Metal exposure is a potential risk factor for amyotrophic lateral sclerosis (ALS). Increasing evidence suggests that elevated levels of DNA damage are present in both familial (fALS) and sporadic (sALS) forms of ALS, characterized by the selective loss of motor neurons in the brain, brainstem, and spinal cord. However, identifying and differentiating initial biomarkers of DNA damage response (DDR) in both forms of ALS remains unclear. The toxicological profiles from the Agency for Toxic Substances and Disease Registry (ATSDR) and our previous studies have demonstrated the influence of metal exposure-induced genotoxicity and neurodegeneration. A comprehensive overview of the ATSDR's toxicological profiles and the available literature identified 15 metals (aluminum (Al), arsenic (As), cadmium (Cd), chromium (Cr), cobalt (Co), copper (Cu), iron (Fe), lead (Pb), manganese (Mn), mercury (Hg), nickel (Ni), selenium (Se), uranium (U), vanadium (V), and zinc (Zn)) showing exposure-induced genotoxicity indicators associated with ALS pathogenesis. Genetic factors including mutations seen in ALS types and with concomitant metal exposure were distinguished, showing that heavy metal exposure can exacerbate the downstream effect of existing genetic mutations in fALS and may contribute to motor neuron degeneration in sALS. Substantial evidence associates heavy metal exposure to genotoxic endpoints in both forms of ALS; however, a data gap has been observed for several of these endpoints. This review aims to (1) provide a comprehensive overview of metal exposure-induced genotoxicity in ALS patients and experimental models, and its potential role in disease risk, (2) summarize the evidence for DNA damage and associated biomarkers in ALS pathogenesis, (3) discuss possible mechanisms for metal exposure-induced genotoxic contributions to ALS pathogenesis, and (4) explore the potential distinction of genotoxic biomarkers in both forms of ALS. Our findings support the association between metal exposure and ALS, highlighting under or unexplored genotoxic endpoints, signaling key data gaps. Given the high prevalence of sALS and studies showing associations with environmental exposures, understanding the mechanisms and identifying early biomarkers is vital for developing preventative therapies and early interventions. Limitations include variability in exposure assessment and the complexity of gene-environment interactions. Studies focusing on longitudinal exposure assessments, mechanistic studies, and biomarker identification to inform preventative and therapeutic strategies for ALS is warranted.

Welding fumes are a Group 1 (carcinogenic to humans) carcinogen as classified by the International Agency for Research on Cancer. The process of welding creates inhalable fumes rich in iron (Fe) that may also contain known carcinogenic metals such as chromium (Cr) and nickel (Ni). Epidemiological evidence has shown that both mild-steel (Fe-rich) and stainless steel (Fe-rich + Cr + Ni) welding fume exposure increase lung cancer risk, and experimental animal data support these findings. Copper-nickel (CuNi) welding processes have not been investigated in the context of lung cancer. Cu is intriguing, however, given the role of Cu in carcinogenesis and cancer therapeutics. This study examines the potential for a CuNi fume to induce mechanistic key characteristics of carcinogenesis in vitro and to promote lung tumorigenesis, using a two-stage mouse bioassay, in vivo. Male A/J mice, initiated with 3-methylcholanthrene (MCA; 10 µg/g), were exposed to CuNi fumes or air by whole-body inhalation for nine weeks (low-deposition-LD and high deposition-HD) then sacrificed at 30 weeks. In BEAS-2B cells, the CuNi fume induced micronuclei and caused DNA damage as measured by γ-H2AX. The fume exhibited high reactivity and a dose response in cytotoxicity and oxidative stress. In vivo, MCA/CuNi HD and LD significantly decreased lung tumor size and adenomas. MCA/CuNi HD exposure significantly decreased gross-evaluated tumor number. In summary, the CuNi fume in vitro exhibited characteristics of a carcinogen, but in vivo the exposure resulted in smaller tumors, fewer adenomas, less hyperplasia severity, and with the HD exposure, less overall lung lesion/tumors.

OBJECTIVE: Early childhood behavioral and emotional disorders are linked to diagnosable mental health problems both later in childhood and into adulthood. However, little work has examined the association between family social stressors and emotional well-being among children under two years of age, including whether differences exist between infancy and toddlerhood. METHODS: Data come from the nationally representative 2019-2022 National Health Interview Survey, an annual, cross-sectional survey conducted by the National Center for Health Statistics. Separate multivariate logistic regression models estimated associations between family social stressors (stressful life events, family food insecurity, family difficulty paying medical bills) and having a Baby Pediatric Symptom Checklist (BPSC) subscale score of 3 or more ("above the BPSC cutoff") for poorer emotional well-being among children 2-23 months. Models were additionally stratified by age group (infants, 2-11 months; toddlers, 12-23 months), and adjusted for child and family sociodemographic and geographical characteristics. RESULTS: Children who had experienced a stressful life event (AOR=3.83, 95% CI: 2.48-5.92), family food insecurity (AOR=1.69, 95% CI: 1.13-2.51), or family difficulty paying medical bills (AOR=2.10, 95% CI: 1.54-2.87) had higher odds of being above the BPSC cutoff, adjusted for all relevant covariates. Toddlers who experienced a stressful life event (66.5% vs. 41.0%) or family difficulty paying medical bills (53.1% vs. 29.8%) had higher odds of being above the BPSC cutoff compared with infants. CONCLUSIONS: Family social stressors were linked to poorer emotional well-being among young children. Future research may benefit from the exploration of additional predictors of emotional well-being among this age group.

