The effect of organelle discovery upon sub-cellular protein localisation.

Prediction of protein sub-cellular localisation by employing quantitative mass spectrometry experiments is an expanding field. Several methods have led to the assignment of proteins to specific subcellular localisations by partial separation of organelles across a fractionation scheme coupled with computational analysis. Methods developed to analyse organelle data have largely employed supervised machine learning algorithms to map unannotated abundance profiles to known protein–organelle associations. Such approaches are likely to make association errors if organelle-related groupings present in experimental output are not included in data used to create a protein–organelle classifier. Currently, there is no automated way to detect organelle-specific clusters within such datasets. In order to address the above issues we adapted a phenotype discovery algorithm, originally created to filter image-based output for RNAi screens, to identify putative subcellular groupings in organelle proteomics experiments. We were able to mine datasets to a deeper level and extract interesting phenotype clusters for more comprehensive evaluation in an unbiased fashion upon application of this approach. Organelle-related protein clusters were identified beyond those sufficiently annotated for use as training data. Furthermore, we propose avenues for the incorporation of observations made into general practice for the classification of protein–organelle membership from quantitative MS experiments. Biological significance Protein sub-cellular localisation plays an important role in molecular interactions, signalling and transport mechanisms. The prediction of protein localisation by quantitative mass-spectrometry (MS) proteomics is a growing field and an important endeavour in improving protein annotation. Several such approaches use gradient-based separation of cellular organelle content to measure relative protein abundance across distinct gradient fractions. The distribution profiles are commonly mapped in silico to known protein–organelle associations via supervised machine learning algorithms, to create classifiers that associate unannotated proteins to specific organelles. These strategies are prone to error, however, if organelle-related groupings present in experimental output are not represented, for example owing to the lack of existing annotation, when creating the protein–organelle mapping. Here, the application of a phenotype discovery approach to LOPIT gradient-based MS data identifies candidate organelle phenotypes for further evaluation in an unbiased fashion. Software implementation and usage guidelines are provided for application to wider protein–organelle association experiments. In the wider context, semi-supervised organelle discovery is discussed as a paradigm with which to generate new protein annotations from MS-based organelle proteomics experiments. This article is part of a Special Issue entitled: New Horizons and Applications for Proteomics [EuPA 2012]

Do you see what I see? Images of the COVID-19 pandemic through the lens of Google

During times of crisis, information access is crucial. Given the opaque processes behind modern search engines, it is important to understand the extent to which the “picture” of the Covid-19 pandemic accessed by users differs. We explore variations in what users “see” concerning the pandemic through Google image search, using a two-step approach. First, we crowdsource a search task to users in four regions of Europe, asking them to help us create a photo documentary of Covid-19 by providing image search queries. Analysing the queries, we find five common themes describing information needs. Next, we study three sources of variation - users’ information needs, their geo-locations and query languages - and analyse their influences on the similarity of results. We find that users see the pandemic differently depending on where they live, as evidenced by the 46% similarity across results. When users expressed a given query in different languages, there was no overlap for most of the results. Our analysis suggests that localisation plays a major role in the (dis)similarity of results, and provides evidence of the diverse “picture” of the pandemic seen through Google

Preserving the memory of the first wave of COVID-19 pandemic: Crowdsourcing a collection of image search queries

The unprecedented events of the COVID-19 pandemic have generated an enormous amount of information and populated the Web with new content relevant to the pandemic and its implications. Visual information such as images has been shown to be crucial in the context of scientific communication. Images are often interpreted as being closer to the truth as compared to other forms of communication, because of their physical representation of an event such as the COVID-19 pandemic. In this work, we ask crowdworkers across four regions of Europe that were severely affected by the first wave of pandemic, to provide us with image search queries related to COVID-19 pandemic. The goal of this study is to understand the similarities/differences of the aspects that are most important to users across different locations regarding the first wave of COVID-19 pandemic. Through a content analysis of their queries, we discovered five common themes of concern to all, although the frequency of use differed across regions

Dynamic proteomic profiling of extra-embryonic endoderm differentiation in mouse embryonic stem cells

