Abiotic Stress in Cotton: Insights into Plant Responses and Biotechnological Solutions

Climate change has rapidly increased incidences of frequent extreme abiotic stresses, such as heat, drought, salinity, and waterlogging. Each of these stressors negatively affects the cotton crop (Gossypium spp.) and results in significant yield decreases. Every stressful event causes specific changes in the metabolism and physiology of plants, which are linked to complex molecular alterations. Understanding the molecular mechanisms that regulate a plant’s response to stress is essential to developing stress-resistant cotton varieties that can withstand various stress factors. Gene expressions in response to multiple stresses have been studied and mapped. These genes include ion transporters and heat shock proteins, which are vital to allowing adaptive responses. These approaches showed the ability to employ advanced genome sequencing and multi-omics techniques to identify dynamic gene expression patterns and elucidate intricate regulatory networks. Using genetic variation in combination with molecular techniques, it would be possible to generate stress-resilient cotton varieties that would enable sustainable cotton output in the face of abiotic stresses. Here, we reviewed the effects of major abiotic stressors on cotton plants, such as heat, salinity, drought, heavy metals, and waterlogging. We also examine the vast network of proteins, genes, and stress-sensitive signaling pathways that help cotton tolerate abiotic stress.</jats:p

Foundations of Black Hole Accretion Disk Theory

This review covers the main aspects of black hole accretion disk theory. We begin with the view that one of the main goals of the theory is to better understand the nature of black holes themselves. In this light we discuss how accretion disks might reveal some of the unique signatures of strong gravity: the event horizon, the innermost stable circular orbit, and the ergosphere. We then review, from a first-principles perspective, the physical processes at play in accretion disks. This leads us to the four primary accretion disk models that we review: Polish doughnuts (thick disks), Shakura-Sunyaev (thin) disks, slim disks, and advection-dominated accretion flows (ADAFs). After presenting the models we discuss issues of stability, oscillations, and jets. Following our review of the analytic work, we take a parallel approach in reviewing numerical studies of black hole accretion disks. We finish with a few select applications that highlight particular astrophysical applications: measurements of black hole mass and spin, black hole vs. neutron star accretion disks, black hole accretion disk spectral states, and quasi-periodic oscillations (QPOs).Comment: 91 pages, 23 figures, final published version available at http://www.livingreviews.org/lrr-2013-

Single-molecule tracking reveals two low-mobility states for chromatin and transcriptional regulators within the nucleus

peer reviewedHow transcription factors (TFs) navigate the complex nuclear environment to assemble the transcriptional machinery at specific genomic loci remains elusive. Using single-molecule tracking, coupled with machine learning, we examined the mobility of multiple transcriptional regulators. We show that H2B and ten different transcriptional regulators display two distinct low-mobility states. Our results indicate that both states represent dynamic interactions with chromatin. Ligand activation results in a dramatic increase in the proportion of steroid receptors in the lowest mobility state. Mutational analysis revealed that only chromatin interactions in the lowest mobility state require an intact DNA-binding domain as well as oligomerization domains. Importantly, these states are not spatially separated as previously believed but in fact, individual H2B and TF molecules can dynamically switch between them. Together, our results identify two unique and distinct low-mobility states of transcriptional regulators that appear to represent common pathways for transcription activation in mammalian cells

Identification of Eps15 as Antigen Recognized by the Monoclonal Antibodies aa2 and ab52 of the Wuerzburg Hybridoma Library against Drosophila Brain

The Wuerzburg Hybridoma Library against the Drosophila brain represents a collection of around 200 monoclonal antibodies that bind to specific structures in the Drosophila brain. Here we describe the immunohistochemical staining patterns, the Western blot signals of one- and two-dimensional electrophoretic separation, and the mass spectrometric characterization of the target protein candidates recognized by the monoclonal antibodies aa2 and ab52 from the library. Analysis of a mutant of a candidate gene identified the Drosophila homolog of the Epidermal growth factor receptor Pathway Substrate clone 15 (Eps15) as the antigen for these two antibodies

Neurexin in Embryonic Drosophila Neuromuscular Junctions

Background: Neurexin is a synaptic cell adhesion protein critical for synapse formation and function. Mutations in neurexin and neurexin-interacting proteins have been implicated in several neurological diseases. Previous studies have described Drosophila neurexin mutant phenotypes in third instar larvae and adults. However, the expression and function of Drosophila neurexin early in synapse development, when neurexin function is thought to be most important, has not been described. Methodology/Principal Findings: We use a variety of techniques, including immunohistochemistry, electron microscopy, in situ hybridization, and electrophysiology, to characterize neurexin expression and phenotypes in embryonic Drosophila neuromuscular junctions (NMJs). Our results surprisingly suggest that neurexin in embryos is present both pre and postsynaptically. Presynaptic neurexin promotes presynaptic active zone formation and neurotransmitter release, but along with postsynaptic neurexin, also suppresses formation of ectopic glutamate receptor clusters. Interestingly, we find that loss of neurexin only affects receptors containing the subunit GluRIIA. Conclusions/Significance: Our study extends previous results and provides important detail regarding the role of neurexin in Drosophila glutamate receptor abundance. The possibility that neurexin is present postsynaptically raises new hypotheses regarding neurexin function in synapses, and our results provide new insights into the role of neurexin i

Mutations in Wnt2 Alter Presynaptic Motor Neuron Morphology and Presynaptic Protein Localization at the Drosophila Neuromuscular Junction

Wnt proteins are secreted proteins involved in a number of developmental processes including neural development and synaptogenesis. We sought to determine the role of the Drosophila Wnt7b ortholog, Wnt2, using the neuromuscular junction (NMJ). Mutations in wnt2 produce an increase in the number of presynaptic branches and a reduction in immunolabeling of the active zone proteins, Bruchpilot and synaptobrevin, at the NMJ. There was no change, however, in immunolabeling for the presynaptic proteins cysteine-string protein (CSP) and synaptotagmin, nor the postsynaptic proteins GluRIIA and DLG at the NMJ. Consistent with the presynaptic defects, wnt2 mutants exhibit approximately a 50% reduction in evoked excitatory junctional currents. Rescue, RNAi, and tissue-specific qRT-PCR experiments indicate that Wnt2 is expressed by the postsynaptic cell where it may serve as a retrograde signal that regulates presynaptic morphology and the localization of presynaptic proteins

On the Reusability of Sentiment Analysis Datasets in Applications with Dissimilar Contexts

Part 8: Sentiment Analysis/Recommender SystemsInternational audienceThe main goal of this paper is to evaluate the usability of several algorithms on various sentiment-labeled datasets. The process of creating good semantic vector representations for textual data is considered a very demanding task for the research community. The first and most important step of a Natural Language Processing (NLP) system, is text preprocessing, which greatly affects the overall accuracy of the classification algorithms. In this work, two vector space models are created, and a study consisting of a variety of algorithms, is performed on them. The work is based on the IMDb dataset which contains movie reviews along with their associated labels (positive or negative). The goal is to obtain the model with the highest accuracy and the best generalization. To measure how well these models generalize in other domains, several datasets, which are further analyzed later, are used