Conformational Dynamics of the Plug Domain of the SecYEG Protein-conducting Channel

The central pore of the SecYEG preprotein-conducting channel is closed at the periplasmic face of the membrane by a plug domain. To study its conformational dynamics, the plug was labeled site-specifically with an environment-sensitive fluorophore. In the presence of a stable preprotein translocation intermediate, the SecY plug showed an enhanced solvent exposure consistent with a displacement from the hydrophobic central pore region. In contrast, binding and insertion of a ribosome-bound nascent membrane protein did not alter the plug conformation. These data indicate different plug dynamics depending on the ligand bound state of the SecYEG channel.

Detectors for the James Webb Space Telescope Near-Infrared Spectrograph I: Readout Mode, Noise Model, and Calibration Considerations

We describe how the James Webb Space Telescope (JWST) Near-Infrared Spectrograph's (NIRSpec's) detectors will be read out, and present a model of how noise scales with the number of multiple non-destructive reads sampling-up-the-ramp. We believe that this noise model, which is validated using real and simulated test data, is applicable to most astronomical near-infrared instruments. We describe some non-ideal behaviors that have been observed in engineering grade NIRSpec detectors, and demonstrate that they are unlikely to affect NIRSpec sensitivity, operations, or calibration. These include a HAWAII-2RG reset anomaly and random telegraph noise (RTN). Using real test data, we show that the reset anomaly is: (1) very nearly noiseless and (2) can be easily calibrated out. Likewise, we show that large-amplitude RTN affects only a small and fixed population of pixels. It can therefore be tracked using standard pixel operability maps.Comment: 55 pages, 10 figure

A Comparative Computer Simulation of Dendritic Morphology

Computational modeling of neuronal morphology is a powerful tool for understanding developmental processes and structure-function relationships. We present a multifaceted approach based on stochastic sampling of morphological measures from digital reconstructions of real cells. We examined how dendritic elongation, branching, and taper are controlled by three morphometric determinants: Branch Order, Radius, and Path Distance from the soma. Virtual dendrites were simulated starting from 3,715 neuronal trees reconstructed in 16 different laboratories, including morphological classes as diverse as spinal motoneurons and dentate granule cells. Several emergent morphometrics were used to compare real and virtual trees. Relating model parameters to Branch Order best constrained the number of terminations for most morphological classes, except pyramidal cell apical trees, which were better described by a dependence on Path Distance. In contrast, bifurcation asymmetry was best constrained by Radius for apical, but Path Distance for basal trees. All determinants showed similar performance in capturing total surface area, while surface area asymmetry was best determined by Path Distance. Grouping by other characteristics, such as size, asymmetry, arborizations, or animal species, showed smaller differences than observed between apical and basal, pointing to the biological importance of this separation. Hybrid models using combinations of the determinants confirmed these trends and allowed a detailed characterization of morphological relations. The differential findings between morphological groups suggest different underlying developmental mechanisms. By comparing the effects of several morphometric determinants on the simulation of different neuronal classes, this approach sheds light on possible growth mechanism variations responsible for the observed neuronal diversity

Brief cognitive assessment in a UK population sample – distributional properties and the relationship between the MMSE and an extended mental state examination

BACKGROUND: Despite the MMSE's known flaws, it is still used extensively as both a screening instrument for dementia and a population measure of cognitive ability. The aim of this paper is to provide data on the distribution of MMSE scores in a representative sample from the UK population and to compare it with an extended cognitive assessment (EMSE) which covers a wider range of cognitive domains and provides a wider range of difficulty levels. METHODS: The MMSE and the EMSE were administered to over 12,000 participants at the screening stage of the MRC Cognitive Function and Ageing Study (MRC CFAS). MRC CFAS is a multi-centre population-based study in England and Wales with respondents aged 65 years and older. RESULTS: Normative values on the MMSE and EMSE are presented by age group, sex and level of education. There are very large differences between age groups, with smaller differences seen between the sexes and by level of education. The EMSE extends the scores at the high end of the ability range, but is no better than the MMSE at differentiating between dementia and non-dementia. CONCLUSION: Population-derived norms are valuable for comparing an individual's score to the score that would be expected among the general population, given the individual's specific demographic characteristics

SecA-Mediated Protein Translocation through the SecYEG Channel

In bacteria, the Sec translocase mediates the translocation of proteins into and across the cytoplasmic membrane. It consists of a protein conducting channel SecYEG, the ATP-dependent motor SecA, and the accessory SecDF complex. Here we discuss the function and structure of the Sec translocase

Missense mutation of Brain Derived Neurotrophic Factor (BDNF) alters neurocognitive performance in patients with mild traumatic brain injury: a longitudinal study

