Entanglement and Timing-Based Mechanisms in the Coherent Control of Scattering Processes

The coherent control of scattering processes is considered, with electron impact dissociation of H$_2^+$ used as an example. The physical mechanism underlying coherently controlled stationary state scattering is exposed by analyzing a control scenario that relies on previously established entanglement requirements between the scattering partners. Specifically, initial state entanglement assures that all collisions in the scattering volume yield the desirable scattering configuration. Scattering is controlled by preparing the particular internal state wave function that leads to the favored collisional configuration in the collision volume. This insight allows coherent control to be extended to the case of time-dependent scattering. Specifically, we identify reactive scattering scenarios using incident wave packets of translational motion where coherent control is operational and initial state entanglement is unnecessary. Both the stationary and time-dependent scenarios incorporate extended coherence features, making them physically distinct. From a theoretical point of view, this work represents a large step forward in the qualitative understanding of coherently controlled reactive scattering. From an experimental viewpoint, it offers an alternative to entanglement-based control schemes. However, both methods present significant challenges to existing experimental technologies

Effects of MDMA on blood glucose levels and brain glucose metabolism

Purpose This study was designed to assess changes in glucose metabolism in rats administered single or repeated doses of MDMA. Methods Two different experiments were performed: (1) A single-dose study with four groups receiving 20 mg/kg, 40 mg/kg, saline or heat, and (2) a repeated-dose study with two groups receiving three doses, at intervals of 2 h, of 5 mg/kg or saline. Rats were imaged using a dedicated small-animal PET scanner 1 h after single-dose administration or 7 days after repeated doses. Glucose metabolism was measured in 12 cerebral regions of interest. Rectal temperature and blood glucose were monitored. Results Peak body temperature was reached 1 h after MDMA administration. Blood glucose levels decreased significantly after MDMA administration. In the single-dose experiment, brain glucose metabolism showed hyperactivation in cerebellum and hypo-activation in the hippocampus, amygdala and auditory cortex. In the repeated-dose experiment, brain glucose metabolism did not show any significant change at day 7. Conclusion These results are the first to indicate that MDMA has the potential to produce significant hypoglycaemia. In addition, they show that MDMA alters glucose metabolism in components of the motor, limbic and somatosensory systems acutely but not on a long-term basisPublicad

Metacognition as Evidence for Evidentialism

Metacognition is the monitoring and controlling of cognitive processes. I examine the role of metacognition in ‘ordinary retrieval cases’, cases in which it is intuitive that via recollection the subject has a justified belief. Drawing on psychological research on metacognition, I argue that evidentialism has a unique, accurate prediction in each ordinary retrieval case: the subject has evidence for the proposition she justifiedly believes. But, I argue, process reliabilism has no unique, accurate predictions in these cases. I conclude that ordinary retrieval cases better support evidentialism than process reliabilism. This conclusion challenges several common assumptions. One is that non-evidentialism alone allows for a naturalized epistemology, i.e., an epistemology that is fully in accordance with scientific research and methodology. Another is that process reliabilism fares much better than evidentialism in the epistemology of memory

Sex genes for genomic analysis in human brain: internal controls for comparison of probe level data extraction.

BACKGROUND: Genomic studies of complex tissues pose unique analytical challenges for assessment of data quality, performance of statistical methods used for data extraction, and detection of differentially expressed genes. Ideally, to assess the accuracy of gene expression analysis methods, one needs a set of genes which are known to be differentially expressed in the samples and which can be used as a "gold standard". We introduce the idea of using sex-chromosome genes as an alternative to spiked-in control genes or simulations for assessment of microarray data and analysis methods. RESULTS: Expression of sex-chromosome genes were used as true internal biological controls to compare alternate probe-level data extraction algorithms (Microarray Suite 5.0 [MAS5.0], Model Based Expression Index [MBEI] and Robust Multi-array Average [RMA]), to assess microarray data quality and to establish some statistical guidelines for analyzing large-scale gene expression. These approaches were implemented on a large new dataset of human brain samples. RMA-generated gene expression values were markedly less variable and more reliable than MAS5.0 and MBEI-derived values. A statistical technique controlling the false discovery rate was applied to adjust for multiple testing, as an alternative to the Bonferroni method, and showed no evidence of false negative results. Fourteen probesets, representing nine Y- and two X-chromosome linked genes, displayed significant sex differences in brain prefrontal cortex gene expression. CONCLUSION: In this study, we have demonstrated the use of sex genes as true biological internal controls for genomic analysis of complex tissues, and suggested analytical guidelines for testing alternate oligonucleotide microarray data extraction protocols and for adjusting multiple statistical analysis of differentially expressed genes. Our results also provided evidence for sex differences in gene expression in the brain prefrontal cortex, supporting the notion of a putative direct role of sex-chromosome genes in differentiation and maintenance of sexual dimorphism of the central nervous system. Importantly, these analytical approaches are applicable to all microarray studies that include male and female human or animal subjects

