Expression of three GnRH receptors in specific tissues in male and female sea lampreys Petromyzon marinus at three distinct life stages

Two recently cloned gonadotropin-releasing hormone (GnRH) receptors (lamprey GnRH-R-2 and lamprey GnRH-R-3) along with lamprey (l) GnRH-R-1 were shown to share similar structural features and amino acid motifs common to other vertebrate receptors. Here we report on our findings of RNA expression of these three GnRH receptors in the three major life stages (larval, parasitic, and adult phases) of the sea lamprey, Petromyzon marinus, a basal vertebrate. For each stage, we examined the expression of messenger RNA encoding the receptors in the brain, pituitary, gonad, heart, muscle, liver, eye, intestine, kidney, skin, thyroid, gill, and endostyle by RT-PCR. In adult lampreys, the spatial expression of the three receptors in the brain and pituitary was investigated by in situ hybridization. In general, the receptors were more widely expressed in adult tissues as compared to parasitic-phase tissues and least widely expressed in the larval tissues. There were noted differences in male and female lampreys in the adult and parasitic phases for all three receptors. The data showed the presence of all three receptor transcripts in brain tissues for adult and parasitic phases and all three receptor transcripts were expressed in the adult pituitaries, but not in the parasitic pituitaries. However, in the larval phase, only lGnRH-R-1 was expressed in the larval brain and pituitary. In situ hybridization revealed that lGnRH-R-2 and -3 were expressed in the pineal tissue of adult female lampreys while lGnRH-R-1 was expressed in the pineal in adult male lampreys, all restricted to the pineal pellucida. In summary, these data provide an initial comparative analysis of expression of three lamprey GnRH receptors suggesting differential regulation within males and females at three different life/reproductive stages

General Bounds on Statistical Query Learning and PAC Learning with Noise via Hypothesis Boosting

AbstractWe derive general bounds on the complexity of learning in the statistical query (SQ) model and in the PAC model with classification noise. We do so by considering the problem of boosting the accuracy of weak learning algorithms which fall within the SQ model. This new model was introduced by Kearns to provide a general framework for efficient PAC learning in the presence of classification noise. We first show a general scheme for boosting the accuracy of weak SQ learning algorithms, proving that weak SQ learning is equivalent to strong SQ learning. The boosting is efficient and is used to show our main result of the first general upper bounds on the complexity of strong SQ learning. Since all SQ algorithms can be simulated in the PAC model with classification noise, we also obtain general upper bounds on learning in the presence of classification noise for classes which can be learned in the SQ model

Specification and Simulation of Statistical Query Algorithms for Efficiency and Noise Tolerance

AbstractA recent innovation in computational learning theory is the statistical query (SQ) model. The advantage of specifying learning algorithms in this model is that SQ algorithms can be simulated in the probably approximately correct (PAC) model, both in the absenceandin the presence of noise. However, simulations of SQ algorithms in the PAC model have non-optimal time and sample complexities. In this paper, we introduce a new method for specifying statistical query algorithms based on a type ofrelative errorand provide simulations in the noise-free and noise-tolerant PAC models which yield more efficient algorithms. Requests for estimates of statistics in this new model take the following form: “Return an estimate of the statistic within a 1±μfactor, or return ⊥, promising that the statistic is less thanθ.” In addition to showing that this is a very natural language for specifying learning algorithms, we also show that this new specification is polynomially equivalent to standard SQ, and thus, known learnability and hardness results for statistical query learning are preserved. We then give highly efficient PAC simulations of relative error SQ algorithms. We show that the learning algorithms obtained by simulating efficient relative error SQ algorithms both in the absence of noise and in the presence of malicious noise have roughly optimal sample complexity. We also show that the simulation of efficient relative error SQ algorithms in the presence of classification noise yields learning algorithms at least as efficient as those obtained through standard methods, and in some cases improved, roughly optimal results are achieved. The sample complexities for all of these simulations are based on thedνmetric, which is a type of relative error metric useful for quantities which are small or even zero. We show that uniform convergence with respect to thedνmetric yields “uniform convergence” with respect to (μ, θ) accuracy. Finally, while we show that manyspecificlearning algorithms can be written as highly efficient relative error SQ algorithms, we also show, in fact, thatallSQ algorithms can be written efficiently by proving general upper bounds on the complexity of (μ, θ) queries as a function of the accuracy parameterε. As a consequence of this result, we give general upper bounds on the complexity of learning algorithms achieved through the use of relative error SQ algorithms and the simulations described above

Investigaton of CO2 Capture Mechanisms of Liquid-like Nanoparticle Organic Hybrid Materials via Structural Characterization

Nanoparticle organic hybrid materials (NOHMs) have been recently developed that comprise an oligomeric or polymeric canopy tethered to surface-modified nanoparticles via ionic or covalent bonds. It has already been shown that the tunable nature of the grafted polymeric canopy allows for enhanced CO2 capture capacity and selectivity via the enthalpic intermolecular interactions between CO2 and the task-specific functional groups, such as amines. Interestingly, for the same amount of CO2 loading NOHMs have also exhibited significantly different swelling behavior compared to that of the corresponding polymers, indicating a potential structural effect during CO2 capture. If the frustrated canopy species favor spontaneous ordering due to steric and/or entropic effects, the inorganic cores of NOHMs could be organized into unusual structural arrangements. Likewise, the introduction of small gaseous molecules such as CO2 could reduce the free energy of the frustrated canopy. This entropic effect, the result of unique structural nature, could allow NOHMs to capture CO2 more effectively. In order to isolate the entropic effect, NOHMs were synthesized without the task-specific functional groups. The relationship between their structural conformation and the underlying mechanisms for the CO2 absorption behavior were investigated by employing NMR and ATR FT-IR spectroscopies. The results provide fundamental information needed for evaluating and developing novel liquid-like CO2 capture materials and give useful insights for designing and synthesizing NOHMs for more effective CO2 capture.This publication was based on work supported by Award No. KUS-C1-018-02, made by King Abdullah University of Science and Technology (KAUST). We are also grateful to Dr Luis Avila, Ms Dolly Shin and Dr Camille Petit for their help with the ATR FT-IR measurement

Investigation of CO2 capture mechanisms of liquid-like nanoparticle organic hybrid materials via structural characterization

Nanoparticle organic hybrid materials (NOHMs) have been recently developed that comprise an oligomeric or polymeric canopy tethered to surface-modified nanoparticles via ionic or covalent bonds. It has already been shown that the tunable nature of the grafted polymeric canopy allows for enhanced CO2 capture capacity and selectivity via the enthalpic intermolecular interactions between CO2 and the task-specific functional groups, such as amines. Interestingly, for the same amount of CO2 loading NOHMs have also exhibited significantly different swelling behavior compared to that of the corresponding polymers, indicating a potential structural effect during CO2 capture. If the frustrated canopy species favor spontaneous ordering due to steric and/or entropic effects, the inorganic cores of NOHMs could be organized into unusual structural arrangements. Likewise, the introduction of small gaseous molecules such as CO2 could reduce the free energy of the frustrated canopy. This entropic effect, the result of unique structural nature, could allow NOHMs to capture CO2 more effectively. In order to isolate the entropic effect, NOHMs were synthesized without the task-specific functional groups. The relationship between their structural conformation and the underlying mechanisms for the CO2 absorption behavior were investigated by employing NMR and ATR FT-IR spectroscopies. The results provide fundamental information needed for evaluating and developing novel liquid-like CO2 capture materials and give useful insights for designing and synthesizing NOHMs for more effective CO2 capture

RNomics and Modomics in the halophilic archaea Haloferax volcanii: identification of RNA modification genes

