The impact of stress and stress hormones on endogenous clocks and circadian rhythms

In mammals, daily rhythms in physiology and behavior are under control of a circadian pacemaker situated in the suprachiasmatic nucleus (SCN). This master clock receives photic input from the retina and coordinates peripheral oscillators present in other tissues, maintaining all rhythms in the body synchronized to the environmental light-dark cycle. In line with its function as a master clock, the SCN appears to be well protected against unpredictable stressful stimuli. However, available data indicate that stress and stress hormones at certain times of day are capable of shifting peripheral oscillators in, e.g., liver, kidney and heart, which are normally under control of the SCN. Such shifts of peripheral oscillators may represent a temporary change in circadian organization that facilitates adaptation to repeated stress. Alternatively, these shifts of internal rhythms may represent an imbalance between precisely orchestrated physiological and behavioral processes that may have severe consequences for health and well-being

Pre-test metyrapone impairs memory recall in fear conditioning tasks: lack of interaction with I--adrenergic activity

Cognitive processes, such as learning and memory, are essential for our adaptation to environmental changes and consequently for survival. Numerous studies indicate that hormones secreted during stressful situations, such as glucocorticoids (GCs), adrenaline and noradrenaline, regulate memory functions, modulating aversive memory consolidation and retrieval, in an interactive and complementary way. Thus, the facilitatory effects of GCs on memory consolidation as well as their suppressive effects on retrieval are substantially explained by this interaction. On the other hand, low levels of GCs are also associated with negative effects on memory consolidation and retrieval and the mechanisms involved are not well understood. the present study sought to investigate the consequences of blocking the rise of GCs on fear memory retrieval in multiple tests, assessing the participation of (3-adrenergic signaling on this effect. Metyrapone (GCs synthesis inhibitor; 75 mg/kg), administered 90 min before the first test of contextual or tone fear conditioning (TFC), negatively affected animals' performances, but this effect did not persist on a subsequent test, when the conditioned response was again expressed. This result suggested that the treatment impaired fear memory retrieval during the first evaluation. the administration immediately after the first test did not affect the animals' performances in contextual fear conditioning (CFC), suggesting that the drug did not interfere with processes triggered by memory reactivation. Moreover, metyrapone effects were independent of beta-adrenergic signaling, since concurrent administration with propranolol (2 mg/kg), alpha,beta-adrenergic antagonist, did not modify the effects induced by metyrapone alone. These results demonstrate that pre-test metyrapone administration led to negative effects on fear memory retrieval and this action was independent of a beta-adrenergic signaling.Associacao Fund de Incentivo a Pesquisa (AFIP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundacao de Amparo Pesquisa do Estado de São PauloUniversidade Federal de São Paulo, Dept Psicobiol, BR-04024002 São Paulo, BrazilUniv Fed ABC, Ctr Matemat Comp & Cognicao, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Psicobiol, BR-04024002 São Paulo, BrazilFundacao de Amparo Pesquisa do Estado de São Paulo: FAPESP 2011/16977-8Web of Scienc

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Measurement of the top quark forward-backward production asymmetry and the anomalous chromoelectric and chromomagnetic moments in pp collisions at √s = 13 TeV

Abstract The parton-level top quark (t) forward-backward asymmetry and the anomalous chromoelectric (d̂ t) and chromomagnetic (μ̂ t) moments have been measured using LHC pp collisions at a center-of-mass energy of 13 TeV, collected in the CMS detector in a data sample corresponding to an integrated luminosity of 35.9 fb−1. The linearized variable AFB(1) is used to approximate the asymmetry. Candidate t t ¯ events decaying to a muon or electron and jets in final states with low and high Lorentz boosts are selected and reconstructed using a fit of the kinematic distributions of the decay products to those expected for t t ¯ final states. The values found for the parameters are AFB(1)=0.048−0.087+0.095(stat)−0.029+0.020(syst),μ̂t=−0.024−0.009+0.013(stat)−0.011+0.016(syst), and a limit is placed on the magnitude of | d̂ t| < 0.03 at 95% confidence level. [Figure not available: see fulltext.

Combined searches for the production of supersymmetric top quark partners in proton-proton collisions at root s=13 TeV

A combination of searches for top squark pair production using proton-proton collision data at a center-of-mass energy of 13 TeV at the CERN LHC, corresponding to an integrated luminosity of 137 fb(-1) collected by the CMS experiment, is presented. Signatures with at least 2 jets and large missing transverse momentum are categorized into events with 0, 1, or 2 leptons. New results for regions of parameter space where the kinematical properties of top squark pair production and top quark pair production are very similar are presented. Depending on themodel, the combined result excludes a top squarkmass up to 1325 GeV for amassless neutralino, and a neutralinomass up to 700 GeV for a top squarkmass of 1150 GeV. Top squarks with masses from 145 to 295 GeV, for neutralino masses from 0 to 100 GeV, with a mass difference between the top squark and the neutralino in a window of 30 GeV around the mass of the top quark, are excluded for the first time with CMS data. The results of theses searches are also interpreted in an alternative signal model of dark matter production via a spin-0 mediator in association with a top quark pair. Upper limits are set on the cross section for mediator particle masses of up to 420 GeV

MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe