Toward a Framework For Systematic Error Modeling Of Spaceborne Precipitation Radar With Noaa/Nssl Ground Radar Based National Mosaic Qpe

Characterization of the error associated with satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving spaceborne passive and active microwave measurements for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. The authors focus here on the error structure of NASA\u27s Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) quantitative precipitation estimation (QPE) at ground. The problem is addressed by comparison of PR QPEs with reference values derived from ground-based measurements using NOAA/NSSL ground radar based National Mosaic and QPE system (NMQ/Q2). A preliminary investigation of this subject has been carried out at the PR estimation scale (instantaneous and 5 km) using a 3-month data sample in the southern part of the United States. The primary contribution of this study is the presentation of the detailed steps required to derive a trustworthy reference rainfall dataset from Q2 at the PR pixel resolution. It relies on a bias correction and a radar quality index, both of which provide a basis to filter out the less trustworthy Q2 values. Several aspects of PR errors are revealed and quantified including sensitivity to the processing steps with the reference rainfall, comparisons of rainfall delectability and rainfall-rate distributions, spatial representativeness of error, and separation of systematic biases and random errors. The methodology and framework developed herein applies more generally to rainfall-rate estimates from other sensors on board low-earth-orbiting satellites such as microwave imagers and dual-wavelength radars such as with the Global Precipitation Measurement (GPM) mission

Toward a Framework for Systematic Error Modeling of NASA Spaceborne Radar with NOAA/NSSL Ground Radar-Based National Mosaic QPE

Characterization of the error associated to satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving space-born passive and active microwave measurement") for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. We focus here on the error structure of NASA's Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) quantitative precipitation estimation (QPE) at ground. The problem is addressed by comparison of PR QPEs with reference values derived from ground-based measurements using NOAA/NSSL ground radar-based National Mosaic and QPE system (NMQ/Q2). A preliminary investigation of this subject has been carried out at the PR estimation scale (instantaneous and 5 km) using a three-month data sample in the southern part of US. The primary contribution of this study is the presentation of the detailed steps required to derive trustworthy reference rainfall dataset from Q2 at the PR pixel resolution. It relics on a bias correction and a radar quality index, both of which provide a basis to filter out the less trustworthy Q2 values. Several aspects of PR errors arc revealed and quantified including sensitivity to the processing steps with the reference rainfall, comparisons of rainfall detectability and rainfall rate distributions, spatial representativeness of error, and separation of systematic biases and random errors. The methodology and framework developed herein applies more generally to rainfall rate estimates from other sensors onboard low-earth orbiting satellites such as microwave imagers and dual-wavelength radars such as with the Global Precipitation Measurement (GPM) mission

Narrowly distributed crystal orientation in biomineral vaterite

Biominerals formed by animals provide skeletal support, and many other functions. They were previously shown to grow by aggregation of amorphous nanoparticles, but never to grow ion-by-ion from solution, which is a common growth mechanism for abiotic crystals. We analyze vaterite CaCO3 multi crystalline spicules from the solitary tunicate Herdmania momus, with Polarization dependent Imaging Contrast PIC mapping, scanning and aberration corrected transmission electron microscopies. The first fully quantitative PIC mapping data, presented here, measured 0{\deg} 30{\deg} angle spreads between immediately adjacent crystals. Such narrowly distributed crystal orientations demonstrate that crystallinity does not propagate from one crystal to another 0{\deg} angle spreads, nor that new crystals with random orientation 90{\deg} nucleate. There are no organic layers at the interface between crystals, hence a new, unknown growth mechanism must be invoked, with crystal nucleation constrained within 30{\deg}. Two observations are consistent with crystal growth from solution: vaterite microcrystals express crystal faces, and are smooth at the nanoscale after cryo fracture. The observation of 30{\deg} angle spreads, lack of interfacial organic layers, and smooth fracture figures broadens the range of known biomineralization mechanisms and may inspire novel synthetic crystal growth strategies. Spherulitic growth from solution is one possible mechanism consistent with all these observations.Comment: Chemistry of Materials 201

Adaptive Evolution in the Glucose Transporter 4 Gene Slc2a4 in Old World Fruit Bats (Family: Pteropodidae)

Frugivorous and nectarivorous bats are able to ingest large quantities of sugar in a short time span while avoiding the potentially adverse side-effects of elevated blood glucose. The glucose transporter 4 protein (GLUT4) encoded by the Slc2a4 gene plays a critical role in transmembrane skeletal muscle glucose uptake and thus glucose homeostasis. To test whether the Slc2a4 gene has undergone adaptive evolution in bats with carbohydrate-rich diets in relation to their insect-eating sister taxa, we sequenced the coding region of the Slc2a4 gene in a number of bat species, including four Old World fruit bats (Pteropodidae) and three New World fruit bats (Phyllostomidae). Our molecular evolutionary analyses revealed evidence that Slc2a4 has undergone a change in selection pressure in Old World fruit bats with 11 amino acid substitutions detected on the ancestral branch, whereas, no positive selection was detected in the New World fruit bats. We noted that in the former group, amino acid replacements were biased towards either Serine or Isoleucine, and, of the 11 changes, six were specific to Old World fruit bats (A133S, A164S, V377F, V386I, V441I and G459S). Our study presents preliminary evidence that the Slc2a4 gene has undergone adaptive changes in Old World fruit bats in relation to their ability to meet the demands of a high sugar diet

Asenapine effects in animal models of psychosis and cognitive function

Asenapine, a novel psychopharmacologic agent in the development for schizophrenia and bipolar disorder, has high affinity for serotonergic, α-adrenergic, and dopaminergic receptors, suggesting potential for antipsychotic and cognitive-enhancing properties. The effects of asenapine in rat models of antipsychotic efficacy and cognition were examined and compared with those of olanzapine and risperidone. Amphetamine-stimulated locomotor activity (Amp-LMA; 1.0 or 3.0 mg/kg s.c.) and apomorphine-disrupted prepulse inhibition (Apo-PPI; 0.5 mg/kg s.c.) were used as tests for antipsychotic activity. Delayed non-match to place (DNMTP) and five-choice serial reaction (5-CSR) tasks were used to assess short-term spatial memory and attention, respectively. Asenapine doses varied across tasks: Amp-LMA (0.01–0.3 mg/kg s.c.), Apo-PPI (0.001–0.3 mg/kg s.c.), DNMTP (0.01–0.1 mg/kg s.c.), and 5-CSR (0.003–0.3 mg/kg s.c.). Asenapine was highly potent (active at 0.03 mg/kg) in the Amp-LMA and Apo-PPI assays. DNMTP or 5-CSR performance was not improved by asenapine, olanzapine, or risperidone. All agents (P < 0.01) reduced DNMTP accuracy at short delays; post hoc analyses revealed that only 0.1 mg/kg asenapine and 0.3 mg/kg risperidone differed from vehicle. All active agents (asenapine, 0.3 mg/kg; olanzapine, 0.03–0.3 mg/kg; and risperidone, 0.01–0.1 mg/kg) significantly impaired 5-CSR accuracy (P < 0.05). Asenapine has potent antidopaminergic properties that are predictive of antipsychotic efficacy. Asenapine, like risperidone and olanzapine, did not improve cognition in normal rats. Rather, at doses greater than those required for antipsychotic activity, asenapine impaired cognitive performance due to disturbance of motor function, an effect also observed with olanzapine and risperidone

Homeostatic Scaling of Excitability in Recurrent Neural Networks

Neurons adjust their intrinsic excitability when experiencing a persistent change in synaptic drive. This process can prevent neural activity from moving into either a quiescent state or a saturated state in the face of ongoing plasticity, and is thought to promote stability of the network in which neurons reside. However, most neurons are embedded in recurrent networks, which require a delicate balance between excitation and inhibition to maintain network stability. This balance could be disrupted when neurons independently adjust their intrinsic excitability. Here, we study the functioning of activity-dependent homeostatic scaling of intrinsic excitability (HSE) in a recurrent neural network. Using both simulations of a recurrent network consisting of excitatory and inhibitory neurons that implement HSE, and a mean-field description of adapting excitatory and inhibitory populations, we show that the stability of such adapting networks critically depends on the relationship between the adaptation time scales of both neuron populations. In a stable adapting network, HSE can keep all neurons functioning within their dynamic range, while the network is undergoing several (patho)physiologically relevant types of plasticity, such as persistent changes in external drive, changes in connection strengths, or the loss of inhibitory cells from the network. However, HSE cannot prevent the unstable network dynamics that result when, due to such plasticity, recurrent excitation in the network becomes too strong compared to feedback inhibition. This suggests that keeping a neural network in a stable and functional state requires the coordination of distinct homeostatic mechanisms that operate not only by adjusting neural excitability, but also by controlling network connectivity