<p>Abstract</p> <p>Background</p> <p>Naturally occurring RNAs contain numerous enzymatically altered nucleosides. Differences in RNA populations (RNomics) and pattern of RNA modifications (Modomics) depends on the organism analyzed and are two of the criteria that distinguish the three kingdoms of life. If the genomic sequences of the RNA molecules can be derived from whole genome sequence information, the modification profile cannot and requires or direct sequencing of the RNAs or predictive methods base on the presence or absence of the modifications genes.</p> <p>Results</p> <p>By employing a comparative genomics approach, we predicted almost all of the genes coding for the t+rRNA modification enzymes in the mesophilic moderate halophile <it>Haloferax volcanii</it>. These encode both guide RNAs and enzymes. Some are orthologous to previously identified genes in Archaea, Bacteria or in <it>Saccharomyces cerevisiae</it>, but several are original predictions.</p> <p>Conclusion</p> <p>The number of modifications in t+rRNAs in the halophilic archaeon is surprisingly low when compared with other Archaea or Bacteria, particularly the hyperthermophilic organisms. This may result from the specific lifestyle of halophiles that require high intracellular salt concentration for survival. This salt content could allow RNA to maintain its functional structural integrity with fewer modifications. We predict that the few modifications present must be particularly important for decoding, accuracy of translation or are modifications that cannot be functionally replaced by the electrostatic interactions provided by the surrounding salt-ions. This analysis also guides future experimental validation work aiming to complete the understanding of the function of RNA modifications in Archaeal translation.</p

Improved Noise-Tolerant Learning and Generalized Statistical Queries

The statistical query learning model can be viewed as a tool for creating (or demonstrating the existence of ) noise-tolerant learning algorithms in the PAC model. The complexity of a statistical query algorithm, in conjunction with the complexity of simulating SQ algorithms in the PAC model with noise, determine the complexity of the noise-tolerant PAC algorithms produced. Although roughly optimal upper bounds have been shown for the complexity of statistical query learning, the corresponding noise-tolerant PAC algorithms are not optimal due to inefficient simulations. In this paper we provide both improved simulations and a new variant of the statistical query model in order to overcome these inefficiencies. We improve the time complexity of the classification noise simulation of statistical query algorithms. Our new simulation has a roughly optimal dependence on the noise rate. We also derive a simpler proof that statistical queries can be simulated in the presence of classification noise. This proof makes fewer assumptions on the queries themselves and therefore allows one to simulate more general types of queries. We also define a new variant of the statistical query model based on relative error, and we show that this variant is more natural and strictly more powerful than the standard additive error model. We demonstrate efficient PAC simulations for algorithms in this new model and give general upper bounds on both learning with relative error statistical queries and PAC simulation. We show that any statistical query algorithm can be simulated in the PAC model with malicious errors in such a way that the resultant PAC algorithm has a roughly optimal tolerable malicious error rate and sample complexity. Finally, we generalize the types of queries allowed in the statistical query model. We discuss the advantages of allowing these generalized queries and show that our results on improved simulations also hold for these queries.Engineering and Applied Science

Ultrafast Structural Dynamics of BlsA, a Photoreceptor from the Pathogenic Bacterium Acinetobacter baumannii

Acinetobacter baumannii is an important human pathogen that can form biofilms and persist under harsh environmental conditions. Biofilm formation and virulence are modulated by blue light, which is thought to be regulated by a BLUF protein, BlsA. To understand the molecular mechanism of light sensing, we have used steady-state and ultrafast vibrational spectroscopy to compare the photoactivation mechanism of BlsA to the BLUF photosensor AppA from Rhodobacter sphaeroides. Although similar photocycles are observed, vibrational data together with homology modeling identify significant differences in the β5 strand in BlsA caused by photoactivation, which are proposed to be directly linked to downstream signaling

Insights from a Convocation: Integrating Discovery-Based Research into the Undergraduate Curriculum

The National Academies of Sciences, Engineering, and Medicine organized a convocation in 2015 to explore and elucidate opportunities, barriers, and realities of course-based undergraduate research experiences, known as CUREs, as a potentially integral component of undergraduate science, technology, engineering, and mathematics education. This paper summarizes the convocation and resulting report