The predictability of neurocognitive outcomes in patients with traumatic brain injury is not straightforward. The extent and nature of recovery in patients with mild traumatic brain injury (mTBI) are usually heterogeneous and not substantially explained by the commonly known demographic and injury-related prognostic factors despite having sustained similar injuries or injury severity. Hence, this study evaluated the effects and association of the Brain Derived Neurotrophic Factor (BDNF) missense mutations in relation to neurocognitive performance among patients with mTBI. 48 patients with mTBI were prospectively recruited and MRI scans of the brain were performed within an average 10.1 (SD 4.2) hours post trauma with assessment of their neuropsychological performance post full Glasgow Coma Scale (GCS) recovery. Neurocognitive assessments were repeated again at 6 months follow-up. The paired t-test, Cohen’s d effect size and repeated measure ANOVA were performed to delineate statistically significant differences between the groups [wildtype G allele (Val homozygotes) vs. minor A allele (Met carriers)] and their neuropsychological performance across the time point (T1 = baseline/ admission vs. T2 = 6th month follow-up). Minor A allele carriers in this study generally performed more poorly on neuropsychological testing in comparison wildtype G allele group at both time points. Significant mean differences were observed among the wildtype group in the domains of memory (M = -11.44, SD = 10.0, p = .01, d = 1.22), executive function (M = -11.56, SD = 11.7, p = .02, d = 1.05) and overall performance (M = -6.89 SD = 5.3, p = .00, d = 1.39), while the minor A allele carriers showed significant mean differences in the domains of attention (M = -11.0, SD = 13.1, p = .00, d = .86) and overall cognitive performance (M = -5.25, SD = 8.1, p = .01, d = .66).The minor A allele carriers in comparison to the wildtype G allele group, showed considerably lower scores at admission and remained impaired in most domains across the timepoints, although delayed signs of recovery were noted to be significant in the domains attention and overall cognition. In conclusion, the current study has demonstrated the role of the BDNF rs6265 Val66Met polymorphism in influencing specific neurocognitive outcomes in patients with mTBI. Findings were more detrimentally profound among Met allele carriers

Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited

Since the late 1990s predicate invention has been under-explored within inductive logic programming due to difficulties in formulating efficient search mechanisms. However, a recent paper demonstrated that both predicate invention and the learning of recursion can be efficiently implemented for regular and context-free grammars, by way of metalogical substitutions with respect to a modified Prolog meta-interpreter which acts as the learning engine. New predicate symbols are introduced as constants representing existentially quantified higher-order variables. The approach demonstrates that predicate invention can be treated as a form of higher-order logical reasoning. In this paper we generalise the approach of meta-interpretive learning (MIL) to that of learning higher-order dyadic datalog programs. We show that with an infinite signature the higher-order dyadic datalog class$$H^2_2$$H22has universal Turing expressivity though$$H^2_2$$H22is decidable given a finite signature. Additionally we show that Knuth–Bendix ordering of the hypothesis space together with logarithmic clause bounding allows our MIL implementation Metagol$$_{D}$$Dto PAC-learn minimal cardinality$$H^2_2$$H22definitions. This result is consistent with our experiments which indicate that Metagol$$_{D}$$Defficiently learns compact$$H^2_2$$H22definitions involving predicate invention for learning robotic strategies, the East–West train challenge and NELL. Additionally higher-order concepts were learned in the NELL language learning domain. The Metagol code and datasets described in this paper have been made publicly available on a website to allow reproduction of results in this paper

Comparing the effectiveness of hyperspectral imaging and Raman spectroscopy:A case study on Armenian manuscripts

Additional file 1. Additional Figures S1–S5 and Tables S1, S2

Chemistry of a polluted cloudy boundary layer

A one-dimensional photochemical model for cloud-topped boundary layers is developed which includes detailed descriptions of gas-phase and aqueous-phase chemistry, and of the radiation field in and below cloud. The model is used to interpret the accumulation of pollutants observed over Bakersfield, California, during a wintertime stagnation episode with low stratus. The main features of the observations are well simulated; in particular, sulfate accumulates progressively over the course of the episode due to sustained aqueous-phase oxidation of SO2 in the stratus cloud. The major source of sulfate is the reaction S(IV) + Fe(III), provided that this reaction proceeds by a non radical mechanism in which Fe(III) is not reduced. A radical mechanism with SO3 − and Fe(II) as immediate products would quench sulfate production because of depletion of Fe(III). The model results suggest that the non radical mechanism is more consistent with observations, although this result follows from the absence of a rapid Fe(II) oxidation pathway in the model. Even with the non-radical mechanism, most of the soluble iron is present as Fe(II) because Fe(III) is rapidly reduced by O2 −. The S(IV) + Fe(III) reaction provides the principal source of H2O2 in the model; photochemical production of H2O2 from HO2 or O2(−I) is slow because HO2 is depleted by high levels of NOx. The aqueous-phase reaction S(IV) + OH initiates a radical-assisted S(IV) oxidation chain but we find that the chain is not propagated due to efficient termination by SO4 − + Cl− followed by Cl + H2O. A major uncertainty attached to that result is that the reactivities of S(IV)-carbonyl adducts with radical oxidants are unknown. The chain could be efficiently propagated, with high sulfate yields, if the S(IV)-carbonyl adducts were involved in chain propagation. A remarkable feature of the observations, which is well reproduced by the model, is the close balance between total atmospheric concentrations of acids and bases. We argue that this balance reflects the control of sulfate production by NH3, which follows from the pH dependence of the S(IV) + Fe(III) reaction. Such a balance should be a general characteristic of polluted environments where aqueous-phase oxidation of SO2 is the main source of acidity. At night, the acidity of the cloud approaches a steady state between NH3 emissions and H2SO4 production by the S(IV) + Fe(III) reaction. A steady state analysis suggests that [H+] at night should be proportional to (ESO 2/ENH 3)1/2 where ESO 2 and ENH 3 are emission rates of SO2 and NH3, respectively. From this analysis it appears that cloud water pH values below 3 are unlikely to occur in the Bakersfield atmosphere during the nighttime hours. Very high acidities could, however, be achieved in the daytime because of photochemical acid production by the gas-phase reactions NO2 + OH and SO2 + OH