Mesoscale dispersal of the introduced kelp Undaria pinnatifida attached to unstable substrata

In areas of Tasmania and New Zealand, the introduced Japanese alga, Undaria pinnatifida, grows attached to unstable substrata such as small cobbles and shells. Observations suggest these algae may disperse by saltation (i.e., a series of jumps) while attached to their substratum. A predictive model was developed to estimate the dispersal rate of U. pinnatifida by this mechanism, depending on drag force (as a function of lamina surface area and water velocity), the buoyant weight of the attached substratum and the depth at which the alga was located. The model was parameterised based on empirical measurements of 89 tagged thalli in the field, and estimates of drag on different sized laminae determined from experiments in a large flume tank. Empirical observations and model predictions suggest that under typical conditions at moderately exposed sites, dispersal via this mechanism is likely to be of the order of at least 10¹–10² m per year. When compared to the likely dispersal of spores from the parent (~10¹ m per year), and the likely dispersal of fertile drift thalli (~10³–10 4 m per year), we suggest that algae on unstable substrata may provide a mechanism for intermediate dispersal over moderate distances, providing sufficient spore density to ensure high fertilisation success. This is likely to enhance the rate of spread of U. pinnatifida in circumstances where habitat suitable for establishment is available

Abundance of the introduced seastar, Asterias amurensis, and spatial variability in soft sediment assemblages in SE Tasmania : clear correlations but complex interpretation

The northern Pacific seastar, Asterias amurensis, was first collected in southeast Tasmania in 1986. Mistaken for the endemic asteroid Uniophora granifera, its true identity was not realised until 1992. It is now a conspicuous predator in soft sediment habitats in this region, and is considered a major threat to native assemblages and commercial species. We examined the structure of soft sediment assemblages at different spatial scales in southeast Tasmania, and correlated spatial variation in community composition with seastar abundances. We found that the structure of soft sediment assemblages is highly variable at a range of spatial scales from metres to tens of kilometres. Clear differences in the composition of assemblages and abundances of major taxa were detected between areas with and without seastars and between areas with low and high seastar densities. However, the nature of these patterns suggests that they are more likely due to differences in sediment characteristics than due to impacts of the seastar. Thus, spatial differences in soft sediment assemblages might have been erroneously attributed to seastars without detailed information on important physical factors such as sediment characteristics. A second survey, using larger sampling units (1 m2) but across a more limited spatial extent, targeted bivalves and heart urchins that were identified as important prey of the seastar in observations of feeding and in experimental studies. Large-scale patterns of abundance and size structure were consistent with seastar effects anticipated from small-scale experimental and feeding studies for some, but not all, species. While the field survey ultimately provided evidence about the presence or absence of seastar impacts at large-scales, the identification of key ecological variables in experimental and feeding studies proved crucial to both the design and interpretation of patterns observed in the large-scale surveys. Overall, this work highlighted the necessity to consider multiple lines of evidence rather than relying on a single ‘inferential’ test, in the absence of pre-impact data

Enhancing polymer electrolyte membrane fuel cell system diagnostics through semantic modelling

Polymer electrolyte membrane fuel cells (PEMFC) are a promising technology for economic and environmentally friendly energy production. However, they haven’t reached their full potential in the market yet as only few reliable PEMFC systems have successfully passed the prototyping face. A drawback of the current diagnostic tools is that only a select few are of high genericity, reliability and can perform efficiently on-line at the same time. Furthermore, there is only limited research identifying both PEMFC stack faults and ancillary system faults simultaneously. While none of the existing tools can be interrogated by the end-user. In this research, we develop novel artificial intelligence-based technologies to overcome these existing barriers, i.e., i) a semantically enriched integrating schema (ontology) of the overall operation and structure of the PEMFC that allows automatic inference engines to automatically deduce fault detection; ii) a knowledgebased, light-weight, on-line fuel cell system diagnosis (FuCSyDi) platform. FuCSyDi detects and provides the location of failures by considering only the data from the reliable sensors. Additionally, it provides the reasons underpinning any forthcoming failures and enables the end-user to interrogate the platform for further information regarding its operation and structure. Our platform is validated by performing tests against common automotive stress conditions. This innovative approach enhances the reliability of the fuel cell system diagnosis and, hence, its lifetime performanc

Evaluation of IMproving Palliative care Education and Training Using Simulation in Dementia (IMPETUS-D) a staff simulation training intervention to improve palliative care of people with advanced dementia living in nursing homes: a cluster randomised controlled trial

