Local inflammation enables a basophil-neuronal circuITCH in atopic dermatitis.

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An unsupervised data completion method for physically-based data-driven models

Data-driven methods are an innovative model-free approach for engineering and sciences, still in process of maturation. The idea behind is the combination of data analytics techniques, to handle the huge amount of data derived from continuous monitoring or experimental measurements, and of the constraints imposed by universal physical laws, particular to the field in hands. A well-known problem in the former corresponds to the quality and completeness of the available data that, sometimes, are so poor that make the predictions useless. In data-driven simulation-based engineering and sciences (DDSBES), the intrinsic physical constraints may help in completing the missing data in a more precise manner, by forcing them to remain in the manifold defined by the physical laws. In this work, a suitable imputation method to complete incomplete data that preserves the data context-dependent structure is presented. This is accomplished by enforcing the data to fulfill the set of physical constraints, specific to the problem. For this purpose, a generalization of the weighted mean concept is proposed, where the distance to the admissible points (in a physical sense) is used as a weighting function to get the optimal candidate. The method is evaluated in a classical regression problem, where it is compared with other standard methods, showing better results. Then, its application is illustrated in two data-driven problems, where no filling data procedure has been yet proposed, showing good predictive capability, provided that the data are close enough to the actual system state

Distribution of melanopsin positive neurons in pigmented and albino mice: evidence for melanopsin interneurons in the mouse retina.

Here we have studied the population of intrinsically photosensitive retinal ganglion cells (ipRGCs) in adult pigmented and albino mice. Our data show that although pigmented (C57Bl/6) and albino (Swiss) mice have a similar total number of ipRGCs, their distribution is slightly different: while in pigmented mice ipRGCs are more abundant in the temporal retina, in albinos the ipRGCs are more abundant in superior retina. In both strains, ipRGCs are located in the retinal periphery, in the areas of lower Brn3a(+)RGC density. Both strains also contain displaced ipRGCs (d-ipRGCs) in the inner nuclear layer (INL) that account for 14% of total ipRGCs in pigmented mice and 5% in albinos. Tracing from both superior colliculli shows that 98% (pigmented) and 97% (albino) of the total ipRGCs, become retrogradely labeled, while double immunodetection of melanopsin and Brn3a confirms that few ipRGCs express this transcription factor in mice. Rather surprisingly, application of a retrograde tracer to the optic nerve (ON) labels all ipRGCs, except for a sub-population of the d-ipRGCs (14% in pigmented and 28% in albino, respectively) and melanopsin positive cells residing in the ciliary marginal zone (CMZ) of the retina. In the CMZ, between 20% (pigmented) and 24% (albino) of the melanopsin positive cells are unlabeled by the tracer and we suggest that this may be because they fail to send an axon into the ON. As such, this study provides the first evidence for a population of melanopsin interneurons in the mammalian retina

Analysis of the parametric correlation in mathematical modeling of in vitro glioblastoma evolution using copulas

Modeling and simulation are essential tools for better understanding complex biological processes, such as cancer evolution. However, the resulting mathematical models are often highly non-linear and include many parameters, which, in many cases, are difficult to estimate and present strong correlations. Therefore, a proper parametric analysis is mandatory. Following a previous work in which we modeled the in vitro evolution of Glioblastoma Multiforme (GBM) under hypoxic conditions, we analyze and solve here the problem found of parametric correlation. With this aim, we develop a methodology based on copulas to approximate the multidimensional probability density function of the correlated parameters. Once the model is defined, we analyze the experimental setting to optimize the utility of each configuration in terms of gathered information. We prove that experimental configurations with oxygen gradient and high cell concentration have the highest utility when we want to separate correlated effects in our experimental design. We demonstrate that copulas are an adequate tool to analyze highly-correlated multiparametric mathematical models such as those appearing in Biology, with the added value of providing key information for the optimal design of experiments, reducing time and cost in in vivo and in vitro experimental campaigns, like those required in microfluidic models of GBM evolution

Micelle-Triggered b-Hairpin to a-Helix Transition in a 14-Residue Peptide from aBinding Choline- Repeat of the Pneumococcal Autolysin LytA

