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An M25 Learning Technology Group Discussion on Barriers to Opening Educational Resources. Slides from presentation / workshop including collated results

Quality Control Analysis in Real-time (QC-ART) : A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those because of collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected. In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality because of the need for instrument cleaning and/or re-calibration. To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired to dynamically flag potential issues with instrument performance or sample quality. QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis. We demonstrate the utility and performance of QC-ART in identifying deviations in data quality because of both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. We also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments.Peer reviewe

The problem of scale in predicting biological responses to climate

This is the final version. Available on open access from Wiley via the DOI in this record Many analyses of biological responses to climate rely on gridded climate data derived from weather stations, which differ from the conditions experienced by organisms in at least two respects. First, the microclimate recorded by a weather station is often quite different to that near the ground surface, where many organisms live. Second, the temporal and spatial resolutions of gridded climate datasets derived from weather stations are often too coarse to capture the conditions experienced by organisms. Temporally and spatially coarse data have clear benefits in terms of reduced model size and complexity, but here we argue that coarse-grained data introduce errors that, in biological studies, are too often ignored. However, in contrast to common perception, these errors are not necessarily caused directly by a spatial mismatch between the size of organisms and the scale at which climate data are collected. Rather, errors and biases are primarily due to (i) systematic discrepancies between the climate used in analysis and that experienced by organisms under study and (ii) the non-linearity of most biological responses in combination with differences in climate variance between locations and time periods for which models are fitted and those for which projections are made. We discuss when exactly problems of scale can be expected to arise and highlight the potential to circumvent these by spatially and temporally down-scaling climate. We also suggest ways in which adjustments to deal with issues of scale could be made without the need to run high-resolution models over wide extents.European Regional Development Fund (ERDF

Homogeneous and heterogeneous distributed classification for pocket data mining

Pocket Data Mining (PDM) describes the full process of analysing data streams in mobile ad hoc distributed environments. Advances in mobile devices like smart phones and tablet computers have made it possible for a wide range of applications to run in such an environment. In this paper, we propose the adoption of data stream classification techniques for PDM. Evident by a thorough experimental study, it has been proved that running heterogeneous/different, or homogeneous/similar data stream classification techniques over vertically partitioned data (data partitioned according to the feature space) results in comparable performance to batch and centralised learning techniques

Modifying the Symbolic Aggregate Approximation Method to Capture Segment Trend Information

The Symbolic Aggregate approXimation (SAX) is a very popular symbolic dimensionality reduction technique of time series data, as it has several advantages over other dimensionality reduction techniques. One of its major advantages is its efficiency, as it uses precomputed distances. The other main advantage is that in SAX the distance measure defined on the reduced space lower bounds the distance measure defined on the original space. This enables SAX to return exact results in query-by-content tasks. Yet SAX has an inherent drawback, which is its inability to capture segment trend information. Several researchers have attempted to enhance SAX by proposing modifications to include trend information. However, this comes at the expense of giving up on one or more of the advantages of SAX. In this paper we investigate three modifications of SAX to add trend capturing ability to it. These modifications retain the same features of SAX in terms of simplicity, efficiency, as well as the exact results it returns. They are simple procedures based on a different segmentation of the time series than that used in classic-SAX. We test the performance of these three modifications on 45 time series datasets of different sizes, dimensions, and nature, on a classification task and we compare it to that of classic-SAX. The results we obtained show that one of these modifications manages to outperform classic-SAX and that another one slightly gives better results than classic-SAX.Comment: International Conference on Modeling Decisions for Artificial Intelligence - MDAI 2020: Modeling Decisions for Artificial Intelligence pp 230-23

The efficacy and tolerability of latency-reversing agents in reactivating the HIV-1 reservoir in clinical studies:a systematic review