Impact of coronavirus syndromes on physical and mental health of health care workers: Systematic review and meta-analysis

Background: Health care workers (HCW) are at high risk of developing physical/mental health outcomes related to coronavirus syndromes. Nature and frequency of these outcomes are undetermined. Methods: PRISMA/MOOSE-compliant (PROSPERO-CRD42020180205) systematic review of Web of Science/grey literature until 15th April 2020, to identify studies reporting physical/mental health outcomes in HCW infected/exposed to Severe Acute Respiratory Syndrome -SARS-, Middle East Respiratory Syndrome -MERS-, Novel coronavirus -COVID-19-. Proportion random effect meta-analyses, I2 statistic, quality assessment and sensitivity analysis. Results: 115 articles were included (n=60,458 HCW, age 36.1±7.1, 77.1% female). Physical health outcomes: 75.9% HCW infected by SARS/MERS/COVID-19 reported fever (95%CI=65.9–83.7%, k=12, n=949), 47.9% cough (95%CI=39.2–56.8%, k=14, n=970), 43.6% myalgias (95%CI=31.9–56.0%, k=13, n=898), 42.3% chills (95%CI=20.2–67.9%, k=7, n=716), 41.2% fatigue (95%CI=18.2–68.8%, k=6, n=386), 34.6% headaches (95%CI=23.1–48.2%, k=11, n=893), 31.2% dyspnoea (95%CI=23.2–40.5%, k=12, n=1003), 25.3% sore throat (95%CI=18.8–33.2%, k=8, n=747), 22.2% nausea/vomiting (95%CI=14.9–31.8%, k=6, n=662), 18.8% diarrhoea (95%CI=11.9–28.4%, k=9, n=824). Mental health outcomes: 62.5% HCW exposed to SARS/MERS/COVID-19 reported general health concerns (95%CI=57.0–67,8%, k=2, n=2254), 43.7% fear (95%CI=33.9–54.0%, k=4, n=584), 37.9% insomnia (95%CI=30.9–45.5%, k=6, n=5067), 37.8% psychological distress (95%CI=28.4–48.2%, k=15, n=24,346), 34.4% burnout (95%CI=19.3–53.5%, k=3, n=1337), 29.0% anxiety features (95%CI=14.2–50.3%, k=6, n=9191), 26.3% depressive symptoms (95%CI=12.5–47.1%, k=8, n=9893), 20.7% post-traumatic stress disorder features (95%CI=13.2–31%, k=11, n=3826), 16.1% somatisation (95%CI=0.2–96.0%, k=2, n=2184), 14.0% stigmatisation feelings (95%CI=6.4–28.1%, k=2, n=411). Limitations: Limited amount of evidence for some outcomes and suboptimal design in several studies included. Conclusions: SARS/MERS/COVID-19 have a substantial impact on the physical and mental health of HCW, which should become a priority for public health strategies

Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics

Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper, we present an extension of the BHC algorithm. Our Gaussian BHC (GBHC) algorithm represents data as a mixture of Gaussian distributions. It uses normal-gamma distribution as a conjugate prior on the mean and precision of each of the Gaussian components. We tested GBHC over 11 cancer and 3 synthetic datasets. The results on cancer datasets show that in sample clustering, GBHC on average produces a clustering partition that is more concordant with the ground truth than those obtained from other commonly used algorithms. Furthermore, GBHC frequently infers the number of clusters that is often close to the ground truth. In gene clustering, GBHC also produces a clustering partition that is more biologically plausible than several other state-of-the-art methods. This suggests GBHC as an alternative tool for studying gene expression data. The implementation of GBHC is available at https://sites. google.com/site/gaussianbhc

Diverged subpopulations in tropical Urochloa (Brachiaria) forage species indicate a role for facultative apomixis and varying ploidy in their population structure and evolution

Abstract Background Urochloa (syn. Brachiaria) is a genus of tropical grasses sown as forage feedstock, particularly in marginal soils. Here we aimed to clarify the genetic diversity and population structure in Urochloa species to understand better how population evolution relates to ploidy level and occurrence of apomictic reproduction. Methods We explored the genetic diversity of 111 accessions from the five Urochloa species used to develop commercial cultivars. These accessions were conserved from wild materials collected at their centre of origin in Africa, and they tentatively represent the complete Urochloa gene pool used in breeding programmes. We used RNA-sequencing to generate 1.1 million single nucleotide polymorphism loci. We employed genetic admixture, principal component and phylogenetic analyses to define subpopulations. Results We observed three highly differentiated subpopulations in U. brizantha, which were unrelated to ploidy: one intermixed with U. decumbens, and two diverged from the former and the other species in the complex. We also observed two subpopulations in U. humidicola, unrelated to ploidy; one subpopulation had fewer accessions but included the only characterized sexual accession in the species. Our results also supported a division of U. decumbens between diploids and polyploids, and no subpopulations within U. ruziziensis and U. maxima. Conclusions Polyploid U. decumbens are more closely related to polyploid U. brizantha than to diploid U. decumbens, which supports the divergence of both polyploid groups from a common tetraploid ancestor and provides evidence for the hybridization barrier of ploidy. The three differentiated subpopulations of apomictic polyploid U. brizantha accessions constitute diverged ecotypes, which can probably be utilized in hybrid breeding. Subpopulations were not observed in non-apomictic U. ruziziensis. Sexual Urochloa polyploids were not found (U. brizantha, U. decumbens) or were limited to small subpopulations (U. humidicola). The subpopulation structure observed in the Urochloa sexual–apomictic multiploidy complexes supports geographical parthenogenesis, where the polyploid genotypes exploit the evolutionary advantage of apomixis, i.e. uniparental reproduction and clonality, to occupy extensive geographical areas

Association of extent of cannabis use and psychotic like intoxication experiences in a multi-national sample of first episode psychosis patients and controls

BackgroundFirst episode psychosis (FEP) patients who use cannabis experience more frequent psychotic and euphoric intoxication experiences compared to controls. It is not clear whether this is consequent to patients being more vulnerable to the effects of cannabis use or to their heavier pattern of use. We aimed to determine whether extent of use predicted psychotic-like and euphoric intoxication experiences in patients and controls and whether this differs between groups.MethodsWe analysed data on patients who had ever used cannabis (n = 655) and controls who had ever used cannabis (n = 654) across 15 sites from six countries in the EU-GEI study (2010-2015). We used multiple regression to model predictors of cannabis-induced experiences and to determine if there was an interaction between caseness and extent of use.ResultsCaseness, frequency of cannabis use and money spent on cannabis predicted psychotic-like and euphoric experiences (p ≤ 0.001). For psychotic-like experiences (PEs) there was a significant interaction for caseness × frequency of use (p < 0.001) and caseness × money spent on cannabis (p = 0.001) such that FEP patients had increased experiences at increased levels of use compared to controls. There was no significant interaction for euphoric experiences (p > 0.5).ConclusionsFEP patients are particularly sensitive to increased psychotic-like, but not euphoric experiences, at higher levels of cannabis use compared to controls. This suggests a specific psychotomimetic response in FEP patients related to heavy cannabis use. Clinicians should enquire regarding cannabis related PEs and advise that lower levels of cannabis use are associated with less frequent PEs