A MicroRNA that Regulates TLR-Mediated Fibrosis

Hepatic damage can be caused by an array of factors which, if sustained, can lead to hepatic fibrosis.[...

DNA methylation in fibrosis

Fibrosis is characterised by an exuberant wound healing response and the major cell type responsible is the myofibroblast. The myofibroblast is typified by excessive ECM production and contractile activity and is demarcated by alpha-smooth muscle actin expression. What has recently come to light is that the activation of the fibroblast to myofibroblast may be under epigenetic control, specifically methylation. Methylation of DNA is a conserved mechanism to precisely regulate gene expression in a specific context. Hypermethylation leads to gene repression and hypomethylation results in gene induction. Methylation abnormalities have recently been uncovered in fibrosis, both organ specific and widespread fibrosis. The fact that these methylation changes are rapid and reversible lends themselves amenable to therapeutic intervention. This review considers the role of methylation in fibrosis and the activation of the myofibroblasts and how this could be targeted for fibrosis. Fibrosis is of course currently intractable to therapeutics and is a leading cause of morbidity and mortality and is an urgent unmet clinical need

Differentiation Potential of CD14+ Monocytes into Myofibroblasts in Patients with Systemic Sclerosis

BACKGROUND: Circulating monocytes are a highly plastic and functionally heterogeneic cell type with an activated phenotype in patients with systemic sclerosis (SSc). CD14(+) monocytes have the potential to differentiate into extra-cellular matrix (ECM) producing cells, possibly participating in fibrogenesis. AIM: To study the effect of GM-CSF, IL-4 and endothelin -1 (ET-1) alone or in combination on monocyte differentiation into myofibroblasts. METHODS: CD14(+) cells were isolated from peripheral blood from 14 SSc patients and healthy controls by positive selection and incubated with different combinations of GM-CSF, IL-4 and ET-1 for 14 days. Type-1 collagen and α-SMA were detected by Western blot, qPCR and confocal microscopy. HLA-DR, CD11c and CD14 expression was analysed by flow cytometry. A collagen gel contraction assay was performed for functional myofibroblast assessment. RESULTS: GM-CSF both induced collagen and α-SMA expression after 14 days. ET-1 further increased GM-CSF-induced collagen expression in a dose dependent manner up to 30-fold. IL-4/GM-CSF combination leads to a more DC-like phenotype of monocytes associated with reduced collagen and α-SMA expression compared to GM-CSF alone. Collagen and α-SMA expression was higher in monocytes from SSc patients and monocytes were more prone to obtain a spindle form. In contrast to controls, ET-1 and IL-4 alone were sufficient to induce α-SMA expression in monocytes from SSc patients. Despite the induction of α-SMA expression, monocyte-derived myofibroblasts only had a moderate capability of contraction in functional analyses. CONCLUSION: SSc monocytes display increased maturation towards myofibroblasts demonstrated by their phenotype and α-SMA expression when compared to monocytes from healthy controls, however only with minor functional contraction properties

Towards privatized social and employment protections in the platform economy? Evidence from the UK courier sector

Platform capitalism has facilitated the widespread replacement of employment contracts with contracts for services. These offer significantly fewer social and employment protections for the independent contractors engaged. What does this mean for the future of national social and employment protection (SEPs) systems? We show how the question of platform workers’ employment status – and therefore access to SEPs – remain unresolved under UK law. Drawing on socio-legal theory, we demonstrate why digital labor platforms represent a challenge to existing modes of employment law and labor market regulation. In the absence of immediate legal ‘fixes’, some unions and firms are innovating new ‘privatized social protection systems’. A ‘Self-Employed Plus’ (SE+) agreement in the UK parcel courier sector developed between Hermes, a UK-based courier service, and the GMB union represents an important example of such attempts being made to bridge the current regulatory void. We critically analyze the agreement and draw lessons for platform governance theory. We demonstrate that privatized SE+ provisions potentially offer significant benefits for platforms by reducing regulatory oversight, boosting productivity, and enhancing managerial control over platform complementors. At the same time, while they risk undermining national SEP systems and degrading worker protections, they also offer a window of opportunity for trade unions to gain a foothold in the platform economy

Citizen scientist monitoring accurately reveals nutrient pollution dynamics in Lake Tanganyika coastal waters

Several studies in Lake Tanganyika have effectively employed traditional methods to explore changes in water quality in open waters; however, coastal monitoring has been restricted and sporadic, relying on costly sample and analytical methods that require skilled technical staff. This study aims in validating citizen science water quality collected data (nitrate, phosphate and turbidity) with those collected and measured by professional scientists in the laboratory. A second objective of the study is to use citizen scientist data to identify the patterns of seasonal and spatial variations in nutrient conditions and forecast potential changes based on expected changes in population and climate (to 2050). The results showed that the concentrations of nitrate and phosphate measured by citizen scientists nearly matched those established by professional scientists, with overall accuracy of 91% and 74%, respectively. For total suspended solids measured by professional and turbidity measured by citizen scientists, results show that, using 14 NTU as a cut-off, citizen scientist measurements of Sec-chi tube depth to identify lake TSS below 7.0 mg/L showed an accuracy of 88%. In both laboratory and citizen scientist-based studies, all measured water quality variables were significantly higher during the wet season compared to the dry season. Climate factors were discovered to have a major impact on the likelihood of exceeding water quality restrictions in the next decades (2050), which could deteriorate lake conditions. Upscaling citizen science to more communities on the lake and other African Great Lakes would raise environmental awareness, inform management and mitigation activities, and aid long-term decision-making