Background: People with dementia have unique palliative and end-of-life needs. However, access to quality palliative and end-of-life care for people with dementia living in nursing homes is often suboptimal. There is a recognised need for nursing home staff training in dementia-specific palliative care to equip them with knowledge and skills to deliver high quality care. Objective: The primary aim was to evaluate the effectiveness of a simulation training intervention (IMPETUS-D) aimed at nursing home staff on reducing unplanned transfers to hospital and/or deaths in hospital among residents living with dementia. Design: Cluster randomised controlled trial of nursing homes with process evaluation conducted alongside. Subjects & setting: One thousand three hundred four people with dementia living in 24 nursing homes (12 intervention/12 control) in three Australian cities, their families and direct care staff. Methods: Randomisation was conducted at the level of the nursing home (cluster). The allocation sequence was generated by an independent statistician using a computer-generated allocation sequence. Staff from intervention nursing homes had access to the IMPETUS-D training intervention, and staff from control nursing homes had access to usual training opportunities. The predicted primary outcome measure was a 20% reduction in the proportion of people with dementia who had an unplanned transfer to hospital and/or death in hospital at 6-months follow-up in the intervention nursing homes compared to the control nursing homes. Results: At 6-months follow-up, 128 (21.1%) people with dementia from the intervention group had an unplanned transfer or death in hospital compared to 132 (19.0%) residents from the control group; odds ratio 1.14 (95% CI, 0.82-1.59). There were suboptimal levels of staff participation in the training intervention and several barriers to participation identified. Conclusion: This study of a dementia-specific palliative care staff training intervention found no difference in the proportion of residents with dementia who had an unplanned hospital transfer. Implementation of the intervention was challenging and likely did not achieve adequate staff coverage to improve staff practice or resident outcomes. Trial registration: Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12618002012257. Registered 14 December 2018

ICORG 10-14: NEOadjuvant trial in adenocarcinoma of the oEsophagus and oesophagoGastric junction international study (Neo-AEGIS)

Background: Neoadjuvant therapy is increasingly the standard of care in the management of locally advanced adenocarcinoma of the oesophagus and junction (AEG). In randomised controlled trials (RCTs), the MAGIC regimen of pre- and postoperative chemotherapy, and the CROSS regimen of preoperative chemotherapy combined with radiation, were superior to surgery only in RCTs that included AEG but were not powered on this cohort. No completed RCT has directly compared neoadjuvant or perioperative chemotherapy and neoadjuvant chemoradiation. The Neo-AEGIS trial, uniquely powered on AEG, and including comprehensive modern staging, compares both these regimens. Methods: This open label, multicentre, phase III RCT randomises patients (cT2-3, N0-3, M0) in a 1:1 fashion to receive CROSS protocol (Carboplatin and Paclitaxel with concurrent radiotherapy, 41.4Gy/23Fr, over 5 weeks). The power calculation is a 10% difference in favour of CROSS, powered at 80%, two-sided alpha level of 0.05, requiring 540 patients to be evaluable, 594 to be recruited if a 10% dropout is included (297 in each group). The primary endpoint is overall survival, with a minimum 3-year follow up. Secondary endpoints include: disease free survival, recurrence rates, clinical and pathological response rates, toxicities of induction regimens, post-operative pathology and tumour regression grade, operative in-hospital complications, and health-related quality of life. The trial also affords opportunities for establishing a bio-resource of pre-treatment and resected tumour, and translational research. Discussion: This RCT directly compares two established treatment regimens, and addresses whether radiation therapy positively impacts on overall survival compared with a standard perioperative chemotherapy regimen Sponsor: Irish Clinical Research Group (ICORG). Trial registration: NCT01726452 . Protocol 10-14. Date of registration 06/11/2012.</p

Additional file 1 of ICORG 10-14: NEOadjuvant trial in Adenocarcinoma of the oEsophagus and oesophagoGastric junction International Study (Neo-AEGIS)

Appendix A: Description of data: copy of consent form (DOCX 60 kb

Evaluation of local media surveillance for improved disease recognition and monitoring in global hotspot regions

Digital disease detection tools are technologically sophisticated, but dependent on digital information, which for many areas suffering from high disease burdens is simply not an option. In areas where news is often reported in local media with no digital counterpart, integration of local news information with digital surveillance systems, such as HealthMap (Boston Children's Hospital), is critical. Little research has been published in regards to the specific contribution of local healthrelated articles to digital surveillance systems. In response, the USAID PREDICT project implemented a local media surveillance (LMS) pilot study in partner countries to monitor disease events reported in print media. This research assessed the potential of LMS to enhance digital surveillance reach in five low- and middle-income countries. Over 16 weeks, select surveillance system attributes of LMS, such as simplicity, flexibility, acceptability, timeliness, and stability were evaluated to identify strengths and weaknesses in the surveillance method. Findings revealed that LMS filled gaps in digital surveillance network coverage by contributing valuable localized information on disease events to the global HealthMap database. A total of 87 health events were reported through the LMS pilot in the 16-week monitoring period, including 71 unique reports not found by the HealthMap digital detection tool. Furthermore, HealthMap identified an additional 236 health events outside of LMS. It was also observed that belief in the importance of the project and proper source selection from the participants was crucial to the success of this method. The timely identification of disease outbreaks near points of emergence and the recognition of risk factors associated with disease occurrence continue to be important components of any comprehensive surveillance system for monitoring disease activity across populations. The LMS method, with its minimal resource commitment, could be one tool used to address the information gaps seen in global 'hot spot' regions. Copyright

