Recent advances in electronic structure theory and their influence on the accuracy of ab initio potential energy surfaces

Recent advances in electronic structure theory and the availability of high speed vector processors have substantially increased the accuracy of ab initio potential energy surfaces. The recently developed atomic natural orbital approach for basis set contraction has reduced both the basis set incompleteness and superposition errors in molecular calculations. Furthermore, full CI calculations can often be used to calibrate a CASSCF/MRCI approach that quantitatively accounts for the valence correlation energy. These computational advances also provide a vehicle for systematically improving the calculations and for estimating the residual error in the calculations. Calculations on selected diatomic and triatomic systems will be used to illustrate the accuracy that currently can be achieved for molecular systems. In particular, the F+H2 yields HF+H potential energy hypersurface is used to illustrate the impact of these computational advances on the calculation of potential energy surfaces

An Age-Structured Extension to the Vectorial Capacity Model

Vectorial capacity and the basic reproductive number (R(0)) have been instrumental in structuring thinking about vector-borne pathogen transmission and how best to prevent the diseases they cause. One of the more important simplifying assumptions of these models is age-independent vector mortality. A growing body of evidence indicates that insect vectors exhibit age-dependent mortality, which can have strong and varied affects on pathogen transmission dynamics and strategies for disease prevention.Based on survival analysis we derived new equations for vectorial capacity and R(0) that are valid for any pattern of age-dependent (or age-independent) vector mortality and explore the behavior of the models across various mortality patterns. The framework we present (1) lays the groundwork for an extension and refinement of the vectorial capacity paradigm by introducing an age-structured extension to the model, (2) encourages further research on the actuarial dynamics of vectors in particular and the relationship of vector mortality to pathogen transmission in general, and (3) provides a detailed quantitative basis for understanding the relative impact of reductions in vector longevity compared to other vector-borne disease prevention strategies.Accounting for age-dependent vector mortality in estimates of vectorial capacity and R(0) was most important when (1) vector densities are relatively low and the pattern of mortality can determine whether pathogen transmission will persist; i.e., determines whether R(0) is above or below 1, (2) vector population growth rate is relatively low and there are complex interactions between birth and death that differ fundamentally from birth-death relationships with age-independent mortality, and (3) the vector exhibits complex patterns of age-dependent mortality and R(0) ∼ 1. A limiting factor in the construction and evaluation of new age-dependent mortality models is the paucity of data characterizing vector mortality patterns, particularly for free ranging vectors in the field

Quantifying the effects of temperature on mosquito and parasite traits that determine the transmission potential of human malaria

Malaria transmission is known to be strongly impacted by temperature. The current understanding of how temperature affects mosquito and parasite life history traits derives from a limited number of empirical studies. These studies, some dating back to the early part of last century, are often poorly controlled, have limited replication, explore a narrow range of temperatures, and use a mixture of parasite and mosquito species. Here, we use a single pairing of the Asian mosquito vector, An. stephensi and the human malaria parasite, P. falciparum to conduct a comprehensive evaluation of the thermal performance curves of a range of mosquito and parasite traits relevant to transmission. We show that biting rate, adult mortality rate, parasite development rate, and vector competence are temperature sensitive. Importantly, we find qualitative and quantitative differences to the assumed temperature-dependent relationships. To explore the overall implications of temperature for transmission, we first use a standard model of relative vectorial capacity. This approach suggests a temperature optimum for transmission of 29°C, with minimum and maximum temperatures of 12°C and 38°C, respectively. However, the robustness of the vectorial capacity approach is challenged by the fact that the empirical data violate several of the model's simplifying assumptions. Accordingly, we present an alternative model of relative force of infection that better captures the observed biology of the vector-parasite interaction. This model suggests a temperature optimum for transmission of 26°C, with a minimum and maximum of 17°C and 35°C, respectively. The differences between the models lead to potentially divergent predictions for the potential impacts of current and future climate change on malaria transmission. The study provides a framework for more detailed, system-specific studies that are essential to develop an improved understanding on the effects of temperature on malaria transmission

Architecture of the RNA polymerase II–TFIIF complex revealed by cross-linking and mass spectrometry

Higher-order multi-protein complexes such as RNA polymerase II (Pol II) complexes with transcription initiation factors are often not amenable to X-ray structure determination. Here, we show that protein cross-linking coupled to mass spectrometry (MS) has now sufficiently advanced as a tool to extend the Pol II structure to a 15-subunit, 670 kDa complex of Pol II with the initiation factor TFIIF at peptide resolution. The N-terminal regions of TFIIF subunits Tfg1 and Tfg2 form a dimerization domain that binds the Pol II lobe on the Rpb2 side of the active centre cleft near downstream DNA. The C-terminal winged helix (WH) domains of Tfg1 and Tfg2 are mobile, but the Tfg2 WH domain can reside at the Pol II protrusion near the predicted path of upstream DNA in the initiation complex. The linkers between the dimerization domain and the WH domains in Tfg1 and Tfg2 are located to the jaws and protrusion, respectively. The results suggest how TFIIF suppresses non-specific DNA binding and how it helps to recruit promoter DNA and to set the transcription start site. This work establishes cross-linking/MS as an integrated structure analysis tool for large multi-protein complexes

Quantifying the potential for bluetongue virus transmission in Danish cattle farms

