11,156 research outputs found
Nicotinic acetylcholine receptors in rat forebrain that bind ¹⁸F-nifene: relating PET imaging, autoradiography, and behavior
No full textNicotinic acetylcholine receptors (nAChRs) in the brain are important for cognitive function; however, their specific role in relevant brain regions remains unclear. In this study, we used the novel compound ¹⁸F-nifene to examine the distribution of nAChRs in the rat forebrain, and for individual animals related the results to behavioral performance on an auditory-cognitive task. We first show negligible binding of ¹⁸F-nifene in mice lacking the β2 nAChR subunit, consistent with previous findings that ¹⁸F-nifene binds to α4β2* nAChRs. We then examined the distribution of ¹⁸F-nifene in rat using three methods: in vivo PET, ex vivo PET and autoradiography. Generally, ¹⁸F-nifene labeled forebrain regions known to contain nAChRs, and the three methods produced similar relative binding among regions. Importantly, ¹⁸F-nifene also labeled some white matter (myelinated axon) tracts, most prominently in the temporal subcortical region that contains the auditory thalamocortical pathway. Finally, we related ¹⁸F-nifene binding in several forebrain regions to each animal's performance on an auditory-cued, active avoidance task. The strongest correlations with performance after 14 days training were found for ¹⁸F-nifene binding in the temporal subcortical white matter, subiculum, and medial frontal cortex (correlation coefficients, r > 0.8); there was no correlation with binding in the auditory thalamus or auditory cortex. These findings suggest that individual performance is linked to nicotinic functions in specific brain regions, and further support a role for nAChRs in sensory-cognitive function.Peer reviewedAuthor's Manuscript is also available open access in PubMed Central: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3292694.This is the peer reviewed version of the following article: Bieszczad, K. M., Kant, R., Constantinescu, C. C., Pandey, S. K., Kawai, H. D., Metherate, R., Weinberger, N. M. and Mukherjee, J. (2012), Nicotinic acetylcholine receptors in rat forebrain that bind 18F-nifene: Relating PET imaging, autoradiography, and behavior. Synapse, 66: 418–434. doi: 10.1002/syn.21530, which has been published in final form at http://dx.doi.org/10.1002/syn.21530. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving
Allele Mining for Crop Genomic Designing in Peanut
No full textThe dissection of naturally existing allelic variations in the candidate genes responsible for crucial agronomic traits is made possible by allele mining. Allele mining may now be used to analyze the precise allelic variations of functional genes found in a variety of peanut cultivars as a result of the finding, isolation, and characterization of several genes in peanut. The complex alleles serve as a reservoir of diversity to produce an array of functional genes. One of the primary mechanisms governing the evolution and development of R genes is regular sequence exchange. The generation of allele-specific markers for use in marker-assisted selection, together with the identification of new alleles and haplotypes, can be accomplished by allele mining. In modern plant breeding that is driven by genomics, allele mining can be seen as a crucial link between the efficient usage of genetic and genomic resources. The information presented here is crucial for giving the peanut breeder a valuable introduction to allele mining and its methods for the ground-breaking finding of novel alleles concealed in hereditary variation, which is essential for crop development. This chapter explores the theoretical underpinnings and use of allele mining techniques for the identification of alleles and their possible implications for peanut improvement
Similarities between 2D and 3D convection for large Prandtl number
No full textUsing direct numerical simulations of Rayleigh-B\'enard convection (RBC), we perform a comparative study of the spectra and fluxes of energy and entropy for large and infinite Prandtl numbers in two (2D) and three (3D) dimensions. We observe close similarities between the 2D and 3D RBC, in particular the kinetic energy spectrum , and the entropy spectrum exhibits a dual branch with a dominant spectrum. We showed that the dominant Fourier modes in the 2D and 3D flows are very close
The Peanut Genome
No full textThis book presents the current state of the art in peanut genomics, focusing particularly on the latest genomic findings, tools and strategies employed in genome sequencing, transcriptomes and analysis, availability of public and private genomic resources, and ways to maximize the use of this information in peanut breeding programs. Further, it demonstrates how advances in plant genomics can be used to improve crop breeding. The peanut or groundnut (Arachis hypogaea L. Millsp) is a globally important grain legume and oilseed crop, cultivated in over 100 countries and consumed in the form of roasted seeds, oil and confectionary in nearly every country on Earth. The peanut contributes towards achieving food and nutritional security, in addition to financial security through income generation; as such, it is also vital to the livelihood of the poor in the developing world. There have been significant advances in peanut research, especially in the last five years, including sequencing the genome of both diploid progenitors, and the availability of tremendous transcriptome resources, large-scale genomic variations that can be used as genetic markers, genetic populations (bi- and multiparent populations and germplasm sets), marker-trait associations and molecular breeding products. The immediate availability of the genome sequence for tetraploid cultivated peanuts is the most essential genomic resource for achieving a deeper understanding of peanut traits and their use in breeding programs
