Transgenerational transmission of a stress-coping phenotype programmed by early-life stress in the Japanese quail

This study was funded by a BBSRC David Phillips Research Fellowship to K.A. Spencer (BB/L002264/1).An interesting aspect of developmental programming is the existence of transgenerational effects that influence offspring characteristics and performance later in life. These transgenerational effects have been hypothesized to allow individuals to cope better with predictable environmental fluctuations and thus facilitate adaptation to changing environments. Here, we test for the first time how early-life stress drives developmental programming and transgenerational effects of maternal exposure to early-life stress on several phenotypic traits in their offspring in a functionally relevant context using a fully factorial design. We manipulated pre- and/or post-natal stress in both Japanese quail mothers and offspring and examined the consequences for several stress-related traits in the offspring generation. We show that pre-natal stress experienced by the mother did not simply affect offspring phenotype but resulted in the inheritance of the same stress-coping traits in the offspring across all phenotypic levels that we investigated, shaping neuroendocrine, physiological and behavioural traits. This may serve mothers to better prepare their offspring to cope with later environments where the same stressors are experienced.Publisher PDFPeer reviewe

A marker of biological age explains individual variation in the strength of the adult stress response

This research was funded by the Biotechnology and Biological Sciences Research Council (BBSRC) under grants BB/J016446/1, BB/J015091/1 and BB/J016292/1. The project has also received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no. AdG 666669 (D.N.) and 268926 (P.M.)) K.A.S. was also funded by a BBSRC David Phillips Research Fellowship. The raw data and R script from this experiment are publicly available at: https://doi.org/10.5281/zenodo.846830 [38].The acute stress response functions to prioritize behavioural and physiological processes that maximize survival in the face of immediate threat. There is variation between individuals in the strength of the adult stress response that is of interest in both evolutionary biology and medicine. Age is an established source of this variation-stress responsiveness diminishes with increasing age in a range of species-but unexplained variation remains. Since individuals of the same chronological age may differ markedly in their pace of biological ageing, we asked whether biological age-measured here via erythrocyte telomere length-predicts variation in stress responsiveness in adult animals of the same chronological age. We studied two cohorts of European starlings in which we had previously manipulated the rate of biological ageing by experimentally altering the competition experienced by chicks in the fortnight following hatching. We predicted that individuals with greater developmental telomere attrition, and hence greater biological age, would show an attenuated corticosterone (CORT) response to an acute stressor when tested as adults. In both cohorts, we found that birds with greater developmental telomere attrition had lower peak CORT levels and a more negative change in CORT levels between 15 and 30 min following stress exposure. Our results, therefore, provide strong evidence that a measure of biological age explains individual variation in stress responsiveness: birds that were biologically older were less stress responsive. Our results provide a novel explanation for the phenomenon of developmental programming of the stress response: observed changes in stress physiology as a result of exposure to early-life adversity may reflect changes in ageing.Publisher PDFPeer reviewe

Japón, Corea del Sur y la OTAN: desafíos comunes a la distancia

This article explores the relationship between the North Atlantic Treaty Organization with Japan and South Korea. NATO's presence has generally been limited to Europe and the North Atlantic but has remained constant since the conflicts in Iraq and Syria, however due to Russia's invasion of Ukraine, the Organization after more than twenty-five years has again a conflict near its members. In this sense, given the size of Russia, the perception of threat has not only been limited to Europe, since in Asia, Russia's invasion has raised alarm in China's neighbours, particularly South Korea and Japan, since the success of Russia could increase China's assertiveness. NATO did not consider China a concern until 2022, so the role of Tokyo and Seoul as allies is very important.El presente artículo explora la relación entre la Organización del Tratado del Atlántico Norte con Japón y Corea del Sur. La presencia de la OTAN ha estado limitada en general a Europa y al Atlántico Norte y ha permanecido constante desde los conflictos en Irak y Siria, sin embargo debido a la invasión de Rusia a Ucrania, la Organización después de más de veinticinco años tiene nuevamente un conflicto cerca de sus miembros. En este sentido, dado el tamaño de Rusia, la percepción de amenaza no solamente se ha limitado a Europa, ya que en Asia la invasión de Rusia a los vecinos de China, particularmente Corea del Sur y Japón les ha causado alarma ya que el éxito de Rusia podría incrementar la asertividad de China. La OTAN no consideraba a China como una preocupación hasta 2022, por lo cual el papel de Tokio y Seúl como aliados cobra una gran relevancia

Chronological age, biological age, and individual variation in the stress response in the European starling : a follow-up study

