HLA typing: Conventional techniques v. next-generation sequencing

Background. The large number of population-specific polymorphisms present in the HLA complex in the South African (SA) population reduces the probability of finding an adequate HLA-matched donor for individuals in need of an unrelated haematopoietic stem cell transplantation (HSCT). Next-generation sequencing (NGS) has numerous advantages compared with conventional typing techniques.Objective. To evaluate whether NGS can provide any additional value over conventional techniques in the SA context for the purpose of HSCT and cord blood banking.Methods. HLA genotyping was performed using NGS on 20 samples that had previously been HLA typed by conventional methods to evaluate whether NGS might provide any additional value over conventional HLA determination techniques.Results. NGS of routinely sequenced loci and exons yielded accurate genotypes for 98.5% of the five loci of interest, compared with 98% when additional exons were included.Conclusion. The study shows that the additional value of NGS over conventional techniques is limited, and unless done on a large scale to reduce cost may not be appropriate in SA at this stage in the context of HSCT and cord blood banking

Examining whether exposure to external information influences perceptions of increased crime at an Olympic Games host destination: The case of London 2012

Risks associated with the Olympic Games have been studied; however, there is a lack of research that empirically examines whether exposure to external information influences prospective tourists’ destination risk perceptions. A survey of 1,200 British, Australian, and Canadian residents was conducted to examine factors that influence prospective tourists’ perceptions of increased crime in London during the 2012 Summer Olympic Games. The age group 55-64 was a significant predictor, while other age groups, income, and gender were not significant predictors. While controlling for demographics, past experience traveling to London and attending the Games were not significant predictors. Travel advisories and reading about the London riots were significant predictors, while watching television coverage of the riots and reading social media messages related to crises in London were not significant predictors while controlling for demographics and past experience. Lastly, travel risk perceptions were a significant predictor, while controlling for the previous independent variables

Mutual information rate and bounds for it

The amount of information exchanged per unit of time between two nodes in a dynamical network or between two data sets is a powerful concept for analysing complex systems. This quantity, known as the mutual information rate (MIR), is calculated from the mutual information, which is rigorously defined only for random systems. Moreover, the definition of mutual information is based on probabilities of significant events. This work offers a simple alternative way to calculate the MIR in dynamical (deterministic) networks or between two data sets (not fully deterministic), and to calculate its upper and lower bounds without having to calculate probabilities, but rather in terms of well known and well defined quantities in dynamical systems. As possible applications of our bounds, we study the relationship between synchronisation and the exchange of information in a system of two coupled maps and in experimental networks of coupled oscillators

Cracking the Code: The Systematic Development of a Matrix to Increase Credible and Dependable Coding of Qualitative Data

A systematic, credible, and dependable coding matrix was developed to deductively code the qualitative data from the Clinician’s Perceptions of Infusing Coaching into their Occupational Therapy Practice study (CPIC). A coding matrix is used to organize qualitative data into meaningful units of text to be interpreted by the researchers. Codes for this project were deductively organized under categories from Roger’s Diffusion of Innovation Theory (RDIT), a framework that identifies how a new idea is adopted in practice. Five preliminary coders, with one leading the process, participated in the development of the coding matrix to reduce the risk of bias influencing the coding of the data. There was a total of ten rounds of preliminary coding necessary to develop the coding matrix. Two preliminary coders\u27 coding was considered and analyzed for each round of coding. After each round of coding had occurred, the lead coder calculated percentages agreement and analyzed similarities and discrepancies between coders. Then, the preliminary coders met to discuss codes, discrepancies, agreements, and definitions. New preliminary coders were integrated into the coding matrix development process at intervals to enhance the clarity of the coding matrix. The results was the creation of a systematic, credible, and dependable coding matrix with 80% interrater reliability. Coding ended at the tenth round when no additional categories or codes emerged from the data. The coding matrix includes definitions of categories and codes, examples of codes, and coding notes. The completed coding matrix will be used to code the transcripts in the CPIC study. Synopsis: Through this project, an organized list of codes by categories, or coding matrix, was developed for the Clinician’s Perceptions of Infusing Coaching into Practice study. A systematic and rigorous process was used to increase the credibility and dependability of the coding matrix. The process included an audit trail, multiple preliminary coders, preliminary coding data analysis, and a reflexivity journal. Acknowledgments: The authors thank for their contributions to this project, Dr. Namrata Grampurohit, Dr. Nicole Gerhardt, Dr. Vikita Patel and Dr. Marissa LaSalle, as well as students: Kyndall Scheffey, OTS, Hannah Berry MSOT, SROT, and Rachel Smith MSOT, OTR/

Fast, scalable, Bayesian spike identification for multi-electrode arrays

We present an algorithm to identify individual neural spikes observed on high-density multi-electrode arrays (MEAs). Our method can distinguish large numbers of distinct neural units, even when spikes overlap, and accounts for intrinsic variability of spikes from each unit. As MEAs grow larger, it is important to find spike-identification methods that are scalable, that is, the computational cost of spike fitting should scale well with the number of units observed. Our algorithm accomplishes this goal, and is fast, because it exploits the spatial locality of each unit and the basic biophysics of extracellular signal propagation. Human intervention is minimized and streamlined via a graphical interface. We illustrate our method on data from a mammalian retina preparation and document its performance on simulated data consisting of spikes added to experimentally measured background noise. The algorithm is highly accurate

