Slides for a lightning talk presented as part of the Challenges in Professionalizing Data Stewardship Birds of a Feather (BoF) session. This session was due to be held at the Research Data Alliance (RDA) Plenary 15 in Melbourne, which was cancelled, so was held virtually online instead.

This Here we present an investigation into whether vocal timbre impacts on emotional perception of sung words, and whether this effect is intersubjective. That is, does vocal timbre influence the processing of emotion in words, and does it do so in a similar way across listeners? If so, this could help overcome the lack of appropriate analytical techniques for vocal timbre analysis in popular music by approaching such analysis from the perspective of vocal timbres emotive content and how this emotive content impacts emotional perception of sung words (lyrics), specifically in popular, lyric-based, vocal songs. The results of a reception test on emotional word perception according to timbre valence show that participants are significantly less accurate in identifying the emotional valence of words when they are sung with a vocal timbre that has an incongruent emotional valence and, for sad words, they are also slower in arriving at a correct identification of the word’s emotional valence when sung with an emotionally incongruent timbre. This supports the hypothesis that timbre conveys emotional meaning and that the experience of vocal timbre may be intersubjective.

Purpose: People enjoy supervision during visual field assessment, although resource demands often make this difficult. We evaluated outcomes and subjective experience of methods of receiving feedback during perimetry, with specific goals to compare a humanoid robot to a computerized voice in participants with minimal prior perimetric experience. Human feedback and no feedback also were compared. Methods: Twenty-two younger (aged 21-31 years) and 18 older (aged 52-76 years) adults participated. Visual field tests were conducted using an Octopus 900, controlled with the Open Perimetry Interface. Participants underwent four tests with the following feedback conditions: (1) human, (2) humanoid robot, (3) computer speaker, and (4) no feedback, in random order. Feedback rules for the speaker and robot were identical, with the difference being a social interaction with the robot before the test. Quantitative perimetric performance compared mean sensitivity (dB), fixation losses, and false-positives. Subjective experience was collected via survey. Results: There was no significant effect of feedback type on the quantitative measures. For younger adults, the human and robot were preferred to the computer speaker (P < 0.01). For older adults, the experience rating was similar for the speaker and robot. No feedback was the least preferred option of 77% younger and 50% older adults. Conclusions: During perimetry, a social robot was preferred to a computer speaker providing the same feedback, despite the robot not being visible during the test. Making visual field testing more enjoyable for patients and operators may improve compliance and attitude to perimetry, leading to improved clinical outcomes. Translational Relevance: Our data suggest that humanoid robots can replace some aspects of human interaction during perimetry and are preferable to receiving no human feedback.

Ubiquitous expression of mutant Cu/Zn-superoxide dismutase (SOD1) selectively affects motor neurons in the central nervous system (CNS), causing the adult-onset degenerative disease amyotrophic lateral sclerosis (ALS). The CNS-specific impact of ubiquitous mutant SOD1 expression is recapitulated in transgenic mouse models of the disease. Here we present outcomes for the metallo-complex CuII(atsm) tested for therapeutic efficacy in mice expressing SOD1G93A on a mixed genetic background. Oral administration of CuII(atsm) delayed the onset of neurological symptoms, improved locomotive capacity and extended overall survival. Although the ALS-like phenotype of SOD1G93A mice is instigated by expression of the mutant SOD1, we show the improved phenotype of the CuII(atsm)-treated animals involves an increase in mature mutant SOD1 protein in the disease-affected spinal cord, where concomitant increases in copper and SOD1 activity are also evident. In contrast to these effects in the spinal cord, treating with CuII(atsm) had no effect in liver on either mutant SOD1 protein levels or its activity, indicating a CNS-selective SOD1 response to the drug. These data provide support for CuII(atsm) as a treatment option for ALS as well as insight to the CNS-selective effects of mutant SOD1.

