IL-15 modulates the effect of retinoic acid, promoting inflammation rather than oral tolerance to dietary antigens

3 páginas.-- Evaluation of: DePaolo RW, Abadie V, Tang F et al. Co-adjuvant effects of retinoic acid and IL-15 induce inflammatory immunity to dietary antigens. Nature 471(7337), 220–224 (2011).The physiological immune response in the intestine against dietary proteins and commensal flora is characterized by regulatory mechanisms (tolerance) that prevent harmful consequences. Intestinal dendritic cells (DCs) have a central role in the development of immunosuppressive regulatory T cells owing to their ability to produce TGF-b and retinoic acid (RA). However, the article under evaluation shows an unexpected effect of RA – that of promoting a proinflammatory phenotype in intestinal DCs involved in the generation of inflammatory immune responses to dietary antigens. By using a double transgenic murine model that resembles human celiac disease, it was demonstrated that RA synergizes with IL‑15 in promoting the breakdown of gluten tolerance and the development of enteropathy. The tissue microenvironment modulates DC function, and immune therapies that are based on RA aiming to restore oral tolerance should be used with caution because the presence of IL‑15 (and/or other proinflammatory cytokines) may have undesirable effects.Peer reviewe

Fütterungseinflüsse auf das Fress- und Wiederkäuverhalten von Milchkühen auf einem Biobetrieb

In einer ökologischen Milchviehherde in der Schweiz wurden 23 Kühe mit verschiedenen Rationen gefüttert. Futteraufnahme und Wiederkäuverhalten wurden mit Kausensoren erfasst. Proteinkonzentrate sowie eine separate Heugabe zeigten signifikante Einflüsse auf das Fressen und Wiederkäuen während des Tages, jedoch nicht während der Nacht. Die Daten zeigen das Potential der Erhebung von Fress- und Wiederkäuverhalten zur Beurteilung von Fütterungssituationen mit grundfutterreichen Rationen

Temporal Dynamics of Preferential Flow to a Subsurface Drain

We conducted a sequential tracer leaching study on a 24.4 by 42.7 m field plot to investigate the temporal behavior of chemical movement to a 1.2-m deep field drain during irrigation and subsequent rainfall events over a 14-d period. The herbicides atrazine [6-chloroN-ethyl-N′-(1-methylethyl)-1,3,5-triazine-2,4-diamine], and alachlor [2-chloro-N-(2,6-diethylphenyl)-N-(methoxymethyl)acetamide] along with the conservative tracer Br were applied to a 1-m wide strip, offset 1.5 m laterally from a subsurface drain pipe, immediately before an 11.3-h long, 4.2-mm h−1 irrigation. Three additional conservative tracers, pentafluorobenzoate (PF), o-trifluoromethylbenzoate (TF), and difluorobenzoate (DF) were applied to the strip during the irrigation at 2-h intervals. Breakthrough of Br and the two herbicides occurred within the first 2-h of irrigation, indicating that a fraction of the solute transport was along preferential flow paths. Retardation and attenuation of the herbicides indicated that there was interaction between the chemicals and the soil lining the preferential pathways. The conservative tracers applied during the later stages of irrigation arrived at the subsurface drain much faster than tracers applied earlier. The final tracer, applied 6 h after the start of irrigation (DF), took only 15 min and 1 mm of irrigation water to travel to the subsurface drain. Model simulations using a two-dimensional, convective, and dispersive numerical model without an explicit preferential flow component failed to reproduce Br tracer concentrations in the drain effluent, confirming the importance of preferential flow. This study showed that preferential flow in this soil is not a uniform process during a leaching event

Sampling Once…Using Data Multiple Times.

presentaciónMarine ecosystem variability shows large fluctuations on a wide variety of scales, from seconds to millennia and from local to global. This limits our ability to observe these systems and to develop good tools to predict how changes in the environment may affect their physical and biological properties. It also limits our ability to differentiate anthropogenic from natural processes. An example is how difficult it is to compare data collected in different sampling locations and at different times. Time series data help resolve both short- and longer-term scales of variability and provide context for traditional process-oriented studies. Time series projects focusing on biogeochemical and ecological observations have yielded important scientific results. They have helped to: (i) evaluate the statistical significance of the ranges of variability of many parameters and environmental variables and biological communities, and (ii) quantify and evaluate the dimension of the interactions between key physical/chemical oceanographic processes and biological rates in plankton communities. As a result, time series are helping estimate warming rates and trends as well as the effects of global change on biota. They have established reference baselines to evaluate the magnitude of environmental perturbations and estimate recovery times on biodiversity and productivity of specific trophic levels. In spite of their scientific value, marine time series are difficult to maintain over time because of costs and availability of trained personnel. Only a few survive beyond a decade. There is great potential in sharing and combining marine data sets from different time series programs from around the world. This allows for comparisons of changes occurring in distant locations, and helps detect changes that occur at broad scales, perhaps even global scales, and to distinguish them from local imbalances or fluctuation. Sharing data can have important economic and social benefits. For instance, efficient use of existing marine data represents a significant cost saving from the 2 billion Euro spent each year now in the EU collecting and accessing to marine data. From the social point of view, the demand from different stakeholders for answers to the challenges posed by changes in the marine environment is growing rapidly. Sharing and accessing time series data would reduce the uncertainties in the management of marine resources and ecosystem services. The UNESCO IOC advocates that: (i) an observation not made today is lost forever, (ii) existing observations are lost if not made accessible, (iii) the collective value of data sets is greater than its dispersed value, and (iv) open access to standardised time series data must be pursued as a common, coordinated international goal.IOC-UNESCO, IE