This research was funded by the Biotechnology and Biological Sciences Research Council (BBSRC) under grants BB/J016446/1 and BB/J016292/1; a doctoral training studentship to Annie Gott; and a David Phillips fellowship to Karen Spencer. The project has also received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. AdG 666669 (COMSTAR)).The strength of the avian stress response declines with age. A recently published study of European starlings (Sturnus vulgaris) found that a marker of biological age predicted the strength of the stress response even in individuals of the same chronological age. Specifically, birds that had experienced greater developmental telomere attrition (DTA) showed a lower peak corticosterone (CORT) response to an acute stressor, and more rapid recovery of CORT levels towards baseline. Here, we performed a follow-up study using the same capture-handling-restraint stressor in a separate cohort of starlings that had been subjected to a developmental manipulation of food availability and begging effort. We measured the CORT response at two different age points (4 and 18 months). Our data suggest a decline in the strength of the CORT response with chronological age: peak CORT was lower at the second age point, and there was relatively more reduction in CORT between 15 and 30 min. Individual consistency between the two age points was low, but there were modest familial effects on baseline and peak CORT. The manipulation of begging effort affected the stress response (specifically, the reduction in CORT between 15 and 30 min) in an age-dependent manner. However, we did not replicate the associations with DTA observed in the earlier study. We meta-analysed the data from the present and the earlier study combined, and found some support for the conclusions of the earlier paper.Publisher PDFPeer reviewe

Metabolomics analysis of type 2 diabetes remission identifies 12 metabolites with predictive capacity: a CORDIOPREV clinical trial study.

Type 2 diabetes mellitus (T2DM) is one of the most widely spread diseases, affecting around 90% of the patients with diabetes. Metabolomics has proven useful in diabetes research discovering new biomarkers to assist in therapeutical studies and elucidating pathways of interest. However, this technique has not yet been applied to a cohort of patients that have remitted from T2DM. All patients with a newly diagnosed T2DM at baseline (n = 190) were included. An untargeted metabolomics approach was employed to identify metabolic differences between individuals who remitted (RE), and those who did not (non-RE) from T2DM, during a 5-year study of dietary intervention. The biostatistical pipeline consisted of an orthogonal projection on the latent structure discriminant analysis (O-PLS DA), a generalized linear model (GLM), a receiver operating characteristic (ROC), a DeLong test, a Cox regression, and pathway analyses. The model identified a significant increase in 12 metabolites in the non-RE group compared to the RE group. Cox proportional hazard models, calculated using these 12 metabolites, showed that patients in the high-score tercile had significantly (p-value < 0.001) higher remission probabilities (Hazard Ratio, HR, high versus low = 2.70) than those in the lowest tercile. The predictive power of these metabolites was further studied using GLMs and ROCs. The area under the curve (AUC) of the clinical variables alone is 0.61, but this increases up to 0.72 if the 12 metabolites are considered. A DeLong test shows that this difference is statistically significant (p-value = 0.01). Our study identified 12 endogenous metabolites with the potential to predict T2DM remission following a dietary intervention. These metabolites, combined with clinical variables, can be used to provide, in clinical practice, a more precise therapy. ClinicalTrials.gov, NCT00924937.The CORDIOPREV study is supported by the Ministerio de Economia y Competitividad, Spain, under the grants AGL2012/39615, PIE14/00005, and PIE14/00031 associated to J.L.-M.; AGL2015-67896-P to J.L.-M. and A.C.; CP14/00114 to A.C.; PI19/00299 to A.C.; DTS19/00007 to A.C.; FIS PI13/00023 to J.D.-L., PI16/01777 to F.P.-J. and P.P.-M.; Antonio Camargo is supported by an ISCIII research contract (Programa Miguel-Servet CPII19/00007); Marina Mora-Ortiz has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 847468; ‘Fundacion Patrimonio Comunal Olivarero’, Junta de Andalucía (Consejería de Salud, Consejeria de Agricultura y Pesca, Consejería de Innovacion, Ciencia y Empresa), ‘Diputaciones de Jaen y Cordoba’, ‘Centro de Excelencia en Investigación sobre Aceite de Oliva y Salud’ and ‘Ministerio de Medio Ambiente, Medio Rural y Marino’, Gobierno de España; ‘Consejeria de Innovación, Ciencia y Empresa, Proyectos de Investigación de Excelencia’, Junta de Andalucía under the grant CVI-7450 obtaiend by J.L.-M.; and we would also like to thank the ‘Fondo Europeo de Desarrollo Regional (FEDER)’.S

Status and results of the prototype LST of CTA

The Large-Sized Telescopes (LSTs) of Cherenkov Telescope Array (CTA) are designed for gamma-ray studies focusing on low energy threshold, high flux sensitivity, rapid telescope repositioning speed and a large field of view. Once the CTA array is complete, the LSTs will be dominating the CTA performance between 20 GeV and 150 GeV. During most of the CTA Observatory construction phase, however, the LSTs will be dominating the array performance until several TeVs. In this presentation we will report on the status of the LST-1 telescope inaugurated in La Palma, Canary islands, Spain in 2018. We will show the progress of the telescope commissioning, compare the expectations with the achieved performance, and give a glance of the first physics results