A clear understanding of the genetic basis of antibiotic resistance in Mycobacterium tuberculosis is required to accelerate the development of rapid drug susceptibility testing methods based on genetic sequence.Raw genotype-phenotype correlation data were extracted as part of a comprehensive systematic review to develop a standardised analytical approach for interpreting resistance associated mutations for rifampicin, isoniazid, ofloxacin/levofloxacin, moxifloxacin, amikacin, kanamycin, capreomycin, streptomycin, ethionamide/prothionamide and pyrazinamide. Mutation frequencies in resistant and susceptible isolates were calculated, together with novel statistical measures to classify mutations as high, moderate, minimal or indeterminate confidence for predicting resistance.We identified 286 confidence-graded mutations associated with resistance. Compared to phenotypic methods, sensitivity (95% CI) for rifampicin was 90.3% (89.6-90.9%), while for isoniazid it was 78.2% (77.4-79.0%) and their specificities were 96.3% (95.7-96.8%) and 94.4% (93.1-95.5%), respectively. For second-line drugs, sensitivity varied from 67.4% (64.1-70.6%) for capreomycin to 88.2% (85.1-90.9%) for moxifloxacin, with specificity ranging from 90.0% (87.1-92.5%) for moxifloxacin to 99.5% (99.0-99.8%) for amikacin.This study provides a standardised and comprehensive approach for the interpretation of mutations as predictors of M. tuberculosis drug-resistant phenotypes. These data have implications for the clinical interpretation of molecular diagnostics and next-generation sequencing as well as efficient individualised therapy for patients with drug-resistant tuberculosis.

A breathable air source is required for a confined space such as an underground refuge alternative (RA) when it is occupied. To minimize the risk of suffocation, federal regulations require that mechanisms be provided and procedures be included so that, within the refuge alternative, the oxygen concentration is maintained at levels between 18.5% and 23% for 96 h. The regulation also requires that, during use of the RA, the concentration of carbon dioxide should not exceed 1%, and the concentration of carbon monoxide should not exceed 25 ppm. The National Institute for Occupational Safety and Health (NIOSH) evaluated the cryogenic air supply's ability to provide breathable air for a refuge alternative. A propane smoker was used to simulate human breathing by burning propane gas which will consume O(2) and generate CO(2) and H(2)O. The rate of propane burned at the smoker was controlled to represent the O(2) consumption rate for the breathing of a certain number of people. Two 96-h tests were conducted in a sealed shipping container, which was used as a surrogate for a refuge alternative. While burning propane gas to simulate human oxygen consumption, cryogenic air was provided to the shipping container to determine if the cryogenic air supply would keep the O(2) level above 18.5% and CO(2) level below 1% inside the shipping container as required by the federal regulations pertaining to refuge alternatives. Both of the 96-h tests simulated the breathing of 21 persons. The first test used the oxygen consumption rate (1.32 cu ft of pure oxygen per hour per person) specified in federal regulations, while the second test used the oxygen consumption rate specified by (Bernard et al. 2018, "Estimation of Metabolic Heat Input for Refuge Alternative Thermal Testing and Simulation," Min. Eng., 70(8), pp. 50-54) (0.67 cu ft of pure oxygen per hour per person). The test data shows that during both 96-h tests, the oxygen level was maintained within a 21-23% range, and the CO(2) level was maintained below 1% (0.2-0.45%). The information in this paper could be useful when applying a cryogenic air supply as a breathable air source for an underground refuge alternative or other confined space. [DOI: 10.1115/1.4064062].

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident hospitalizations, incident cases, incident deaths, and cumulative deaths due to COVID-19 at national, state, and county levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work. Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below: AIpert-pwllnod: Natural Sciences and Engineering Research Council of Canada; Caltech-CS156: Gary Clinard Innovation Fund; CEID-Walk: University of Georgia; CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook; COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health; Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information & Data Science Pilot Project; Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation; CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation; DDS-NBDS: NSF III-1812699; epiforecasts-ensemble1: Wellcome Trust (210758/Z/18/Z) FDANIHASU: supported by the Intramural Research Program of the NIH/NIDDK; GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowment, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. & Charlene Zalesky, and Claudia & Paul Raines, CDC MInD-Healthcare U01CK000531-Supplement; IHME: This work was supported by the Bill & Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096); Imperial-ensemble1: SB acknowledges funding from the Wellcome Trust (219415); Institute of Business Forecasting: IBF; IowaStateLW-STEM: NSF DMS-1916204, Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics; IUPUI CIS: NSF; JHU_CSSE-DECOM: JHU CSSE: National Science Foundation (NSF) RAPID Real-time Forecasting of COVID-19 risk in the USA. 2021-2022. Award ID: 2108526. National Science Foundation (NSF) RAPID Development of an interactive web-based dashboard to track COVID-19 in real-time. 2020. Award ID: 2028604; JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers for Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, & Infectious Disease Initiative (26798 Seed Grant); JHU_UNC_GAS-StatMechP ol: NIH NIGMS: R01GM140564; JHUAPL-Bucky: US Dept of Health and Human Services; KITmetricslab-select_ensemble: Daniel Wolffram gratefully acknowledges support by the Klaus Tschira Foundation; LANL-GrowthRate: LANL LDRD 20200700ER; MIT-Cassandra: MIT Quest for Intelligence; MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01; CA NU38OT000297 from the Council of State and Territorial Epidemiologists (CSTE); NotreDame-FRED: NSF RAPID DEB 2027718; NotreDame-mobility: NSF RAPID DEB 2027718; PSI-DRAFT: NSF RAPID Grant # 2031536; QJHong-Encounter: NSF DMR-2001411 and DMR-1835939; SDSC_ISG-TrendModel: The development of the dashboard was partly funded by the Fondation Privee des Hopitaux Universitaires de Geneve; UA-EpiCovDA: NSF RAPID Grant # 2028401; UChicagoCHATTOPADHYAY-UnIT: Defense Advanced Research Projects Agency (DARPA) #HR00111890043/P00004 (I. Chattopadhyay, University of Chicago); UCSB-ACTS: NSF RAPID IIS 2029626; UCSD_NEU-DeepGLEAM: Google Faculty Award, W31P4Q-21-C-0014; UMass-MechBayes: NIGMS #R35GM119582, NSF #1749854, NIGMS #R35GM119582; UMich-RidgeTfReg: This project is funded by the University of Michigan Physics Department and the University of Michigan Office of Research; UVA-Ensemble: National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and Virginia Dept of Health Grant VDH-21-501-0141; Wadnwani_AI-BayesOpt: This study is made possible by the generous support of the American People through the United States Agency for International Development (USAID). The work described in this article was implemented under the TRACETB Project, managed by WIAI under the terms of Cooperative Agreement Number 72038620CA00006. The contents of this manuscript are the sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government; WalmartLabsML-LogForecasting: Team acknowledges Walmart to support this study Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesI confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data produced are available online at https://github.com/reichlab/covid19-forecast-hub https://github.com/reichlab/covid19-forecast-hub

