Born to yawn? Understanding yawning as a warning of the rise in cortisol levels: Randomized trial

Background: Yawning consistently poses a conundrum to the medical profession and neuroscientists. Despite neurological evidence such as parakinesia brachialis oscitans in stroke patients and thermo-irregulation in multiple sclerosis patients, there is considerable debate over the reasons for yawning with the mechanisms and hormonal pathways still not fully understood. Cortisol is implicated during yawning and may link many neurological disorders. Evidence was found in support of the Thompson cortisol hypothesis that proposes cortisol levels are elevated during yawning just as they tend to rise during stress and fatigue. Objectives: To investigate whether saliva cortisol levels rise during yawning and, therefore, support the Thompson cortisol hypothesis. Methods: We exposed 20 male and female volunteers aged between 18 and 53 years to conditions that provoked a yawning response in a randomized controlled trial. Saliva samples were collected at the start and again after the yawning response, or at the end of the stimuli presentations if the participant did not yawn. In addition, we collected electromyographic data of the jaw muscles to determine rest and yawning phases of neural activity. Yawning susceptibility scale, Hospital Anxiety and Depression Scale, General Health Questionnaire, and demographic and health details were also collected from each participant. A comprehensive data set allowed comparison between yawners and nonyawners, as well as between rest and yawning phases. Collecting electromyographic data from the yawning phase is novel, and we hope this will provide new information about neuromuscular activity related to cortisol levels. Exclusion criteria included chronic fatigue, diabetes, fibromyalgia, heart conditions, high blood pressure, hormone replacement therapy, multiple sclerosis, and stroke. We compared data between and within participants. Results: In the yawning group, there was a significant difference between saliva cortisol samples (t = -3.071, P = .01). Power and effect size were computed based on repeated-measures t tests for both the yawning and nonyawning groups. There was a medium effect size for the nonyawners group (r = .467) but low power (36%). Results were similar for the yawners group: medium effect size (r = .440) and low power (33%). Conclusions: There was significant evidence in support of the Thompson cortisol hypothesis that suggests cortisol levels are elevated during yawning. A further longitudinal study is planned to test neurological patients. We intend to devise a diagnostic tool based on changes in cortisol levels that may assist in the early diagnosis of neurological disorders based on the data collected. Trial Registration: International Standard Randomized Controlled Trial Number (ISRCTN): 61942768; http://www.controlled-trials.com/ISRCTN61942768/61942768 (Archived by WebCite at http://www.webcitation.org/6A75ZNYvr)

Challenges of Profile Likelihood Evaluation in Multi-Dimensional SUSY Scans

Statistical inference of the fundamental parameters of supersymmetric theories is a challenging and active endeavor. Several sophisticated algorithms have been employed to this end. While Markov-Chain Monte Carlo (MCMC) and nested sampling techniques are geared towards Bayesian inference, they have also been used to estimate frequentist confidence intervals based on the profile likelihood ratio. We investigate the performance and appropriate configuration of MultiNest, a nested sampling based algorithm, when used for profile likelihood-based analyses both on toy models and on the parameter space of the Constrained MSSM. We find that while the standard configuration is appropriate for an accurate reconstruction of the Bayesian posterior, the profile likelihood is poorly approximated. We identify a more appropriate MultiNest configuration for profile likelihood analyses, which gives an excellent exploration of the profile likelihood (albeit at a larger computational cost), including the identification of the global maximum likelihood value. We conclude that with the appropriate configuration MultiNest is a suitable tool for profile likelihood studies, indicating previous claims to the contrary are not well founded.Comment: 21 pages, 9 figures, 1 table; minor changes following referee report. Matches version accepted by JHE

The Co-Regulation of Emotions Between Mothers and their Children with Autism

Thirty-four toddlers with autism and their mothers participated in an early intervention targeting joint engagement. Across the 24 intervention sessions, any significant distress episode in the child was coded for emotion regulation outcomes including child negativity, child emotion self-regulation, and mother emotion co-regulation. Results revealed that emotion regulation strategies by both mother and child were employed during distress episodes. An effect of intervention was found such that children decreased their expression of negativity across the intervention and mothers increased their emotional and motivational scaffolding. The results of this study indicate a positive effect of an intervention targeting joint engagement on emotion co-regulation outcomes

“When will this end? Will it end?” The impact of the March-June 2020 UK Covid-19 lockdown response on mental health : a longitudinal survey of mothers in the Born in Bradford study

OBJECTIVES: To explore clinically important increases in depression/anxiety from before to during the first UK COVID-19 lockdown and factors related to this change, with a particular focus on ethnic differences. DESIGN: Pre-COVID-19 and lockdown surveys nested within two longitudinal Born in Bradford cohort studies. PARTICIPANTS: 1860 mothers with a child aged 0–5 or 9–13, 48% Pakistani heritage. MAIN OUTCOME MEASURES: ORs for a clinically important increase (5 points or more) in depression (eight item Patient Health Questionnaire (PHQ-8)) and anxiety (Generalised Anxiety Disorder Assessment (GAD-7)) in unadjusted regression analyses, repeated with exposures of interest separated by ethnicity to look for differences in magnitude of associations, and lived experience of mothers captured in open text questions. RESULTS: The number of women reporting clinically important depression/anxiety increased from 11% to 20% (95% CI 10%–13%; 18%–22%) and from 10% to 16% (95% CI 8%–11%; 15%–18%), respectively. Increases in depression/anxiety were associated with loneliness (OR=8.37, 95% CI 5.70 to 12.27; 8.50, 95% CI 5.71 to 12.65, respectively); financial (6.23, 95% CI 3.96 to 9.80; 6.03, 95% CI 3.82 to 9.51), food (3.33, 95% CI 2.09 to 5.28; 3.46, 95% CI 2.15 to 5.58) and housing insecurity (3.29, 95% CI 2.36 to 4.58; 3.0, 95% CI 2.11 to 4.25); a lack of physical activity (3.13, 95% CI 2.15 to 4.56; 2.55, 95% CI 1.72 to 3.78); and a poor partner relationship (3.6, 95% CI 2.44 to 5.43; 5.1, 95% CI 3.37 to 7.62). The magnitude of associations between key exposures and worsening mental health varied between ethnic groups. Responses to open text questions illustrated a complex interplay of challenges contributing to mental ill health including: acute health anxieties; the mental load of managing multiple responsibilities; loss of social support and coping strategies; pressures of financial and employment insecurity; and being unable to switch off from the pandemic. CONCLUSIONS: Mental ill health has worsened for many during the COVID-19 lockdown, particularly in those who are lonely and economically insecure. The magnitude of associations between key exposures and worsening mental health varied between ethnic groups. Mental health problems may have longer term consequences for public health and interventions that address the potential causes are needed

Antiviral resistance during pandemic influenza: implications for stockpiling and drug use

<p>Abstract</p> <p>Background</p> <p>The anticipated extent of antiviral use during an influenza pandemic can have adverse consequences for the development of drug resistance and rationing of limited stockpiles. The strategic use of drugs is therefore a major public health concern in planning for effective pandemic responses.</p> <p>Methods</p> <p>We employed a mathematical model that includes both sensitive and resistant strains of a virus with pandemic potential, and applies antiviral drugs for treatment of clinical infections. Using estimated parameters in the published literature, the model was simulated for various sizes of stockpiles to evaluate the outcome of different antiviral strategies.</p> <p>Results</p> <p>We demonstrated that the emergence of highly transmissible resistant strains has no significant impact on the use of available stockpiles if treatment is maintained at low levels or the reproduction number of the sensitive strain is sufficiently high. However, moderate to high treatment levels can result in a more rapid depletion of stockpiles, leading to run-out, by promoting wide-spread drug resistance. We applied an antiviral strategy that delays the onset of aggressive treatment for a certain amount of time after the onset of the outbreak. Our results show that if high treatment levels are enforced too early during the outbreak, a second wave of infections can potentially occur with a substantially larger magnitude. However, a timely implementation of wide-scale treatment can prevent resistance spread in the population, and minimize the final size of the pandemic.</p> <p>Conclusion</p> <p>Our results reveal that conservative treatment levels during the early stages of the outbreak, followed by a timely increase in the scale of drug-use, will offer an effective strategy to manage drug resistance in the population and avoid run-out. For a 1918-like strain, the findings suggest that pandemic plans should consider stockpiling antiviral drugs to cover at least 20% of the population.</p

Impact of Emerging Antiviral Drug Resistance on Influenza Containment and Spread: Influence of Subclinical Infection and Strategic Use of a Stockpile Containing One or Two Drugs