Cognitive and psychiatric symptom trajectories 2–3 years after hospital admission for COVID-19: a longitudinal, prospective cohort study in the UK

Background: COVID-19 is known to be associated with increased risks of cognitive and psychiatric outcomes after the acute phase of disease. We aimed to assess whether these symptoms can emerge or persist more than 1 year after hospitalisation for COVID-19, to identify which early aspects of COVID-19 illness predict longer-term symptoms, and to establish how these symptoms relate to occupational functioning. Methods: The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study of adults (aged ≥18 years) who were hospitalised with a clinical diagnosis of COVID-19 at participating National Health Service hospitals across the UK. In the C-Fog study, a subset of PHOSP-COVID participants who consented to be recontacted for other research were invited to complete a computerised cognitive assessment and clinical scales between 2 years and 3 years after hospital admission. Participants completed eight cognitive tasks, covering eight cognitive domains, from the Cognitron battery, in addition to the 9-item Patient Health Questionnaire for depression, the Generalised Anxiety Disorder 7-item scale, the Functional Assessment of Chronic Illness Therapy Fatigue Scale, and the 20-item Cognitive Change Index (CCI-20) questionnaire to assess subjective cognitive decline. We evaluated how the absolute risks of symptoms evolved between follow-ups at 6 months, 12 months, and 2–3 years, and whether symptoms at 2–3 years were predicted by earlier aspects of COVID-19 illness. Participants completed an occupation change questionnaire to establish whether their occupation or working status had changed and, if so, why. We assessed which symptoms at 2–3 years were associated with occupation change. People with lived experience were involved in the study. Findings: 2469 PHOSP-COVID participants were invited to participate in the C-Fog study, and 475 participants (191 [40·2%] females and 284 [59·8%] males; mean age 58·26 [SD 11·13] years) who were discharged from one of 83 hospitals provided data at the 2–3-year follow-up. Participants had worse cognitive scores than would be expected on the basis of their sociodemographic characteristics across all cognitive domains tested (average score 0·71 SD below the mean [IQR 0·16–1·04]; p<0·0001). Most participants reported at least mild depression (263 [74·5%] of 353), anxiety (189 [53·5%] of 353), fatigue (220 [62·3%] of 353), or subjective cognitive decline (184 [52·1%] of 353), and more than a fifth reported severe depression (79 [22·4%] of 353), fatigue (87 [24·6%] of 353), or subjective cognitive decline (88 [24·9%] of 353). Depression, anxiety, and fatigue were worse at 2–3 years than at 6 months or 12 months, with evidence of both worsening of existing symptoms and emergence of new symptoms. Symptoms at 2–3 years were not predicted by the severity of acute COVID-19 illness, but were strongly predicted by the degree of recovery at 6 months (explaining 35·0–48·8% of the variance in anxiety, depression, fatigue, and subjective cognitive decline); by a biocognitive profile linking acutely raised D-dimer relative to C-reactive protein with subjective cognitive deficits at 6 months (explaining 7·0–17·2% of the variance in anxiety, depression, fatigue, and subjective cognitive decline); and by anxiety, depression, fatigue, and subjective cognitive deficit at 6 months. Objective cognitive deficits at 2–3 years were not predicted by any of the factors tested, except for cognitive deficits at 6 months, explaining 10·6% of their variance. 95 of 353 participants (26·9% [95% CI 22·6–31·8]) reported occupational change, with poor health being the most common reason for this change. Occupation change was strongly and specifically associated with objective cognitive deficits (odds ratio [OR] 1·51 [95% CI 1·04–2·22] for every SD decrease in overall cognitive score) and subjective cognitive decline (OR 1·54 [1·21–1·98] for every point increase in CCI-20). Interpretation: Psychiatric and cognitive symptoms appear to increase over the first 2–3 years post-hospitalisation due to both worsening of symptoms already present at 6 months and emergence of new symptoms. New symptoms occur mostly in people with other symptoms already present at 6 months. Early identification and management of symptoms might therefore be an effective strategy to prevent later onset of a complex syndrome. Occupation change is common and associated mainly with objective and subjective cognitive deficits. Interventions to promote cognitive recovery or to prevent cognitive decline are therefore needed to limit the functional and economic impacts of COVID-19. Funding: National Institute for Health and Care Research Oxford Health Biomedical Research Centre, Wolfson Foundation, MQ Mental Health Research, MRC-UK Research and Innovation, and National Institute for Health and Care Research.</p