Everything You and Your Teachers Need to Know About the Learning Brain

Children go to school to learn, and learning takes place in the brain. In the age period of formal schooling, a child’s brain is still undergoing major developmental changes. For these reasons, neuroscience (the study of the brain) and education are closely connected. Learning is possible because the brain is plastic: plasticity refers to the capacity of the brain to reorganize its structure and thereby change function and behavior. But what exactly changes in the brain when we learn something new? What are optimal conditions for the brain to learn? Why do we also forget things? What developmental changes occur in the brain during childhood and adolescence, and how are these processes different or similar to the neural mechanisms of learning and memory? Neuro-imaging research, or ‘brain scanning’, has accelerated our current understanding of brain development, learning, memory and other school-related skills such as reading and math but also creativity, metacognition and learning-related emotions and anxieties. But what do these brain scanning techniques actually measure? What kind of questions can we address with neuro-imaging, and what are the limitations? In this Collection, we will provide an accessible overview of the current state-of-the-art insights into the mechanisms of brain development, learning and memory. The collection will help children understand how their brains learn and develop, and how these processes are shaped by their environment and their own efforts. Moreover, we will discuss why it is important that their teachers and other educational practitioners know about the brain and neuroscience methods. Finally, we will also explain what happens if wrong ideas about the brain circulate, or the correct knowledge is misinterpreted. Neuromyths such as ‘we only use 10 percent of our brain’ are persistent, but important to counter with explaining why they are false, and what is true instead. In sum, this Collection will provide children with all the relevant knowledge about the brain to understand themselves and their learning processes better, and to equip them to distinguish myths and facts

Igneous rock area and age in continental crust

Abstract Rock quantity and age are fundamental features of Earth's crust that pertain to many problems in geoscience. Here we combine new estimates of igneous rock area in continental crust from the Macrostrat database (https://macrostrat.org/) with a compilation of detrital zircon ages in order to investigate rock cycling and crustal growth. We find that there is little or no decrease in igneous rock area with increasing rock age. Instead, igneous rock area in North America exhibits four distinct Precambrian peaks, remains low through the Neoproterozoic, and then increases only modestly toward the recent. Peaks in Precambrian detrital zircon age frequency distributions align broadly with peaks in igneous rock area, regardless of grain depositional age. However, detrital zircon ages do underrepresent a Neoarchean peak in igneous rock area; young grains and ca. 1.1 Ga grains are also overrepresented relative to igneous area. Together, these results suggest that detrital zircon age distributions contain signatures of continental denudation and sedimentary cycling that are decoupled from the cycling of igneous source rocks. Models of continental crustal evolution that incorporate significant early increase in volume and increased sedimentation in the Phanerozoic are well supported by these data.</jats:p

Hierarchical statistical techniques are necessary to draw reliable conclusions from analysis of isolated cardiomyocyte studies

Aims It is generally accepted that post-MI heart failure (HF) changes a variety of aspects of sarcoplasmic reticular Ca2+ fluxes but for some aspects there is disagreement over whether there is an increase or decrease. The commonest statistical approach is to treat data collected from each cell as independent, even though they are really clustered with multiple likely similar cells from each heart. In this study, we test whether this statistical assumption of independence can lead the investigator to draw conclusions that would be considered erroneous if the analysis handled clustering with specific statistical techniques (hierarchical tests). Methods and results Ca2+ transients were recorded in cells loaded with Fura-2AM and sparks were recorded in cells loaded with Fluo-4AM. Data were analysed twice, once with the common statistical approach (assumption of independence) and once with hierarchical statistical methodologies designed to allow for any clustering. The statistical tests found that there was significant hierarchical clustering. This caused the common statistical approach to underestimate the standard error and report artificially small P values. For example, this would have led to the erroneous conclusion that time to 50% peak transient amplitude was significantly prolonged in HF. Spark analysis showed clustering, both within each cell and also within each rat, for morphological variables. This means that a three-level hierarchical model is sometimes required for such measures. Standard statistical methodologies, if used instead, erroneously suggest that spark amplitude is significantly greater in HF and spark duration is reduced in HF. Conclusion Ca2+ fluxes in isolated cardiomyocytes show so much clustering that the common statistical approach that assumes independence of each data point will frequently give the false appearance of statistically significant changes. Hierarchical statistical methodologies need a little more effort, but are necessary for reliable conclusions. We present cost-free simple tools for performing these analyses

The essential genome of Streptococcus agalactiae.

BACKGROUND: Next-generation sequencing of transposon-genome junctions from a saturated bacterial mutant library (Tn-seq) is a powerful tool that permits genome-wide determination of the contribution of genes to fitness of the organism under a wide range of experimental conditions. We report development, testing, and results from a Tn-seq system for use in Streptococcus agalactiae (group B Streptococcus; GBS), an important cause of neonatal sepsis. METHODS: Our method uses a Himar1 mini-transposon that inserts at genomic TA dinucleotide sites, delivered to GBS on a temperature-sensitive plasmid that is subsequently cured from the bacterial population. In order to establish the GBS essential genome, we performed Tn-seq on DNA collected from three independent mutant libraries-with at least 135,000 mutants per library-at serial 24 h time points after outgrowth in rich media. RESULTS: After statistical analysis of transposon insertion density and distribution, we identified 13.5 % of genes as essential and 1.2 % as critical, with high levels of reproducibility. Essential and critical genes are enriched for fundamental cellular housekeeping functions, such as acyl-tRNA biosynthesis, nucleotide metabolism, and glycolysis. We further validated our system by comparing fitness assignments of homologous genes in GBS and a close bacterial relative, Streptococcus pyogenes, which demonstrated 93 % concordance. Finally, we used our fitness assignments to identify signal transduction pathway components predicted to be essential or critical in GBS. CONCLUSIONS: We believe that our baseline fitness assignments will be a valuable tool for GBS researchers and that our system has the potential to reveal key pathogenesis gene networks and potential therapeutic/preventative targets.This work was supported by NIH/NIAID R01 AI092743, R33 AI098654, and R21 AI11020 to A.J.R.; NIH/NICHD K23 HD065844 to T.M.R.; John M. Driscoll, Jr., M.D. Children’s Fund (Columbia University Department of Pediatrics) and the Pediatric Scientist Development Program (NIH/NICHD K12 HD000850) to T.A.H