BACKGROUND: Wide-scale use of antiviral agents in the event of an influenza pandemic is likely to promote the emergence of drug resistance, with potentially deleterious effects for outbreak control. We explored factors promoting resistance within a dynamic infection model, and considered ways in which one or two drugs might be distributed to delay the spread of resistant strains or mitigate their impact. METHODS AND FINDINGS: We have previously developed a novel deterministic model of influenza transmission that simulates treatment and targeted contact prophylaxis, using a limited stockpile of antiviral agents. This model was extended to incorporate subclinical infections, and the emergence of resistant virus strains under the selective pressure imposed by various uses of one or two antiviral agents. For a fixed clinical attack rate, R(0) rises with the proportion of subclinical infections thus reducing the number of infections amenable to treatment or prophylaxis. In consequence, outbreak control is more difficult, but emergence of drug resistance is relatively uncommon. Where an epidemic may be constrained by use of a single antiviral agent, strategies that combine treatment and prophylaxis are most effective at controlling transmission, at the cost of facilitating the spread of resistant viruses. If two drugs are available, using one drug for treatment and the other for prophylaxis is more effective at preventing propagation of mutant strains than either random allocation or drug cycling strategies. Our model is relatively straightforward, and of necessity makes a number of simplifying assumptions. Our results are, however, consistent with the wider body of work in this area and are able to place related research in context while extending the analysis of resistance emergence and optimal drug use within the constraints of a finite drug stockpile. CONCLUSIONS: Combined treatment and prophylaxis represents optimal use of antiviral agents to control transmission, at the cost of drug resistance. Where two drugs are available, allocating different drugs to cases and contacts is likely to be most effective at constraining resistance emergence in a pandemic scenario

Genetic Differentiation, Structure, and a Transition Zone among Populations of the Pitcher Plant Moth Exyra semicrocea: Implications for Conservation

Pitcher plant bogs, or carnivorous plant wetlands, have experienced extensive habitat loss and fragmentation throughout the southeastern United States Coastal Plain, resulting in an estimated reduction to <3% of their former range. This situation has lead to increased management attention of these habitats and their carnivorous plant species. However, conservation priorities focus primarily on the plants since little information currently exists on other community members, such as their endemic arthropod biota. Here, we investigated the population structure of one of these, the obligate pitcher plant moth Exyra semicrocea (Lepidoptera: Noctuidae), using mitochondrial cytochrome c oxidase subunit I (COI) gene sequences. Examination of 221 individuals from 11 populations across eight southeastern US states identified 51 unique haplotypes. These haplotypes belonged to one of two divergent (∼1.9–3.0%) lineages separated by the Mississippi alluvial plain. Populations of the West Gulf Coastal Plain exhibited significant genetic structure, contrasting with similarly distanced populations east of the Mississippi alluvial plain. In the eastern portion of the Coastal Plain, an apparent transition zone exists between two regionally distinct population groups, with a well-established genetic discontinuity for other organisms coinciding with this zone. The structure of E. semicrocea appears to have been influenced by patchy pitcher plant bog habitats in the West Gulf Coastal Plain as well as impacts of Pleistocene interglacials on the Apalachicola-Chattahoochee-Flint River Basin. These findings, along with potential extirpation of E. semicrocea at four visited, but isolated, sites highlight the need to consider other endemic or associated community members when managing and restoring pitcher plant bog habitats

Detection of copy number variations in rice using array-based comparative genomic hybridization

<p>Abstract</p> <p>Background</p> <p>Copy number variations (CNVs) can create new genes, change gene dosage, reshape gene structures, and modify elements regulating gene expression. As with all types of genetic variation, CNVs may influence phenotypic variation and gene expression. CNVs are thus considered major sources of genetic variation. Little is known, however, about their contribution to genetic variation in rice.</p> <p>Results</p> <p>To detect CNVs, we used a set of NimbleGen whole-genome comparative genomic hybridization arrays containing 718,256 oligonucleotide probes with a median probe spacing of 500 bp. We compiled a high-resolution map of CNVs in the rice genome, showing 641 CNVs between the genomes of the rice cultivars 'Nipponbare' (from <it>O. sativa </it>ssp. <it>japonica</it>) and 'Guang-lu-ai 4' (from <it>O. sativa </it>ssp. <it>indica</it>). The CNVs identified vary in size from 1.1 kb to 180.7 kb, and encompass approximately 7.6 Mb of the rice genome. The largest regions showing copy gain and loss are of 37.4 kb on chromosome 4, and 180.7 kb on chromosome 8. In addition, 85 DNA segments were identified, including some genic sequences. Contracted genes greatly outnumbered duplicated ones. Many of the contracted genes corresponded to either the same genes or genes involved in the same biological processes; this was also the case for genes involved in disease and defense.</p> <p>Conclusion</p> <p>We detected CNVs in rice by array-based comparative genomic hybridization. These CNVs contain known genes. Further discussion of CNVs is important, as they are linked to variation among rice varieties, and are likely to contribute to subspecific characteristics.</p