Does 'playtime' reduce stimulus-seeking and other boredom-like behaviour in laboratory ferrets?

Much environmental enrichment for laboratory animals is intended to enhance animal welfare and normalcy by providing stimulation to reduce 'boredom'. Behavioural manifestations of boredom include restless sensation-seeking behaviours combined with indicators of sub-optimal arousal. Here we explored whether these signs could be reduced by extra daily play opportunity in laboratory ferrets. Specifically, we hypothesised that playtime would reduce restlessness, aggression, sensation-seeking and awake drowsiness, even 24h later in the homecage. Female ferrets (n = 14) were group housed in enriched multi-level cages. Playtime involved exploring a room containing a ball pool, paper bags, balls containing bells, and a familiar interactive human for 1h. This was repeated on three consecutive mornings, and on the fourth morning, homecage behaviour was compared between ferrets who had experienced the playtime treatment versus control cagemates who had not. Their investigation of stimuli (positive = mouse odour or ball; ambiguous = empty bottle or tea-strainer; and negative = peppermint or bitter apple odour) was also recorded. We then swapped treatments, creating a paired experimental design. Ferrets under control conditions lay awake with their eyes open and screeched significantly more, but slept and sat/stood less, than following playtime. They also contacted negative and ambiguous stimuli significantly more under control conditions than they did following playtime; contact with positive stimuli showed no effects. Attempts to blind the observer to treatments were unsuccessful, so replication is required, but the findings suggest that playtime may have reduced both sub-optimal arousal and restless sensation seeking behaviour, consistent with reducing boredom.

Use of Whole-Genome Sequencing in the Investigation of a Nosocomial Influenza Virus Outbreak.

Traditional epidemiological investigation of nosocomial transmission of influenza involves the identification of patients who have the same influenza virus type and who have overlapped in time and place. This method may misidentify transmission where it has not occurred or miss transmission when it has. We used influenza virus whole-genome sequencing (WGS) to investigate an outbreak of influenza A virus infection in a hematology/oncology ward and identified 2 separate introductions, one of which resulted in 5 additional infections and 79 bed-days lost. Results from WGS are becoming rapidly available and may supplement traditional infection control procedures in the investigation and management of nosocomial outbreaks.

Emergence of a novel subclade of influenza A(H3N2) virus in London, December 2016 to January 2017.

We report the molecular investigations of a large influenza A(H3N2) outbreak, in a season characterised by sharp increase in influenza admissions since December 2016. Analysis of haemagglutinin (HA) sequences demonstrated co-circulation of multiple clades (3C.3a, 3C.2a and 3C.2a1). Most variants fell into a novel subclade (proposed as 3C.2a2); they possessed four unique amino acid substitutions in the HA protein and loss of a potential glycosylation site. These changes potentially modify the H3N2 strain antigenicity.

Big Data Analytics, Infectious Diseases and Associated Ethical Impacts.

The exponential accumulation, processing and accrual of big data in healthcare are only possible through an equally rapidly evolving field of big data analytics. The latter offers the capacity to rationalize, understand and use big data to serve many different purposes, from improved services modelling to prediction of treatment outcomes, to greater patient and disease stratification. In the area of infectious diseases, the application of big data analytics has introduced a number of changes in the information accumulation models. These are discussed by comparing the traditional and new models of data accumulation. Big data analytics is fast becoming a crucial component for the modelling of transmission-aiding infection control measures and policies-emergency response analyses required during local or international outbreaks. However, the application of big data analytics in infectious diseases is coupled with a number of ethical impacts. Four key areas are discussed in this paper: (i) automation and algorithmic reliance impacting freedom of choice, (ii) big data analytics complexity impacting informed consent, (iii) reliance on profiling impacting individual and group identities and justice/fair access and (iv) increased surveillance and population intervention capabilities impacting behavioural norms and practices. Furthermore, the extension of big data analytics to include information derived from personal devices, such as mobile phones and wearables as part of infectious disease frameworks in the near future and their potential ethical impacts are discussed. Considered together, the need for a constructive and transparent inclusion of ethical questioning in this rapidly evolving field becomes an increasing necessity in order to provide a moral foundation for the societal acceptance and responsible development of the technological advancement.