Imaging of X-Ray-Excited Emissions from Quantum Dots and Biological Tissue in Whole Mouse

© The Author(s) 2019. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.Optical imaging in clinical and preclinical settings can provide a wealth of biological information, particularly when coupled with targetted nanoparticles, but optical scattering and absorption limit the depth and resolution in both animal and human subjects. Two new hybrid approaches are presented, using the penetrating power of X-rays to increase the depth of optical imaging. Foremost, we demonstrate the excitation by X-rays of quantum-dots (QD) emitting in the near-infrared (NIR), using a clinical X-ray system to map the distribution of QDs at depth in whole mouse. We elicit a clear, spatially-resolved NIR signal from deep organs (brain, liver and kidney) with short (1 second) exposures and tolerable radiation doses that will permit future in vivo applications. Furthermore, X-ray-excited endogenous emission is also detected from whole mouse. The use of keV X-rays to excite emission from QDs and tissue represent novel biomedical imaging technologies, and exploit emerging QDs as optical probes for spatial-temporal molecular imaging at greater depth than previously possible.Peer reviewe

Discovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers

Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8 x 10(-4); Bonferroni-corrected threshold). Sex-specific genome-wide association studies (GWAS) showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8 x 10(-10); Bonferroni-corrected threshold) for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and interpretation

Use of Proteins Identified through a Functional Genomic Screen To Develop a Protein Subunit Vaccine That Provides Significant Protection against Virulent Streptococcus suis in Pigs.

Streptococcus suis is a bacterium that is commonly carried in the respiratory tract and that is also one of the most important invasive pathogens of swine, commonly causing meningitis, arthritis, and septicemia. Due to the existence of many serotypes and a wide range of immune evasion capabilities, efficacious vaccines are not readily available. The selection of S. suis protein candidates for inclusion in a vaccine was accomplished by identifying fitness genes through a functional genomics screen and selecting conserved predicted surface-associated proteins. Five candidate proteins were selected for evaluation in a vaccine trial and administered both intranasally and intramuscularly with one of two different adjuvant formulations. Clinical protection was evaluated by subsequent intranasal challenge with virulent S. suis While subunit vaccination with the S. suis proteins induced IgG antibodies to each individual protein and a cellular immune response to the pool of proteins and provided substantial protection from challenge with virulent S. suis, the immune response elicited and the degree of protection were dependent on the parenteral adjuvant given. Subunit vaccination induced IgG reactive against different S. suis serotypes, indicating a potential for cross protection

A [4Fe-4S]-Fe(CO)(CN)-L-cysteine intermediate is the first organometallic precursor in [FeFe] hydrogenase H-cluster bioassembly.

Biosynthesis of the [FeFe] hydrogenase active site (the 'H-cluster') requires the interplay of multiple proteins and small molecules. Among them, the radical S-adenosylmethionine enzyme HydG, a tyrosine lyase, has been proposed to generate a complex that contains an Fe(CO)2(CN) moiety that is eventually incorporated into the H-cluster. Here we describe the characterization of an intermediate in the HydG reaction: a [4Fe-4S][(Cys)Fe(CO)(CN)] species, 'Complex A', in which a CO, a CN- and a cysteine (Cys) molecule bind to the unique 'dangler' Fe site of the auxiliary [5Fe-4S] cluster of HydG. The identification of this intermediate-the first organometallic precursor to the H-cluster-validates the previously hypothesized HydG reaction cycle and provides a basis for elucidating the biosynthetic origin of other moieties of the H-cluster

Long-term cycles in the history of life: Periodic biodiversity in the Paleobiology Database

Time series analysis of fossil biodiversity of marine invertebrates in the Paleobiology Database (PBDB) shows a significant periodicity at approximately 63 My, in agreement with previous analyses based on the Sepkoski database. I discuss how this result did not appear in a previous analysis of the PBDB. The existence of the 63 My periodicity, despite very different treatment of systematic error in both PBDB and Sepkoski databases strongly argues for consideration of its reality in the fossil record. Cross-spectral analysis of the two datasets finds that a 62 My periodicity coincides in phase by 1.6 My, equivalent to better than the errors in either measurement. Consequently, the two data sets not only contain the same strong periodicity, but its peaks and valleys closely correspond in time. Two other spectral peaks appear in the PBDB analysis, but appear to be artifacts associated with detrending and with the increased interval length. Sampling-standardization procedures implemented by the PBDB collaboration suggest that the signal is not an artifact of sampling bias. Further work should focus on finding the cause of the 62 My periodicity.Comment: Published in PLoS ONE. 5 pages, 3 figures. Version with live links, discussion available at http://www.plosone.org/article/info:doi/10.1371/journal.pone.0004044#to