Unfolding and de-confounding: biologically meaningful causal inference from longitudinal multi-omic networks using METALICA.

Unlabelled: A key challenge in the analysis of microbiome data is the integration of multi-omic datasets and the discovery of interactions between microbial taxa, their expressed genes, and the metabolites they consume and/or produce. In an effort to improve the state of the art in inferring biologically meaningful multi-omic interactions, we sought to address some of the most fundamental issues in causal inference from longitudinal multi-omics microbiome data sets. We developed METALICA, a suite of tools and techniques that can infer interactions between microbiome entities.

Unfolding and De-confounding: Biologically meaningful causal inference from longitudinal multi-omic networks using METALICA.

A key challenge in the analysis of microbiome data is the integration of multi-omic datasets and the discovery of interactions between microbial taxa, their expressed genes, and the metabolites they consume and/or produce. In an effort to improve the state-of-the-art in inferring biologically meaningful multi-omic interactions, we sought to address some of the most fundamental issues in causal inference from longitudinal multi-omics microbiome data sets. We developed METALICA, a suite of tools and techniques that can infer interactions between microbiome entities.

Microbiome maps: Hilbert curve visualizations of metagenomic profiles.

Abundance profiles from metagenomic sequencing data synthesize information from billions of sequenced reads coming from thousands of microbial genomes. Analyzing and understanding these profiles can be a challenge since the data they represent are complex. Particularly challenging is their visualization, as existing techniques are inadequate when the taxa number is in the thousands.

The Case for Modernizing Biomedical Research in Ireland through the Creation of an Irish 3Rs Centre.

Since its publication, the 3Rs principle has provided a cornerstone for more ethical and humane biomedical and regulatory research. In Europe, the 3Rs principle has been incorporated into the European Directive 63/2010/EU, with the ultimate aim of fully replacing the procedures on live animals for scientific and educational purposes as soon as it is scientifically possible to do so. Thus, a critical shift in the discussion on animal use in biomedical and regulatory research is undergoing in Europe, a discussion where satisfying the "replacement" principle is becoming more and more defined as a scientific rather than ethical need.

Effect of metronidazole on vaginal microbiota associated with asymptomatic bacterial vaginosis.

Vaginal dysbiosis-induced by an overgrowth of anaerobic bacteria is referred to as bacterial vaginosis (BV). The dysbiosis is associated with an increased risk for acquisition of sexually transmitted infections. Women with symptomatic BV are treated with oral metronidazole (MET), but its effectiveness remains to be elucidated.

Dynamic Bayesian Networks for Integrating Multi-omics Time Series Microbiome Data.

A key challenge in the analysis of longitudinal microbiome data is the inference of temporal interactions between microbial taxa, their genes, the metabolites that they consume and produce, and host genes. To address these challenges, we developed a computational pipeline, a pipeline for the analysis of longitudinal multi-omics data (PALM), that first aligns multi-omics data and then uses dynamic Bayesian networks (DBNs) to reconstruct a unified model. Our approach overcomes differences in sampling and progression rates, utilizes a biologically inspired multi-omic framework, reduces the large number of entities and parameters in the DBNs, and validates the learned network.

Inferring directional relationships in microbial communities using signed Bayesian networks.

Background: Microbe-microbe and host-microbe interactions in a microbiome play a vital role in both health and disease. However, the structure of the microbial community and the colonization patterns are highly complex to infer even under controlled wet laboratory conditions. In this study, we investigate what information, if any, can be provided by a Bayesian Network (BN) about a microbial community.

So you think you can PLS-DA?

Background: Partial Least-Squares Discriminant Analysis (PLS-DA) is a popular machine learning tool that is gaining increasing attention as a useful feature selector and classifier. In an effort to understand its strengths and weaknesses, we performed a series of experiments with synthetic data and compared its performance to its close relative from which it was initially invented, namely Principal Component Analysis (PCA).

Results: We demonstrate that even though PCA ignores the information regarding the class labels of the samples, this unsupervised tool can be remarkably effective as a feature selector.

IL-22 is required for the induction of bronchus-associated lymphoid tissue in tolerant lung allografts.

Long-term survival after lung transplantation remains profoundly limited by graft rejection. Recent work has shown that bronchus-associated lymphoid tissue (BALT), characterized by the development of peripheral nodal addressin (PNAd)-expressing high endothelial venules and enriched in B and Foxp3 T cells, is important for the maintenance of allograft tolerance. Mechanisms underlying BALT induction in tolerant pulmonary allografts, however, remain poorly understood.