During mammalian pre-implantation development, the cells of the blastocyst’s inner cell mass differentiate into the epiblast and primitive endoderm lineages, which give rise to the fetus and extra-embryonic tissues, respectively. Extra-embryonic endoderm differentiation can be modeled in vitro by induced expression of GATA transcription factors in mouse embryonic stem cells. Here we use this GATA-inducible system to quantitatively monitor the dynamics of global proteomic changes during the early stages of this differentiation event and also investigate the fully differentiated phenotype, as represented by embryo-derived extra-embryonic endoderm (XEN) cells. Using mass spectrometry-based quantitative proteomic profiling with multivariate data analysis tools, we reproducibly quantified 2,336 proteins across three biological replicates and have identified clusters of proteins characterized by distinct, dynamic temporal abundance profiles. We first used this approach to highlight novel marker candidates of the pluripotent state and extra-embryonic endoderm differentiation. Through functional annotation enrichment analysis, we have shown that the downregulation of chromatin-modifying enzymes, the re-organization of membrane trafficking machinery and the breakdown of cell-cell adhesion are successive steps of the extra-embryonic differentiation process. Thus, applying a range of sophisticated clustering approaches to a time-resolved proteomic dataset has allowed the elucidation of complex biological processes which characterize stem cell differentiation and could establish a general paradigm for the investigation of these processes.This work was supported by the European Union 7th Framework Program (PRIME-XS project grant number 262067 to K.S.L., L.G and C.M.M), the Biotechnology and Biological Sciences Research Council (BBSRC grant number BB/L002817/1 to K.S.L and L.G.), as well as a HFSP grant (RGP0029/2010) and a European Research Council (ERC) Advanced Investigator grant to A.M.A.. C.S was supported by an EMBO long term fellowship and a Marie Curie IEF. L.T.Y.C. and K.K.N. were supported by the Medical Research Council (MRC, UK, MC_UP_1202/9) and the March of Dimes Foundation (FY11-436). We also thank Professor Steve Oliver and Dr. A.K.Hadjantonakis for helpful discussions and advice.This is the author accepted manuscript. The final version is available from Wiley via http://dx.doi.org/10.1002/stem.206

Dynamic Proteomic Profiling of Extra-Embryonic Endoderm Differentiation in Mouse Embryonic Stem Cells.

During mammalian preimplantation development, the cells of the blastocyst's inner cell mass differentiate into the epiblast and primitive endoderm lineages, which give rise to the fetus and extra-embryonic tissues, respectively. Extra-embryonic endoderm (XEN) differentiation can be modeled in vitro by induced expression of GATA transcription factors in mouse embryonic stem cells. Here, we use this GATA-inducible system to quantitatively monitor the dynamics of global proteomic changes during the early stages of this differentiation event and also investigate the fully differentiated phenotype, as represented by embryo-derived XEN cells. Using mass spectrometry-based quantitative proteomic profiling with multivariate data analysis tools, we reproducibly quantified 2,336 proteins across three biological replicates and have identified clusters of proteins characterized by distinct, dynamic temporal abundance profiles. We first used this approach to highlight novel marker candidates of the pluripotent state and XEN differentiation. Through functional annotation enrichment analysis, we have shown that the downregulation of chromatin-modifying enzymes, the reorganization of membrane trafficking machinery, and the breakdown of cell-cell adhesion are successive steps of the extra-embryonic differentiation process. Thus, applying a range of sophisticated clustering approaches to a time-resolved proteomic dataset has allowed the elucidation of complex biological processes which characterize stem cell differentiation and could establish a general paradigm for the investigation of these processes.This work was supported by the European Union 7th Framework Program (PRIME-XS project grant number 262067 to K.S.L., L.G and C.M.M), the Biotechnology and Biological Sciences Research Council (BBSRC grant number BB/L002817/1 to K.S.L and L.G.), as well as a HFSP grant (RGP0029/2010) and a European Research Council (ERC) Advanced Investigator grant to A.M.A.. C.S was supported by an EMBO long term fellowship and a Marie Curie IEF. L.T.Y.C. and K.K.N. were supported by the Medical Research Council (MRC, UK, MC_UP_1202/9) and the March of Dimes Foundation (FY11-436). We also thank Professor Steve Oliver and Dr. A.K.Hadjantonakis for helpful discussions and advice.This is the author accepted manuscript. The final version is available from Wiley via http://dx.doi.org/10.1002/stem.206