We used a mechanistic transmission model to estimate the number of infectious bites (IBs) generated per bluetongue virus (BTV) infected host (cattle) using estimated hourly microclimatic temperatures at 22,004 Danish cattle farms for the period 2000–2016, and Culicoides midge abundance based on 1,453 light-trap collections during 2007–2016. We used a range of published estimates of the duration of the hosts’ infectious period and equations for the relationship between temperature and four key transmission parameters: extrinsic incubation period, daily vector survival rate, daily vector biting rate and host-to-vector transmission rate resulting in 147,456 combinations of daily IBs. More than 82% combinations of the parameter values predicted > 1 IBs per host. The mean IBs (10–90th percentiles) for BTV per infectious host were 59 (0–73) during the transmission period. We estimated a maximum of 14,954 IBs per infectious host at some farms, while a best-case scenario suggested transmission was never possible at some farms. The use of different equations for the vector survival rate and host-to-vector transmission rates resulted in large uncertainty in the predictions. If BTV is introduced in Denmark, local transmission is very likely to occur. Vectors infected as late as mid-September (early autumn) can successfully transmit BTV to a new host until mid-November (late autumn)

Projections of climate conditions that increase coral disease susceptibility and pathogen abundance and virulence

Rising sea temperatures are likely to increase the frequency of disease outbreaks affecting reef-building corals through impacts on coral hosts and pathogens. We present and compare climate model projections of temperature conditions that will increase coral susceptibility to disease, pathogen abundance and pathogen virulence. Both moderate (RCP 4.5) and fossil fuel aggressive (RCP 8.5) emissions scenarios are examined. We also compare projections for the onset of disease-conducive conditions and severe annual coral bleaching, and produce a disease risk summary that combines climate stress with stress caused by local human activities. There is great spatial variation in the projections, both among and within the major ocean basins, in conditions favouring disease development. Our results indicate that disease is as likely to cause coral mortality as bleaching in the coming decades. These projections identify priority locations to reduce stress caused by local human activities and test management interventions to reduce disease impacts

Visual inspection with acetic acid as a cervical cancer test: accuracy validated using latent class analysis

<p>Abstract</p> <p>Background</p> <p>The purpose of this study was to validate the accuracy of an alternative cervical cancer test – visual inspection with acetic acid (VIA) – by addressing possible imperfections in the gold standard through latent class analysis (LCA). The data were originally collected at peri-urban health clinics in Zimbabwe.</p> <p>Methods</p> <p>Conventional accuracy (sensitivity/specificity) estimates for VIA and two other screening tests using colposcopy/biopsy as the reference standard were compared to LCA estimates based on results from all four tests. For conventional analysis, negative colposcopy was accepted as a negative outcome when biopsy was not available as the reference standard. With LCA, local dependencies between tests were handled through adding direct effect parameters or additional latent classes to the model.</p> <p>Results</p> <p>Two models yielded good fit to the data, a 2-class model with two adjustments and a 3-class model with one adjustment. The definition of latent disease associated with the latter was more stringent, backed by three of the four tests. Under that model, sensitivity for VIA (abnormal+) was 0.74 compared to 0.78 with conventional analyses. Specificity was 0.639 versus 0.568, respectively. By contrast, the LCA-derived sensitivity for colposcopy/biopsy was 0.63.</p> <p>Conclusion</p> <p>VIA sensitivity and specificity with the 3-class LCA model were within the range of published data and relatively consistent with conventional analyses, thus validating the original assessment of test accuracy. LCA probably yielded more likely estimates of the true accuracy than did conventional analysis with in-country colposcopy/biopsy as the reference standard. Colpscopy with biopsy can be problematic as a study reference standard and LCA offers the possibility of obtaining estimates adjusted for referent imperfections.</p

Purine metabolism regulates DNA repair and therapy resistance in glioblastoma

Intratumoral genomic heterogeneity in glioblastoma (GBM) is a barrier to overcoming therapy resistance. Treatments that are effective independent of genotype are urgently needed. By correlating intracellular metabolite levels with radiation resistance across dozens of genomically-distinct models of GBM, we find that purine metabolites, especially guanylates, strongly correlate with radiation resistance. Inhibiting GTP synthesis radiosensitizes GBM cells and patient-derived neurospheres by impairing DNA repair. Likewise, administration of exogenous purine nucleosides protects sensitive GBM models from radiation by promoting DNA repair. Neither modulating pyrimidine metabolism nor purine salvage has similar effects. An FDA-approved inhibitor of GTP synthesis potentiates the effects of radiation in flank and orthotopic patient-derived xenograft models of GBM. High expression of the rate-limiting enzyme of de novo GTP synthesis is associated with shorter survival in GBM patients. These findings indicate that inhibiting purine synthesis may be a promising strategy to overcome therapy resistance in this genomically heterogeneous disease

Toward a model-based predictive controller design in brain-computer interfaces

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain-computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8-23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications.Grants K25NS061001 (MK) and K02MH01493 (SJS) from the National Institute of Neurological Disorders And Stroke (NINDS) and the National Institute of Mental Health (NIMH), the Portuguese Foundation for Science and Technology (FCT) Grant SFRH/BD/21529/2005 (NSD), the Pennsylvania Department of Community and Economic Development Keystone Innovation Zone Program Fund (SJS), and the Pennsylvania Department of Health using Tobacco Settlement Fund (SJS)