‘Special agents’ trigger social waves in giant honeybees (Apis dorsata)

Giant honeybees (Apis dorsata) nest in the open and have therefore evolved a variety of defence strategies. Against predatory wasps, they produce highly coordinated Mexican wavelike cascades termed ‘shimmering’, whereby hundreds of bees flip their abdomens upwards. Although it is well known that shimmering commences at distinct spots on the nest surface, it is still unclear how shimmering is generated. In this study, colonies were exposed to living tethered wasps that were moved in front of the experimental nest. Temporal and spatial patterns of shimmering were investigated in and after the presence of the wasp. The numbers and locations of bees that participated in the shimmering were assessed, and those bees that triggered the waves were identified. The findings reveal that the position of identified trigger cohorts did not reflect the experimental path of the tethered wasp. Instead, the trigger centres were primarily arranged in the close periphery of the mouth zone of the nest, around those parts where the main locomotory activity occurs. This favours the ‘special-agents’ hypothesis that suggest that groups of specialized bees initiate the shimmering

Social Waves in Giant Honeybees Repel Hornets

Giant honeybees (Apis dorsata) nest in the open and have evolved a plethora of defence behaviors. Against predatory wasps, including hornets, they display highly coordinated Mexican wave-like cascades termed ‘shimmering’. Shimmering starts at distinct spots on the nest surface and then spreads across the nest within a split second whereby hundreds of individual bees flip their abdomens upwards. However, so far it is not known whether prey and predator interact and if shimmering has anti-predatory significance. This article reports on the complex spatial and temporal patterns of interaction between Giant honeybee and hornet exemplified in 450 filmed episodes of two A. dorsata colonies and hornets (Vespa sp.). Detailed frame-by-frame analysis showed that shimmering elicits an avoidance response from the hornets showing a strong temporal correlation with the time course of shimmering. In turn, the strength and the rate of the bees' shimmering are modulated by the hornets' flight speed and proximity. The findings suggest that shimmering creates a ‘shelter zone’ of around 50 cm that prevents predatory wasps from foraging bees directly from the nest surface. Thus shimmering appears to be a key defence strategy that supports the Giant honeybees' open-nesting life-style

Analysis of chloroplast genomes and a supermatrix inform reclassification of the Rhodomelaceae (Rhodophyta).

With over a thousand species, the Rhodomelaceae is the most species-rich family of red algae. While its genera have been assigned to 14 tribes, the high-level classification of the family has never been evaluated with a molecular phylogeny. Here, we reassess its classification by integrating genome-scale phylogenetic analysis with observations of the morphological characters of clades. In order to resolve relationships among the main lineages of the family we constructed a phylogeny with 55 chloroplast genomes (52 newly determined). The majority of branches were resolved with full bootstrap support. We then added 266 rbcL, 125 18S rRNA gene and 143 cox1 sequences to construct a comprehensive phylogeny containing nearly half of all known species in the family (407 species in 89 genera). These analyses suggest the same subdivision into higher-level lineages, but included many branches with moderate or poor support. The circumscription for nine of the 13 previously described tribes was supported, but the Lophothalieae, Polysiphonieae, Pterosiphonieae and Herposiphonieae required revision, and five new tribes and one resurrected tribe were segregated from them. Rhizoid anatomy is highlighted as a key diagnostic character for the morphological delineation of several lineages. This work provides the most extensive phylogenetic analysis of the Rhodomelaceae to date and successfully resolves the relationships among major clades of the family. Our data show that organellar genomes obtained through high-throughput sequencing produce well-resolved phylogenies of difficult groups, and their more general application in algal systematics will likely permit deciphering questions about classification at many taxonomic levels

Analysis of chloroplast genomes and a supermatrix inform reclassification of the Rhodomelaceae (Rhodophyta).

With over a thousand species, the Rhodomelaceae is the most species-rich family of red algae. While its genera have been assigned to 14 tribes, the high-level classification of the family has never been evaluated with a molecular phylogeny. Here, we reassess its classification by integrating genome-scale phylogenetic analysis with observations of the morphological characters of clades. In order to resolve relationships among the main lineages of the family we constructed a phylogeny with 55 chloroplast genomes (52 newly determined). The majority of branches were resolved with full bootstrap support. We then added 266 rbcL, 125 18S rRNA gene and 143 cox1 sequences to construct a comprehensive phylogeny containing nearly half of all known species in the family (407 species in 89 genera). These analyses suggest the same subdivision into higher-level lineages, but included many branches with moderate or poor support. The circumscription for nine of the 13 previously described tribes was supported, but the Lophothalieae, Polysiphonieae, Pterosiphonieae and Herposiphonieae required revision, and five new tribes and one resurrected tribe were segregated from them. Rhizoid anatomy is highlighted as a key diagnostic character for the morphological delineation of several lineages. This work provides the most extensive phylogenetic analysis of the Rhodomelaceae to date and successfully resolves the relationships among major clades of the family. Our data show that organellar genomes obtained through high-throughput sequencing produce well-resolved phylogenies of difficult groups, and their more general application in algal systematics will likely permit deciphering questions about classification at many taxonomic levels

