Defining and using microbial spectral databases

AbstractThis work shows how fingerprints of mass spectral patterns from microbial isolates are affected by variations in instrumental condition, by sample environment, and by sample handling factors. It describes a novel method by which pattern distortions can be mathematically corrected for variations in factors not amenable to experimental control. One uncontrollable variable is “between-batch” differences in culture media. Another, relevant for determination of noncultured extracts, is differences between the cells’ environmental experience (e.g., starved environmental extracts versus cultured standards). The method suggests that, after a single growth cycle on a solid medium (perhaps, a selective one), pyrolysis MS spectra of microbial isolates can be algorithmically compensated and an unknown isolate identified using a spectral database defined by culture on a different (perhaps, nonselective) medium. This reduces identification time to as few as 24 h from sample collection. The concept also proposes a possible way to compensate certain noncultured, nonisolated samples (e.g., cells concentrated from urine or impacted from aerosol or semi-selectively extracted by immunoaffinity methods from heavily contaminated matrices) for identification within half an hour. Using the method, microbial mass spectra from different labs can be assembled into coherent databases similar to those routinely used to identify pure compounds. This type of data treatment is applicable for rapid detection in biowarfare and bioterror events as well as in forensic, research, and clinical laboratory contexts

Modeling Chemical Interaction Profiles: II. Molecular Docking, Spectral Data-Activity Relationship, and Structure-Activity Relationship Models for Potent and Weak Inhibitors of Cytochrome P450 CYP3A4 Isozyme

Polypharmacy increasingly has become a topic of public health concern, particularly as the U.S. population ages. Drug labels often contain insufficient information to enable the clinician to safely use multiple drugs. Because many of the drugs are bio-transformed by cytochrome P450 (CYP) enzymes, inhibition of CYP activity has long been associated with potentially adverse health effects. In an attempt to reduce the uncertainty pertaining to CYP-mediated drug-drug/chemical interactions, an interagency collaborative group developed a consensus approach to prioritizing information concerning CYP inhibition. The consensus involved computational molecular docking, spectral data-activity relationship (SDAR), and structure-activity relationship (SAR) models that addressed the clinical potency of CYP inhibition. The models were built upon chemicals that were categorized as either potent or weak inhibitors of the CYP3A4 isozyme. The categorization was carried out using information from clinical trials because currently available in vitro high-throughput screening data were not fully representative of the in vivo potency of inhibition. During categorization it was found that compounds, which break the Lipinski rule of five by molecular weight, were about twice more likely to be inhibitors of CYP3A4 compared to those, which obey the rule. Similarly, among inhibitors that break the rule, potent inhibitors were 2–3 times more frequent. The molecular docking classification relied on logistic regression, by which the docking scores from different docking algorithms, CYP3A4 three-dimensional structures, and binding sites on them were combined in a unified probabilistic model. The SDAR models employed a multiple linear regression approach applied to binned 1D 13C-NMR and 1D 15N-NMR spectral descriptors. Structure-based and physical-chemical descriptors were used as the basis for developing SAR models by the decision forest method. Thirty-three potent inhibitors and 88 weak inhibitors of CYP3A4 were used to train the models. Using these models, a synthetic majority rules consensus classifier was implemented, while the confidence of estimation was assigned following the percent agreement strategy. The classifier was applied to a testing set of 120 inhibitors not included in the development of the models. Five compounds of the test set, including known strong inhibitors dalfopristin and tioconazole, were classified as probable potent inhibitors of CYP3A4. Other known strong inhibitors, such as lopinavir, oltipraz, quercetin, raloxifene, and troglitazone, were among 18 compounds classified as plausible potent inhibitors of CYP3A4. The consensus estimation of inhibition potency is expected to aid in the nomination of pharmaceuticals, dietary supplements, environmental pollutants, and occupational and other chemicals for in-depth evaluation of the CYP3A4 inhibitory activity. It may serve also as an estimate of chemical interactions via CYP3A4 metabolic pharmacokinetic pathways occurring through polypharmacy and nutritional and environmental exposures to chemical mixtures

The Far-Infrared Spectral Energy Distributions of X-ray-selected Active Galaxies

[Abridged] We present ISO far-infrared (IR) observations of 21 hard X-ray selected AGN from the HEAO-1 A2 sample. We compare the far-IR to X-ray spectral energy distributions (SEDs) of this sample with various radio and optically selected AGN samples. The hard-X-ray selected sample shows a wider range of optical/UV shapes extending to redder near-IR colors. The bluer objects are Seyfert 1s, while the redder AGN are mostly intermediate or type 2 Seyferts. This is consistent with a modified unification model in which the amount of obscuring material increases with viewing angle and may be clumpy. Such a scenario, already suggested by differing optical/near-IR spectroscopic and X-ray AGN classifications, allows for different amounts of obscuration of the continuum emission in different wavebands and of the broad emission line region which results in a mixture of behaviors for AGN with similar optical emission line classifications. The resulting limits on the column density of obscuring material through which we are viewing the redder AGN are 100 times lower than for the standard optically thick torus models. The resulting decrease in optical depth of the obscuring material allows the AGN to heat more dust at larger radial distances. We show that an AGN-heated, flared, dusty disk with mass 10^9 solar and size of few hundred pc is able to generate optical-far-IR SEDs which reproduce the wide range of SEDs present in our sample with no need for an additional starburst component to generate the long-wavelength, cooler part of the IR continuum.Comment: 40 pages, 14 figures, accepted for publication in Astrophysical Journal, V. 590, June 10, 200