Reconstruction of extensive air shower images of the Large Size Telescope prototype of CTA using a novel likelihood technique

Ground-based gamma-ray astronomy aims at reconstructing the energy and direction of gamma rays from the extensive air showers they initiate in the atmosphere. Imaging Atmospheric Cherenkov Telescopes (IACT) collect the Cherenkov light induced by secondary charged particles in extensive air showers (EAS), creating an image of the shower in a camera positioned in the focal plane of optical systems. This image is used to evaluate the type, energy and arrival direction of the primary particle that initiated the shower. This contribution shows the results of a novel reconstruction method based on likelihood maximization. The novelty with respect to previous likelihood reconstruction methods lies in the definition of a likelihood per single camera pixel, accounting not only for the total measured charge, but also for its development over time. This leads to more precise reconstruction of shower images. The method is applied to observations of the Crab Nebula acquired with the Large Size Telescope prototype (LST-1) deployed at the northern site of the Cherenkov Telescope Array

First follow-up of transient events with the CTA Large Size Telescope prototype

When very-high-energy gamma rays interact high in the Earth’s atmosphere, they produce cascades of particles that induce flashes of Cherenkov light. Imaging Atmospheric Cherenkov Telescopes (IACTs) detect these flashes and convert them into shower images that can be analyzed to extract the properties of the primary gamma ray. The dominant background for IACTs is comprised of air shower images produced by cosmic hadrons, with typical noise-to-signal ratios of several orders of magnitude. The standard technique adopted to differentiate between images initiated by gamma rays and those initiated by hadrons is based on classical machine learning algorithms, such as Random Forests, that operate on a set of handcrafted parameters extracted from the images. Likewise, the inference of the energy and the arrival direction of the primary gamma ray is performed using those parameters. State-of-the-art deep learning techniques based on convolutional neural networks (CNNs) have the potential to enhance the event reconstruction performance, since they are able to autonomously extract features from raw images, exploiting the pixel-wise information washed out during the parametrization process. Here we present the results obtained by applying deep learning techniques to the reconstruction of Monte Carlo simulated events from a single, next-generation IACT, the Large-Sized Telescope (LST) of the Cherenkov Telescope Array (CTA). We use CNNs to separate the gamma-ray-induced events from hadronic events and to reconstruct the properties of the former, comparing their performance to the standard reconstruction technique. Three independent implementations of CNN-based event reconstruction models have been utilized in this work, producing consistent results

Development of an advanced SiPM camera for the Large Size Telescope of the Cherenkov TelescopeArray Observatory

Silicon photomultipliers (SiPMs) have become the baseline choice for cameras of the small-sized telescopes (SSTs) of the Cherenkov Telescope Array (CTA). On the other hand, SiPMs are relatively new to the field and covering large surfaces and operating at high data rates still are challenges to outperform photomultipliers (PMTs). The higher sensitivity in the near infra-red and longer signals compared to PMTs result in higher night sky background rate for SiPMs. However, the robustness of the SiPMs represents a unique opportunity to ensure long-term operation with low maintenance and better duty cycle than PMTs. The proposed camera for large size telescopes will feature 0.05 degree pixels, low power and fast front-end electronics and a fully digital readout. In this work, we present the status of dedicated simulations and data analysis for the performance estimation. The design features and the different strategies identified, so far, to tackle the demanding requirements and the improved performance are described

Analysis of the Cherenkov Telescope Array first Large Size Telescope real data using convolutional neural networks

The Cherenkov Telescope Array (CTA) is the future ground-based gamma-ray observatory and will be composed of two arrays of imaging atmospheric Cherenkov telescopes (IACTs) located in the Northern and Southern hemispheres respectively. The first CTA prototype telescope built on-site, the Large-Sized Telescope (LST-1), is under commissioning in La Palma and has already taken data on numerous known sources. IACTs detect the faint flash of Cherenkov light indirectly produced after a very energetic gamma-ray photon has interacted with the atmosphere and generated an atmospheric shower. Reconstruction of the characteristics of the primary photons is usually done using a parameterization up to the third order of the light distribution of the images. In order to go beyond this classical method, new approaches are being developed using state-of-the-art methods based on convolutional neural networks (CNN) to reconstruct the properties of each event (incoming direction, energy and particle type) directly from the telescope images. While promising, these methods are notoriously difficult to apply to real data due to differences (such as different levels of night sky background) between Monte Carlo (MC) data used to train the network and real data. The GammaLearn project, based on these CNN approaches, has already shown an increase in sensitivity on MC simulations for LST-1 as well as a lower energy threshold. This work applies the GammaLearn network to real data acquired by LST-1 and compares the results to the classical approach that uses random forests trained on extracted image parameters. The improvements on the background rejection, event direction, and energy reconstruction are discussed in this contribution