Introduction: Understanding the clinical potency of latency-reversing agents (LRAs) on the HIV-1 reservoir is useful to deploy future strategies. This systematic review evaluated the effects of LRAs in human intervention studies. Methods: A literature search was performed using medical databases focusing on studies with adults living with HIV-1 receiving LRAs. Eligibility criteria required participants from prospective clinical studies, a studied compound hypothesised as LRA, and reactivation or tolerability assessments. Relevant demographical data, LRA reactivation capacity, reservoir size, and adverse events were extracted. A study quality assessment with analysis of bias was performed by RoB 2 and ROBINS-I tools. The primary endpoints were HIV-1 reservoir reactivation after LRA treatment quantified by cell-associated unspliced HIV-1 RNA, and LRA tolerability defined by adverse events. Secondary outcomes were reservoir size and the effect of LRAs on analytical treatment interruption (ATI) duration. Results: After excluding duplicates, 5182 publications were screened. In total 45 publications fulfilled eligibility criteria including 26 intervention studies and 16 randomised trials. The risk of bias was evaluated as high. Chromatin modulators were the main investigated LRA class in 24 studies. Participants were mostly males (90.1%). Where reported, HIV-1 subtype B was most frequently observed. Reactivation after LRA treatment occurred in 78% of studies and was observed with nearly all chromatin modulators. When measured, reactivation mostly occurred within 24 h after treatment initiation. Combination LRA strategies have been infrequently studied and were without synergistic reactivation. Adverse events, where reported, were mostly low grade, yet occurred frequently. Seven studies had individuals who discontinued LRAs for related adverse events. The reservoir size was assessed by HIV-1 DNA in 80% of studies. A small decrease in reservoir was observed in three studies on immune checkpoint inhibitors and the histone deacetylase inhibitors romidepsin and chidamide. No clear effect of LRAs on ATI duration was observed. Conclusion: This systematic review provides a summary of the reactivation of LRAs used in current clinical trials whilst highlighting the importance of pharmacovigilance. Highly heterogeneous study designs and underrepresentation of relevant patient groups are to be considered when interpreting these results. The observed reactivation did not lead to cure or a significant reduction in the size of the reservoir. Finding more effective LRAs by including well-designed studies are needed to define the required reactivation level to reduce the HIV-1 reservoir.</p

House dust mite allergen avoidance strategies for the treatment of allergic asthma:A hypothesis-generating meta-analysis

Background: This study continues the review by Gøtzsche and Johansen (Cochrane Database of Systematic Reviews, 2008, Art. No: CD001187), aiming to systematically generate hypotheses on the effectiveness of (sub)strategies for house dust mite allergen avoidance in the treatment of allergic asthma. Methods: We used the trials previously analysed by Gøtzsche and Johansen and searched recently published studies. Data on asthma symptom scores (ASS), ACQ, number of improved patients, AQLQ-scores, medication use, FEV1%, PC20, and FeNO levels were analysed. The effectiveness of strategies was assessed using Metafor in R. Results: Thirty-five trials involving 2419 patients were included in the final study. The patient-reported outcome number of patients with improved condition following total bedroom control was RR = 3.39 (95% confidence interval: 1.04 to 11.04, P = 0.04). The mean differences in the ASS by nocturnal air purification was −0.7 (95% confidence interval: −1.08 to −0.32, P &lt; 0.001). Other outcomes including partial bedroom control were non-significant or clinically not of importance. Conclusions: Total bedroom control and nocturnal air purification of the breathing zone hypothetically provides clinical benefits in patients with house dust mite-induced allergic asthma. The number of patients with improvements in their condition respectively the asthma symptom score differences showed potential in small subgroups, consisting of single studies. Partial bedroom control is not recommended. Systematic Review Registration: Prospero CRD42022323660.</p

Congenital Forearm Pseudarthrosis, a Systematic Review for a Treatment Algorithm on a Rare Condition

Background: A congenital forearm pseudarthrosis is a rare condition and is strongly associated with neurofibromatosis type 1. Several surgical techniques are described in the literature, but the most optimal treatment strategy remains unclear. This systematic review aims to develop a treatment algorithm that may aid i