Recollection, Familiarity, and Cortical Reinstatement: A Multivoxel Pattern Analysis

SummaryEpisodic memory retrieval is thought to involve reinstatement of the neurocognitive processes engaged when an episode was encoded. Prior fMRI studies and computational models have suggested that reinstatement is limited to instances in which specific episodic details are recollected. We used multivoxel pattern-classification analyses of fMRI data to investigate how reinstatement is associated with different memory judgments, particularly those accompanied by recollection versus a feeling of familiarity (when recollection is absent). Classifiers were trained to distinguish between brain activity patterns associated with different encoding tasks and were subsequently applied to recognition-related fMRI data to determine the degree to which patterns were reinstated. Reinstatement was evident during both recollection- and familiarity-based judgments, providing clear evidence that reinstatement is not sufficient for eliciting a recollective experience. The findings are interpreted as support for a continuous, recollection-related neural signal that has been central to recent debate over the nature of recognition memory processes

Defect configurations and dynamical behavior in a Gay-Berne nematic emulsion

To model a nematic emulsion consisting of a surfactant-coated water droplet dispersed in a nematic host, we performed a molecular dynamics simulation of a droplet immersed in a system of 2048 Gay-Berne ellipsoids in a nematic phase. Strong radial anchoring at the surface of the droplet induced a Saturn ring defect configuration, consistent with theoretical predictions for very small droplets. A surface ring configuration was observed for lower radial anchoring strengths, and a pair of point defects was found near the poles of the droplet for tangential anchoring. We also simulated the falling ball experiment and measured the drag force anisotropy, in the presence of strong radial anchoring as well as zero anchoring strength.Comment: 17 pages, 15 figure

Approaches to dose finding in neonates, illustrating the variability between neonatal drug development programs

Drug dosing in neonates should be based on integrated knowledge concerning the disease to be treated, the physiological characteristics of the neonate, and the pharmacokinetics (PK) and pharmacodynamics (PD) of a given drug. It is critically important that all sources of information be leveraged to optimize dose selection for neonates. Sources may include data from adult studies, pediatric studies, non-clinical (juvenile) animal models, in vitro studies, and in silico models. Depending on the drug development program, each of these modalities could be used to varying degrees and with varying levels of confidence to guide dosing. This paper aims to illustrate the variability between neonatal drug development programs for neonatal diseases that are similar to those seen in other populations (meropenem), neonatal diseases related but not similar to pediatric or adult populations (clopidogrel, thyroid hormone), and diseases unique to neonates (caffeine, surfactant). Extrapolation of efficacy from older children or adults to neonates is infrequently used. Even if a disease process is similar between neonates and children or adults, such as with anti-infectives, additional dosing and safety information will be necessary for labeling, recognizing that dosing in neonates is confounded by maturational PK in addition to body size

Assessing associations between the AURKAHMMR-TPX2-TUBG1 functional module and breast cancer risk in BRCA1/2 mutation carriers

While interplay between BRCA1 and AURKA-RHAMM-TPX2-TUBG1 regulates mammary epithelial polarization, common genetic variation in HMMR (gene product RHAMM) may be associated with risk of breast cancer in BRCA1 mutation carriers. Following on these observations, we further assessed the link between the AURKA-HMMR-TPX2-TUBG1 functional module and risk of breast cancer in BRCA1 or BRCA2 mutation carriers. Forty-one single nucleotide polymorphisms (SNPs) were genotyped in 15,252 BRCA1 and 8,211 BRCA2 mutation carriers and subsequently analyzed using a retrospective likelihood appr

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Identification of post-blast explosive residues using direct-analysis-in-real-time and mass spectrometry (DART-MS)

Application of Direct-Analysis-in-Real-Time (DART) ionization with mass spectrometry (DART-MS) to identify homemade explosive (HME) residue recovered from genuine post-blast bomb fragments is presented. A variety of simulated improvised explosive devices (IEDs) were configured to replicate post-blast debris representative of materials encountered in real forensic casework scenarios. Peroxide-based HME was used as explosive filler: triacetone triperoxide (TATP), hexamethylene triperoxide diamine (HMTD) and methyl ethyl ketone peroxide (MEKP). Each IED was fired separately and the recovered fragments analyzed using full scan with high-resolution mass spectrometry. Fragments were analyzed directly and indirectly using cotton swabs and the target explosive was detected using either sampling technique. This work demonstrates the forensic validity of DART-MS to provide rapid and quality-assured identification of explosive residues from real post-blast IED fragments