Clinical and cost-effectiveness of contingency management for cannabis use in early psychosis: the CIRCLE randomised clinical trial

Cannabis is the most commonly used illicit substance amongst people with psychosis. Continued cannabis use following the onset of psychosis is associated with poorer functional and clinical outcomes. However, finding effective ways of intervening has been very challenging. We examined the clinical and cost-effectiveness of adjunctive contingency management (CM), which involves incentives for abstinence from cannabis use, in people with a recent diagnosis of psychosis. CIRCLE was a pragmatic multi-centre randomised controlled trial. Participants were recruited via Early Intervention in Psychosis (EIP) services across the Midlands and South East of England. They had had at least one episode of clinically diagnosed psychosis (affective or non-affective); were aged 18 to 36; reported cannabis use in at least 12 out of the previous 24 weeks; and were not currently receiving treatment for cannabis misuse, or subject to a legal requirement for cannabis testing. Participants were randomised via a secure web-based service 1:1 to either an experimental arm, involving 12 weeks of CM plus a six-session psychoeducation package, or a control arm receiving the psychoeducation package only. The total potential voucher reward in the CM intervention was £240. The primary outcome was time to acute psychiatric care, operationalised as admission to an acute mental health service (including community alternatives to admission). Primary outcome data were collected from patient records at 18 months post-consent by assessors masked to allocation. The trial was registered with the ISRCTN registry, number ISRCTN33576045. Five hundred fifty-one participants were recruited between June 2012 and April 2016. Primary outcome data were obtained for 272 (98%) in the CM (experimental) group and 259 (95%) in the control group. There was no statistically significant difference in time to acute psychiatric care (the primary outcome) (HR 1.03, 95% CI 0.76, 1.40) between groups. By 18 months, 90 (33%) of participants in the CM group, and 85 (30%) of the control groups had been admitted at least once to an acute psychiatric service. Amongst those who had experienced an acute psychiatric admission, the median time to admission was 196 days (IQR 82, 364) in the CM group and 245 days (IQR 99, 382) in the control group. Cost-effectiveness analyses suggest that there is an 81% likelihood that the intervention was cost-effective, mainly resulting from higher mean inpatient costs for the control group compared with the CM group; however, the cost difference between groups was not statistically significant. There were 58 adverse events, 27 in the CM group and 31 in the control group. Overall, these results suggest that CM is not an effective intervention for improving the time to acute psychiatric admission or reducing cannabis use in psychosis, at least at the level of voucher reward offered

Learning episodes in an intercultural virtual exchange: The case of social high-immersion virtual reality

Computer-mediated communication tools facilitate international collaboration projects between foreign language learners and peers abroad (O’Dowd, 2018). Social Virtual Reality (VR) applications allow for synchronous interactions and task-based communication in which learners can experience telepresence and immersion and conversate in a foreign language. Based on previous pilot experiences (Jauregi-Ondarra, Gruber, & Canto, 2020, 2021), this Virtual Exchange (VE) project aims to investigate how the specific affordances of Social High-immersion VR (SHiVR) in conjunction with designed tasks influence interaction patterns, and learning episodes. The VE took place between two groups of university students in the Netherlands (N=15) and Cyprus (N=14) through SHiVR in March 2022. The main aims of the tasks were to raise student intercultural awareness, stimulate task-based communication processes using English as a lingua franca and digital pedagogical competences of language education students. Different sources of data were gathered and analysed. In this paper, we describe and present the pedagogical experience and the initial result

An analysis of the quality of experimental design and reliability of results in tribology research

