Passage and concentration-dependent effects of Indomethacin on tendon derived cells

<p>Abstract</p> <p>Background</p> <p>Non-steroidal anti-inflammatory drugs (NSAID) are commonly used in the treatment of tendinopathies such as tendonitis and tendinosis. Despite this, little is known of their direct actions on tendon-derived cells. As NSAIDs have been shown to delay healing in a number of mesenchymal tissues we have investigated the direct effects of indomethacin on the proliferation of tendon-derived cells.</p> <p>Results and Discussion</p> <p>The results obtained were dependent on both the type of cells used and the method of measurement. When measured using the Alamar blue assay, a common method for the measurement of cell proliferation and viability, no effect of indomethacin was seen regardless of cell source. It is likely that this lack of effect was due to a paucity of mitochondrial enzymes in tendon cells.</p> <p>However, when cell number was assessed using the methylene blue assay, which is a simple nuclear staining technique, an Indomethacin-induced inhibition of proliferation was seen in primary cells but not in secondary subcultures.</p> <p>Conclusion</p> <p>These results suggest that firstly, care must be taken when deciding on methodology used to investigate tendon-derived cells as these cells have a quite different metabolism to other mesenchymal derive cells. Secondly, Indomethacin can inhibit the proliferation of primary tendon derived cells and that secondary subculture selects for a population of cells that is unresponsive to this drug.</p

A Taxonomy of Explainable Bayesian Networks

Artificial Intelligence (AI), and in particular, the explainability thereof, has gained phenomenal attention over the last few years. Whilst we usually do not question the decision-making process of these systems in situations where only the outcome is of interest, we do however pay close attention when these systems are applied in areas where the decisions directly influence the lives of humans. It is especially noisy and uncertain observations close to the decision boundary which results in predictions which cannot necessarily be explained that may foster mistrust among end-users. This drew attention to AI methods for which the outcomes can be explained. Bayesian networks are probabilistic graphical models that can be used as a tool to manage uncertainty. The probabilistic framework of a Bayesian network allows for explainability in the model, reasoning and evidence. The use of these methods is mostly ad hoc and not as well organised as explainability methods in the wider AI research field. As such, we introduce a taxonomy of explainability in Bayesian networks. We extend the existing categorisation of explainability in the model, reasoning or evidence to include explanation of decisions. The explanations obtained from the explainability methods are illustrated by means of a simple medical diagnostic scenario. The taxonomy introduced in this paper has the potential not only to encourage end-users to efficiently communicate outcomes obtained, but also support their understanding of how and, more importantly, why certain predictions were made

Clinical significance of the nuclear receptor co-regulator DC-SCRIPT in breast cancer: an independent retrospective validation study

Contains fulltext : 88921.pdf (publisher's version ) (Open Access

Optimal deployment of components of cloud-hosted application for guaranteeing multitenancy isolation

One of the challenges of deploying multitenant cloud-hosted services that are designed to use (or be integrated with) several components is how to implement the required degree of isolation between the components when there is a change in the workload. Achieving the highest degree of isolation implies deploying a component exclusively for one tenant; which leads to high resource consumption and running cost per component. A low degree of isolation allows sharing of resources which could possibly reduce cost, but with known limitations of performance and security interference. This paper presents a model-based algorithm together with four variants of a metaheuristic that can be used with it, to provide near-optimal solutions for deploying components of a cloud-hosted application in a way that guarantees multitenancy isolation. When the workload changes, the model based algorithm solves an open multiclass QN model to determine the average number of requests that can access the components and then uses a metaheuristic to provide near-optimal solutions for deploying the components. Performance evaluation showed that the obtained solutions had low variability and percent deviation when compared to the reference/optimal solution. We also provide recommendations and best practice guidelines for deploying components in a way that guarantees the required degree of isolation

Hybridization in parasites: consequences for adaptive evolution, pathogenesis and public health in a changing world

[No abstract available

IFN-γ-Inducible Irga6 Mediates Host Resistance against Chlamydia trachomatis via Autophagy

Chlamydial infection of the host cell induces Gamma interferon (IFNγ), a central immunoprotector for humans and mice. The primary defense against Chlamydia infection in the mouse involves the IFNγ-inducible family of IRG proteins; however, the precise mechanisms mediating the pathogen's elimination are unknown. In this study, we identify Irga6 as an important resistance factor against C. trachomatis, but not C. muridarum, infection in IFNγ-stimulated mouse embryonic fibroblasts (MEFs). We show that Irga6, Irgd, Irgm2 and Irgm3 accumulate at bacterial inclusions in MEFs upon stimulation with IFNγ, whereas Irgb6 colocalized in the presence or absence of the cytokine. This accumulation triggers a rerouting of bacterial inclusions to autophagosomes that subsequently fuse to lysosomes for elimination. Autophagy-deficient Atg5−/− MEFs and lysosomal acidification impaired cells surrender to infection. Irgm2, Irgm3 and Irgd still localize to inclusions in IFNγ-induced Atg5−/− cells, but Irga6 localization is disrupted indicating its pivotal role in pathogen resistance. Irga6-deficient (Irga6−/−) MEFs, in which chlamydial growth is enhanced, do not respond to IFNγ even though Irgb6, Irgd, Irgm2 and Irgm3 still localize to inclusions. Taken together, we identify Irga6 as a necessary factor in conferring host resistance by remodelling a classically nonfusogenic intracellular pathogen to stimulate fusion with autophagosomes, thereby rerouting the intruder to the lysosomal compartment for destruction