One-pot synthesis of micron-sized polybetaine particles: innovative use of supercritical carbon dioxide

Polybetaines exhibit unique properties combining anti-polyelectrolyte and low protein fouling behaviour, as well as biocompatibility. To date, the synthesis of polybetaine particles >50 nm has proved to be extremely challenging with standard emulsion and dispersion techniques being unsuccessful. Here we present the first reported synthesis of micron-sized, discrete cross-linked polybetaine particles, using polymerisation in scCO2 with methanol as a co-solvent. Discrete particles are produced only when the methanol is efficiently removed in situ using scCO2 extraction. A relatively high crosslinking agent initial concentration (10 wt%) was found to result in the most well defined particles, and particle integrity reduced as the crosslinking agent initial concentration was decreased. A monomer loading of between 3.0 × 10−2 mol L−1 and 1.8 × 10−1 mol L−1 resulted in discrete micron sized particles, with significant agglomoration occuring as the monomer loading was increased further. A spherical morphology and extremely low size dispersity was observed by SEM analysis for the optimised particles. The particles were readily re-dispersed in aqueous solution and light scattering measurements confirmed their low size dispersity

Learning Representations that Support Extrapolation

Extrapolation -- the ability to make inferences that go beyond the scope of one's experiences -- is a hallmark of human intelligence. By contrast, the generalization exhibited by contemporary neural network algorithms is largely limited to interpolation between data points in their training corpora. In this paper, we consider the challenge of learning representations that support extrapolation. We introduce a novel visual analogy benchmark that allows the graded evaluation of extrapolation as a function of distance from the convex domain defined by the training data. We also introduce a simple technique, temporal context normalization, that encourages representations that emphasize the relations between objects. We find that this technique enables a significant improvement in the ability to extrapolate, considerably outperforming a number of competitive techniques.Comment: ICML 202

The Relational Bottleneck as an Inductive Bias for Efficient Abstraction

A central challenge for cognitive science is to explain how abstract concepts are acquired from limited experience. This effort has often been framed in terms of a dichotomy between empiricist and nativist approaches, most recently embodied by debates concerning deep neural networks and symbolic cognitive models. Here, we highlight a recently emerging line of work that suggests a novel reconciliation of these approaches, by exploiting an inductive bias that we term the relational bottleneck. We review a family of models that employ this approach to induce abstractions in a data-efficient manner, emphasizing their potential as candidate models for the acquisition of abstract concepts in the human mind and brain

Protocol for development and validation of postpartum cardiovascular disease (CVD) risk prediction model incorporating reproductive and pregnancy-related candidate predictors

Funding: This work is funded by the Strategic Priority Fund “Tackling multimorbidity at scale” programme (grant number MR/W014432/1) delivered by the Medical Research Council and the National Institute for Health Research in partnership with the Economic and Social Research Council and in collaboration with the Engineering and Physical Sciences Research Council. SW PhD studentship is funded by the British Heart Foundation (BHF) Data Science Centre (BHF grant number SP/19/3/34678, awarded to Health Data Research (HDR)). His PhD is also supported through the HDR-UK-Turing Wellcome PhD Programme.Background Cardiovascular disease (CVD) is a leading cause of death among women. CVD is associated with reduced quality of life, significant treatment and management costs, and lost productivity. Estimating the risk of CVD would help patients at a higher risk of CVD to initiate preventive measures to reduce risk of disease. The Framingham risk score and the QRISK® score are two risk prediction models used to evaluate future CVD risk in the UK. Although the algorithms perform well in the general population, they do not take into account pregnancy complications, which are well known risk factors for CVD in women and have been highlighted in a recent umbrella review. We plan to develop a robust CVD risk prediction model to assess the additional value of pregnancy risk factors in risk prediction of CVD in women postpartum. Methods Using candidate predictors from QRISK®-3, the umbrella review identified from literature and from discussions with clinical experts and patient research partners, we will use time-to-event Cox proportional hazards models to develop and validate a 10-year risk prediction model for CVD postpartum using Clinical Practice Research Datalink (CPRD) primary care database for development and internal validation of the algorithm and the Secure Anonymised Information Linkage (SAIL) databank for external validation. We will then assess the value of additional candidate predictors to the QRISK®-3 in our internal and external validations. Discussion The developed risk prediction model will incorporate pregnancy-related factors which have been shown to be associated with future risk of CVD but have not been taken into account in current risk prediction models. Our study will therefore highlight the importance of incorporating pregnancy-related risk factors into risk prediction modeling for CVD postpartum.Publisher PDFPeer reviewe