Annual and Seasonal Patterns of Burned Area Products in Arctic-Boreal North America and Russia for 2001-2020

Boreal and Arctic regions have warmed up to four times quicker than the rest of the planet since the 1970s. As a result, boreal and tundra ecosystems are experiencing more frequent and higher intensity extreme weather events and disturbances, such as wildfires. Yet limitations in ground and satellite data across the Arctic and boreal regions have challenged efforts to track these disturbances at regional scales. In order to effectively monitor the progression and extent of wildfires in the Arctic-boreal zone, it is essential to determine whether burned area (BA) products are accurate representations of BA. Here, we use 12 different datasets together with MODIS active fire data to determine the total yearly BA and seasonal patterns of fires in Arctic-boreal North America and Russia for the years 2001–2020. We found relatively little variability between the datasets in North America, both in terms of total BA and seasonality, with an average BA of 2.55 ± 1.24 (standard deviation) Mha/year for our analysis period, the majority (ca. 41%) of which occurs in July. In contrast, in Russia, there are large disparities between the products—GFED5 produces over four times more BA than GFED4s in southern Siberia. These disparities occur due to the different methodologies used; dNBR (differenced Normalized Burn Ratio) of short-term composites from Landsat images used alongside hotspot data was the most consistently successful in representing BA. We stress caution using GABAM in these regions, especially for the years 2001–2013, as Landsat-7 ETM+ scan lines are mistaken as burnt patches, increasing errors of commission. On the other hand, we highlight using regional products where possible, such as ABoVE-FED or ABBA in North America, and the Talucci et al. fire perimeter product in Russia, due to their detection of smaller fires which are often missed by global products

Proteomic Profile of Reversible Protein Oxidation Using PROP, Purification of Reversibly Oxidized Proteins

Signal transduction pathways that are modulated by thiol oxidation events are beginning to be uncovered, but these discoveries are limited by the availability of relatively few analytical methods to examine protein oxidation compared to other signaling events such as protein phosphorylation. We report here the coupling of PROP, a method to purify reversibly oxidized proteins, with the proteomic identification of the purified mixture using mass spectrometry. A gene ontology (GO), KEGG enrichment and Wikipathways analysis of the identified proteins indicated a significant enrichment in proteins associated with both translation and mRNA splicing. This methodology also enabled the identification of some of the specific cysteine residue targets within identified proteins that are reversibly oxidized by hydrogen peroxide treatment of intact cells. From these identifications, we determined a potential consensus sequence motif associated with oxidized cysteine residues. Furthermore, because we identified proteins and specific sites of oxidation from both abundant proteins and from far less abundant signaling proteins (e.g. hepatoma derived growth factor, prostaglandin E synthase 3), the results suggest that the PROP procedure was efficient. Thus, this PROP-proteomics methodology offers a sensitive means to identify biologically relevant redox signaling events that occur within intact cells

The isothiocyanate class of bioactive nutrients covalently inhibit the MEKK1 protein kinase

<p>Abstract</p> <p>Background</p> <p>Dietary isothiocyanates (ITCs) are electrophilic compounds that have diverse biological activities including induction of apoptosis and effects on cell cycle. They protect against experimental carcinogenesis in animals, an activity believed to result from the transcriptional induction of "Phase 2" enzymes. The molecular mechanism of action of ITCs is unknown. Since ITCs are electrophiles capable of reacting with sulfhydryl groups on amino acids, we hypothesized that ITCs induce their biological effects through covalent modification of proteins, leading to changes in cell regulatory events. We previously demonstrated that stress-signaling kinase pathways are inhibited by other electrophilic compounds such as menadione. We therefore tested the effects of nutritional ITCs on MEKK1, an upstream regulator of the SAPK/JNK signal transduction pathway.</p> <p>Methods</p> <p>The activity of MEKK1 expressed in cells was monitored using in vitro kinase assays to measure changes in catalytic activity. The activity of endogenous MEKK1, immunopurified from ITC treated and untreated LnCAP cells was also measured by in vitro kinase assay. A novel labeling and affinity reagent for detection of protein modification by ITCs was synthesized and used in competition assays to monitor direct modification of MEKK1 by ITC. Finally, immunoblots with phospho-specific antibodies were used to measure the activity of MAPK protein kinases.</p> <p>Results</p> <p>ITCs inhibited the MEKK1 protein kinase in a manner dependent on a specific cysteine residue in the ATP binding pocket. Inhibition of MEKK1 catalytic activity was due to direct, covalent and irreversible modification of the MEKK1 protein itself. In addition, ITCs inhibited the catalytic activity of endogenous MEKK1. This correlated with inhibition of the downstream target of MEKK1 activity, i.e. the SAPK/JNK kinase. This inhibition was specific to SAPK, as parallel MAPK pathways were unaffected.</p> <p>Conclusion</p> <p>These results demonstrate that MEKK1 is directly modified and inhibited by ITCs, and that this correlates with inhibition of downstream activation of SAPK. These results support the conclusion that ITCs may carry out many of their actions by directly targeting important cell regulatory proteins.</p

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

Selected peptides that were observed with a cysteine residue that had been biologically oxidized from proteins that were preferentially identified <i>before</i> H₂O₂ oxidation treatment of cells.

†<p>The total number of scans that were observed for that peptide. All of the scans tabulated passed a 3% FDR filter cutoff. The replicate analysis of 6 independent biological samples for both the control and H₂O₂ treated cells are shown. Data referred to in the text combine the replicate analyses.</p>‡<p>The eValue represents the best (i.e. smallest) OMSSA eValue score matched to the particular peptide sequence. This provides a relative measure of the overall confidence that the peptide was in the sample (i.e. a true positive), with 0.00E+000 representing the highest confidence.</p>*<p>Lower case “c” indicates location of carboxyamidomethyl derivatization(s).</p

Selected proteins identified using the PROP analysis that were preferentially identified <i>before</i> H₂O₂ oxidation treatment of cells.

†<p>Leading number indicates the number of unique peptides for a particular protein that were observed while the number in parentheses indicates the total number of scans that were observed for that protein. All of the scans tabulated passed a 3% FDR filter cutoff. An “X” indicates that no scans were observed that passed the FDR filter. The replicate analysis of 6 independent biological samples for both the control and H₂O₂ treated cells are shown. Data referred to in the text combine the replicate analyses.</p>‡<p>The pValue represents the product of the best (i.e. smallest) eValue score observed for each <i>unique</i> peptide sequence for the given protein. This provides a relative measure of the overall confidence that the protein was in the sample (i.e. a true positive), with 0.00E+000 representing the highest confidence.</p

PROP-proteomics procedure.

<p>Schematic diagram showing steps involved in the PROP-proteomics procedure that are described in detail in both <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032527#s2" target="_blank">Methods</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0032527#s3" target="_blank">Results</a>.</p

Selected proteins identified using the PROP analysis on six replicate cell cultures treated or not with H₂O₂ that were preferentially identified <i>after</i> H₂O₂ oxidation treatment of cells.

†<p>Leading number indicates the number of unique peptides for a particular protein that were observed while the number in parentheses indicates the total number of scans that were observed for that protein; in other words, a protein indicated as 3(13) had three unique peptides identified a total of 13 times. All of the scans tabulated passed a 3% FDR filter cutoff. An “X” indicates that no scans were observed that passed the FDR filter. The replicate analysis of 6 independent biological samples for both the control and H₂O₂ treated cells are shown. Data referred to in the text combine the replicate analyses.</p>‡<p>The pValue represents the product of the best (i.e. smallest) eValue score observed for each <i>unique</i> peptide sequence for the given protein. This provides a relative measure of the overall confidence that the protein was in the sample (i.e. a true positive), with 0.00E+000 representing the highest confidence.</p

Potential Consensus Sequence for Oxidized Cysteine Residues.

<p>The sequence logo representation of the frequency of the amino acid residues surrounding the oxidized cysteine residues, located at position “0”, that were identified from the PROP proteomics procedure.</p