It is increasingly recognized that Alzheimer's disease (AD) exists before dementia is present and that shifts in amyloid beta occur long before clinical symptoms can be detected. Early detection of these molecular changes is a key aspect for the success of interventions aimed at slowing down rates of cognitive decline. Recent evidence indicates that of the two established methods for measuring amyloid, a decrease in cerebrospinal fluid (CSF) amyloid β1-42 (Aβ1-42) may be an earlier indicator of Alzheimer's disease risk than measures of amyloid obtained from Positron Emission Tomography (PET). However, CSF collection is highly invasive and expensive. In contrast, blood collection is routinely performed, minimally invasive and cheap. In this work, we develop a blood-based signature that can provide a cheap and minimally invasive estimation of an individual's CSF amyloid status using a machine learning approach. We show that a Random Forest model derived from plasma analytes can accurately predict subjects as having abnormal (low) CSF Aβ1-42 levels indicative of AD risk (0.84 AUC, 0.78 sensitivity, and 0.73 specificity). Refinement of the modeling indicates that only APOEε4 carrier status and four plasma analytes (CGA, Aβ1-42, Eotaxin 3, APOE) are required to achieve a high level of accuracy. Furthermore, we show across an independent validation cohort that individuals with predicted abnormal CSF Aβ1-42 levels transitioned to an AD diagnosis over 120 months significantly faster than those with predicted normal CSF Aβ1-42 levels and that the resulting model also validates reasonably across PET Aβ1-42 status (0.78 AUC). This is the first study to show that a machine learning approach, using plasma protein levels, age and APOEε4 carrier status, is able to predict CSF Aβ1-42 status, the earliest risk indicator for AD, with high accuracy.

The Protein Folding Database (PFD) is a publicly accessible repository of thermodynamic and kinetic protein folding data. Here we describe the first major revision of this work, featuring extensive restructuring that conforms to standards set out by the recently formed International Foldeomics Consortium. The database now adopts standards for data acquisition, analysis and reporting proposed by the consortium, which will facilitate the comparison of folding rates, energies and structure across diverse sets of proteins. Data can now be easily deposited using a rich set of deposition tools. Enhanced search tools allow sophisticated searching and graphical data analysis affords simple data analysis online. PFD can be accessed freely at http://www.foldeomics.org/pfd/.

BACKGROUND: Knowledge of phase, the specific allele sequence on each copy of homologous chromosomes, is increasingly recognized as critical for detecting certain classes of disease-associated mutations. One approach for detecting such mutations is through phased haplotype association analysis. While the accuracy of methods for phasing genotype data has been widely explored, there has been little attention given to phasing accuracy at haplotype block scale. Understanding the combined impact of the accuracy of phasing tool and the method used to determine haplotype blocks on the error rate within the determined blocks is essential to conduct accurate haplotype analyses. RESULTS: We present a systematic study exploring the relationship between seven widely used phasing methods and two common methods for determining haplotype blocks. The evaluation focuses on the number of haplotype blocks that are incorrectly phased. Insights from these results are used to develop a haplotype estimator based on a consensus of three tools. The consensus estimator achieved the most accurate phasing in all applied tests. Individually, EAGLE2, BEAGLE and SHAPEIT2 alternate in being the best performing tool in different scenarios. Determining haplotype blocks based on linkage disequilibrium leads to more correctly phased blocks compared to a sliding window approach. We find that there is little difference between phasing sections of a genome (e.g. a gene) compared to phasing entire chromosomes. Finally, we show that the location of phasing error varies when the tools are applied to the same data several times, a finding that could be important for downstream analyses. CONCLUSIONS: The choice of phasing and block determination algorithms and their interaction impacts the accuracy of phased haplotype blocks. This work provides guidance and evidence for the different design choices needed for analyses using haplotype blocks. The study highlights a number of issues that may have limited the replicability of previous haplotype analysis.

Mucosal-associated invariant T (MAIT) cells represent up to 10% of circulating human T cells. They are usually defined using combinations of non-lineage-specific (surrogate) markers such as anti-TRAV1-2, CD161, IL-18Rα and CD26. The development of MR1-Ag tetramers now permits the specific identification of MAIT cells based on T-cell receptor specificity. Here, we compare these approaches for identifying MAIT cells and show that surrogate markers are not always accurate in identifying these cells, particularly the CD4+ fraction. Moreover, while all MAIT cell subsets produced comparable levels of IFNγ, TNF and IL-17A, the CD4+ population produced more IL-2 than the other subsets. In a human ontogeny study, we show that the frequencies of most MR1 tetramer+ MAIT cells, with the exception of CD4+ MAIT cells, increased from birth to about 25 years of age and declined thereafter. We also demonstrate a positive association between the frequency of MAIT cells and other unconventional T cells including Natural Killer T (NKT) cells and Vδ2+ γδ T cells. Accordingly, this study demonstrates that MAIT cells are phenotypically and functionally diverse, that surrogate markers may not reliably identify all of these cells, and that their numbers are regulated in an age-dependent manner and correlate with NKT and Vδ2+ γδ T cells.

