Comparison of rainforest butterfly assemblages across three biogeographical regions using standardized protocols

Insects, like most other organisms, are more diverse in tropical than in temperate regions, but standardized comparisons of diversity among tropical regions are rare. Disentangling the effects of ecological, evolutionary, and biogeographic factors on community diversity requires standardized protocols and long-term studies. We compared the abundance and diversity of butterflies using standardised ‘Pollard walk’ transect counts in the understory of closed-canopy lowland rainforests in Panama (Barro Colorado Island, BCI), Thailand (Khao Chong, KHC) and Papua New Guinea (Wanang, WAN). We observed 1792, 1797 and 3331 butterflies representing 128, 131 and 134 species during 230, 231 and 120 transects at BCI, KHC and WAN, respectively. When corrected for length and duration of transects, butterfly abundance and species richness were highest at WAN and KHC, respectively. Although high butterfly abundance at WAN did not appear to result from methodological artefacts, the biological meaning of this observation remains obscure. The WAN site appeared as floristically diverse as KHC, but supported lower butterfly diversity. This emphasizes that factors other than plant diversity, such as biogeographic history, may be crucial for explaining butterfly diversity. The KHC butterfly fauna may be unusually species rich because the site is at a biogeographic crossroads between the Indochinese and Sundaland regions. In contrast, WAN is firmly within the Australian biogeographic region and relatively low species numbers may result from island biogeographic processes. The common species at each of the three sites shared several traits: fruit and nectar feeders were equally represented, more than half of common species fed on either epiphytes or lianas as larvae, and their range in wing sizes was similar. These observations suggest that Pollard walks in different tropical rainforests target similar assemblages of common species, and, hence, represent a useful tool for long-term monitoring of rainforest butterfly assemblages.Organismic and Evolutionary Biolog

Repurposing existing medications for coronavirus disease 2019: protocol for a rapid and living systematic review

BACKGROUND Coronavirus disease 2019 (COVID-19) has no confirmed specific treatments. However, there might be in vitro and early clinical data as well as evidence from severe acute respiratory syndrome and Middle Eastern respiratory syndrome that could inform clinicians and researchers. This systematic review aims to create priorities for future research of drugs repurposed for COVID-19. METHODS This systematic review will include in vitro, animal, and clinical studies evaluating the efficacy of a list of 34 specific compounds and 4 groups of drugs identified in a previous scoping review. Studies will be identified both from traditional literature databases and pre-print servers. Outcomes assessed will include time to clinical improvement, time to viral clearance, mortality, length of hospital stay, and proportions transferred to the intensive care unit and intubated, respectively. We will use the GRADE methodology to assess the quality of the evidence. DISCUSSION The challenge posed by COVID-19 requires not just a rapid review of drugs that can be repurposed but also a sustained effort to integrate new evidence into a living systematic review. TRIAL REGISTRATION PROSPERO 2020 CRD42020175648

Investigation of attentional bias in obsessive compulsive disorder with and without depression in visual search

Copyright: © 2013 Morein-Zamir et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedWhether Obsessive Compulsive Disorder (OCD) is associated with an increased attentional bias to emotive stimuli remains controversial. Additionally, it is unclear whether comorbid depression modulates abnormal emotional processing in OCD. This study examined attentional bias to OC-relevant scenes using a visual search task. Controls, non-depressed and depressed OCD patients searched for their personally selected positive images amongst their negative distractors, and vice versa. Whilst the OCD groups were slower than healthy individuals in rating the images, there were no group differences in the magnitude of negative bias to concern-related scenes. A second experiment employing a common set of images replicated the results on an additional sample of OCD patients. Although there was a larger bias to negative OC-related images without pre-exposure overall, no group differences in attentional bias were observed. However, OCD patients subsequently rated the images more slowly and more negatively, again suggesting post-attentional processing abnormalities. The results argue against a robust attentional bias in OCD patients, regardless of their depression status and speak to generalized difficulties disengaging from negative valence stimuli. Rather, post-attentional processing abnormalities may account for differences in emotional processing in OCD.Peer reviewedFinal Published versio

Effects of Hypothermia vs Normothermia on Societal Participation and Cognitive Function at 6 Months in Survivors After Out-of-Hospital Cardiac Arrest