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. In 2020, the COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized hundreds of thousands of specific predictions from more than 50 different academic, industry, and independent research groups. This manuscript systematically evaluates 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level. One of these models was a multi-model ensemble that combined all available forecasts each week. The performance of individual models showed high variability across time, geospatial units, and forecast horizons. Half of the models evaluated showed better accuracy than a naïve baseline model. In combining the forecasts from all teams, the ensemble showed the best overall probabilistic accuracy of any model. Forecast accuracy degraded as models made predictions farther into the future, with probabilistic accuracy at a 20-week horizon more than 5 times worse than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work.Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below. CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook. CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation. COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health. Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information& Data Science Pilot Project. Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation. DDS-NBDS: NSF III-1812699. EPIFORECASTS-ENSEMBLE1: Wellcome Trust (210758/Z/18/Z) GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowments, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. & Charlene Zalesky, and Claudia & Paul Raines GT-DeepCOVID: CDC MInD-Healthcare U01CK000531-Supplement. NSF (Expeditions CCF-1918770, CAREER IIS-2028586, RAPID IIS-2027862, Medium IIS-1955883, NRT DGE-1545362), CDC MInD program, ORNL and funds/computing resources from Georgia Tech and GTRI. IHME: This work was supported by the Bill & Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096). IowaStateLW-STEM: Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1916204, NSF CCF-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics. JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, US Office of Foreign Disaster Assistance, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers fo Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, & Infectious Disease Initiative (26798 Seed Grant). LANL-GrowthRate: LANL LDRD 20200700ER. MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01. NotreDame-mobility and NotreDame-FRED: NSF RAPID DEB 2027718 UA-EpiCovDA: NSF RAPID Grant # 2028401. UCSB-ACTS: NSF RAPID IIS 2029626. UCSD-NEU: Google Faculty Award, DARPA W31P4Q-21-C-0014, COVID Supplement CDC-HHS-6U01IP001137-01. UMass-MechBayes: NIGMS R35GM119582, NSF 1749854. UMich-RidgeTfReg: The University of Michigan Physics Department and the University of Michigan Office of Research.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:UMass-Amherst IRBAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data and code referred to in the manuscript are publicly available. https://github.com/reichlab/covid19-forecast-hub/ https://github.com/reichlab/covidEnsembles https://zoltardata.com/project/44

Research gaps exist in toxic metals characterization in e-cigarette, or vaping, products (EVPs) as these analytes typically have low concentrations and most standard aerosol trapping techniques have high metals background. An additional complication arises from differences in the EVP liquid formulations with nicotine products having polar properties and non-nicotine products often being non-polar. Differences in polar and non-polar matrices and the subsequent aerosol chemistries from various EVPs required modifications of our previously reported nicotine-based EVP aerosol method. Validation and application of the expanded method, suitable for both hydrophobic and hydrophilic aerosols, are reported here. The metals analyzed for this study were Al, Cr, Fe, Co, Ni, Cu, Cd, Sn, Ba, and Pb. The method limits of detection for the modified method ranged from 0.120 ng/10 puffs for Cd to 29.3 ng/10 puffs for Al and were higher than reported for the previous method. Results of the analyses for metals in aerosols obtained from 50 EVP products are reported. Cannabinoid based EVP aerosols were below reportable levels, except for one sample with 16.08 ng/10 puffs for Cu. Nicotine-based EVP results ranged from 6.72 ng/10 puffs for Pb to 203 ng/10 puffs for Sn. Results of the analyses for these metals showed that aerosols from only 5 of the 50 devices tested had detectable metal concentrations. Concentrations of toxic elements in the aerosols for nicotine-based EVP aerosol metal concentration ranges were consistent with previously published results of aerosol analyses from this class of devices.

BACKGROUND: Over the course of the COVID-19 pandemic, colleges and universities have focused on creating policies, such as mask mandates, to minimize COVID-19 transmission both on their campuses and in the surrounding community. Adherence to and opinions about these policies remain largely unknown. METHODS: The Centers for Disease Control and Prevention (CDC) developed a cross-sectional study, the Mask Adherence and Surveillance at Colleges and Universities Project (MASCUP!), to objectively and inconspicuously measure rates of mask use at institutes of higher education via direct observation. From February 15 through April 11, 2021 the University of Colorado Boulder (CU, n = 2,808 observations) and Colorado State University Fort Collins (CSU, n = 3,225 observations) participated in MASCUP! along with 52 other institutes of higher education (n = 100,353 observations) spanning 21 states and the District of Columbia. Mask use was mandatory at both Colorado universities and student surveys were administered to assess student beliefs and attitudes. RESULTS: We found that 91.7%, 93.4%, and 90.8% of persons observed at indoor locations on campus wore a mask correctly at University of Colorado, Colorado State University, and across the 52 other schools, respectively. Student responses to questions about masking were in line with these observed rates of mask use where 92.9% of respondents at CU and 89.8% at CSU believe that wearing masks can protect the health of others. Both Colorado universities saw their largest surges in COVID-19 cases in the fall of 2020, with markedly lower case counts during the mask observation window in the spring of 2021. CONCLUSION: High levels of mask use at Colorado's two largest campuses aligned with rates observed at other institutes across the country. These high rates of use, coupled with positive student attitudes about mask use, demonstrate that masks were widely accepted and may have contributed to reduced COVID-19 case counts. This study supports an emerging body of literature substantiating masks as an effective, low-cost measure to reduce disease transmission and establishes masking (with proper education and promotion) as a viable tactic to reduce respiratory disease transmission on college campuses.

