Sperm activate TLR2/TLR1 heterodimerization to induce a weak proinflammatory response in the bovine uterus

Toll-like receptor 2 (TLR2) signaling pathway is involved in the sperm-triggered uterine inflammatory response at insemination, but its precise mechanism at molecular-level remains unknown. According to the ligand specificity, TLR2 forms a heterodimer with TLR1 or TLR6 as an initial step to mediate intracellular signaling, leading to a specific type of immune response. Hence, the present study aimed to identify the active TLR2 heterodimer (TLR2/1 or TLR2/6) that is involved in sperm-uterine immune crosstalk in bovine using various models. First, in-vitro (bovine endometrial epithelial cells, BEECs) and ex-vivo (bovine uterine explant) models were employed to test different TLR2 dimerization pathways in endometrial epithelia after exposure to sperm or TLR2 agonists; PAM3 (TLR2/1 agonist), and PAM2 (TLR2/6 agonist). Additionally, in-silico approaches were performed to confirm the dimer stability using de novo protein structure prediction model for bovine TLRs. The in-vitro approach revealed that sperm triggered the mRNA and protein expression of TLR1 and TLR2 but not TLR6 in BEECs. Moreover, this model disclosed that activation of TLR2/6 heterodimer, triggers a much stronger inflammatory response than TLR2/1 and sperm in bovine uterine epithelia. In the ex-vivo model that mimics the intact uterine tissue at insemination, sperm also induced the protein expression of both TLR1 and TLR2, but not TLR6, in bovine endometrium, particularly in uterine glands. Importantly, PAM3 and sperm induced similar and low mRNA expression of pro-inflammatory cytokines and TNFA protein to a lesser extent than PAM2 in endometrial epithelia. This implied that sperm might trigger a weak inflammatory response via TLR2/TLR1 activation which is similar to that of PAM3. Additionally, the in-silico analyses showed that the existence of bridging ligands is essential for heterodimer stability in bovine TLR2 with either TLR1 or TLR6. Altogether, the present findings revealed that sperm utilize TLR2/1, but not TLR2/6, heterodimerization to trigger a weak physiological inflammatory response in the bovine uterus. This might be the way to remove excess dead sperm remaining in the uterine lumen without tissue damage for providing an ideal uterine environment for early embryo reception and implantation

Genomics Virtual Laboratory: a practical bioinformatics workbench for the cloud

Analyzing high throughput genomics data is a complex and compute intensive task, generally requiring numerous software tools and large reference data sets, tied together in successive stages of data transformation and visualisation. A computational platform enabling best practice genomics analysis ideally meets a number of requirements, including: a wide range of analysis and visualisation tools, closely linked to large user and reference data sets ; workflow platform(s) enabling accessible, reproducible, portable analyses, through a flexible set of interfaces ; highly available, scalable computational resources ; and flexibility and versatility in the use of these resources to meet demands and expertise of a variety of users. Access to an appropriate computational platform can be a significant barrier to researchers, as establishing such a platform requires a large upfront investment in hardware, experience, and expertise

Resource Efficient Machine Learning Techniques for Monitoring Repetitive Activities through Wearable Devices in Real-time

© 2020 Yousef KowsarWeight training activities have become an inseparable part of an athlete's training to reach their maximum performance. However, at the same time, weight training is considered as the fifth costliest sport in terms of injuries. Studies have shown that monitoring weight training performance is one of the most effective ways of reducing injuries caused by this type of exercise. Given the complexity of weight training exercises, it is a challenge for trainees to know whether they are performing their exercises correctly or not. Considering the fact that incorrect performance of a weight training exercise can result in life-long injuries, which may cost athletes their professional careers, it is of utmost importance to design systems that can detect the incorrect performance of weight training activities. In this thesis, we motivate the importance of personalised monitoring of weight training performance using wearable devices. We show why current supervised approaches for monitoring weight training routines fail to address the needs of professional athletes. We discuss the emerging need for resource efficient machine learning techniques to monitor weight training activities in real-time, using a wearable device. We then present a novel workflow to detect weight training performance anomalies from observing only the correct performance of an exercise by the trainee. Our workflow motivates two fundamental questions to be addressed in the time series domain: 1- Identifying a trainee's weight training performance from the incoming stream of data generated from wearable devices efficiently and in real-time, 2 Analysing a trainee's weight training performance efficiently. We address the first question of identifying the trainee's weight training performance using wearable devices by formally defining weight training activities as intervals of recurrence---short bursts of consecutive repeating signals---from the incoming time series data. We present an efficient, online, one-pass and real-time algorithm for finding and tracking intervals of recurrence in a time series data stream. We provide a detailed theoretical analysis of the behaviour of any interval of recurrence, and derive fundamental properties that can be used on real world data streams. We demonstrate the robustness of our method to variations in repetitions of the same pattern adjacent to each other. We then advance our signal processing approach to monitoring weight training exercises by addressing the shape analogy of signals. Shape analogy is a technique where signals in the form of time series waveforms are compared in terms of how much they look alike. This concept has been applied for many years in geometry. Notably, none of the current techniques describe a time series as a geometric curve that is expressed by its relative location and form in space. To fill this gap, we introduce Shape-Sphere, a vector space where time series are presented as points on the surface of a sphere. We prove a pseudo-metric property for distances in the Shape-Sphere. We show how to describe the average shape of a time series set using the pseudo-metric property of the Shape-Sphere by deriving a centroid from the set. We demonstrate the effectiveness of the pseudo-metric property and its centroid in capturing the shape of a time series set, using two important machine learning techniques, namely: Nearest Centroid Classifiers and K-Means clustering, through 48 publicly available data sets. Our results show that Shape-Sphere significantly improves the efficiency of both techniques. Shape-Sphere improves the nearest centroid classification results when shape is the differentiating feature, while keeping the quality of clustering equivalent to current state-of-the-art techniques. We subsequently design and develop LiftSmart: a novel smart wearable to detect, track and analyse weight training activities. LiftSmart is the first wearable for weight training that is based on unsupervised machine learning techniques designed in this thesis to eliminate reliance on labelled data. We developed LiftSmart with the ultimate goal of personalised monitoring of professional weight trainers. LiftSmart is tailored to the needs of individual professional weight trainers to monitor their performance by automatically adapting the standard performance of an exercise, which is set for each individual athlete. In summary, in this thesis we design resource efficient machine learning techniques for monitoring weight training activities in real-time using a wearable device. We demonstrate the effectiveness of our technique in monitoring weight training activities in real-time by designing the first wearable device that automatically detects, tracks and provides feedback about any weight training activity that an athlete performs in a gym