A high HIV-1 strain variability in London, UK, revealed by full-genome analysis: Results from the ICONIC project.

BACKGROUND & METHODS: The ICONIC project has developed an automated high-throughput pipeline to generate HIV nearly full-length genomes (NFLG, i.e. from gag to nef) from next-generation sequencing (NGS) data. The pipeline was applied to 420 HIV samples collected at University College London Hospitals NHS Trust and Barts Health NHS Trust (London) and sequenced using an Illumina MiSeq at the Wellcome Trust Sanger Institute (Cambridge). Consensus genomes were generated and subtyped using COMET, and unique recombinants were studied with jpHMM and SimPlot. Maximum-likelihood phylogenetic trees were constructed using RAxML to identify transmission networks using the Cluster Picker. RESULTS: The pipeline generated sequences of at least 1Kb of length (median = 7.46Kb, IQR = 4.01Kb) for 375 out of the 420 samples (89%), with 174 (46.4%) being NFLG. A total of 365 sequences (169 of them NFLG) corresponded to unique subjects and were included in the down-stream analyses. The most frequent HIV subtypes were B (n = 149, 40.8%) and C (n = 77, 21.1%) and the circulating recombinant form CRF02_AG (n = 32, 8.8%). We found 14 different CRFs (n = 66, 18.1%) and multiple URFs (n = 32, 8.8%) that involved recombination between 12 different subtypes/CRFs. The most frequent URFs were B/CRF01_AE (4 cases) and A1/D, B/C, and B/CRF02_AG (3 cases each). Most URFs (19/26, 73%) lacked breakpoints in the PR+RT pol region, rendering them undetectable if only that was sequenced. Twelve (37.5%) of the URFs could have emerged within the UK, whereas the rest were probably imported from sub-Saharan Africa, South East Asia and South America. For 2 URFs we found highly similar pol sequences circulating in the UK. We detected 31 phylogenetic clusters using the full dataset: 25 pairs (mostly subtypes B and C), 4 triplets and 2 quadruplets. Some of these were not consistent across different genes due to inter- and intra-subtype recombination. Clusters involved 70 sequences, 19.2% of the dataset. CONCLUSIONS: The initial analysis of genome sequences detected substantial hidden variability in the London HIV epidemic. Analysing full genome sequences, as opposed to only PR+RT, identified previously undetected recombinants. It provided a more reliable description of CRFs (that would be otherwise misclassified) and transmission clusters.

Near Full-length Genomic Sequencing and Molecular Analysis of HIV-Infected Individuals in a Network-based Intervention (TRIP) in Athens, Greece: Evidence that Transmissions Occur More Frequently from those with High HIV-RNA.

BACKGROUND: TRIP (Transmission Reduction Intervention Project) was a network-based, contact tracing approach to locate and link to care, mostly people who inject drugs (PWID) with recent HIV infection. OBJECTIVE: We investigated whether sequences from HIV-infected participants with high viral load cluster together more frequently than what is expected by chance. METHODS: Paired end reads were generated for 104 samples using Illumina MiSeq next-generation sequencing. RESULTS: 63 sequences belonged to previously identified local transmission networks of PWID (LTNs) of an HIV outbreak in Athens, Greece. For two HIV-RNA cut-offs (105 and 106 IU/mL), HIV transmissions were more likely between PWID with similar levels of HIV-RNA (p<0.001). 10 of the 14 sequences (71.4%) from PWID with HIV-RNA >106 IU/mL were clustered in 5 pairs. For 4 of these clusters (80%), there was in each one of them at least one sequence from a recently HIVinfected PWID. CONCLUSION: We showed that transmissions are more likely among PWID with high viremia.