In recent years several high profile projects have questioned the repeatability and validity of scientific research in the fields of psychology and medicine. In general, these studies have shown or estimated that less than 50% of published research findings are true or replicable even when no breaches of ethics are made. This high percentage stems from widespread poor study design; either through the use of underpowered studies or designs that allow the introduction of bias into the results. In this work, we have aimed to assess, for the first time, the prevalence of good study design in the field of tribology. A set of simple criteria for factors such as randomisation, blinding, use of control and repeated tests has been made. These criteria have been used in a mass review of the output of five highly regarded tribology journals for the year 2017. In total 379 papers were reviewed by 26 reviewers, 28% of the total output of the journals selected for 2017. Our results show that the prevalence of these simple aspects of study design is poor. Out of 290 experimental studies, 2.2% used any form of blinding, 3.2% used randomisation of either the tests or the test samples, while none randomised both. 30% repeated experiments 3 or more times and 86% of those who repeated tests used single batches of test materials. 4.4% completed statistical tests on their data. Due to the low prevalence of repeated tests and statistical analysis it is impossible to give a realistic indication of the percentage of the published works that are likely to be false positives, however these results compare poorly to other more well studied fields. Finally, recommendations for improved study design for researchers and group design for research group leaders are given

Crisis resolution teams for people experiencing mental health crises: the CORE mixed-methods research programme including two RCTs

Background Crisis resolution teams (CRTs) seek to avert hospital admissions by providing intensive home treatment for people experiencing a mental health crisis. The CRT model has not been highly specified. CRT care is often experienced as ending abruptly and relapse rates following CRT discharge are high. Aims The aims of CORE (Crisis resolution team Optimisation and RElapse prevention) workstream 1 were to specify a model of best practice for CRTs, develop a measure to assess adherence to this model and evaluate service improvement resources to help CRTs implement the model with high fidelity. The aim of CORE workstream 2 was to evaluate a peer-provided self-management programme aimed at reducing relapse following CRT support. Methods Workstream 1 was based on a systematic review, national CRT manager survey and stakeholder qualitative interviews to develop a CRT fidelity scale through a concept mapping process with stakeholders (n = 68). This was piloted in CRTs nationwide (n = 75). A CRT service improvement programme (SIP) was then developed and evaluated in a cluster randomised trial: 15 CRTs received the SIP over 1 year; 10 teams acted as controls. The primary outcome was service user satisfaction. Secondary outcomes included CRT model fidelity, catchment area inpatient admission rates and staff well-being. Workstream 2 was a peer-provided self-management programme that was developed through an iterative process of systematic literature reviewing, stakeholder consultation and preliminary testing. This intervention was evaluated in a randomised controlled trial: 221 participants recruited from CRTs received the intervention and 220 did not. The primary outcome was re-admission to acute care at 1 year of follow-up. Secondary outcomes included time to re-admission and number of days in acute care over 1 year of follow-up and symptoms and personal recovery measured at 4 and 18 months’ follow-up. Results Workstream 1 – a 39-item CRT fidelity scale demonstrated acceptability, face validity and promising inter-rater reliability. CRT implementation in England was highly variable. The SIP trial did not produce a positive result for patient satisfaction [median Client Satisfaction Questionnaire score of 28 in both groups at follow-up; coefficient 0.97, 95% confidence interval (CI) –1.02 to 2.97]. The programme achieved modest increases in model fidelity. Intervention teams achieved lower inpatient admission rates and less inpatient bed use. Qualitative evaluation suggested that the programme was generally well received. Workstream 2 – the trial yielded a statistically significant result for the primary outcome, in which rates of re-admission to acute care over 1 year of follow-up were lower in the intervention group than in the control group (odds ratio 0.66, 95% CI 0.43 to 0.99; p = 0.044). Time to re-admission was lower and satisfaction with care was greater in the intervention group at 4 months’ follow-up. There were no other significant differences between groups in the secondary outcomes. Limitations Limitations in workstream 1 included uncertainty regarding the representativeness of the sample for the primary outcome and lack of blinding for assessment. In workstream 2, the limitations included the complexity of the intervention, preventing clarity about which were effective elements. Conclusions The CRT SIP did not achieve all its aims but showed potential promise as a means to increase CRT model fidelity and reduce inpatient service use. The peer-provided self-management intervention is an effective means to reduce relapse rates for people leaving CRT care. Study registration The randomised controlled trials were registered as Current Controlled Trials ISRCTN47185233 and ISRCTN01027104. The systematic reviews were registered as PROSPERO CRD42013006415 and CRD42017043048. Funding The National Institute for Health Research Programme Grants for Applied Research programme