Identification of the emerging multidrug-resistant yeast Candida auris is challenging. Here, we describe the role of the Mexico national reference laboratory Instituto de Diagnóstico y Referencia Epidemiológicos Dr. Manuel Martínez Báez (InDRE) and the Mexican national laboratory network in the identification of C. auris. Reference identification of six suspected isolates was done based on phenotypic and molecular laboratory methods, including growth in special media, evaluation of isolate micromorphology, and species-specific PCR and pan-fungal PCR and sequencing. The four C. auris isolates identified were able to grow on modified Sabouraud agar with 10% NaCl incubated at 42 °C. With one exception, isolates of C. auris were spherical to ovoid yeast-like cells and blastoconidia, with no hyphae or pseudohyphae on cornmeal agar. C. auris isolates were resistant to fluconazole. Species-specific and pan-fungal PCR confirmed isolates as C. auris. Sequence analysis revealed the presence of two different C. auris clades in Mexico, clade I (South Asia) and clade IV (South America).

Objective: Stainless steel welding creates fumes rich in carcinogenic metals such as chromium (Cr). Welding consumables devoid of Cr are being produced in an attempt to limit worker exposures to toxic and carcinogenic metals. The study objective was to characterize a copper-nickel (Cu-Ni) fume generated using gas metal arc welding (GMAW) and determine the pulmonary deposition and toxicity of the fume in mice exposed by inhalation. Materials and Methods: Male A/J mice (6-8 weeks of age) were exposed to air or Cu-Ni welding fumes for 2 (low deposition) or 4 (high deposition) hours/day for 10 days. Mice were sacrificed, and bronchoalveolar lavage (BAL), macrophage function, and histopathological analyses were performed at different timepoints post-exposure to evaluate resolution. Results and Discussion: Characterization of the fume indicated that most of the particles were between 0.1 and 1 µm in diameter, with a mass median aerodynamic diameter of 0.43 µm. Metal content of the fume was Cu (∼76%) and Ni (∼12%). Post-exposure, BAL macrophages had a reduced ability to phagocytose E. coli, and lung cytotoxicity was evident and significant (>12%-19% fold change). Loss of body weight was also significant at the early timepoints. Lung inflammation, the predominant finding identified by histopathology, was observed as a subacute response early that progressively resolved by 28 days with only macrophage aggregates remaining late (84 days). Conclusions: Overall, there was high acute lung toxicity with a resolution of the response in mice which suggests that the Cu-Ni fume may not be ideal for reducing toxic and inflammatory lung effects.

Copper-based preservatives consisting of micronized and nanoscale copper particles have been widely used in applications for wood protection. The widespread use of these preservatives along with the potential release of copper-containing nanoparticles (Cu NPs) during the life cycle of treated wood, has raised concerns over the impacts on the environment and occupational exposure. Along with assessing the potential hazards of these materials, a critical step is determining the chemical and morphological characteristics of the copper species released from copper-treated wood. Therefore, a combination of scanning transmission electron microscopy (STEM) and electron energy-loss spectroscopy (EELS) was utilized to characterize and differentiate the released copper-containing particles based on their structures, sizing, and chemical properties. Airborne wood dust samples were collected during the abrasion and sawing of micronized copper (MC) treated wood in a laboratory testing system. Based on the signature Cu L(2,3) edge of EEL spectra, three different copper species (i.e., basic copper carbonate, copper, and copper-wood complex) were identified as major components of the embedded particles in wood dust. In addition, two types of individual Cu NPs consisting of basic copper carbonate and copper were identified. The variation of morphologies and chemical properties of copper-containing particles indicates the importance of copper-wood interactions to determine the formation and distribution of copper species in wood components. Our findings will advance the fundamental understanding of their released forms, potential transformation, and environmental fate during the life cycle.