Excessive Protein Accumulation and Impaired Autophagy in the Hippocampus of Angelman Syndrome Modeled in Mice
No full textBACKGROUND: Angelman syndrome (AS), a neurodevelopmental disorder caused by abnormalities of the 15q11.2-q13.1 chromosome region, is characterized by impairment of cognitive and motor functions, sleep problems, and seizures. How the genetic defects of AS produce these neurological symptoms is unclear. Mice modeling AS (AS mice) accumulate activity-regulated cytoskeleton-associated protein (ARC/ARG3.1), a neuronal immediate early gene (IEG) critical for synaptic plasticity. This accumulation suggests an altered protein metabolism.METHODS: Focusing on the dorsal hippocampus (dHC), a brain region critical for memory formation and cognitive functions, we assessed levels and tissue distribution of IEGs, de novo protein synthesis, and markers of protein synthesis, endosomes, autophagy, and synaptic functions in AS mice at baseline and following learning. We also tested autophagic flux and memory retention following autophagy-promoting treatment.RESULTS: AS dHC exhibited accumulation of IEGs ARC, FOS, and EGR1; autophagy proteins MLP3B, SQSTM1, and LAMP1; and reduction of the endosomal protein RAB5A. AS dHC also had increased levels of de novo protein synthesis, impaired autophagic flux with accumulation of autophagosome, and altered synaptic protein levels. Contextual fear conditioning significantly increased levels of IEGs and autophagy proteins, de novo protein synthesis, and autophagic flux in the dHC of normal mice, but not in AS mice. Enhancing autophagy in the dHC alleviated ASrelated memory and autophagic flux impairments.CONCLUSIONS: A major biological deficit of AS brain is a defective protein metabolism, particularly that dynamically regulated by learning, resulting in stalled autophagy and accumulation of neuronal proteins. Activating autophagy ameliorates AS cognitive impairments and dHC protein accumulation
Deep Learning-Based Femoral Cartilage Automatic Segmentation in Ultrasound Imaging for Guidance in Robotic Knee Arthroscopy
No full textIn final from 18 October 2019.Knee arthroscopy is a minimally invasive surgery used in the treatment of intra-articular knee pathology which may cause unintended damage to femoral cartilage. An ultrasound (US)-guided autonomous robotic platform for knee arthroscopy can be envisioned to minimise these risks and possibly to improve surgical outcomes. The first necessary tool for reliable guidance during robotic surgeries was an automatic segmentation algorithm to outline the regions at risk. In this work, we studied the feasibility of using a state-of-the-art deep neural network (UNet) to automatically segment femoral cartilage imaged with dynamic volumetric US (at the refresh rate of 1 Hz), under simulated surgical conditions. Six volunteers were scanned which resulted in the extraction of 18278 2-D US images from 35 dynamic 3-D US scans, and these were manually labelled. The UNet was evaluated using a five-fold cross-validation with an average of 15531 training and 3124 testing labelled images per fold. An intra-observer study was performed to assess intra-observer variability due to inherent US physical properties. To account for this variability, a novel metric concept named Dice coefficient with boundary uncertainty (DSCUB) was proposed and used to test the algorithm. The algorithm performed comparably to an experienced orthopaedic surgeon, with DSCUB of 0.87. The proposed UNet has the potential to localise femoral cartilage in robotic knee arthroscopy with clinical accuracy.M. Antico, F. Sasazawa, M. Dunnhofer, S.M. Camps, A.T. Jaiprakash, A.K. Pandey, R. Crawford, G. Carneiro, and D. Fontanaros
Plant Genetics and Molecular Biology: An Introduction
No full textThe rapidly evolving technologies can serve as a potential growth engine in agriculture as many of these technologies have revolutionized several industries in the recent past. The tremendous advancements in biotechnology methods, cost-effective sequencing technology, refinement of genomic tools, and standardization of modern genomics-assisted breeding methods hold great promise in taking the global agriculture to the next level through development of improved climate-smart seeds. These technologies can dramatically increase our capacity to understand the molecular basis of traits and utilize the available resources for accelerated development of stable high-yielding, nutritious, input-use efficient, and climate-smart crop varieties. This book aimed to document the monumental advances witnessed during the last decade in multiple fields of plant biotechnology such as genetics, structural and functional genomics, trait and gene discovery, transcriptomics, proteomics, metabolomics, epigenomics, nanotechnology, and analytical tools. This book will serve to update the scientific community, academicians, and other stakeholders in global agriculture on the rapid progress in various areas of agricultural biotechnology. This chapter provides a summary of the book, “Plant Genetics and Molecular Biology.
