Development and optimization of a hybridization technique to type the classical class I and class II B genes of the chicken MHC

The classical class I and class II molecules of the major histocompatibility complex (MHC) play crucial roles in immune responses to infectious pathogens and vaccines as well as being important for autoimmunity, allergy, cancer and reproduction. These classical MHC genes are the most polymorphic known, with roughly 10,000 alleles in humans. In chickens, the MHC (also known as the BF-BL region) determines decisive resistance and susceptibility to infectious pathogens, but relatively few MHC alleles and haplotypes have been described in any detail. We describe a typing protocol for classical chicken class I (BF) and class II B (BLB) genes based on a hybridization method called reference strand-mediated conformational analysis (RSCA). We optimize the various steps, validate the analysis using well-characterized chicken MHC haplotypes, apply the system to type some experimental lines and discover a new chicken class I allele. This work establishes a basis for typing the MHC genes of chickens worldwide and provides an opportunity to correlate with microsatellite and with single nucleotide polymorphism (SNP) typing for approaches involving imputation

Optimising the use of bio-loggers for movement ecology research

1.The paradigm‐changing opportunities of bio‐logging sensors for ecological research, especially movement ecology, are vast, but the crucial questions of how best to match the most appropriate sensors and sensor combinations to specific biological questions, and how to analyse complex bio‐logging data, are mostly ignored. 2.Here, we fill this gap by reviewing how to optimise the use of bio‐logging techniques to answer questions in movement ecology and synthesise this into an Integrated Bio‐logging Framework (IBF). 3.We highlight that multi‐sensor approaches are a new frontier in bio‐logging, whilst identifying current limitations and avenues for future development in sensor technology. 4.We focus on the importance of efficient data exploration, and more advanced multi‐dimensional visualisation methods, combined with appropriate archiving and sharing approaches, to tackle the big data issues presented by bio‐logging. We also discuss the challenges and opportunities in matching the peculiarities of specific sensor data to the statistical models used, highlighting at the same time the large advances which will be required in the latter to properly analyse bio‐logging data. 5.Taking advantage of the bio‐logging revolution will require a large improvement in the theoretical and mathematical foundations of movement ecology, to include the rich set of high‐frequency multivariate data, which greatly expand the fundamentally limited and coarse data that could be collected using location‐only technology such as GPS. Equally important will be the establishment of multi‐disciplinary collaborations to catalyse the opportunities offered by current and future bio‐logging technology. If this is achieved, clear potential exists for developing a vastly improved mechanistic understanding of animal movements and their roles in ecological processes, and for building realistic predictive models

Post-acute COVID-19 neuropsychiatric symptoms are not associated with ongoing nervous system injury

A proportion of patients infected with severe acute respiratory syndrome coronavirus 2 experience a range of neuropsychiatric symptoms months after infection, including cognitive deficits, depression and anxiety. The mechanisms underpinning such symptoms remain elusive. Recent research has demonstrated that nervous system injury can occur during COVID-19. Whether ongoing neural injury in the months after COVID-19 accounts for the ongoing or emergent neuropsychiatric symptoms is unclear. Within a large prospective cohort study of adult survivors who were hospitalized for severe acute respiratory syndrome coronavirus 2 infection, we analysed plasma markers of nervous system injury and astrocytic activation, measured 6 months post-infection: neurofilament light, glial fibrillary acidic protein and total tau protein. We assessed whether these markers were associated with the severity of the acute COVID-19 illness and with post-acute neuropsychiatric symptoms (as measured by the Patient Health Questionnaire for depression, the General Anxiety Disorder assessment for anxiety, the Montreal Cognitive Assessment for objective cognitive deficit and the cognitive items of the Patient Symptom Questionnaire for subjective cognitive deficit) at 6 months and 1 year post-hospital discharge from COVID-19. No robust associations were found between markers of nervous system injury and severity of acute COVID-19 (except for an association of small effect size between duration of admission and neurofilament light) nor with post-acute neuropsychiatric symptoms. These results suggest that ongoing neuropsychiatric symptoms are not due to ongoing neural injury

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

A Controlled Experiment of a Method for Early Requirements Triage Utilizing Product Strategies

[Context and motivation] In market-driven product development of software intensive products large numbers of requirements threaten to overload the development organization. It is critical for product management to select the requirements aligned with the overall business goals, product strategies and discard others as early as possible. Thus, there is a need for an effective and efficient method that deals with this challenge and supports product managers in the continuous effort of early requirements triage [1, 2] based on product strategies. This paper evaluates such a method - A Method for Early Requirements Triage Utilizing Product Strategies (MERTS), which is built based on the needs identified in literature and industry. [Question/problem] The research question answered in this paper is "If two groups of subjects have a product strategy, one group in NL format and one in MERTS format, will there be a difference between the two groups with regards to effectiveness and efficiency of requirements triage?" The effectiveness and efficiency of the MERTS were evaluated through controlled experiment in a lab environment with 50 software engineering graduate students as subjects. [Principal ideas/results] It was found through results that MERTS method is highly effective and efficient. [Contribution] The contribution of this paper is validation of effectiveness and efficiency of the product strategies created through MERTS method for requirements triage, prior to industry trials. A major limitation of the results is that the experiment was performed with the graduate students and not the product managers. However, the results showed that MERTS is ready for industry trials