that influence model outcomes.
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Diet is an important determinant of overall health, and has been linked to the risk of various cancers. To understand the mechanisms involved, transcriptomic responses from human intervention studies are very informative. However, gene expression analysis of human biopsy material only represents the average profile of a mixture of cell types that can mask more subtle, but relevant cell-specific changes.

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Introduction: Phthalates are a class of endocrine-disrupting chemicals that have been shown to negatively correlate with thyroid hormone serum levels in humans and to cause a state of hyperactivity in the thyroid. However, their mechanism of action is not well described at the molecular level.

Methods: We analyzed the response of mouse thyroid organoids to the exposure to a biologically relevant dose range of the phthalates bis(2-ethylhexyl) phthalate (DEHP), di-iso-decylphthalate (DIDP), di-iso-nonylphthalate (DINP), and di-n-octylphthalate (DnOP) for 24 h and simultaneously analyzed mRNA and miRNA expression via RNA sequencing.

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Cerebral small vessel disease is characterised by decreased cerebral blood flow and blood-brain barrier impairments which play a key role in the development of white matter lesions. We hypothesised that cerebral hypoperfusion causes local hypoxia, affecting oligodendrocyte precursor cell-endothelial cell signalling leading to blood-brain barrier dysfunction as an early mechanism for the development of white matter lesions. Bilateral carotid artery stenosis was used as a mouse model for cerebral hypoperfusion.

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In a joint effort involving scientists from academia, industry and regulatory agencies, ECETOC's activities in Omics have led to conceptual proposals for: (1) A framework that assures data quality for reporting and inclusion of Omics data in regulatory assessments; and (2) an approach to robustly quantify these data, prior to interpretation for regulatory use. In continuation of these activities this workshop explored and identified areas of need to facilitate robust interpretation of such data in the context of deriving points of departure (POD) for risk assessment and determining an adverse change from normal variation. ECETOC was amongst the first to systematically explore the application of Omics methods, now incorporated into the group of methods known as New Approach Methodologies (NAMs), to regulatory toxicology.

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Motivation: Long-read transcriptome sequencing (LRTS) has the potential to enhance our understanding of alternative splicing and the complexity of this process requires the use of versatile computational tools, with the ability to accommodate various stages of the workflow with maximum flexibility.

Results: We introduce IsoTools, a Python-based LRTS analysis framework that offers a wide range of functionality for transcriptome reconstruction and quantification of transcripts. Furthermore, we integrate a graph-based method for identifying alternative splicing events and a statistical approach based on the beta-binomial distribution for detecting differential events.

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Introduction: Cancer cachexia, highly prevalent in lung cancer, is a debilitating syndrome characterized by involuntary loss of skeletal muscle mass and is associated with poor clinical outcome, decreased survival and negative impact on tumour therapy. Various lung tumour-bearing animal models have been used to explore underlying mechanisms of cancer cachexia. However, these models do not simulate anatomical and immunological features key to lung cancer and associated muscle wasting.

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Thyroid is a glandular tissue in the human body in which the function can be severely affected by endocrine disrupting chemicals (EDCs). Current in vitro assays to test endocrine disruption by chemical compounds are largely based on 2D thyroid cell cultures, which often fail to precisely evaluate the safety of these compounds. New and more advanced 3D cell culture systems are urgently needed to better recapitulate the thyroid follicular architecture and functions and help to improve the predictive power of such assays.

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The analysis of the combined mRNA and miRNA content of a biological sample can be of interest for answering several research questions, like biomarkers discovery, or mRNA-miRNA interactions. However, the process is costly and time-consuming, separate libraries need to be prepared and sequenced on different flowcells. Combo-Seq is a library prep kit that allows us to prepare combined mRNA-miRNA libraries starting from very low total RNA.

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The data currently described was generated within the EU/FP7 HeCaToS project (Hepatic and Cardiac Toxicity Systems modeling). The project aimed to develop an in silico prediction system to contribute to drug safety assessment for humans. For this purpose, multi-omics data of repeated dose toxicity were obtained for 10 hepatotoxic and 10 cardiotoxic compounds.

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Anthracycline-induced cardiotoxicity is the most severe collateral effect of chemotherapy originated by an excess of oxidative stress in cardiomyocytes that leads to cardiac dysfunction. We assessed clinical data from patients with breast cancer receiving anthracyclines and searched for discriminating microRNAs between patients that developed cardiotoxicity (cases) and those that did not (controls), using RNA sequencing and regression analysis. Serum levels of 25 microRNAs were differentially expressed in cases versus controls within the first year after anthracycline treatment, as assessed by three different regression models (elastic net, Robinson and Smyth exact negative binomial test and random forest).

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Non-alcoholic fatty liver disease (NAFLD) is the most prevalent form of chronic liver disease worldwide, but a reliable non-invasive method to quantify liver steatosis in primary healthcare is not available. Circulating microRNAs have been proposed as biomarkers of severe/advanced NAFLD (steatohepatitis and fibrosis). However, the use of circulating miRNAs to quantitatively assess the % of liver fat in suspected NAFLD patients has not been investigated.

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Parkinson's disease (PD) is a progressive, neurodegenerative disease affecting over 1% of the population beyond 65 years of age. Although some PD cases are inheritable, the majority of PD cases occur in a sporadic manner. Risk factors comprise next to heredity, age, and gender also exposure to neurotoxins from for instance pesticides and herbicides.

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Proteins are often considered the main biological element in charge of the different functions and structures of a cell. However, proteomics, the global study of all expressed proteins, often performed by mass spectrometry, is limited by its stochastic sampling and can only quantify a limited amount of protein per sample. Transcriptomics, which allows an exhaustive analysis of all expressed transcripts, is often used as a surrogate.

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Despite the widespread use of transcriptomics technologies in toxicology research, acceptance of the data by regulatory agencies to support the hazard assessment is still limited. Fundamental issues contributing to this are the lack of reproducibility in transcriptomics data analysis arising from variance in the methods used to generate data and differences in the data processing. While research applications are flexible in the way the data are generated and interpreted, this is not the case for regulatory applications where an unambiguous answer, possibly later subject to legal scrutiny, is required.

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Alzheimer's disease (AD) is the most common cause of dementia, characterized by the progressive impairment of cognition and memory loss. Sporadic AD (sAD) represents approximately 95 % of the AD cases and is induced by a complex interplay between genetic and environmental factors called "Alzheimerogens". Heavy metals (e.

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Individuals with hepatic steatosis often display several metabolic abnormalities including insulin resistance and muscle atrophy. Previously, we found that hepatic steatosis results in an altered hepatokine secretion profile, thereby inducing skeletal muscle insulin resistance inter-organ crosstalk. In this study, we aimed to investigate whether the altered secretion profile in the state of hepatic steatosis also induces skeletal muscle atrophy effects on muscle protein turnover.

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