Circulating TRAIL Shows a Significant Post-Partum Decline Associated to Stressful Conditions

Background: Since circulating levels of TNF-related apoptosis inducing ligand (TRAIL) may be important in the physiopathology of pregnancy, we tested the hypothesis that TRAIL levels change at delivery in response to stressful conditions. Methods/Principal Findings: We conducted a longitudinal study in a cohort of 73 women examined at week 12, week 16, delivery and in the corresponding cord blood (CB). Serum TRAIL was assessed in relationship with maternal characteristics and to biochemical parameters. TRAIL did not vary between 12 (67.6627.6 pg/ml, means6SD) and 16 (64.0616.2 pg/ml) weeks ’ gestation, while displaying a significant decline after partum (49.3626.4 pg/ml). Using a cut-off decline.20 pg/ml between week 12 and delivery, the subset of women with the higher decline of circulating TRAIL (41.7%) showed the following characteristics: i) nullipara, ii) higher age, iii) operational vaginal delivery or urgent CS, iv) did not receive analgesia during labor, v) induced labor. CB TRAIL was significantly higher (131.6652 pg/ml) with respect to the corresponding maternal TRAIL, and the variables significantly associated with the first quartile of CB TRAIL (,90 pg/ml) were higher prepregnancy BMI, induction of labor and fetal distress. With respect to the biochemical parameters, maternal TRAIL at delivery showed an inverse correlation with C-reactive protein (CRP), total cortisol, glycemia and insulin at bivariate analysis, but only with CRP at multivariate analysis

The Expression of BAFF, APRIL and TWEAK Is Altered in Eczema Skin but Not in the Circulation of Atopic and Seborrheic Eczema Patients

The TNF family cytokines BAFF (B-cell activating factor of the TNF family) and APRIL (a proliferation-inducing ligand) are crucial survival factors for B-cell development and activation. B-cell directed treatments have been shown to improve atopic eczema (AE), suggesting the involvement of these cytokines in the pathogenesis of AE. We therefore analyzed the expression of these TNF cytokines in AE, seborrheic eczema (SE) and healthy controls (HC). The serum/plasma concentration of BAFF, APRIL and a close TNF member TWEAK (TNF-like weak inducer of apoptosis) was measured by ELISA. The expression of these cytokines and their receptors in skin was analyzed by quantitative RT-PCR and immunofluorescence. Unlike other inflammatory diseases including autoimmune diseases and asthma, the circulating levels of BAFF, APRIL and TWEAK were not elevated in AE or SE patients compared with HCs and did not correlate with the disease severity or systemic IgE levels in AE patients. Interestingly, we found that the expression of these cytokines and their receptors was altered in positive atopy patch test reactions in AE patients (APT-AE) and in lesional skin of AE and SE patients. The expression of APRIL was decreased and the expression of BAFF was increased in eczema skin of AE and SE, which could contribute to a reduced negative regulatory input on B-cells. This was found to be more pronounced in APT-AE, the initiating acute stage of AE, which may result in dysregulation of over-activated B-cells. Furthermore, the expression levels of TWEAK and its receptor positively correlated to each other in SE lesions, but inversely correlated in AE lesions. These results shed light on potential pathogenic roles of these TNF factors in AE and SE, and pinpoint a potential of tailored treatments towards these factors in AE and SE

Molecular mechanisms of vaspin action: from adipose tissue to skin and bone, from blood vessels to the brain

Visceral adipose tissue derived serine protease inhibitor (vaspin) or SERPINA12 according to the serpin nomenclature was identified together with other genes and gene products that  were specifically expressed or overexpressed in the intra abdominal or visceral adipose tissue  (AT) of the Otsuka Long-Evans Tokushima fatty rat. These rats spontaneously develop visceral  obesity, insulin resistance, hyperinsulinemia and ‐glycemia, as well as hypertension and thus represent a well suited animal model of obesity and related metabolic disorders such as type  2 diabetes.  The follow-up study reporting the cloning, expression and functional characterization of  vaspin suggested the great and promising potential of this molecule to counteract obesity induced insulin resistance and inflammation and has since initiated over 300 publications, clinical and experimental, that have contributed to uncover the multifaceted functions and molecular mechanisms of vaspin action not only in the adipose, but in many different cells, tissues and organs. This review will give an update on mechanistic and structural aspects of vaspin with a focus on its serpin function, the physiology and regulation of vaspin expression, and will summarize the latest on vaspin function in various tissues such as the different adipose tissue depots as well as the vasculature, skin, bone and the brain

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between data and simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation