The Particulate Methane Monooxygenase from Methylococcus capsulatus (Bath) Is a Novel Copper-containing Three-subunit Enzyme: isolation and charactization

The particulate methane monooxygenase (pMMO) is known to be very difficult to study mainly due to its unusual activity instability in vitro. By cultivating Methylococcus capsulatus (Bath) under methane stress conditions and high copper levels in the growth medium, membranes highly enriched in the pMMO with exceptionally stable activity can be isolated from these cells. Purified and active pMMO can be subsequently obtained from these membrane preparations using protocols in which an excess of reductants and anaerobic conditions were maintained during membrane solubilization by dodecyl beta-D-maltoside and purification by chromatography. The pMMO was found to be the major constituent in these membranes, constituting 60-80% of total membrane proteins. The dominant species of the pMMO was found to consist of three subunits, alpha, beta, and gamma, with an apparent molecular mass of 45, 26, and 23 kDa, respectively. A second species of the pMMO, a proteolytically processed version of the enzyme, was found to be composed of three subunits, alpha', beta, and gamma, with an apparent molecular mass of 35, 26, and 23 kDa, respectively. The alpha and alpha' subunits from these two forms of the pMMO contain identical N-terminal sequences. The gamma subunit, however, exhibits variation in its N-terminal sequence. The pMMO is a copper-containing protein only and shows a requirement for Cu(I) ions. Approximately 12-15 Cu ions per 94-kDa monomeric unit were observed. The pMMO is sensitive to dioxygen tension. On the basis of dioxygen sensitivity, three kinetically distinct forms of the enzyme can be distinguished. A slow but air-stable form, which is converted into a "pulsed" state upon direct exposure to atmospheric oxygen pressure, is considered as type I pMMO. This form was the subject of our pMMO isolation effort. Other forms (types II and III) are deactivated to various extents upon exposure to atmospheric dioxygen pressure. Under inactivating conditions, these unstable forms release protons to the buffer (~10 H+/94-kDa monomeric unit) and eventually become completely inactive

The Future of the Trans-Atlantic Defense Partnership: A Case for Realignment

Sean Kay is a Professor in the Department of Politics and Government at Ohio Wesleyan University specializing in international politics, international security, international organizations, and U.S. foreign and defense policy. He is also the Chair of the International Studies Program and holds the Libuse L. Reed Endowed Professorship. In addition, he is an Associate at the Mershon Center for International Security Studies at The Ohio State University and a Non-Resident Fellow at the Eisenhower Institute in Washington, D.C.Alexander Hamilton Society. Ohio State ChapterOhio State University. Mershon Center for International Security StudiesEvent Web page, event photo

Ontological Security and Locating Danger in Peace-Building: The Case of Northern Ireland

Streaming video requires Flash Player, RealPlayer, or Windows Media Player to viewKay discussed parts of his forthcoming book, Celtic Revival?: The Rise, Fall, and Renewal of Global Ireland (Rowman & Littlefield)Ohio State University. Mershon Center for International Security StudiesEvent Web page, streaming video, event photo

Proteomic profiling of bovine M. longissimus lumborum from Crossbred Aberdeen Angus and Belgian Blue sired steers varying in genetic merit for carcass weight

Bovine skeletal muscle is a tissue of significant value to the beef industry and global economy. Proteomic analyses offer the opportunity to detect molecular mechanisms regulating muscle growth and intramuscular fat accumulation. The current study aimed to investigate differences in protein abundance in skeletal muscle tissue of cattle from two breeds of contrasting maturity (early vs. late maturing), adiposity, and muscle growth potential, namely, Belgian Blue (BB) × Holstein Friesian and Aberdeen Angus (AA) × Holstein Friesian. Twenty AA (n = 10) and BB (n = 10) sired steers, the progeny of sires of either high or low genetic merit, expressed as expected progeny difference for carcass weight (EPDcwt), and bred through AI, were evaluated as 4 genetic groups, BB-High, BB-Low, AA-High, and AA-Low (n = 5 per treatment). Chemical composition analysis of M. longissimus lumborum showed greater protein and moisture and decreased lipid concentrations for BB-sired compared with AA-sired steers. To investigate the effects of both sire breed and EPDcwt on M. longissimus lumborum, proteomic analysis was performed using 2-dimensional difference gel electrophoresis followed by mass spectrometry. Proteins were identified from their peptide sequences, using the National Center for Biotechnology Information (NCBI) and Swiss-prot databases. Metabolic enzymes involved in glycolysis (glycogen phosphorylase, phosphoglycerate mutase) and the citric acid cycle (aconitase 2, oxoglutarate dehydrogenase) were increased in AA- vs. BB-sired steers. Expression of proteins involved in cell structure, such as myosin light chain isoforms and troponins I and T, were also altered due to sire breed. Furthermore, heat shock protein β-1 and peroxiredoxin 6, involved in cell defense, had increased abundance in muscle of AA-sired relative to BB-sired steers. Protein abundance of glucose-6-phosphate isomerase, enolase-3, and pyruvate kinase was greater in AA-sired animals of High compared with Low EPDcwt. Changes in the expression of these proteins were supported by gene expression analysis using quantitative real-time PCR. This information will aid in our understanding of genetic infl uences controlling muscle growth and fat accumulation and could contribute to future breeding programs to increase lean tissue gain of beef cattle

Risk of SARS-CoV-2 Transmission During Flexible Laryngoscopy: A Systematic Review.

IMPORTANCE: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reportedly infected otolaryngologists disproportionately in the early parts of the coronavirus disease 2019 pandemic. Recommendations from national and international health organizations suggest minimizing the use of flexible laryngoscopy as a result. OBJECTIVE: To review evidence on the risks of aerosolization and transmission of SARS-CoV-2 from patients to health care personnel during endoscopy of the upper aerodigestive tract. EVIDENCE REVIEW: A comprehensive review of literature was performed on April 19, 2020, using the PubMed/MEDLINE (1966-April 2020), Embase (1975-April 2020), and Web of Science (1900-April 2020) databases. All English-language primary research studies were included if they assessed the transmission of SARS-CoV-2 or SARS-CoV-1 during procedures in the upper aerodigestive tract. The primary outcome measure was disease transmission among health care workers. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used for accuracy of reporting. FINDINGS: The queries for SARS-CoV-2 and SARS-CoV-1 identified 6 articles for systematic review. No studies included in this review provided data for SARS-CoV-2 transmission during flexible laryngoscopy. A total of 204 of 1264 health care workers (16.1%) had procedure-specific infections of SARS-CoV-1 or SARS-CoV-2. Among those, 53 of 221 (24.0%) were exposed during intubation, 1 of 15 (6.7%) during bronchoscopy, and 1 of 1 (100%) during endoscopy-assisted intubation. CONCLUSIONS AND RELEVANCE: A substantial lack of research precludes formal conclusions about the safety of flexible laryngoscopy and transmission of SARS-CoV-2 from patients to health care workers. The use of appropriate precautionary measures and personal protective equipment appears to reduce the risk of transmission. Given the uncertainty in transmission and the known benefits of safety precautions, upper airway endoscopy may be reasonable to perform if precautionary steps are taken

Trusted CI Experiences in Cybersecurity and Service to Open Science

This article describes experiences and lessons learned from the Trusted CI project, funded by the US National Science Foundation to serve the community as the NSF Cybersecurity Center of Excellence. Trusted CI is an effort to address cybersecurity for the open science community through a single organization that provides leadership, training, consulting, and knowledge to that community. The article describes the experiences and lessons learned of Trusted CI regarding both cybersecurity for open science and managing the process of providing centralized services to a broad and diverse community.Comment: 8 pages, PEARC '19: Practice and Experience in Advanced Research Computing, July 28-August 1, 2019, Chicago, IL, US

Markov models and the ensemble Kalman filter for estimation of sorption rates.

Non-equilibrium sorption of contaminants in ground water systems is examined from the perspective of sorption rate estimation. A previously developed Markov transition probability model for solute transport is used in conjunction with a new conditional probability-based model of the sorption and desorption rates based on breakthrough curve data. Two models for prediction of spatially varying sorption and desorption rates along a one-dimensional streamline are developed. These models are a Markov model that utilizes conditional probabilities to determine the rates and an ensemble Kalman filter (EnKF) applied to the conditional probability method. Both approaches rely on a previously developed Markov-model of mass transfer, and both models assimilate the observed concentration data into the rate estimation at each observation time. Initial values of the rates are perturbed from the true values to form ensembles of rates and the ability of both estimation approaches to recover the true rates is examined over three different sets of perturbations. The models accurately estimate the rates when the mean of the perturbations are zero, the unbiased case. For the cases containing some bias, addition of the ensemble Kalman filter is shown to improve accuracy of the rate estimation by as much as an order of magnitude

Kepler Presearch Data Conditioning II - A Bayesian Approach to Systematic Error Correction

With the unprecedented photometric precision of the Kepler Spacecraft, significant systematic and stochastic errors on transit signal levels are observable in the Kepler photometric data. These errors, which include discontinuities, outliers, systematic trends and other instrumental signatures, obscure astrophysical signals. The Presearch Data Conditioning (PDC) module of the Kepler data analysis pipeline tries to remove these errors while preserving planet transits and other astrophysically interesting signals. The completely new noise and stellar variability regime observed in Kepler data poses a significant problem to standard cotrending methods such as SYSREM and TFA. Variable stars are often of particular astrophysical interest so the preservation of their signals is of significant importance to the astrophysical community. We present a Bayesian Maximum A Posteriori (MAP) approach where a subset of highly correlated and quiet stars is used to generate a cotrending basis vector set which is in turn used to establish a range of "reasonable" robust fit parameters. These robust fit parameters are then used to generate a Bayesian Prior and a Bayesian Posterior Probability Distribution Function (PDF) which when maximized finds the best fit that simultaneously removes systematic effects while reducing the signal distortion and noise injection which commonly afflicts simple least-squares (LS) fitting. A numerical and empirical approach is taken where the Bayesian Prior PDFs are generated from fits to the light curve distributions themselves.Comment: 43 pages, 21 figures, Submitted for publication in PASP. Also see companion paper "Kepler Presearch Data Conditioning I - Architecture and Algorithms for Error Correction in Kepler Light Curves" by Martin C. Stumpe, et a