Physical and Sexual Violence, Mental Health indicators, and treatment seeking among street-based population groups in Tegucigalpa, Honduras

To establish the prevalence of exposure to physical and sexual violence, mental health symptoms, and medical treatment-seeking behavior among three street-based subpopulation groups in Tegucigalpa, Honduras, and to assess the association between sociodemographic group, mental health indicators, and exposure to violence

Industrial data science - a review of machine learning applications for chemical and process industries

In the literature, machine learning (ML) and artificial intelligence (AI) applications tend to start with examples that are irrelevant to process engineers (e.g. classification of images between cats and dogs, house pricing, types of flowers, etc.). However, process engineering principles are also based on pseudo-empirical correlations and heuristics, which are a form of ML. In this work, industrial data science fundamentals will be explained and linked with commonly-known examples in process engineering, followed by a review of industrial applications using state-of-art ML techniques

Renormalized stress-energy tensor for spin-1/2 fields in expanding universes

We provide an explicit expression for the renormalized expectation value of the stress-energy tensor of a spin-1/2 field in a spatially flat Friedmann-Lemaitre-Robertson-Walker universe. Its computation is based on the extension of the adiabatic regularization method to fermion fields introduced recently in the literature. The tensor is given in terms of UV-finite integrals in momentum space, which involve the mode functions that define the quantum state. As illustrative examples of the method efficiency, we see how to compute the renormalized energy density and pressure in two interesting cosmological scenarios: a de Sitter spacetime and a radiation-dominated universe. In the second case, we explicitly show that the late-time renormalized stress-energy tensor behaves as that of classical cold matter. We also check that, if we obtain the adiabatic expansion of the scalar field mode functions with a similar procedure to the one used for fermions, we recover the well-known WKB-type expansion

Geographical variations in the risk of adverse birth outcomes in Spain

The objective of this study was to describe the spatial risk-patterns of prematurity and low birth weight in Spain. A descriptive spatial analysis of births registered in the Spanish Vital Statistics during 2004–2008 using municipalities as the observation unit was carried out. Besag-York-Mollié autoregressive spatial models were adjusted using the Integrated Nested Laplace approximation to calculate relative risks and posterior probabilities of having very and moderate preterm or low weight newborns. Results were represented in maps to assess geographic risk-patterns. Spatial analysis shows geographical variations in the risk of adverse reproductive outcomes in Spain highlighting three main high-risk zones, namely, municipalities in Asturias, Madrid City and Murcia. The specific risk patterns identified on each zone suggests some differences regarding the potential underlying risk factors and specific areas for future research. A differential exposure during pregnancy to some risks potentially related to industry or agriculture and other contextual factors could underlie an unequal vulnerability to adverse reproductive outcomes in some Spanish regions.Fondo de Investigación Sanitaria (PI081330); Spanish Ministry of Science and Innovation (SEJ 2005/07679); CIBER en Epidemiología y Salud Pública (CIBERESP), Spain.S

Upregulation of NKG2D ligands impairs hematopoietic stem cell function in Fanconi anemia

Altres ajuts: Fondo Europeo de Desarrollo Regional (FEDER); Next Generation EU; EUROFANCOLEN); Comunidad de Madrid (AvanCell, B2017/BMD-3692); ICREA-Academia program.Fanconi anemia (FA) is the most prevalent inherited bone marrow failure (BMF) syndrome. Nevertheless, the pathophysiological mechanisms of BMF in FA have not been fully elucidated. Since FA cells are defective in DNA repair, we hypothesized that FA hematopoietic stem and progenitor cells (HSPCs) might express DNA damage-associated stress molecules such as natural killer group 2 member D ligands (NKG2D-Ls). These ligands could then interact with the activating NKG2D receptor expressed in cytotoxic NK or CD8+ T cells, which may result in progressive HSPC depletion. Our results indeed demonstrated upregulated levels of NKG2D-Ls in cultured FA fibroblasts and T cells, and these levels were further exacerbated by mitomycin C or formaldehyde. Notably, a high proportion of BM CD34+ HSPCs from patients with FA also expressed increased levels of NKG2D-Ls, which correlated inversely with the percentage of CD34+ cells in BM. Remarkably, the reduced clonogenic potential characteristic of FA HSPCs was improved by blocking NKG2D-NKG2D-L interactions. Moreover, the in vivo blockage of these interactions in a BMF FA mouse model ameliorated the anemia in these animals. Our study demonstrates the involvement of NKG2D-NKG2D-L interactions in FA HSPC functionality, suggesting an unexpected role of the immune system in the progressive BMF that is characteristic of FA

CD32 is expressed on cells with transcriptionally active HIV but does not enrich for HIV DNA in resting T cells