Main histological parameters to be evaluated in an experimental model of myocardial infarct treated by stem cells on pigs.

Myocardial infarction has been carefully studied in numerous experimental models. Most of these models are based on electrophysiological and functional data, and pay less attention to histological discoveries. During the last decade, treatment using advanced therapies, mainly cell therapy, has prevailed from among all the options to be studied for treating myocardial infarction.

Dynamic interaction network inference from longitudinal microbiome data.

Background: Several studies have focused on the microbiota living in environmental niches including human body sites. In many of these studies, researchers collect longitudinal data with the goal of understanding not only just the composition of the microbiome but also the interactions between the different taxa. However, analysis of such data is challenging and very few methods have been developed to reconstruct dynamic models from time series microbiome data.

Ferroptotic cell death and TLR4/Trif signaling initiate neutrophil recruitment after heart transplantation.

Non-apoptotic forms of cell death can trigger sterile inflammation through the release of danger-associated molecular patterns, which are recognized by innate immune receptors. However, despite years of investigation the mechanisms which initiate inflammatory responses after heart transplantation remain elusive. Here, we demonstrate that ferrostatin-1 (Fer-1), a specific inhibitor of ferroptosis, decreases the level of pro-ferroptotic hydroperoxy-arachidonoyl-phosphatidylethanolamine, reduces cardiomyocyte cell death and blocks neutrophil recruitment following heart transplantation.

Spleen-derived classical monocytes mediate lung ischemia-reperfusion injury through IL-1β.

Ischemia-reperfusion injury, a form of sterile inflammation, is the leading risk factor for both short-term mortality following pulmonary transplantation and chronic lung allograft dysfunction. While it is well recognized that neutrophils are critical mediators of acute lung injury, processes that guide their entry into pulmonary tissue are not well understood. Here, we found that CCR2+ classical monocytes are necessary and sufficient for mediating extravasation of neutrophils into pulmonary tissue during ischemia-reperfusion injury following hilar clamping or lung transplantation.

Diagnosis, Pathophysiology and Experimental Models of Chronic Lung Allograft Rejection.

Chronic rejection is the Achilles heel of modern lung transplantation, characterized by a slow, progressive decline in allograft function. Clinically, this manifests as obstructive disease, restrictive disease, or a mixture of the 2 depending on the underlying pathology. The 2 major phenotypes of chronic rejection include bronchiolitis obliterans syndrome and restrictive allograft syndrome.

Metamizole (dipyrone) effects on sevoflurane requirements and postoperative hyperalgesia in rats.

Unlike non-steroidal anti-inflammatory drugs (NSAIDs), metamizole has poor anti-inflammatory effects; and is suitable for models where analgesia, but not anti-inflammatory effects, is desirable. Like opioids, these drugs produce perioperative analgesia while reducing anaesthetic requirements, but it remains unclear whether they may develop tolerance or hyperalgesia, and thus decrease in analgesic efficacy. The aim was to determine whether tolerance or hyperalgesia to metamizole occurred in rats, and whether the sevoflurane minimum alveolar concentration (MAC) was affected.

Technical Aspects and Benefits of Experimental Mouse Lung Transplantation.

In recent years, the number of lung transplantations performed as the last option for many respiratory diseases has grown considerably, both in adults and children. However, the causes for the relatively short survival of lungs compared to other organ transplants still need to be studied. Techniques have improved since the 1950s when experimental lung transplantation began, and the different animal species used now include rodents.

The Effects of the Toll-Like Receptor 4 Antagonist, Ibudilast, on Sevoflurane's Minimum Alveolar Concentration and the Delayed Remifentanil-Induced Increase in the Minimum Alveolar Concentration in Rats.

Background: Ultralow doses of naloxone, an opioid and toll-like receptor 4 antagonist, blocked remifentanil-induced hyperalgesia and the associated increase in the minimum alveolar concentration (MAC), but not tolerance. The aim was to determine the effects of the toll-like receptor 4 antagonist, ibudilast, on the MAC in the rat and how it might prevent the effects of remifentanil.

Methods: Male Wistar rats were randomly allocated to 5 treatment groups (n = 7 per group): 10 mg/kg ibudilast intraperitoneally, 240 µg/kg/h remifentanil IV, ibudilast plus remifentanil, remifentanil plus naloxone IV, or saline.