Choline-binding modules (CBMs) have a bb-solenoid structure composed of choline-binding repeats (CBR), which consist of a b-hairpin followed by a short linker. To find minimal peptides that are able to maintain the CBR native structure and to evaluate their remaining cholinebinding ability, we have analysed the third b-hairpin of the CBM from the pneumococcal LytA autolysin. Circular dichroism and NMR data reveal that this peptide forms a highly stable native-like b-hairpin both in aqueous solution and in the presence of trifluoroethanol, but, strikingly, the peptide structure is a stable amphipathic a-helix in both zwitterionic (dodecylphosphocholine) and anionic (sodium dodecylsulfate) detergent micelles, as well as in small unilamellar vesicles. This b-hairpin to a-helix conversion is reversible. Given that the b-hairpin and a-helix differ greatly in the distribution of hydrophobic and hydrophilic side chains, we propose that the amphipathicity is a requirement for a peptide structure to interact and to be stable in micelles or lipid vesicles. To our knowledge, this “chameleonic” behaviour is the only described case of a micelle-induced structural transition between two ordered peptide structures

Finding answers in lipid profile in COVID-19 patients

Introduction: A small percentage of patients will develop a severe form of COVID-19 caused by SARS-CoV-2 infection. Thus, it is important to predict the potential outcomes identifying early markers of poor prognosis. In this context, we evaluated the association of SARS-CoV-2 infection with lipid abnormalities and their role in prognosis. Methods: Single-center, retrospective, observational study of COVID-19 patients admitted from March to October 2020. Clinical and laboratory data, comorbidities, and treatments for COVID-19 were evaluated. Main outcomes including intensive care unit (ICU) admission and mortality were analyzed with a multivariable Cox proportional hazards regression model. Results: We selected 1489 from a total of 2038 consecutive patients with confirmed COVID-19, who had a complete lipid profile before ICU admission. During the follow-up performed in 1109 patients, we observed a decrease in T-c, HDL-c, and LDL-c in 28.6%, 42.9%, and 30.4% of patients, respectively, and an increase in TG in 76.8%. The decrease of both T-c and HDL- c was correlated with a decrease in albumin levels (r = 0.39 and r = 0.37, respectively). Kaplan–Meier survival curves found an increased ICU admission in patients with lower T-c (HR 0.55, CI 0.36–0.86), HDL-c (HR 0.61, CI 0.45–0.84), and LDL-c (HR 0.85, CI 0.74–0.97). Higher values of T-c (HR 0.45, CI 0.36–0.57), HDL-c (HR 0.66, CI 0.54–0.81), and LDL-c (HR 0.86, CI 0.78–0.94) showed a protective effect on mortality. Conclusions: Abnormalities in lipid profile are a frequent complication of SARS-CoV-2 infection and might be related to morbidity and mortalityThis work was supported by the following grants: Proyectos de Investigación en Salud (FIS) PI16-02091 and PI19-00584 (funded by Instituto de Salud Carlos III), TIRONET2-CM, B2017/BMD-3724 (funded by Comunidad de Madrid) and cofinanced by FEDER funds to M.M

Gene expression pattern in swine neutrophils after lipopolysaccharide exposure: a time course comparison

Background: Experimental exposure of swine neutrophils to bacterial lipopolysaccharide (LPS) represents a model to study the innate immune response during bacterial infection. Neutrophils can effectively limit the infection by secreting lipid mediators, antimicrobial molecules and a combination of reactive oxygen species (ROS) without new synthesis of proteins. However, it is known that neutrophils can modify the gene expression after LPS exposure. We performed microarray gene expression analysis in order to elucidate the less known transcriptional response of neutrophils during infection. Methods: Blood samples were collected from four healthy Iberian pigs and neutrophils were isolated and incubated during 6, 9 and 18 hrs in presence or absence of lipopolysaccharide (LPS) from Salmonella enterica serovar Typhimurium. RNA was isolated and hybridized to Affymetrix Porcine GeneChip®. Microarray data were normalized using Robust Microarray Analysis (RMA) and then, differential expression was obtained by an analysis of variance (ANOVA). Results: ANOVA data analysis showed that the number of differentially expressed genes (DEG) after LPS treatment vary with time. The highest transcriptional response occurred at 9 hr post LPS stimulation with 1494 DEG whereas at 6 and 18 hr showed 125 and 108 DEG, respectively. Three different gene expression tendencies were observed: genes in cluster 1 showed a tendency toward up-regulation; cluster 2 genes showing a tendency for down-regulation at 9 hr; and cluster 3 genes were up-regulated at 9 hr post LPS stimulation. Ingenuity Pathway Analysis revealed a delay of neutrophil apoptosis at 9 hr. Many genes controlling biological functions were altered with time including those controlling metabolism and cell organization, ubiquitination, adhesion, movement or inflammatory response. Conclusions: LPS stimulation alters the transcriptional pattern in neutrophils and the present results show that the robust transcriptional potential of neutrophils under infection conditions, indicating that active regulation of gene expression plays a major role in the neutrophil-mediated- innate immune respons