Efficacy and moderators of efficacy of cognitive behavioural therapies with a trauma focus in children and adolescents: an individual participant data meta-analysis of randomised trials

Background: Existing clinical trials of cognitive behavioural therapies with a trauma focus (CBTs-TF) are underpowered to examine key variables that might moderate treatment effects. We aimed to determine the efficacy of CBTs-TF for young people, relative to passive and active control conditions, and elucidate putative individual-level and treatment-level moderators. Methods: This was an individual participant data meta-analysis of published and unpublished randomised studies in young people aged 6-18 years exposed to trauma. We included studies identified by the latest UK National Institute of Health and Care Excellence guidelines (completed on Jan 29, 2018) and updated their search. The search strategy included database searches restricted to publications between Jan 1, 2018, and Nov 12, 2019; grey literature search of trial registries ClinicalTrials.gov and ISRCTN; preprint archives PsyArXiv and bioRxiv; and use of social media and emails to key authors to identify any unpublished datasets. The primary outcome was post-traumatic stress symptoms after treatment (<1 month after the final session). Predominantly, one-stage random-effects models were fitted. This study is registered with PROSPERO, CRD42019151954. Findings: We identified 38 studies; 25 studies provided individual participant data, comprising 1686 young people (mean age 13·65 years [SD 3·01]), with 802 receiving CBTs-TF and 884 a control condition. The risk-of-bias assessment indicated five studies as low risk and 20 studies with some concerns. Participants who received CBTs-TF had lower mean post-traumatic stress symptoms after treatment than those who received the control conditions, after adjusting for post-traumatic stress symptoms before treatment (b=-13·17, 95% CI -17·84 to -8·50, p<0·001, τ2=103·72). Moderation analysis indicated that this effect of CBTs-TF on post-traumatic stress symptoms post-treatment increased by 0·15 units (b=-0·15, 95% CI -0·29 to -0·01, p=0·041, τ2=0·03) for each unit increase in pre-treatment post-traumatic stress symptoms. Interpretation: This is the first individual participant data meta-analysis of young people exposed to trauma. Our findings support CBTs-TF as the first-line treatment, irrespective of age, gender, trauma characteristics, or carer involvement in treatment, with particular benefits for those with higher initial distress

Use of mental health services among disaster survivors: predisposing factors

<p>Abstract</p> <p>Background</p> <p>Given the high prevalence of mental health problems after disasters it is important to study health services utilization. This study examines predictors for mental health services (MHS) utilization among survivors of a man-made disaster in the Netherlands (May 2000).</p> <p>Methods</p> <p>Electronic records of survivors (n = 339; over 18 years and older) registered in a mental health service (MHS) were linked with general practice based electronic medical records (EMRs) of survivors and data obtained in surveys. EMR data were available from 16 months pre-disaster until 3 years post-disaster. Symptoms and diagnoses in the EMRs were coded according to the International Classification of Primary Care (ICPC). Surveys were carried out 2–3 weeks and 18 months post-disaster, and included validated questionnaires on psychological distress, post-traumatic stress reactions and social functioning. Demographic and disaster-related variables were available. Predisposing factors for MHS utilization 0–18 months and 18–36 months post-disaster were examined using multiple logistic regression models.</p> <p>Results</p> <p>In multiple logistic models, adjusting for demographic and disaster related variables, MHS utilization was predicted by demographic variables (young age, immigrant, public health insurance, unemployment), disaster-related exposure (relocation and injuries), self-reported psychological problems and pre- and post-disaster physician diagnosed health problems (chronic diseases, musculoskeletal problems). After controlling for all health variables, disaster intrusions and avoidance reactions (OR:2.86; CI:1.48–5.53), hostility (OR:2.04; CI:1.28–3.25), pre-disaster chronic diseases (OR:1.82; CI:1.25–2.65), injuries as a result of the disaster (OR:1.80;CI:1.13–2.86), social functioning problems (OR:1.61;CI:1.05–2.44) and younger age (OR:0.98;CI:0.96–0.99) predicted MHS utilization within 18 months post-disaster. Furthermore, disaster intrusions and avoidance reactions (OR:2.29;CI:1.04–5.07) and hostility (OR:3.77;CI:1.51–9.40) predicted MHS utilization following 18 months post-disaster.</p> <p>Conclusion</p> <p>This study showed that several demographic and disaster-related variables and self-reported and physician diagnosed health problems predicted post-disaster MHS-use. The most important factors to predict post-disaster MHS utilization were disaster intrusions and avoidance reactions and symptoms of hostility (which can be identified as symptoms of PTSD) and pre-disaster chronic diseases.</p

Social Algorithms

This article concerns the review of a special class of swarm intelligence based algorithms for solving optimization problems and these algorithms can be referred to as social algorithms. Social algorithms use multiple agents and the social interactions to design rules for algorithms so as to mimic certain successful characteristics of the social/biological systems such as ants, bees, bats, birds and animals.Comment: Encyclopedia of Complexity and Systems Science, 201