Zearalenone (ZEN) disrupts the anti-inflammatory response of bovine oviductal epithelial cells to sperm in vitro

Dietary contamination by Zearalenone (ZEN) has a detrimental effect on bovine fertility. Recently, we showed a novel anti-inflammatory response of bovine oviductal epithelial cells (BOEC) to active sperm cells in vitro. The aim of the present study was to investigate the effect of ZEN exposure of BOEC on the immune-related cytokine expression in response to bovine sperm. At concentrations of 100 and 1000ng/mL, ZEN induced the expression of TNF and IL1B (pro-inflammatory cytokines) as well as IL8 (chemokine) in BOEC in a dose-dependent manner. Furthermore, ZEN induced PTGES expression and PGE2 secretion in BOEC. Sperm co-culture induced an anti-inflammatory response in BOEC with upregulation of TGFB, secretion of PGE2 and downregulation of TNF. Most importantly, ZEN at 1-1000ng/mL eliminated the response of BOEC to sperm. Estradiol-17β (5ng/mL) treatment did not produce the same effects as ZEN, suggesting that the response of BOEC to ZEN is, at least in part, not mediated by estrogen receptors. Taken together, ZEN can produce inflammatory effects on BOEC by stimulating the expressions of pro-inflammatory cytokines and disrupt the normal interaction between sperm and BOEC at the level of cytokine expressions and PGE2 production. Thus, exposure of the bovine oviduct to ZEN may negatively affect sperm survival and reduce fertility

Zearalenone (ZEN) disrupts the anti-inflammatory response of bovine oviductal epithelial cells to sperm in vitro

Dietary contamination by Zearalenone (ZEN) has a detrimental effect on bovine fertility. Recently, we showed a novel anti-inflammatory response of bovine oviductal epithelial cells (BOEC) to active sperm cells in vitro. The aim of the present study was to investigate the effect of ZEN exposure of BOEC on the immune-related cytokine expression in response to bovine sperm. At concentrations of 100 and 1000ng/mL, ZEN induced the expression of TNF and IL1B (pro-inflammatory cytokines) as well as IL8 (chemokine) in BOEC in a dose-dependent manner. Furthermore, ZEN induced PTGES expression and PGE2 secretion in BOEC. Sperm co-culture induced an anti-inflammatory response in BOEC with upregulation of TGFB, secretion of PGE2 and downregulation of TNF. Most importantly, ZEN at 1-1000ng/mL eliminated the response of BOEC to sperm. Estradiol-17β (5ng/mL) treatment did not produce the same effects as ZEN, suggesting that the response of BOEC to ZEN is, at least in part, not mediated by estrogen receptors. Taken together, ZEN can produce inflammatory effects on BOEC by stimulating the expressions of pro-inflammatory cytokines and disrupt the normal interaction between sperm and BOEC at the level of cytokine expressions and PGE2 production. Thus, exposure of the bovine oviduct to ZEN may negatively affect sperm survival and reduce fertility

A summary of the criteria that would define a general genomics workbench environment, and suggested implications on technical requirements.

<p>A summary of the criteria that would define a general genomics workbench environment, and suggested implications on technical requirements.</p

The GVL launch process for starting self-launched instances of the GVL workbench.

<p><b>(a)</b> A user initiates the launch process via the launch service (<i>launch</i>.<i>genome</i>.<i>edu</i>.<i>au</i>) by providing their cloud credentials to the launcher application and <b>(b)</b> within a few minutes is able to access the management interface (CloudMan) on the deployed instance of the workbench. <b>(c)</b> After workbench services have started, the researcher can use the applications as desired (e.g., Galaxy).</p

A screenshot of the GVL Dashboard.

<p>The GVL Dashboard is a portal running on every GVL instance. It lists all of the available services, their status, and offers a direct link to access those.</p

Summary of specific technical solutions used to meet the design requirements of the GVL.

<p>Summary of specific technical solutions used to meet the design requirements of the GVL.</p