The persistence of HIV reservoirs, including latently infected, resting CD4+ T cells, is the major obstacle to cure HIV infection. CD32a expression was recently reported to mark CD4+ T cells harboring a replication-competent HIV reservoir during antiretroviral therapy (ART) suppression. We aimed to determine whether CD32 expression marks HIV latently or transcriptionally active infected CD4+ T cells. Using peripheral blood and lymphoid tissue of ART-treated HIV+ or SIV+ subjects, we found that most of the circulating memory CD32+ CD4+ T cells expressed markers of activation, including CD69, HLA-DR, CD25, CD38, and Ki67, and bore a TH2 phenotype as defined by CXCR3, CCR4, and CCR6. CD32 expression did not selectively enrich for HIV- or SIV-infected CD4+ T cells in peripheral blood or lymphoid tissue; isolated CD32+ resting CD4+ T cells accounted for less than 3% of the total HIV DNA in CD4+ T cells. Cell-associated HIV DNA and RNA loads in CD4+ T cells positively correlated with the frequency of CD32+ CD69+ CD4+ T cells but not with CD32 expression on resting CD4+ T cells. Using RNA fluorescence in situ hybridization, CD32 coexpression with HIV RNA or p24 was detected after in vitro HIV infection (peripheral blood mononuclear cell and tissue) and in vivo within lymph node tissue from HIV-infected individuals. Together, these results indicate that CD32 is not a marker of resting CD4+ T cells or of enriched HIV DNA–positive cells after ART; rather, CD32 is predominately expressed on a subset of activated CD4+ T cells enriched for transcriptionally active HIV after long-term ART

Neurons of the Dentate Molecular Layer in the Rabbit Hippocampus

The molecular layer of the dentate gyrus appears as the main entrance gate for information into the hippocampus, i.e., where the perforant path axons from the entorhinal cortex synapse onto the spines and dendrites of granule cells. A few dispersed neuronal somata appear intermingled in between and probably control the flow of information in this area. In rabbits, the number of neurons in the molecular layer increases in the first week of postnatal life and then stabilizes to appear permanent and heterogeneous over the individuals’ life span, including old animals. By means of Golgi impregnations, NADPH histochemistry, immunocytochemical stainings and intracellular labelings (lucifer yellow and biocytin injections), eight neuronal morphological types have been detected in the molecular layer of developing adult and old rabbits. Six of them appear as interneurons displaying smooth dendrites and GABA immunoreactivity: those here called as globoid, vertical, small horizontal, large horizontal, inverted pyramidal and polymorphic. Additionally there are two GABA negative types: the sarmentous and ectopic granular neurons. The distribution of the somata and dendritic trees of these neurons shows preferences for a definite sublayer of the molecular layer: small horizontal, sarmentous and inverted pyramidal neurons are preferably found in the outer third of the molecular layer; vertical, globoid and polymorph neurons locate the intermediate third, while large horizontal and ectopic granular neurons occupy the inner third or the juxtagranular molecular layer. Our results reveal substantial differences in the morphology and electrophysiological behaviour between each neuronal archetype in the dentate molecular layer, allowing us to propose a new classification for this neural population

Improving sea level simulation in Mediterranean regional climate models

For now, the question about future sea level change in the Mediterranean remains a challenge. Previous climate modelling attempts to estimate future sea level change in the Mediterranean did not meet a consensus. The low resolution of CMIP-type models prevents an accurate representation of important small scales processes acting over the Mediterranean region. For this reason among others, the use of high resolution regional ocean modelling has been recommended in literature to address the question of ongoing and future Mediterranean sea level change in response to climate change or greenhouse gases emissions. Also, it has been shown that east Atlantic sea level variability is the dominant driver of the Mediterranean variability at interannual and interdecadal scales. However, up to now, long-term regional simulations of the Mediterranean Sea do not integrate the full sea level information from the Atlantic, which is a substantial shortcoming when analysing Mediterranean sea level response. In the present study we analyse different approaches followed by state-of-the-art regional climate models to simulate Mediterranean sea level variability. Additionally we present a new simulation which incorporates improved information of Atlantic sea level forcing at the lateral boundary. We evaluate the skills of the different simulations in the frame of long-term hindcast simulations spanning from 1980 to 2012 analysing sea level variability from seasonal to multidecadal scales. Results from the new simulation show a substantial improvement in the modelled Mediterranean sea level signal. This confirms that Mediterranean mean sea level is strongly influenced by the Atlantic conditions, and thus suggests that the quality of the information in the lateral boundary conditions (LBCs) is crucial for the good modelling of Mediterranean sea level. We also found that the regional differences inside the basin, that are induced by circulation changes, are model-dependent and thus not affected by the LBCs. Finally, we argue that a correct configuration of LBCs in the Atlantic should be used for future Mediterranean simulations, which cover hindcast period, but also for scenarios

Advancing fishery-independent stock assessments for the Norway lobster (Nephrops norvegicus) with new monitoring techn

The Norway lobster, Nephrops norvegicus, supports a key European fishery. Stock assessments for this species are mostly based on trawling and UnderWater TeleVision (UWTV) surveys. However, N. norvegicus are burrowing organisms and these survey methods are unable to sample or observe individuals in their burrows. To account for this, UWTV surveys generally assume that “1 burrow system = 1 animal”, due to the territorial behavior of N. norvegicus. Nevertheless, this assumption still requires in-situ validation. Here, we outline how to improve the accuracy of current stock assessments for N. norvegicus with novel ecological monitoring technologies, including: robotic fixed and mobile camera-platforms, telemetry, environmental DNA (eDNA), and Artificial Intelligence (AI). First, we outline the present status and threat for overexploitation in N. norvegicus stocks. Then, we discuss how the burrowing behavior of N. norvegicus biases current stock assessment methods. We propose that state-of-the-art stationary and mobile robotic platforms endowed with innovative sensors and complemented with AI tools could be used to count both animals and burrows systems in-situ, as well as to provide key insights into burrowing behavior. Next, we illustrate how multiparametric monitoring can be incorporated into assessments of physiology and burrowing behavior. Finally, we develop a flowchart for the appropriate treatment of multiparametric biological and environmental data required to improve current stock assessment methods