Ring-Like Distribution of Constitutive Heterochromatin in Bovine Senescent Cells

Background: Cells that reach ‘‘Hayflick limit’ ’ of proliferation, known as senescent cells, possess a particular type of nuclear architecture. Human senescent cells are characterized by the presence of highly condensed senescent associated heterochromatin foci (SAHF) that can be detected both by immunostaining for histone H3 three-methylated at lysine 9 (H3K9me3) and by DAPI counterstaining. Methods: We have studied nuclear architecture in bovine senescent cells using a combination of immunofluorescence and 3D fluorescent in-situ hybridization (FISH). Results: Analysis of heterochromatin distribution in bovine senescent cells using fluorescent in situ hybridization for pericentric chromosomal regions, immunostaining of H3K9me3, centromeric proteins CENP A/B and DNA methylation showed a lower level of heterochromatin condensation as compared to young cells. No SAHF foci were observed. Instead, we observed fibrous ring-like or ribbon-like heterochromatin patterns that were undetectable with DAPI counterstaining. These heterochromatin fibers were associated with nucleoli

"You have to get wet to learn how to swim" applied to bridging the gap between research into personnel scheduling and its implementation in practice

Personnel scheduling problems have attracted research interests for several decades. They have been considerably changed over time, accommodating a variety of constraints related to legal and organisation requirements, part-time staff, flexible hours of staff, staff preferences, etc. This led to a myriad of approaches developed for solving personnel scheduling problems including optimisation, meta-heuristics, artificial intelligence, decision-support, and also hybrids of these approaches. However, this still does not imply that this research has a large impact on practice and that state-of-the art models and algorithms are widely in use in organisations. One can find a reasonably large number of software packages that aim to assist in personnel scheduling. A classification of this software based on its purpose will be proposed, accompanied with a discussion about the level of support that this software offers to schedulers. A general conclusion is that the available software, with some exceptions, does not benefit from the wealth of developed models and methods. The remaining of the paper will provide insights into some characteristics of real-world scheduling problems that, in the author’s opinion, have not been given a due attention in the personnel scheduling research community yet and which could contribute to the enhancement of the implementation of research results in practice. Concluding remarks are that in order to bridge the gap that still exists between research into personnel scheduling and practice, we need to engage more with schedulers in practice and also with software developers; one may say we need to get wet if we want to learn how to swim

Utilisation of Mucin Glycans by the Human Gut Symbiont Ruminococcus gnavus Is Strain-Dependent

Commensal bacteria often have an especially rich source of glycan-degrading enzymes which allow them to utilize undigested carbohydrates from the food or the host. The species Ruminococcus gnavus is present in the digestive tract of ≥90% of humans and has been implicated in gut-related diseases such as inflammatory bowel diseases (IBD). Here we analysed the ability of two R. gnavus human strains, E1 and ATCC 29149, to utilize host glycans. We showed that although both strains could assimilate mucin monosaccharides, only R. gnavus ATCC 29149 was able to grow on mucin as a sole carbon source. Comparative genomic analysis of the two R. gnavus strains highlighted potential clusters and glycoside hydrolases (GHs) responsible for the breakdown and utilization of mucin-derived glycans. Transcriptomic and functional activity assays confirmed the importance of specific GH33 sialidase, and GH29 and GH95 fucosidases in the mucin utilisation pathway. Notably, we uncovered a novel pathway by which R. gnavus ATCC 29149 utilises sialic acid from sialylated substrates. Our results also demonstrated the ability of R. gnavus ATCC 29149 to produce propanol and propionate as the end products of metabolism when grown on mucin and fucosylated glycans. These new findings provide molecular insights into the strain-specificity of R. gnavus adaptation to the gut environment advancing our understanding of the role of gut commensals in health and disease

Toxoplasma gondii Clonal Strains All Inhibit STAT1 Transcriptional Activity but Polymorphic Effectors Differentially Modulate IFN gamma Induced Gene Expression and STAT1 Phosphorylation

Host defense against the parasite Toxoplasma gondii requires the cytokine interferon-gamma (IFNγ). However, Toxoplasma inhibits the host cell transcriptional response to IFNγ, which is thought to allow the parasite to establish a chronic infection. It is not known whether all strains of Toxoplasma block IFNγ-responsive transcription equally and whether this inhibition occurs solely through the modulation of STAT1 activity or whether other transcription factors are involved. We find that strains from three North American/European clonal lineages of Toxoplasma, types I, II, and III, can differentially modulate specific aspects of IFNγ signaling through the polymorphic effector proteins ROP16 and GRA15. STAT1 tyrosine phosphorylation is activated in the absence of IFNγ by the Toxoplasma kinase ROP16, but this ROP16-activated STAT1 is not transcriptionally active. Many genes induced by STAT1 can also be controlled by other transcription factors and therefore using these genes as specific readouts to determine Toxoplasma inhibition of STAT1 activity might be inappropriate. Indeed, GRA15 and ROP16 modulate the expression of subsets of IFNγ responsive genes through activation of the NF-κB/IRF1 and STAT3/6 transcription factors, respectively. However, using a stable STAT1-specific reporter cell line we show that strains from the type I, II, and III clonal lineages equally inhibit STAT1 transcriptional activity. Furthermore, all three of the clonal lineages significantly inhibit global IFNγ induced gene expression