Structure and regulation of the Asr gene family in banana

Abscisic acid, stress, ripening proteins (ASR) are a family of plant-specific small hydrophilic proteins. Studies in various plant species have highlighted their role in increased resistance to abiotic stress, including drought, but their specific function remains unknown. As a first step toward their potential use in crop improvement, we investigated the structure and regulation of the Asr gene family in Musa species (bananas and plantains). We determined that the MusaAsr gene family contained at least four members, all of which exhibited the typical two exons, one intron structure of Asr genes and the “ABA/WDS” (abscisic acid/water deficit stress) domain characteristic of Asr genes. Phylogenetic analyses determined that the MusaAsr genes were closely related to each other, probably as the product of recent duplication events. For two of the four members, two versions corresponding to the two sub-genomes of Musa, acuminata and balbisiana were identified. Gene expression and protein analyses were performed and Asr expression could be detected in meristem cultures, root, pseudostem, leaf and cormus. In meristem cultures, mAsr1 and mAsr3 were induced by osmotic stress and wounding, while mAsr3 and mAsr4 were induced by exposure to ABA. mASR3 exhibited the most variation both in terms of amino acid sequence and expression pattern, making it the most promising candidate for further functional study and use in crop improvement

Predicting disease-associated substitution of a single amino acid by analyzing residue interactions

<p>Abstract</p> <p>Background</p> <p>The rapid accumulation of data on non-synonymous single nucleotide polymorphisms (nsSNPs, also called SAPs) should allow us to further our understanding of the underlying disease-associated mechanisms. Here, we use complex networks to study the role of an amino acid in both local and global structures and determine the extent to which disease-associated and polymorphic SAPs differ in terms of their interactions to other residues.</p> <p>Results</p> <p>We found that SAPs can be well characterized by network topological features. Mutations are probably disease-associated when they occur at a site with a high centrality value and/or high degree value in a protein structure network. We also discovered that study of the neighboring residues around a mutation site can help to determine whether the mutation is disease-related or not. We compiled a dataset from the Swiss-Prot variant pages and constructed a model to predict disease-associated SAPs based on the random forest algorithm. The values of total accuracy and MCC were 83.0% and 0.64, respectively, as determined by 5-fold cross-validation. With an independent dataset, our model achieved a total accuracy of 80.8% and MCC of 0.59, respectively.</p> <p>Conclusions</p> <p>The satisfactory performance suggests that network topological features can be used as quantification measures to determine the importance of a site on a protein, and this approach can complement existing methods for prediction of disease-associated SAPs. Moreover, the use of this method in SAP studies would help to determine the underlying linkage between SAPs and diseases through extensive investigation of mutual interactions between residues.</p

Computer-Based Screening of Functional Conformers of Proteins

A long-standing goal in biology is to establish the link between function, structure, and dynamics of proteins. Considering that protein function at the molecular level is understood by the ability of proteins to bind to other molecules, the limited structural data of proteins in association with other bio-molecules represents a major hurdle to understanding protein function at the structural level. Recent reports show that protein function can be linked to protein structure and dynamics through network centrality analysis, suggesting that the structures of proteins bound to natural ligands may be inferred computationally. In the present work, a new method is described to discriminate protein conformations relevant to the specific recognition of a ligand. The method relies on a scoring system that matches critical residues with central residues in different structures of a given protein. Central residues are the most traversed residues with the same frequency in networks derived from protein structures. We tested our method in a set of 24 different proteins and more than 260,000 structures of these in the absence of a ligand or bound to it. To illustrate the usefulness of our method in the study of the structure/dynamics/function relationship of proteins, we analyzed mutants of the yeast TATA-binding protein with impaired DNA binding. Our results indicate that critical residues for an interaction are preferentially found as central residues of protein structures in complex with a ligand. Thus, our scoring system effectively distinguishes protein conformations relevant to the function of interest

Patterns of Positive Selection and Neutral Evolution in the Protein-Coding Genes of Tetraodon and Takifugu

Recent genome-wide analyses have revealed patterns of positive selection acting on protein-coding genes in humans and mammals. To assess whether the conclusions drawn from these analyses are valid for other vertebrates and to identify mammalian specificities, I have investigated the selective pressure acting on protein-coding genes of the puffer fishes Tetraodon and Takifugu. My results indicate that the strength of purifying selection in puffer fishes is similar to previous reports for murids but stronger in hominids, which have a smaller population size. Gene ontology analyses show that more than half of the biological processes targeted by positive selection in mammals are also targeted in puffer fishes, highlighting general patterns for vertebrates. Biological processes enriched with positively selected genes that are shared between mammals and fishes include immune and defense responses, signal transduction, regulation of transcription and several of their descendent terms. Mammalian-specific processes displaying an excess of positively selected genes are related to sensory perception and neurological processes. The comparative analyses also revealed that, for both mammals and fishes, genes encoding extracellular proteins are preferentially targeted by positive selection, indicating that adaptive evolution occurs more often in the extra-cellular environment rather than inside the cell. Moreover, I present here the first genome-wide characterization of neutrally-evolving regions of protein-coding genes. This analysis revealed an unexpectedly high proportion of genes containing both positively selected motifs and neutrally-evolving regions, uncovering a strong link between neutral evolution and positive selection. I speculate that neutrally-evolving regions are a major source of novelties screened by natural selection