A rapidly convecting lava lake at Masaya Volcano, Nicaragua

Lava lakes provide a rare opportunity to study conduit flow processes through direct observation of the exposed magma surface. The recent lava lake activity at Masaya volcano (Nicaragua), which commenced in 2015, displayed several unusual phenomena. We report on the dynamics of this rapidly convecting lake, which, to the best of our knowledge manifested the highest lava flow velocities ever reported for a lava lake: 13.7–16.4 m s−1, in addition to unusual fluid dynamic behavior involving alteration in surface flow direction. We studied this system with multiparametric and high time resolution remote sensing measurements, performed during June 2017, including ultraviolet camera observations of SO2 emission rates, near infrared thermal camera measurements and video analyses of the lake surface. Median SO2 emission rates of 3.1 (±0.8) and 3.7 (±0.9) kg s−1 were found, which are lower than previously published estimates, and could represent challenging remote sensing conditions or a waning in lava lake activity. Video analyses enabled characterization of frequent bursts of approximately hemispherical spherical-cap bubbles on the surface with diameters ranging 0.6–8.5 m (median of 2.6 m), and calculation of individual bubble masses, which contribute to active bubble bursting values estimated at 1.9 to 3.9 kg s−1. We show that only a small fraction, 7–17%, of total emission volumes are contributed by these bubbles, based on estimated emission rates of 22.5 and 26.9 kg s−1. Furthermore, periodicity analysis reveals regular 200–300 s oscillations in SO2 emissions. These are not shared by any of our other datasets and particularly during the contemporaenously acquried thermal data, hence, we tentatively assign an atmospheric causal generation mechanism, driven by atmospheric transport and turbulence phenomena, such as eddying. Overall, we highlight the uniquely high velocity and fluid dynamic behavior of Masaya lava lake

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Models of classroom assessment for course-based research experiences

Course-based research pedagogy involves positioning students as contributors to authentic research projects as part of an engaging educational experience that promotes their learning and persistence in science. To develop a model for assessing and grading students engaged in this type of learning experience, the assessment aims and practices of a community of experienced course-based research instructors were collected and analyzed. This approach defines four aims of course-based research assessment—(1) Assessing Laboratory Work and Scientific Thinking; (2) Evaluating Mastery of Concepts, Quantitative Thinking and Skills; (3) Appraising Forms of Scientific Communication; and (4) Metacognition of Learning—along with a set of practices for each aim. These aims and practices of assessment were then integrated with previously developed models of course-based research instruction to reveal an assessment program in which instructors provide extensive feedback to support productive student engagement in research while grading those aspects of research that are necessary for the student to succeed. Assessment conducted in this way delicately balances the need to facilitate students’ ongoing research with the requirement of a final grade without undercutting the important aims of a CRE education

Rapid Flow Cytometry Detection of a Single Viable Escherichia coli O157:H7 Cell in Raw Spinach Using a Simplified Sample Preparation Technique

Very low cell count detection of Escherichia coli O157:H7 in foods is critical, since an infective dose for this pathogen may be only 10 cells, and fewer still for vulnerable populations. A flow cytometer is able to detect and count individual cells of a target bacterium, in this case E. coli O157:H7. The challenge is to find the single cell in a complex matrix like raw spinach. To find that cell requires growing it as quickly as possible to a number sufficiently in excess of matrix background that identification is certain. The experimental design for this work was that of a U.S. Food and Drug Administration (FDA) In-House Level 3 validation executed in the technology’s originating laboratory. Using non-selective enrichment broth, 6.5 h incubation at 42°C, centrifugation for target cell concentration, and a highly selective E. coli O157 fluorescent antibody tag, the cytometry method proved more sensitive than a reference regulatory method (p = 0.01) for detecting a single target cell, one E. coli O157:H7 cell, in 25 g of spinach. It counted that cell’s daughters with at least 38× signal-to-noise ratio, analyzing 25 samples in total-time-to-results of 9 h

An integrated flow cytometry-based system for real-time, high sensitivity bacterial detection and identification.

Foodborne illnesses occur in both industrialized and developing countries, and may be increasing due to rapidly evolving food production practices. Yet some primary tools used to assess food safety are decades, if not centuries, old. To improve the time to result for food safety assessment a sensitive flow cytometer based system to detect microbial contamination was developed. By eliminating background fluorescence and improving signal to noise the assays accurately measure bacterial load or specifically identify pathogens. These assays provide results in minutes or, if sensitivity to one cell in a complex matrix is required, after several hours enrichment. Conventional assessments of food safety require 48 to 56 hours. The assays described within are linear over 5 orders of magnitude with results identical to culture plates, and report live and dead microorganisms. This system offers a powerful approach to real-time assessment of food safety, useful for industry self-monitoring and regulatory inspection