Increased interaction between endoplasmic reticulum and mitochondria following sleep deprivation

Background: Prolonged cellular activity may overload cell function, leading to high rates of protein synthesis and accumulation of misfolded or unassembled proteins, which cause endoplasmic reticulum (ER) stress and activate the unfolded protein response (UPR) to re-establish normal protein homeostasis. Previous molecular work has demonstrated that sleep deprivation (SD) leads to ER stress in neurons, with a number of ER-specific proteins being upregulated to maintain optimal cellular proteostasis. It is still not clear which cellular processes activated by sleep deprivation lead to ER-stress, but increased cellular metabolism, higher request for protein synthesis, and over production of oxygen radicals have been proposed as potential contributing factors. Here, we investigate the transcriptional and ultrastructural ER and mitochondrial modifications induced by sleep loss.Results: We used gene expression analysis in mouse forebrains to show that SD was associated with significant transcriptional modifications of genes involved in ER stress but also in ER-mitochondria interaction, calcium homeostasis, and mitochondrial respiratory activity. Using electron microscopy, we also showed that SD was associated with a general increase in the density of ER cisternae in pyramidal neurons of the motor cortex. Moreover, ER cisternae established new contact sites with mitochondria, the so-called mitochondria associated membranes (MAMs), important hubs for molecule shuttling, such as calcium and lipids, and for the modulation of ATP production and redox state. Finally, we demonstrated that Drosophila male mutant flies (elav > linker), in which the number of MAMs had been genetically increased, showed a reduction in the amount and consolidation of sleep without alterations in the homeostatic sleep response to SD. Conclusions: We provide evidence that sleep loss induces ER stress characterized by increased crosstalk between ER and mitochondria. MAMs formation associated with SD could represent a key phenomenon for the modulation of multiple cellular processes that ensure appropriate responses to increased cell metabolism. In addition, MAMs establishment may play a role in the regulation of sleep under baseline conditions

Decline in macrolide resistance rates among Streptococcus pyogenes causing pharyngitis in children isolated in Italy

Macrolides are often used to treat group A streptococcus (GAS) infections, but their resistance rates reached high proportions worldwide. The aim of the present study was to give an update on the characteristics and contemporary prevalence of macrolide-resistant pharyngeal GAS in Central Italy. A total of 592 isolates causing pharyngitis in children were collected in the period 2012-2013. Clonality was assessed by emm typing and pulsed-field gel electrophoresis (PFGE) for all macrolide-resistant strains and for selected susceptible isolates. Genetic determinants of resistance were screened by polymerase chain reaction (PCR). Forty-four GAS were erythromycin-resistant (7.4 %). Among them, 52.3 % and 50 % were clindamycin- and tetracycline-resistant, respectively. erm(B)-positive isolates (52.3 %) expressed the constitutive cMLSB phenotype. mef(A) and its associated M phenotype were recorded in 40.9 % of the cases. The remaining erm(A)-positive isolates expressed the iMLSB phenotype. Seventeen tetracycline-resistant isolates carried tet(M) and five isolates carried tet(O). Twenty-five emm types were found among all strains, with the predominance of emm types 12, 89, 1, and 4. Eleven emm types and 12 PFGE clusters characterized macrolide-resistant strains, with almost two-thirds belonging to emm12, emm4, and emm11. Macrolide-susceptible and -resistant emm types 12, 89, 11, and 4 shared related PFGE profiles. There was a dramatic decline in macrolide resistance in Central Italy among pharyngeal GAS isolates in 2012-2013 when compared to previous studies from the same region (p < 0.05), although macrolide consumption remained stable over the past 15 years. We observed a decrease in the proportion of macrolide-resistant strains within emm types commonly associated with macrolide resistance in the past, namely emm12, 1, and 89

Reduction of EEG Theta Power and Changes in Motor Activity in Rats Treated with Ceftriaxone

The glutamate transporter GLT-1 is responsible for the largest proportion of total glutamate transport. Recently, it has been demonstrated that ceftriaxone (CEF) robustly increases GLT-1 expression. In addition, physiological studies have shown that GLT-1 up-regulation strongly affects synaptic plasticity, and leads to an impairment of the prepulse inhibition, a simple form of information processing, thus suggesting that GLT-1 over-expression may lead to dysfunctions of large populations of neurons. To test this possibility, we assessed whether CEF affects cortical electrical activity by using chronic electroencephalographic (EEG) recordings in male WKY rats. Spectral analysis showed that 8 days of CEF treatment resulted in a delayed reduction in EEG theta power (7–9 Hz) in both frontal and parietal derivations. This decrease peaked at day 10, i.e., 2 days after the end of treatment, and disappeared by day 16. In addition, we found that the same CEF treatment increased motor activity, especially when EEG changes are more prominent. Taken together, these data indicate that GLT-1 up-regulation, by modulating glutamatergic transmission, impairs the activity of widespread neural circuits. In addition, the increased motor activity and prepulse inhibition alterations previously described suggest that neural circuits involved in sensorimotor control are particularly sensitive to GLT-1 up-regulation

SNPs in DNA repair or oxidative stress genes and late subcutaneous fibrosis in patients following single shot partial breast irradiation