Background: Molecular diagnostics are considered the most promising route to achievement of rapid, universal drug susceptibility testing for Mycobacterium tuberculosis complex (MTBC). We aimed to generate a WHO-endorsed catalogue of mutations to serve as a global standard for interpreting molecular information for drug resistance prediction. Methods: In this systematic analysis, we used a candidate gene approach to identify mutations associated with resistance or consistent with susceptibility for 13 WHO-endorsed antituberculosis drugs. We collected existing worldwide MTBC whole-genome sequencing data and phenotypic data from academic groups and consortia, reference laboratories, public health organisations, and published literature. We categorised phenotypes as follows: methods and critical concentrations currently endorsed by WHO (category 1); critical concentrations previously endorsed by WHO for those methods (category 2); methods or critical concentrations not currently endorsed by WHO (category 3). For each mutation, we used a contingency table of binary phenotypes and presence or absence of the mutation to compute positive predictive value, and we used Fisher's exact tests to generate odds ratios and Benjamini-Hochberg corrected p values. Mutations were graded as associated with resistance if present in at least five isolates, if the odds ratio was more than 1 with a statistically significant corrected p value, and if the lower bound of the 95% CI on the positive predictive value for phenotypic resistance was greater than 25%. A series of expert rules were applied for final confidence grading of each mutation. Findings: We analysed 41 137 MTBC isolates with phenotypic and whole-genome sequencing data from 45 countries. 38 215 MTBC isolates passed quality control steps and were included in the final analysis. 15 667 associations were computed for 13 211 unique mutations linked to one or more drugs. 1149 (73%) of 15 667 mutations were classified as associated with phenotypic resistance and 107 (07%) were deemed consistent with susceptibility. For rifampicin, isoniazid, ethambutol, fluoroquinolones, and streptomycin, the mutations' pooled sensitivity was more than 80%. Specificity was over 95% for all drugs except ethionamide (914%), moxifloxacin (916%) and ethambutol (933%). Only two resistance mutations were identified for bedaquiline, delamanid, clofazimine, and linezolid as prevalence of phenotypic resistance was low for these drugs. Interpretation: We present the first WHO-endorsed catalogue of molecular targets for MTBC drug susceptibility testing, which is intended to provide a global standard for resistance interpretation. The existence of this catalogue should encourage the implementation of molecular diagnostics by national tuberculosis programmes. Funding: Unitaid, Wellcome Trust, UK Medical Research Council, and Bill and Melinda Gates Foundation. 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

Co-infections with sexually transmittable pathogens are common and more likely in women with disturbed vaginal bacteriome. Among those pathogens, the protozoan parasite Trichomonas vaginalis (TV) is most common after accounting for the highly persistent DNA viruses human papillomavirus (HPV) and genital herpes. The parasitic infection often concurs with the dysbiotic syndrome diagnosed as bacterial vaginosis (BV) and both are associated with risks of superimposed viral infections. Yet, the mechanisms of microbial synergisms in evading host immunity remain elusive. We present clinical and experimental evidence for a new role of galectins, glycan-sensing family of proteins, in mixed infections. We assessed participants of the HIV Epidemiology Research Study (HERS) at each of their incident TV visits (223 case visits) matched to controls who remained TV-negative throughout the study. Matching criteria included age, race, BV (by Nugent score), HIV status, hysterectomy, and contraceptive use. Non-matched variables included BV status at 6 months before the matched visit, and variables examined at baseline, within 6 months of and/or at the matched visit e.g. HSV-2, HPV, and relevant laboratory and socio-demographic parameters. Conditional logistic regression models using generalized estimating equations calculated odds ratios (OR) for incident TV occurrence with each log(10) unit higher cervicovaginal concentration of galectins and cytokines. Incident TV was associated with higher levels of galectin-1, galectin-9, IL-1β and chemokines (ORs 1.53 to 2.91, p <0.001). Galectin-9, IL-1β and chemokines were up and galectin-3 down in TV cases with BV or intermediate Nugent versus normal Nugent scores (p <0.001). Galectin-9, IL-1β and chemokines were up in TV-HIV and down in TV-HPV co-infections. In-vitro, TV synergized with its endosymbiont Trichomonasvirus (TVV) and BV bacteria to upregulate galectin-1, galectin-9, and inflammatory cytokines. The BV-bacterium Prevotella bivia alone and together with TV downregulated galectin-3 and synergistically upregulated galectin-1, galectin-9 and IL-1β, mirroring the clinical findings of mixed TV-BV infections. P. bivia also downregulated TVV+TV-induced anti-viral response e.g. IP-10 and RANTES, providing a mechanism for conducing viral persistence in TV-BV co-infections. Collectively, the experimental and clinical data suggest that galectin-mediated immunity may be dysregulated and exploited by viral-protozoan-bacterial synergisms exacerbating inflammatory complications from dysbiosis and sexually transmitted infections.

This study investigated the effects of particle transfer to the covers of aerosol samplers during transportation of wood dust and welding fume samples. Wood dust samples were collected in a sanding chamber using four sampler types: closed-face cassettes (CFC), CFC with Accu-CAP inserts, disposable inhalable samplers (DIS), and Institute of Occupational Medicine (IOM). Welding fumes were collected in a walk-in chamber using the same samplers, with Solu-Sert replacing Accu-CAP. The samples were divided into two groups, with one group transported by air and the other by land. They were returned in the same manner and analyzed gravimetrically for wood dust and chemically for welding fumes. For wood dust, IOM showed a significantly higher percentage of particles transferred to the covers compared with the other samplers regardless of the transportation mode (p < 0.0001; 64% by air and 15% by land), while other samplers showed less than or close to 10% (3.5-12%). When the percentages of particle transfer to the covers were compared between the air and land transportation, both IOM and CFC samples showed differences between modes of transportation, while others did not. For welding fumes, most samples (61% of samples for copper [Cu] and 76% of samples for manganese [Mn]) showed nondetectable amounts of the analyte on the covers. For all samplers, the particle transfer to the covers for both transportation modes ranged from 0.2-33% for Cu and less than 4.5% for Mn. Overall, this study confirms that particle transfer to sampler covers during transport highly depends upon the transportation mode and sampler type for wood dust, whereas particle transfer seems minimal for welding fumes. The findings of this study are based on two materials and limited sample sizes. Further investigation considering different industry types and tasks, particle size ranges, and materials might be necessary. Nevertheless, occupational professionals should account for this transfer when handling and analyzing samples in practice.

