Collaborations Workshop 2018 - Lightning talk - James Baker

Presentation during Collaborations Workshop 2018, https://www.software.ac.uk/cw18

Summary of drug dosage and combinations reported.

<p>Summary of drug dosage and combinations reported.</p

Inclusion and exclusion criteria for systematic search.

<p>Inclusion and exclusion criteria for systematic search.</p

Search strategy and results of each search (Capital letters = term from database thesaurus i.e. MeSH).

<p>Search strategy and results of each search (Capital letters = term from database thesaurus i.e. MeSH).</p

PRISMA flowchart.

<p>PRISMA flowchart.</p

Additional file 6: Figure S3. of Charged residues next to transmembrane regions revisited: “Positive-inside rule” is complemented by the “negative inside depletion/outside enrichment rule”

Relative percentage heatmaps from the predictive datasets calculated by fractions of the absolute maximum and by the relative percentage of a given amino acid type. The residue position aligned to the centre of the TMH is on the horizontal axis, and the residue type is on the vertical axis. Amino acid types are listed in order of decreasing hydrophobicity according to the Kyte and Doolittle scale [52]. The flank lengths in the TMH segments were restricted to up to ±5 residues. The scales for each heatmap are shown beneath the respective subfigure. All TMHs and flank lengths are from the UniHuman dataset. (A) The heatmap has been coloured according to a scale that uses column-wise normalisations used in previous studies [9]. See Eq. (1) in the Methods section. As an illustrative example, we show how the value for E at position ±12 is obtained. There are in total 91/22 Es at these positions in 1705 sequences; thus, the represented value is 0.013 at –12 and 0.053 at 12. Note that L is clearly a hotspot as well as trends for other hydrophobic residues, I and V, as is to be expected. A positive inside effect can also be seen. (B) The heatmap has been coloured according to the relative percentage of each amino acid type. Here, 91/22 Es at position ±12 are compared with 615 Es seen within the flanks and the TMH section itself amongst all sequences in the alignment. So, the expectation of an E at position ±12 if there is any E in the TMH + flanks region at all is 0.036 at –12 and 0.148 at position 12. With this type of normalisation, not surprisingly, we see the positive-inside rule is hotter than in subfigure A. There are also hotspots in the flanks for the negatively charged residues on the outside flank. The leucine hotspot is no longer very pronounced, as the leucines are quite evenly spread over many positions. (PDF 120 kb

Pace versus prediction: Implications of age, experience and sex on marathon race performance

PURPOSE: Pacing strategies during exercise are attributed to optimising the balance between the artefacts of fatigue and regulation of substrate metabolism. Pace judgement is set within a continuum of information from the ability to anticipate metabolic demands and select an appropriate strategy through to the accumulation of prior experience for completion of such a task that has a known end-point. Therefore the purpose of this study was evaluate the factors which contribute to successfully regulating pace and attaining a predicted end time during a marathon. METHOD: Following local institutional ethical approval n= 777 runners competing in the 2015 London Marathon of which n= 393 were females and n= 384 were males participated. Using an on-line survey and opportunistic questionnaires at a pre-marathon event participants were asked to predict their race time. Athlete experience (EXP) was established based on the number of previously completed marathons using a Likert scale from 0 to greater than 10 with increments of 1 race. Age was stratified according to those adopted by the marathon organisers: 18-39yrs, 40-49yrs, 50-59yrs and >60yrs. 5Km split times were converted to speed and normalised (%) to the final split time/speed (m.s-1). Prediction time (PT) was used a proxy for end-point and compared to finish time (FT). RESULTS: FT for whole group (WG) was 15479 ± 3311s compared to the group PT 15003 ± 2972s a significant difference of 476s (P= 0.0001). An R2 of 0.863 observed for WG compared to 0.799 (0-EXP) and 0.852 (EXP-5) when comparing FT to PT. 0-EXP showed significant difference across all split times apart from 35-40 km (P=0.0001) with a decrease in normalised speed from 5km (109.0 ± 7.6) – 40km (89.9 ± 7.4%). The 5-EXP group showed significant changes in pace between 25-30 km (P= 0.001) (ES =0.35), 30-35 km (P= 0.0001) (ES= 0.44) and 35-40 km (P= 0.0001), decrease in pace from 5km (105.0 ± 5.7%) to 40km (93.7 ± 5.6%). Large effect sizes (ES) observed for 18-39yrs at 30-35km (r= 0.370), 40-49yrs at 30-35km (r= 0.337), 50-59yrs at 25-30km (r= 0.368) and 30-35km (r= 0.418) and >60yrs at 30-35km (r= 0.527). A significant difference (P= 0.0001) of 476s was observed between PT and FT for the whole group compared to differences of 531 s (p= 0.000) and 419s (P= 0.000) for the males and females respectively. CONCLUSIONS: These data suggest that successful marathon pacing is dependent on the experience of the athlete reflecting the development of the pacing template. Additionally experience is associated with better attainment of prediction time suggesting that less experienced runners should run with more experienced athletes with similar end-point targets