Integrating local and global projections for the generation of water demand scenarios in the Red River Basin, Vietnam
No full textPlanning and management of water supply systems require projections to account for future changes in climate and society. Global and local future scenarios are generated by using models at different spatial scales. The choice of the scale affects if and how the regional socio-economic structure as well as global and local development strategies are considered, and which uncertainties are treated explicitly. This study explores the integration of global and local scale scenarios. Our approach is demonstrated on the Red River basin, Vietnam, where a set of plausible water demands scenarios is generated for 2050. Results show that water demand will increase by 28-58% compared to 2010 when considering all scenarios of climate and socio-economic changes. The ensemble of integrated demands shows a strong dependence of water demand upon the climate-socio-economic state, which allow a better characterization of the future water supply sector dynamics than those obtained by global or local projections only.Copyright (c) 2022 The Authors.This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/
Future Prospects for Peanut Improvement
No full textEvolution in sequencing technologies led to reduction in costs and increase in speed for generating sequence data. The affordability of low-cost sequencing is expected to make other genotyping platforms obsolete in next couple of years. The concept of “single genome sequence” in a crop has evolved to sequencing of multiple genomes to assemble pangenomes. Sequencing combined with precise phenotyping of segregating populations and germplasm collections is expected to measure the accurate genetic diversity present in the germplasm as well as to identify the gene/nucleotide associated with the trait(s). It is time now to move toward using multi-parents populations from bi-parental populations for trait discovery and identify superior haplotypes. Availability of information on functional variation for genes controlling traits of interest will eventually help in manipulating genes more routinely using appropriate technologies such as marker-assisted selection/backcrossing, genomic selection, and genome editing. This chapter provides expected use of genome sequence and allied information on peanut for accelerating biology research as well as peanut improvement
Classical and Molecular Approaches for Mapping of Genes and Quantitative Trait Loci in Peanut
No full textAdvances in availability of genomic resources coupled with genetic resources have accelerated the process of developing better understanding of cytogenetics and genetics of peanut using modern technologies. The cytogenetic studies provided greater insights on chromosomal structures and behaviour of different Arachis species along with their genetic relationship with each other. Researchers are moving faster now in using single nucleotide polymorphism (SNP) markers in their genetic studies as simple sequence repeats (SSRs) did not provide optimum genome density for genetic mapping studies in peanut. Due to availability of reference genome of diploid progenitors, resequencing of some genotypes and soon to be available tetraploid genome, a high-density genotyping array with 58 K SNPs is now available for conducting high-resolution mapping in peanut. ICRISAT has developed next generation genetic mapping populations such as multi-parent advanced generation intercross (MAGIC) and nested association mapping (NAM) populations for conducting high-resolution trait mapping for multiple traits in one go. Affordability of sequencing also encouraged initiation of sequence-based trait mapping such as QTL-seq for dissecting foliar disease resistance trait. Few successful examples are available in peanut regarding development of diagnostic markers and their deployment in breeding to develop improved genotypes, which may see a significant increase in coming years for developing appropriate genomics tools for breeding in peanut
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