ImportanceThe Targeted Hypothermia vs Targeted Normothermia After Out-of-Hospital Cardiac Arrest (TTM2) trial reported no difference in mortality or poor functional outcome at 6 months after out-of-hospital cardiac arrest (OHCA). This predefined exploratory analysis provides more detailed estimation of brain dysfunction for the comparison of the 2 intervention regimens.ObjectivesTo investigate the effects of targeted hypothermia vs targeted normothermia on functional outcome with focus on societal participation and cognitive function in survivors 6 months after OHCA.Design, Setting, and ParticipantsThis study is a predefined analysis of an international multicenter, randomized clinical trial that took place from November 2017 to January 2020 and included participants at 61 hospitals in 14 countries. A structured follow-up for survivors performed at 6 months was by masked outcome assessors. The last follow-up took place in October 2020. Participants included 1861 adult (older than 18 years) patients with OHCA who were comatose at hospital admission. At 6 months, 939 of 1861 were alive and invited to a follow-up, of which 103 of 939 declined or were missing.InterventionsRandomization 1:1 to temperature control with targeted hypothermia at 33 °C or targeted normothermia and early treatment of fever (37.8 °C or higher).Main outcomes and measuresFunctional outcome focusing on societal participation assessed by the Glasgow Outcome Scale Extended ([GOSE] 1 to 8) and cognitive function assessed by the Montreal Cognitive Assessment ([MoCA] 0 to 30) and the Symbol Digit Modalities Test ([SDMT] z scores). Higher scores represent better outcomes.ResultsAt 6 months, 836 of 939 survivors with a mean age of 60 (SD, 13) (range, 18 to 88) years (700 of 836 male [84%]) participated in the follow-up. There were no differences between the 2 intervention groups in functional outcome focusing on societal participation (GOSE score, odds ratio, 0.91; 95% CI, 0.71-1.17; P = .46) or in cognitive function by MoCA (mean difference, 0.36; 95% CI,−0.33 to 1.05; P = .37) and SDMT (mean difference, 0.06; 95% CI,−0.16 to 0.27; P = .62). Limitations in societal participation (GOSE score less than 7) were common regardless of intervention (hypothermia, 178 of 415 [43%]; normothermia, 168 of 419 [40%]). Cognitive impairment was identified in 353 of 599 survivors (59%).ConclusionsIn this predefined analysis of comatose patients after OHCA, hypothermia did not lead to better functional outcome assessed with a focus on societal participation and cognitive function than management with normothermia. At 6 months, many survivors had not regained their pre-arrest activities and roles, and mild cognitive dysfunction was common.Trial RegistrationClinicalTrials.gov Identifier: NCT0290830

A global phylogeny of butterflies reveals their evolutionary history, ancestral hosts and biogeographic origins

Butterflies are a diverse and charismatic insect group that are thought to have evolved with plants and dispersed throughout the world in response to key geological events. However, these hypotheses have not been extensively tested because a comprehensive phylogenetic framework and datasets for butterfly larval hosts and global distributions are lacking. We sequenced 391 genes from nearly 2,300 butterfly species, sampled from 90 countries and 28 specimen collections, to reconstruct a new phylogenomic tree of butterflies representing 92% of all genera. Our phylogeny has strong support for nearly all nodes and demonstrates that at least 36 butterfly tribes require reclassification. Divergence time analyses imply an origin similar to 100 million years ago for butterflies and indicate that all but one family were present before the K/Pg extinction event. We aggregated larval host datasets and global distribution records and found that butterflies are likely to have first fed on Fabaceae and originated in what is now the Americas. Soon after the Cretaceous Thermal Maximum, butterflies crossed Beringia and diversified in the Palaeotropics. Our results also reveal that most butterfly species are specialists that feed on only one larval host plant family. However, generalist butterflies that consume two or more plant families usually feed on closely related plants

Defining Disease Phenotypes in Primary Care Electronic Health Records by a Machine Learning Approach: A Case Study in Identifying Rheumatoid Arthritis.