Data_Sheet_1_Social prescribing of nature therapy for adults with mental illness living in the community: A scoping review of peer-reviewed international evidence.pdf

Social prescribing of nature therapy “green social prescribing” facilitates access to local nature-based activities that improve biopsychosocial wellbeing outcomes, are affordable, accessible, and can be adapted to context. These are becoming increasingly popular and gray literature is emerging, however, peer-reviewed scientific evidence is exiguous. This scoping review aimed to identify and critique peer-reviewed evidence for green social prescribing interventions and develop recommendations for research and clinical practice. Included studies were published in peer-reviewed journals in English on/after 1 January 2000. Participants were community-living adults with mental illness; Intervention was any green social prescribing program; Comparator was not restricted/required; Outcomes were any biopsychosocial measures; and any/all Study Designs were included. Twelve databases were searched on 15 October 2022; these were Academic Search Premier, APA PsycArticles, APA PsycINFO, CINAHL, Cochrane Library, Google Scholar, JSTOR, ProQuest, PubMed, Science Direct, Scopus, and Web of Science. The Mixed Methods Appraisal Tool was used to assess quality. Seven publications describing 6 unique studies (5 UK, 1 Australia) were identified including 3 mixed-methods, 2 qualitative, and 1 RCT. Participants included 334 adults (45% female, aged 35–70 years); sample sizes ranged from 9 to 164. All studies showed improvements in biopsychosocial wellbeing, and participants from most studies (n = 5) reported increased connection to the earth and intention to further access nature. Participant demographics and diagnoses were poorly reported, and intervention activities and assessments varied considerably. However, MMAT scores were good overall suggesting these studies may reliably demonstrate intervention outcomes. We conclude that socially prescribed nature therapy can improve biopsychosocial wellbeing and is a potentially important intervention for mental illness. Recommendations for research and clinical practice are provided.</p

Wolf pack size, 95% and 50% territory sizes and quality metrics

Table describing wolf packs, territories and quality metrics used to evaluate whether wolves adjust pack size or territory size to match habitat qualit

A human tissue-based functional assay platform to evaluate the immune function impact of small molecule inhibitors that target the immune system

<div><p>While the immune system is essential for the maintenance of the homeostasis, health and survival of humans, aberrant immune responses can lead to chronic inflammatory and autoimmune disorders. Pharmacological modulation of drug targets in the immune system to ameliorate disease also carry a risk of immunosuppression that could lead to adverse outcomes. Therefore, it is important to understand the ‘immune fingerprint’ of novel therapeutics as they relate to current and, clinically used immunological therapies to better understand their potential therapeutic benefit as well as immunosuppressive ability that might lead to adverse events such as infection risks and cancer. Since the mechanistic investigation of pharmacological modulators in a drug discovery setting is largely compound- and mechanism-centric but not comprehensive in terms of immune system impact, we developed a human tissue based functional assay platform to evaluate the impact of pharmacological modulators on a range of innate and adaptive immune functions. Here, we demonstrate that it is possible to generate a qualitative and quantitative immune system impact of pharmacological modulators, which might help better understand and predict the benefit-risk profiles of these compounds in the treatment of immune disorders.</p></div