High quality, accurate data on liquid contents and aerosol emissions from electronic nicotine delivery systems (ENDS, e.g. e-cigarettes) are crucial to address potential health concerns as these devices evolve and mature. Metals are an important class of ENDS constituents that merit attention as they have various health implications. Proper sampling, handling, and aerosol trapping materials are essential to generate accurate quantitative metals data and to reduce the likelihood of inaccurate results originating from inappropriate collection vessels and materials that contribute to high background levels. Published methods that meet these criteria were applied to the analyses of chromium, nickel, copper, zinc, cadmium, tin, and lead in liquid and aerosol from mint/menthol and tobacco flavors of currently popular pod-based devices from 3 manufacturers. Metal concentrations from pods that had not been used for generating aerosol ranged from below our lowest reportable level to 0.164 µg/g for Cr, 61.3 µg/g for Ni, 927 µg/g for Cu, 14.9 µg/g for Zn, 58.2 µg/g for Sn, and 2.56 µg/g for Pb. Cadmium was included in our analyte panel and was not present above detection limits in liquid or aerosol. Aerosol metal concentrations (using a 55 mL puff) ranged from below our lowest reportable level to 29.9 ng/10 puffs for Cr, 373 ng/10 puffs for Ni, 209 ng/10 puffs for Cu, 4,580 ng/10 puffs for Zn, 127 ng/10 puffs for Sn, and 463 ng/10 puffs for Pb. Our results showed some metals delivery from all the products examined and highly variable metal levels between manufacturer, brand, and package.

OBJECTIVE: To update a 2016 systematic review on hormonal contraception use and HIV acquisition. METHODS: We searched Pubmed and Embase between 15 January 2016 and 26 June 2019 for longitudinal studies comparing incident HIV infection among women using a hormonal contraceptive method and either non-users or users of another specific hormonal contraceptive method. We extracted information from newly identified studies, assessed study quality, and updated forest plots and meta-analyses. RESULTS: In addition to 31 previously included studies, five more were identified; three provided higher quality evidence. A randomised clinical trial (RCT) found no statistically significant differences in HIV risk among users of intramuscular depot medroxyprogesterone acetate (DMPA-IM), levonorgestrel implant (LNG implant) or the copper intrauterine device (Cu-IUD). An observational study found no statistically significant differences in HIV risk among women using DMPA, norethisterone enanthate (NET-EN), implants (type not specified) or Cu-IUD. Updated results from a previously included observational study continued to find a statistically significant increased HIV risk with oral contraceptives and DMPA compared with no contraceptive use, and found no association between LNG implant and HIV risk. CONCLUSIONS: High-quality RCT data comparing use of DMPA, LNG implant and Cu-IUD does not support previous concerns from observational studies that DMPA-IM use increases the risk of HIV acquisition. Use of other hormonal contraceptive methods (oral contraceptives, NET-EN and implants) is not associated with an increased risk of HIV acquisition.

OBJECTIVES: To review systematically copper intrauterine device (Cu-IUD) use and HIV acquisition in women. METHODS: We searched Pubmed, Embase and the Cochrane Library between database inception and 26 June 2019 for longitudinal studies comparing incident HIV infection among women using an unspecified IUD or Cu-IUD compared with non-hormonal or no contraceptive users, or hormonal contraceptive users. We extracted information from included studies, assessed study quality, and summarised study findings. RESULTS: From 2494 publications identified, seven met our inclusion criteria. One randomised controlled trial (RCT), judged "informative with few limitations", found no statistically significant differences in HIV risk between users of the Cu-IUD and either intramuscular depot medroxyprogesterone acetate (DMPA-IM) or levonorgestrel implant. One observational study, deemed "informative but with important limitations", found no statistically significant difference in HIV incidence among IUD users compared with women who had tubal ligation or who were not using any contraception. Another "informative but with important limitations" observational study found no difference in HIV incidence between Cu-IUD users and DMPA or norethisterone enanthate injectable, or implant users. An RCT considered "unlikely to inform the primary question" also found no difference in HIV risk between Cu-IUD and progestogen-only injectable users. Findings from the other three "unlikely to inform the primary question" cohort studies were consistent with the more robust studies suggesting no increased risk of HIV acquisition among Cu-IUD users. CONCLUSION: The collective evidence, including that from a large high-quality RCT, does not indicate an increased risk of HIV acquisition among users of Cu-IUDs.

As the technology of electronic nicotine delivery systems (ENDS), including e-cigarettes, evolves, assessing metal concentrations in liquids among brands over time becomes challenging. A method for quantification of chromium, nickel, copper, zinc, cadmium, tin, and lead in ENDS liquids using triple quadrupole inductively coupled plasma mass spectrometry was developed. The method's limits of detection (LODs) were 0.031, 0.032, 3.15, 1.27, 0.108, 0.099, 0.066 microg/g for Cr, Ni, Cu, Zn, Cd, Sn, and Pb respectively. Liquids analyzed were from different brands and flavors of refill bottles or single-use, rechargeable, and pod devices from different years. Scanning electron microscopy with energy dispersive spectroscopy further evaluated the device components' compositions. Refill liquids before contacting a device were below lowest reportable levels (LRL) for all metals. Copper and zinc were elevated in liquids from devices containing brass. Cadmium was <LRL in all liquids and was not observed in device components. Cr, Ni, Cu, Zn, Sn, and Pb, reported in microg/g, ranged from <LRL to 0.396, 4.04, 903, 454, 0.898, and 13.5 respectively. Elevated metal concentrations in the liquid were also elevated in aerosol from the corresponding device. The data demonstrates the impact of device design and materials on toxic metals in ENDS liquid.

Attention-deficit/hyperactivity disorder (ADHD) is 1 of the most common neurobehavioral disorders of childhood and can profoundly affect children's academic achievement, well-being, and social interactions. The American Academy of Pediatrics first published clinical recommendations for evaluation and diagnosis of pediatric ADHD in 2000; recommendations for treatment followed in 2001. The guidelines were revised in 2011 and published with an accompanying process of care algorithm (PoCA) providing discrete and manageable steps by which clinicians could fulfill the clinical guideline's recommendations. Since the release of the 2011 guideline, the Diagnostic and Statistical Manual of Mental Disorders has been revised to the fifth edition, and new ADHD-related research has been published. These publications do not support dramatic changes to the previous recommendations. Therefore, only incremental updates have been made in this guideline revision, including the addition of a key action statement related to diagnosis and treatment of comorbid conditions in children and adolescents with ADHD. The accompanying process of care algorithm has also been updated to assist in implementing the guideline recommendations. Throughout the process of revising the guideline and algorithm, numerous systemic barriers were identified that restrict and/or hamper pediatric clinicians' ability to adopt their recommendations. Therefore, the subcommittee created a companion article (available in the Supplemental Information) on systemic barriers to the care of children and adolescents with ADHD, which identifies the major systemic-level barriers and presents recommendations to address those barriers; in this article, we support the recommendations of the clinical practice guideline and accompanying process of care algorithm.

Refuge alternatives provide shelter to miners trapped underground during a disaster. Manufacturers must demonstrate that their refuge alternatives meet the U.S. Mine Safety and Health Administration (MSHA) requirements for oxygen supply, carbon dioxide removal, and management of heat from the occupants and mechanical/chemical systems. In this study, miner size and activity level were used to determine the metabolic heat rate, oxygen requirements and carbon dioxide generation that are representative of miners in a refuge situation. A convenience sample of 198 male miners was used for the distribution of current U.S. coal miners, and the composite 95th percentile height and weight were determined to be 193 cm (76 in.) and 133 kg (293 lb). The resting metabolic rate (RMR) was determined to be representative of activity level in a refuge alternative. The highest likely metabolic heat generation ranged from 113 to 134 W, depending on occupancy. The highest required oxygen supply and carbon dioxide removal were estimated to be 23 L (0.81 cu ft) of oxygen per hour per person and 20 L (0.71 cu ft) of carbon dioxide per hour per person, which means the margin of safety is 50 percent or more compared with the MSHA requirements. The information on metabolic heat generation can be used to assess refuge alternative thermal environments by testing or simulation. The required oxygen supply and carbon dioxide removal can be used to assess refuge alternative requirements.

To explore the health effects of multi-heavy metal exposure, Sprague Dawley (SD) rats were orally given one dose of heavy metal mixtures (HMMs). The eight most common detectable heavy metals in Ningbo area are zinc (Zn), copper (Cu), manganese (Mn), chromium (Cr), nickel (Ni), cadmium (Cd), lead (Pb) and mercury (Hg). In this study, mixtures of these eight heavy metals were prepared using the compounds zinc sulfate heptahydrate, cupric sulfate, manganese dichloride, potassium dichromate, nickel dichloride, cadmium dichloride, lead acetate, and methyl mercury chloride with ion mass proportions of 1070.0, 312.6, 173.1, 82.6, 30.0, 13.3, 6.6, and 1.0, respectively. The rats were randomly divided into four groups. Beside the control group, each rat received a corresponding dose of HMMs 215, 464 or 1000 mg per kg body weight (bwt), respectively. The rats were observed for 4 weeks. During the last week of observation, the Morris water maze test was used to investigate spatial learning and memory in the treated rats. The rats were exsanguinated under complete chloral hydrate anesthesia and organ coefficients were measured. Biochemical tests of blood and serum samples were carried out. The results showed abnormalities in the hematological system, decreased renal function, hepatic injury and disturbances in the electrolyte balance of the rats treated with a high dose of HMMs. Death of some rats was also observed. This paper analyzed how a one-time high dose oral administration of HMMs induced systemic toxicity. © 2018 The Royal Society of Chemistry.

A multivariate calibration approach, using partial least squares regression, has been developed for the measurement of aerosol elemental concentration. A training set consisting of 25 orthogonal aerosol samples with 9 factors (elements: Cr, Mn, Fe, Ni, Cu, Zn, Cd, Pb, and Ti) and 5 levels (elemental concentrations) was designed. Spectral information was obtained for each aerosol sample using aerosol spark emission spectroscopy (ASES) at a time resolution of 1 minute. Simultaneously, filter samples were collected for the determination of elemental concentration using an inductively coupled plasma mass spectrometry (ICP-MS) analysis. Two regression models, PLS1 and PLS2, were developed to predict mass concentration from spectral measurements. The prediction ability of the models improved substantially when only signature wavelengths were included instead of the entire spectrum. The PLS1 model with 45 selected spectral variables (PLS1-45 model) presented the lowest relative root mean square error of cross validation (RMSECV; 16-35%). The detection limits using the PLS1-45 model for the nine elements were in the range of 0.16-0.50 μg m-3. The performance of both multivariate and univariate regression models was tested for an unknown sample of welding fume aerosol. The multivariate model did not provide significantly better prediction compared to the univariate model. In spite of the difference in the matrices of the calibration aerosol and the unknown test aerosol, the results from the PLS model show good agreement with those from filter measurements. The relative root mean square error of prediction (RMSEP) obtained from the PLS1-45 model was 13% for Cr, 23% for Fe, 22% for Mn and 12% for Ni. The study shows that in spite of lower spectral resolution and lack of sample preparation, reliable and robust measurements can be obtained using the proposed calibration method based on PLS regression.