OBJECTIVES: 1) To use data-driven method to examine clinical codes (risk factors) of a medical condition in primary care electronic health records (EHRs) that can accurately predict a diagnosis of the condition in secondary care EHRs. 2) To develop and validate a disease phenotyping algorithm for rheumatoid arthritis using primary care EHRs. METHODS: This study linked routine primary and secondary care EHRs in Wales, UK. A machine learning based scheme was used to identify patients with rheumatoid arthritis from primary care EHRs via the following steps: i) selection of variables by comparing relative frequencies of Read codes in the primary care dataset associated with disease case compared to non-disease control (disease/non-disease based on the secondary care diagnosis); ii) reduction of predictors/associated variables using a Random Forest method, iii) induction of decision rules from decision tree model. The proposed method was then extensively validated on an independent dataset, and compared for performance with two existing deterministic algorithms for RA which had been developed using expert clinical knowledge. RESULTS: Primary care EHRs were available for 2,238,360 patients over the age of 16 and of these 20,667 were also linked in the secondary care rheumatology clinical system. In the linked dataset, 900 predictors (out of a total of 43,100 variables) in the primary care record were discovered more frequently in those with versus those without RA. These variables were reduced to 37 groups of related clinical codes, which were used to develop a decision tree model. The final algorithm identified 8 predictors related to diagnostic codes for RA, medication codes, such as those for disease modifying anti-rheumatic drugs, and absence of alternative diagnoses such as psoriatic arthritis. The proposed data-driven method performed as well as the expert clinical knowledge based methods. CONCLUSION: Data-driven scheme, such as ensemble machine learning methods, has the potential of identifying the most informative predictors in a cost-effective and rapid way to accurately and reliably classify rheumatoid arthritis or other complex medical conditions in primary care EHRs

Genetic associations with sporadic cerebral small vessel disease

Background: Cerebral small vessel disease (SVD) causes substantial cognitive, psychiatric and physical disabilities. Despite its common nature, SVD pathogenesis and molecular mechanisms remain poorly understood, and prevention and treatment are probably suboptimal. Identifying the genetic determinants of SVD will improve understanding and may help identify novel treatment targets. The aim of this thesis is to better understand genetic associations with SVD through investigating its pathological, radiological and clinical phenotypes. Methods: To unravel the genetic associations with SVD, I used three complementary approaches. First, I performed a systematic review looking at existing intracerebral haemorrhage (ICH) classification systems and their reliability, to help inform future studies of ICH genetics. Second, I performed a series of systematic reviews and meta-analyses, investigating associations between genetic polymorphisms and histopathologically confirmed cerebral amyloid angiopathy (CAA). Third, I performed meta-analyses of existing genome-wide datasets to determine associations of >1000 common single nucleotide polymorphisms (SNP) in the COL4A1/COL4A2 genomic region with clinico-radiological SVD phenotypes: ICH and its subtypes, ischaemic stroke and its subtypes, and white matter hyperintensities. Results: The reliability of existing ICH classification systems appeared excellent in eight studies conducted in specialist centres with experienced raters, although these existing systems have several limitations. In my systematic evaluation of CAA genetics, meta-analyses of 24 studies including 3520 participants showed robust evidence for a dose-dependent association between APOE ɛ4 and histopathological CAA. There was, however, no convincing association between APOE ɛ2 and presence of CAA in a meta-analysis of 11 studies including 1640 participants. Meta-analyses of five studies including 497 participants showed, contrary to an existing popular hypothesis, that while APOE 4 may increase the risk of developing severe CAA vasculopathy, there is no clear evidence to support a role of ɛ2. There were few data about the role of APOE in hereditary CAA, but in the three studies that had looked at this, there was no evidence for an association between APOE ɛ4 and CAA severity. There were too few studies and participants to draw firm conclusions about the effect of non-APOE ε2/ε3/ε4 genetic polymorphisms on CAA, but there were positive associations with TGF-β1, TOMM40 and CR1 genes in four studies. Finally, in my meta-analyses of the COL4A1/COL4A2 genomic region, three intronic SNPs in COL4A2 were associated with SVD phenotypes: significantly with deep ICH, and suggestively with lacunar ischaemic stroke and WMH. Conclusions: I have shown that while existing ICH classification systems appear to have very good reliability, further research is needed to determine their performance in different settings. For large population-based prospective studies of ICH genetics, anatomical systems are likely to be more feasible, scalable and appropriate, although they have limitations and will need to be further developed. Using systematic reviews and meta-analyses, I have confirmed a dose-related association between APOE ɛ4 and histopathological CAA, but also demonstrated that, despite popular acceptance, there is insufficient data to draw firm conclusions about the association with APOE ɛ2. I found some positive associations with CAA in other genes, which merit replication in further larger studies, and showed that there is currently insufficient data about the role of APOE in hereditary CAA. Finally, I identified a novel association between a locus in a known hereditary SVD gene – COL4A2 – and sporadic SVD. This highlights a new and successful approach for selecting candidate genes and can be expanded in future studies to include other known hereditary SVD genes

The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia : design, results and future prospects

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.Peer reviewe

Type2 diabetes in pregnancy A multidisciplinary approach to improving outcomes

Type 2 diabetes in pregnancy is becoming more common and is associated with poor maternal, fetal and childhood outcomes. Preconception counselling and a multidisciplinary team approach throughout pregnancy are crucial to improving outcomes