The DWD climate predictions website: Towards a seamless outlook based on subseasonal, seasonal and decadal predictions

The climate predictions website of the Deutscher Wetterdienst (DWD, https://www.dwd.de/climatepredictions) presents a consistent operational outlook for the coming weeks, months and years, focusing on the needs of German users. At global scale, subseasonal predictions from the European Centre of Medium-Range Weather Forecasts as well as seasonal and decadal predictions from the DWD are used. Statistical downscaling is applied to achieve high resolution over Germany. Lead-time dependent bias correction is performed on all time scales. Additionally, decadal predictions are recalibrated. The website offers ensemble mean and probabilistic predictions for temperature and precipitation combined with their skill (mean squared error skill score, ranked probability skill score). Two levels of complexity are offered: basic climate predictions display simple, regionally averaged information for Germany, German regions and cities as maps, time series and tables. The skill is presented as traffic light. Expert climate predictions show complex, gridded predictions for Germany (at high resolution), Europe and the world as maps and time series. The skill is displayed as the size of dots. Their color is related to the signal in the prediction. The website was developed in cooperation with users from different sectors via surveys, workshops and meetings to guarantee its understandability and usability. The users realize the potential of climate predictions, but some need advice in using probabilistic predictions and skill. Future activities will include the further development of predictions to improve skill (multi-model ensembles, teleconnections), the introduction of additional products (data provision, extremes) and the further clarification of the information (interactivity, video clips)

Ocean acidification research for sustainability: co-designing global action on local scales

The global threat that ocean acidification poses to marine ecosystems has been recognized by the UN 2030 Agenda under Sustainable Development Goal, Target 14.3: to reduce ocean acidification. The Global Ocean Acidification Observing Network (GOA-ON) is a collaborative international network to detect and understand the drivers of ocean acidification in estuarine-coastal-open ocean environments, the resulting impacts on marine ecosystems, and to make the information available to optimize modelling studies. The Ocean Acidification Research for Sustainability (OARS) programme, endorsed by the 2021–2030 UN Decade of Ocean Science for Sustainable Development, will build on the work of GOA-ON through its seven Decade Action Outcomes. By employing a Theory of Change framework, and with the co-design of science in mind, OARS will develop an implementation plan for each Decade Action Outcome, which will identify the stakeholders and rights-holders, as well as the tools, means, and positive consequences required for their successful delivery. The organizational structure of GOA-ON, with nine regional hubs, will benefit OARS by providing a vital connection between local and global scales. GOA-ON regional hub case-studies illustrate how activities in the past and future, informed by global and regional priorities, support capacity building and the co-design of ocean acidification science

RecycleNet: Latent Feature Recycling Leads to Iterative Decision Refinement

Despite the remarkable success of deep learning systems over the last decade, a key difference still remains between neural network and human decision-making: As humans, we cannot only form a decision on the spot, but also ponder, revisiting an initial guess from different angles, distilling relevant information, arriving at a better decision. Here, we propose RecycleNet, a latent feature recycling method, instilling the pondering capability for neural networks to refine initial decisions over a number of recycling steps, where outputs are fed back into earlier network layers in an iterative fashion. This approach makes minimal assumptions about the neural network architecture and thus can be implemented in a wide variety of contexts. Using medical image segmentation as the evaluation environment, we show that latent feature recycling enables the network to iteratively refine initial predictions even beyond the iterations seen during training, converging towards an improved decision. We evaluate this across a variety of segmentation benchmarks and show consistent improvements even compared with top-performing segmentation methods. This allows trading increased computation time for improved performance, which can be beneficial, especially for safety-critical applications.Comment: Accepted at 2024 Winter Conference on Applications of Computer Vision (WACV

North Atlantic Ocean

RADIALES (IEO), with the support of the Korea Institute for Ocean Science and Technology (KIOST)Versión del edito

Cigarette smoking, nicotine dependence and anxiety disorders : a systematic review of population-based, epidemiological studies

Background Multiple studies have demonstrated that rates of smoking and nicotine dependence are increased in individuals with anxiety disorders. However, significant variability exists in the epidemiological literature exploring this relationship, including study design (cross-sectional versus prospective), the population assessed (random sample versus clinical population) and diagnostic instrument utilized.Methods We undertook a systematic review of population-based observational studies that utilized recognized structured clinical diagnostic criteria (Diagnostic and Statistical Manual of Mental Disorders (DSM) or International Classification of Diseases (ICD)) for anxiety disorder diagnosis to investigate the relationship between cigarette smoking, nicotine dependence and anxiety disorders.Results In total, 47 studies met the predefined inclusion criteria, with 12 studies providing prospective information and 5 studies providing quasiprospective information. The available evidence suggests that some baseline anxiety disorders are a risk factor for initiation of smoking and nicotine dependence, although the evidence is heterogeneous and many studies did not control for the effect of comorbid substance use disorders. The identified evidence however appeared to more consistently support cigarette smoking and nicotine dependence as being a risk factor for development of some anxiety disorders (for example, panic disorder, generalized anxiety disorder), although these findings were not replicated in all studies. A number of inconsistencies in the literature were identified.Conclusions Although many studies have demonstrated increased rates of smoking and nicotine dependence in individuals with anxiety disorders, there is a limited and heterogeneous literature that has prospectively examined this relationship in population studies using validated diagnostic criteria. The most consistent evidence supports smoking and nicotine dependence as increasing the risk of panic disorder and generalized anxiety disorder. The literature assessing anxiety disorders increasing smoking and nicotine dependence is inconsistent. Potential issues with the current literature are discussed and directions for future research are suggested