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to evaluate the potential association between single nucleotide polymorphisms related response to radiotherapy injury, such as genes related to DNA repair or enzymes involved in anti-oxidative activities. The paper aims to identify marker genes able to predict an increased risk of late toxicity studying our group of patients who underwent a Single Shot 3D-CRT PBI (SSPBI) after BCS (breast conserving surgery).</p> <p>Methods</p> <p>A total of 57 breast cancer patients who underwent SSPBI were genotyped for SNPs (single nucleotide polymorphisms) in XRCC1, XRCC3, GST and RAD51 by Pyrosequencing technology. Univariate analysis (ORs and 95% CI) was performed to correlate SNPs with the risk of developing ≥ G2 fibrosis or fat necrosis.</p> <p>Results</p> <p>A higher significant risk of developing ≥ G2 fibrosis or fat necrosis in patients with: polymorphic variant <it>GSTP1 </it>(Ile105Val) (OR = 2.9; 95%CI, 0.88-10.14, <it>p </it>= 0.047).</p> <p>Conclusions</p> <p>The presence of some SNPs involved in DNA repair or response to oxidative stress seem to be able to predict late toxicity.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01316328">NCT01316328</a></p

A machine-learning parsimonious multivariable predictive model of mortality risk in patients with Covid-19

The COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented in daily practice. The objective of the study was to validate a machine-learning risk prediction model using easy-to-obtain parameters to help to identify patients with COVID-19 who are at higher risk of death. The training cohort included all patients admitted to Fondazione Policlinico Gemelli with COVID-19 from March 5, 2020, to November 5, 2020. Afterward, the model was tested on all patients admitted to the same hospital with COVID-19 from November 6, 2020, to February 5, 2021. The primary outcome was in-hospital case-fatality risk. The out-of-sample performance of the model was estimated from the training set in terms of Area under the Receiving Operator Curve (AUROC) and classification matrix statistics by averaging the results of fivefold cross validation repeated 3-times and comparing the results with those obtained on the test set. An explanation analysis of the model, based on the SHapley Additive exPlanations (SHAP), is also presented. To assess the subsequent time evolution, the change in paO2/FiO2 (P/F) at 48&nbsp;h after the baseline measurement was plotted against its baseline value. Among the 921 patients included in the training cohort, 120 died (13%). Variables selected for the model were age, platelet count, SpO2, blood urea nitrogen (BUN), hemoglobin, C-reactive protein, neutrophil count, and sodium. The results of the fivefold cross-validation repeated 3-times gave AUROC of 0.87, and statistics of the classification matrix to the Youden index as follows: sensitivity 0.840, specificity 0.774, negative predictive value 0.971. Then, the model was tested on a new population (n = 1463) in which the case-fatality rate was 22.6%. The test model showed AUROC 0.818, sensitivity 0.813, specificity 0.650, negative predictive value 0.922. Considering the first quartile of the predicted risk score (low-risk score group), the case-fatality rate was 1.6%, 17.8% in the second and third quartile (high-risk score group) and 53.5% in the fourth quartile (very high-risk score group). The three risk score groups showed good discrimination for the P/F value at admission, and a positive correlation was found for the low-risk class to P/F at 48&nbsp;h after admission (adjusted R-squared = 0.48). We developed a predictive model of death for people with SARS-CoV-2 infection by including only easy-to-obtain variables (abnormal blood count, BUN, C-reactive protein, sodium and lower SpO2). It demonstrated good accuracy and high power of discrimination. The simplicity of the model makes the risk prediction applicable for patients in the Emergency Department, or during hospitalization. Although it is reasonable to assume that the model is also applicable in not-hospitalized persons, only appropriate studies can assess the accuracy of the model also for persons at home

Interactions of bile salts with a dietary fibre, methylcellulose, and impact on lipolysis

Methylcellulose (MC) has a demonstrated capacity to reduce fat absorption, hypothetically through bile salt (BS) activity inhibition. We investigated MC cholesterol-lowering mechanism, and compared the influence of two BS, sodium taurocholate (NaTC) and sodium taurodeoxycholate (NaTDC), which differ slightly by their architecture and exhibit contrasting functions during lipolysis. BS/MC bulk interactions were investigated by rheology, and BS behaviour at the MC/water interface studied with surface pressure and ellipsometry measurements. In vitro lipolysis studies were performed to evaluate the effect of BS on MC-stabilised emulsion droplets microstructure, with confocal microscopy, and free fatty acids release, with the pH-stat method. Our results demonstrate that BS structure dictates their interactions with MC, which, in turn, impact lipolysis. Compared to NaTC, NaTDC alters MC viscoelasticity more significantly, which may correlate with its weaker ability to promote lipolysis, and desorbs from the interface at lower concentrations, which may explain its higher propensity to destabilise emulsions

A Neuron-Glial Perspective for Computational Neuroscience

International audienceThere is growing excitement around glial cells, as compelling evidence point to new, previously unimaginable roles for these cells in information processing of the brain, with the potential to affect behavior and higher cognitive functions. Among their many possible functions, glial cells could be involved in practically every aspect of the brain physiology in health and disease. As a result, many investigators in the field welcome the notion of a Neuron-Glial paradigm of brain function, as opposed to Ramon y Cayal's more classical neuronal doctrine which identifies neurons as the prominent, if not the only, cells capable of a signaling role in the brain. The demonstration of a brain-wide Neuron-Glial paradigm however remains elusive and so does the notion of what neuron-glial interactions could be functionally relevant for the brain computational tasks. In this perspective, we present a selection of arguments inspired by available experimental and modeling studies with the aim to provide a biophysical and conceptual platform to computational neuroscience no longer as a mere prerogative of neuronal signaling but rather as the outcome of a complex interaction between neurons and glial cells