Developmental responses to early-life adversity: Evolutionary and mechanistic perspectives

Adverse ecological and social conditions during early life are known to influence development, with rippling effects that may explain variation in adult health and fitness. The adaptive function of such developmental plasticity, however, remains relatively untested in long-lived animals, resulting in much debate over which evolutionary models are most applicable. Furthermore, despite the promise of clinical interventions that might alleviate the health consequences of early-life adversity, research on the proximate mechanisms governing phenotypic responses to adversity have been largely limited to studies on glucocorticoids. Here, we synthesize the current state of research on developmental plasticity, discussing both ultimate and proximate mechanisms. First, we evaluate the utility of adaptive models proposed to explain developmental responses to early-life adversity, particularly for long-lived mammals such as humans. In doing so, we highlight how parent-offspring conflict complicates our understanding of whether mothers or offspring benefit from these responses. Second, we discuss the role of glucocorticoids and a second physiological system-the gut microbiome-that has emerged as an additional, clinically relevant mechanism by which early-life adversity can influence development. Finally, we suggest ways in which nonhuman primates can serve as models to study the effects of early-life adversity, both from evolutionary and clinical perspectives.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152003/1/evan21791_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/152003/2/evan21791.pd

Signs and symptoms of acute mania: a factor analysis

<p>Abstract</p> <p>Background</p> <p>The major diagnostic classifications consider mania as a uni-dimensional illness. Factor analytic studies of acute mania are fewer compared to schizophrenia and depression. Evidence from factor analysis suggests more categories or subtypes than what is included in the classification systems. Studies have found that these factors can predict differences in treatment response and prognosis.</p> <p>Methods</p> <p>The sample included 131 patients consecutively admitted to an acute psychiatry unit over a period of one year. It included 76 (58%) males. The mean age was 44.05 years (SD = 15.6). Patients met International Classification of Diseases-10 (ICD-10) clinical diagnostic criteria for a manic episode. Patients with a diagnosis of mixed bipolar affective disorder were excluded. Participants were evaluated using the Young Mania Rating Scale (YMRS). Exploratory factor analysis (principal component analysis) was carried out and factors with an eigenvalue > 1 were retained. The significance level for interpretation of factor loadings was 0.40. The unrotated component matrix identified five factors. Oblique rotation was then carried out to identify three factors which were clinically meaningful.</p> <p>Results</p> <p>Unrotated principal component analysis extracted five factors. These five factors explained 65.36% of the total variance. Oblique rotation extracted 3 factors. Factor 1 corresponding to 'irritable mania' had significant loadings of irritability, increased motor activity/energy and disruptive aggressive behaviour. Factor 2 corresponding to 'elated mania' had significant loadings of elevated mood, language abnormalities/thought disorder, increased sexual interest and poor insight. Factor 3 corresponding to 'psychotic mania' had significant loadings of abnormalities in thought content, appearance, poor sleep and speech abnormalities.</p> <p>Conclusions</p> <p>Our findings identified three clinically meaningful factors corresponding to 'elated mania', 'irritable mania' and 'psychotic mania'. These findings support the multidimensional nature of manic symptoms. Further evidence is needed to support the existence of corresponding clinical subtypes.</p

Gravity waves and the LHC: Towards high-scale inflation with low-energy SUSY

It has been argued that rather generic features of string-inspired inflationary theories with low-energy supersymmetry (SUSY) make it difficult to achieve inflation with a Hubble scale H > m_{3/2}, where m_{3/2} is the gravitino mass in the SUSY-breaking vacuum state. We present a class of string-inspired supergravity realizations of chaotic inflation where a simple, dynamical mechanism yields hierarchically small scales of post-inflationary supersymmetry breaking. Within these toy models we can easily achieve small ratios between m_{3/2} and the Hubble scale of inflation. This is possible because the expectation value of the superpotential relaxes from large to small values during the course of inflation. However, our toy models do not provide a reasonable fit to cosmological data if one sets the SUSY-breaking scale to m_{3/2} < TeV. Our work is a small step towards relieving the apparent tension between high-scale inflation and low-scale supersymmetry breaking in string compactifications.Comment: 21+1 pages, 5 figures, LaTeX, v2: added references, v3: very minor changes, version to appear in JHE

Pig abattoir inspection data: Can it be used for surveillance purposes?

Statutory recording of carcass lesions at the abattoir may have significant potential as a resource for surveillance of livestock populations. Food Standards Agency (FSA) data in Great Britain are not currently used for surveillance purposes. There are concerns that the sensitivity of detection, combined with other issues, may make the outputs unreliable. In this study we postulate that FSA data could be used for surveillance purposes. To test this we compared FSA data with BPHS (a targeted surveillance system of slaughtered pigs) and laboratory diagnostic scanning surveillance (FarmFile) data, from mid-2008 to mid- 2012, for respiratory conditions and tail bite lesions in pigs at population level. We also evaluated the agreement/correlation at batch level between FSA and BPHS inspections in four field trials during 2013. Temporal trends and regional differences at population level were described and compared using logistic regression models. Population temporal analysis showed an increase in respiratory disease in all datasets but with regional differences. For tail bite, the temporal trend and monthly patterns were completely different between the datasets. The field trials were run in three abattoirs and included 322 batches. Pearson’s correlation and Cohen’s kappa tests were used to assess correlation/agreement between inspections systems. It was moderate to strong for high prevalence conditions but slight for low prevalence conditions. We conclude that there is potential to use FSA data as a component of a surveillance system to monitor temporal trends and regional differences of chosen indicators at population level. At producer level and for low prevalence conditions it needs further improvement. Overall a number of issues still need to be addressed in order to provide the pig industry with the confidence to base their decisions on these FSA inspection data. Similar conclusions, at national level, may apply to other livestock sectors but require further evaluation of the inspection and data collection processes