Mucosal-associated invariant T (MAIT) cells express an invariant TRAV1/TRAJ33 TCR-α chain and are restricted to the MHC-I-like molecule, MR1. Whether MAIT cell development depends on this invariant TCR-α chain is unclear. Here we generate Traj33-deficient mice and show that they are highly depleted of MAIT cells; however, a residual population remains and can respond to exogenous antigen in vitro or pulmonary Legionella challenge in vivo. These residual cells include some that express Trav1+ TCRs with conservative Traj-gene substitutions, and others that express Trav1- TCRs with a broad range of Traj genes. We further report that human TRAV1-2- MR1-restricted T cells contain both MAIT-like and non-MAIT-like cells, as judged by their TCR repertoire, antigen reactivity and phenotypic features. These include a MAIT-like population that expresses a public, canonical TRAV36+ TRBV28+ TCR. Our findings highlight the TCR diversity and the resulting potential impact on antigen recognition by MR1-restricted T cells.

Pre-treatment screening of individuals for human leukocyte antigens (HLA) HLA-B*57:01 is recommended for the prevention of life-threatening hypersensitivity reactions to abacavir, a drug widely prescribed for HIV treatment. However, the implementation of screening in clinical practice is hindered by the slow turnaround time and high cost of conventional HLA genotyping methods. We have developed a biosensor platform using interdigitated electrode (IDE) functionalized with a monoclonal antibody to detect cells expressing HLA-B*57:01. This platform was evaluated using cell lines and peripheral blood mononuclear cells expressing different HLA-B alleles. The functionalized IDE sensor was able to specifically capture HLA-B*57:01 cells, resulting in a significant change in the impedance magnitude in 20 min. This IDE platform has the potential to be further developed to enable point-of-care HLA-B*57:01 screening

Invasive streptococcal disease (ISD) and toxic shock syndrome (STSS) result in over 160,000 deaths each year. We modelled these in HLA-transgenic mice infected with a clinically lethal isolate expressing Streptococcal pyrogenic exotoxin (Spe) C and demonstrate that both SpeC and streptococcal M protein, acting cooperatively, are required for disease. Vaccination with a conserved M protein peptide, J8, protects against STSS by causing a dramatic reduction in bacterial burden associated with the absence of SpeC and inflammatory cytokines in the blood. Furthermore, passive immunotherapy with antibodies to J8 quickly resolves established disease by clearing the infection and ablating the inflammatory activity of the M protein, which is further enhanced by addition of SpeC antibodies. Analysis of 77 recent isolates of Streptococcus pyogenes causing ISD, demonstrated that anti-J8 antibodies theoretically recognize at least 73, providing strong support for using antibodies to J8, with or without antibodies to SpeC, as a therapeutic approach.

Purpose: We determine the feasibility of using a home-based tablet device to monitor retinal sensitivity (RS) in intermediate age-related macular degeneration (iAMD), the benefits of weekly reminders, and the comparison with clinic-based results. Methods: A customized test for tablets was designed to measure RS (within central 2°) in individuals with iAMD at weekly intervals in their home, with remote data collection. Half of the participants were randomized to receive weekly test reminders. Clinic-based microperimetric macular sensitivity results were compared to tablet results. Participation rates were analyzed at 2 months. Results: Of 38 participants (mean age, 70.3 years) with iAMD enrolled in the study, 21 (55%) were using the tablet-based test at 2 months. Common reasons for inactivity were noncompatible devices (41.1%) or other technology access issues (35.3%). Participants with weekly reminders completed tests more regularly (6.6 ± 3.9 vs. 8.7 ± 4.1 days, P = 0.01), but weekly reminders showed no effect on participation rates (P = 0.69). Mean RS from the tablet device (25.03 ± 2.41 dB) was not significantly different from the clinic-based microperimetry performance (25.21 ± 2.20 dB; P = 0.58). Conclusions: Regular monitoring of retinal function on a tablet device in a home setting in individuals with iAMD is feasible with results comparable to those of clinic-based microperimetry. Weekly reminders resulted in more frequent testing. Seamless ability to access technology will be important for higher participation rates. Translational Relevance: The use of home-monitoring on a tablet-device is promising, but adequate support for an older cohort to take up technology is required if such a tool is to be useful for long-term home monitoring.