Optimising recruitment in clinical trials for progressive multiple sclerosis: observational analysis from the MS-SMART and MS-STAT2 randomised controlled trials

BACKGROUND: Slower than planned recruitment is a major factor contributing to the delay or failure of randomised controlled trials to report on time. There is a limited evidence base regarding the optimisation of recruitment strategies. Here we performed an observational review of our experience in recruitment for two large randomised controlled trials for people with secondary progressive multiple sclerosis. We aimed to explicitly determine those factors which can facilitate trial recruitment in progressive neurodegenerative disease. METHODS: Recruitment data from the sequential MS-SMART [NCT01910259] and MS-STAT2 [NCT03387670] UK randomised controlled trials was reviewed from the largest recruiting site, University College London (UCL). The trial population was similar which allowed comparison over the two recruitment periods of 2015-2016 and 2018-2021. This included sources of referral, progress through stages of recruitment, reasons for participant ineligibility and the impact of publicity events upon recruitment. RESULTS: In MS-SMART, 18% of patients contacted were enrolled, compared to 27% for MS-STAT2. Online registration of interest portals provided the greatest number of referrals (76% in MS-SMART, and 51% in MS-STAT2), with publicity in national media outlets producing a demonstrable increase in the number of potential participants. The introduction of an online self-screening questionnaire for MS-STAT2 resulted in 67% of potential participants (3080 of 4605) automatically determining their own ineligibility. In both studies, however, around 60% of those directly telephoned to discuss the study were not eligible, with difficulties related to travel to trial visits, or excluded medication, being the most common issues. Eighty-four percent of those deemed potentially eligible following telephone calls were enrolled in the MS-STAT2 study, compared to only 55% for MS-SMART. CONCLUSIONS: Through a detailed review of recruiting participants at the largest centre into two large randomised controlled trials with similar entry criteria, we have identified a number of approaches that may improve recruitment efficiency. We highlight here the importance of mandatory online self-screening questionnaires, a coordinated publicity campaign, and simple interventions such as eligibility checklists and appointment reminders. Recruitment approaches should be further assessed through a studies within a trial (SWAT) design. TRIAL REGISTRATION: MS-SMART: NCT01910259 ; registered July 2013 and MS-STAT2: NCT03387670 ; registered Jan 2018

Self-repair ability of evolved self-assembling systems in cellular automata

Self-repairing systems are those that are able to reconfigure themselves following disruptions to bring them back into a defined normal state. In this paper we explore the self-repair ability of some cellular automata-like systems, which differ from classical cellular automata by the introduction of a local diffusion process inspired by chemical signalling processes in biological development. The update rules in these systems are evolved using genetic programming to self-assemble towards a target pattern. In particular, we demonstrate that once the update rules have been evolved for self-assembly, many of those update rules also provide a self-repair ability without any additional evolutionary process aimed specifically at self-repair

Type discrimination of Various Welding Defects Created During Production and In-Service Use

Verification of the quality of welded structures, both post-production and in-service, has long been a concern of the engineering, materials and nondestructive communities. Nondestructive techniques have been developed and refined to address this verification problem. Each technique has inherent limitations, however, that in certain situations preclude its use or severely restrict the type of information that may be obtained particularly concerning the flaw type. Of these techniques, x-ray investigation is probably the most versatile in determining flaw type and size at present. The equipment required for x-ray examination, however, place constraints on its use, particularly for in-service structures, from the standpoint of accessibility and personnel safety.</p

Reputation Agent: Prompting Fair Reviews in Gig Markets

Our study presents a new tool, Reputation Agent, to promote fairer reviews from requesters (employers or customers) on gig markets. Unfair reviews, created when requesters consider factors outside of a worker's control, are known to plague gig workers and can result in lost job opportunities and even termination from the marketplace. Our tool leverages machine learning to implement an intelligent interface that: (1) uses deep learning to automatically detect when an individual has included unfair factors into her review (factors outside the worker's control per the policies of the market); and (2) prompts the individual to reconsider her review if she has incorporated unfair factors. To study the effectiveness of Reputation Agent, we conducted a controlled experiment over different gig markets. Our experiment illustrates that across markets, Reputation Agent, in contrast with traditional approaches, motivates requesters to review gig workers' performance more fairly. We discuss how tools that bring more transparency to employers about the policies of a gig market can help build empathy thus resulting in reasoned discussions around potential injustices towards workers generated by these interfaces. Our vision is that with tools that promote truth and transparency we can bring fairer treatment to gig workers.Comment: 12 pages, 5 figures, The Web Conference 2020, ACM WWW 202

On directed information theory and Granger causality graphs

Directed information theory deals with communication channels with feedback. When applied to networks, a natural extension based on causal conditioning is needed. We show here that measures built from directed information theory in networks can be used to assess Granger causality graphs of stochastic processes. We show that directed information theory includes measures such as the transfer entropy, and that it is the adequate information theoretic framework needed for neuroscience applications, such as connectivity inference problems.Comment: accepted for publications, Journal of Computational Neuroscienc