A computerized analysis of the entire retinal ganglion cell population and its spatial distribution in adult rats

AbstractIn adult albino (SD) and pigmented (PVG) rats the entire population of retinal ganglion cells (RGCs) was quantified and their spatial distribution analyzed using a computerized technique. RGCs were back-labelled from the optic nerves (ON) or the superior colliculi (SCi) with Fluorogold (FG). Numbers of RGCs labelled from the ON [SD: 82,818±3,949, n=27; PVG: 89,241±3,576, n=6) were comparable to those labelled from the SCi [SD: 81,486±4,340, n=37; PVG: 87,229±3,199; n=59]. Detailed methodology to provide cell density information at small scales demonstrated the presence of a horizontal region in the dorsal retina with highest densities, resembling a visual streak

A multiscale data-driven approach for bone tissue biomechanics

The data-driven methodology with application to continuum mechanics relies upon two main pillars: (i) experimental characterization of stress–strain pairs associated to different loading states, and (ii) numerical elaboration of the elasticity equations as an optimization (searching) algorithm using compatibility and equilibrium as constraints. The purpose of this work is to implement a multiscale data-driven approach using experimental data of cortical bone tissue at different scales. First, horse cortical bone samples are biaxially loaded and the strain fields are recorded over a region of interest using a digital image correlation technique. As a result, both microscopic strain fields and macroscopic strain states are obtained by a homogenization procedure, associated to macroscopic stress loading states which are considered uniform along the sample. This experimental outcome is here referred as a multiscale dataset. Second, the proposed multiscale data-driven methodology is implemented and analyzed in an example of application. Results are presented both in the macroscopic and microscopic scales, with the latter considered just as a post-process step in the formulation. The macroscopic results show non-smooth strain and stress patterns as a consequence of the tissue heterogeneity which suggest that a preassumed linear homogeneous orthotropic model may be inaccurate for bone tissue. Microscopic results show fluctuating strain fields – as a consequence of the interaction and evolution of the microconstituents – an order of magnitude higher than the averaged macroscopic solution, which evidences the need of a multiscale approach for the mechanical analysis of cortical bone, since the driving force of many biological bone processes is local at the microstructural level. Finally, the proposed multiscale data-driven technique may also be an adequate strategy for the solution of intractable large size multiscale FE2 computational approaches since the solution at the microscale is obtained as a postprocessing. As a main conclusion, the proposed multiscale data-driven methodology is a useful alternative to overcome limitations in the continuum mechanical study of the bone tissue. This methodology may also be considered as a useful strategy for the analysis of additional biological or technological hierarchical multiscale materials

The Role of Women on Dairy Goat Farms in Southern Spain

One of the factors involved in goat milk production is the role of women as farmers. The aim of this study was to evaluate the role of women on dairy goat farms, considering: (1) the profile of women occupationally involved, (2) the organization of the women’s work, (3) the degree of involvement by women in the decision-making on these farms, and (4) the influence of women’s work on productive results. This study was conducted on 52 dairy goat farms in southern Spain. A descriptive analysis and means comparisons were performed to describe the farms where any women were involved or not. In 61.5% of the farms, at least one woman was involved, with an age of 42.2 ± 8.8 years. Very few women were farm owners, although women took binding decisions in 81.25% of these farms. Their work is dedicated to milking and caring for the kids. Women had a positive influence on the productive variables analysed, and for mastitis in herds, the incidence was lower in herds where women participated (p < 0.01). In conclusion, it is recommended to include women’s work as a factor when characterizing dairy goats farms’ systems to evaluate their positive effect on a farm’s performance