Background: Nonavalent (9v) human papilloma virus vaccine targets high-risk (HR)-HPV types 16, 18, 31, 33, 45, 52, 58, and low-risk 6, 11. We examined prevalence, incidence, and clearance of anal and cervical HR-HPV in HIV-infected women. Methods: From 2004-2006, the SUN Study enrolled 167 women from four US cities. Anal and cervical specimens were collected annually for cytology and identification of 37 HPV types; 14 HR include: 9v 16, 18, 31, 33, 45, 52, 58; non-9v 35, 39, 51, 56, 59, 66, 68. Results: Baseline characteristics of 126 women included: median age 38 years; 57% non-Hispanic black; 67% HIV RNA < 400 copies/mL; 90% CD4 counts >/= 200 cells/mm3. HPV prevalence at anus and cervix was 90% and 83%; for 9v HR-HPV types, 67% and 51%; non-9v HR-HPV, 54% and 29%, respectively. 9v and non-9v HR-HPV incidence rates/100 person-years were similar (10.4 vs 9.5: 8.5 vs 8.3, respectively); 9v clearance rates were 42% and 61%; non-9v 46% and 59%, in anus and cervix, respectively. Conclusions: Anal HR-HPV prevalence was higher than cervical with lower clearance; incidence was similar. Although prevalence of non-9v HR-HPV was substantial, 9v HR-HPV types were generally more prevalent. These findings support use of nonavalent vaccine in HIV-infected women.

The systemic toxicity of different combinations of heavy metal mixtures (HMMs) was studied according to equivalent proportions of the eight most common detectable heavy metals found in fish consumption in the Ningbo area of China. The ion mass proportions of Zn, Cu, Mn, Cr, Ni, Cd, Pb, and Hg were 1070.0, 312.6, 173.1, 82.6, 30.0, 13.3, 6.6, and 1.0, respectively. In this study, 10 experimental groups were set as follows: M8 (Pb + Cd + Hg + Ni + Cu + Zn + Mn + Cr); M5 (Pb + Cd + Hg + Ni + Cr); M4A (Pb + Cd + Hg + Ni); M4B (Cu + Zn + Mn + Cr); M3 (Cu + Zn + Mn); Cr; Cu; Zn; Mn; and control. Sprague Dawley (SD) rats were orally treated with a single dose of each group every three days (10 times in total) for 34 days. After Morris water maze test, blood and tissue samples were collected to obtain biochemical, histopathological and western blot analysis. Results show abnormalities could be observed in different treatment groups, the M4B combination had the most significant change compared to all other groups. In conclusion, combination HMMs may have adverse effects on the hematologic, hepatic, renal and neurobehavioral function, and may also disturb electrolyte and lipid balance. Why M4B combination generated much higher toxic effects than any other combination mixtures or individual heavy metal needs to be further evaluated.

OBJECTIVE: Our study measured the change in head injuries and deaths among motorcycle users in Cu Chi district, a suburban district of Ho Chi Minh City. METHODS: Hospital records for road traffic injuries (RTI) were collected from the Cu Chi Trauma Centre and motorcycle-related death records were obtained from mortality registries in commune health offices. Head injury severity was categorised using the Abbreviated Injury Score (AIS). Rate ratios (RR) were used to compare rates pre- and post-law (2005/06-2009/10). Cu Chi's population, stratified by year, age, and sex was used as the denominator. RESULTS: Of records identifying the transportation mode at the time of injury, motorcyclists accounted for most injuries (3,035, 87%) and deaths (238, 90%). Head injuries accounted for 70% of motorcycle-related hospitalisations. Helmet use was not recorded in any death records and not in 97% of medical records. Males accounted for most injuries (73%) and deaths (88%). The median age was 28 years and 32 years for injuries and deaths, respectively. Compared to the pre-law period, rates of motorcycle injuries (RR 0.53; 95% CI 0.49-0.58), head injuries (RR 0.35; 95% CI 0.31-0.39), severe head injuries (RR 0.47; 95% CI 0.34-0.63) and deaths (RR 0.69; 95% CI 0.53-0.89) significantly decreased in the post-law period. CONCLUSIONS: Rates of head injuries and deaths among motorcycle riders decreased significantly after implementation of the mandatory helmet law in Vietnam. To further examine the impact of the motorcycle helmet law, including compliance and helmet quality, further emphasis should be placed on gathering helmet use data from injured motorcyclists.

BACKGROUND: Whether providers who regularly provide family planning services consider contraceptive methods as unsafe for women with obesity is unknown. METHODS: We analyzed questionnaire responses received from December 2009 to March 2010 from 635 office-based physicians and 1323 Title X clinic providers delivering family planning services, who were randomly sampled (response rate 65%) before the release of national evidence-based contraception guidelines. We examined provider and clinical setting characteristics and clinic patient demographics for association with provider misconceptions about safety of combined oral contraceptives (COCs), depot medroxyprogesterone acetate (DMPA), or intrauterine devices (IUDs) for women with obesity. If providers considered methods as unsafe or do not know, we categorized those responses as misconceptions. We used multivariable logistic regression to estimate adjusted odds ratios (aORs) and 95% confidence intervals (CIs). RESULTS: A substantial proportion of respondents had misconceptions about the safety of COCs (31%), DMPA (24%), copper (Cu) (18%), and levonorgestrel (LNG)-IUDs (16%) for women with obesity. Provider type was associated with increased odds of misconceptions for all four methods compared with office-based obstetrician/gynecologists. Not having the method available onsite was associated with safety misconceptions of DMPA (aOR 1.90, 95% CI 1.07-3.36), Cu-IUD (aOR 4.19, 95% CI 1.51-11.61), and LNG-IUD (aOR 5.25, 95% CI 1.67-16.49). CONCLUSION: While the majority of providers considered all four contraceptive methods safe for women with obesity, substantial proportions had misconceptions about safety of COCs, DMPA, and IUDs. Provider education, particularly among certain specialties, is needed to increase knowledge regarding moderate and highly effective contraceptive methods among this patient population.

OBJECTIVE: To determine the association between use of intrauterine devices (IUDs) by young women and risk of adverse outcomes. METHODS: We searched Pubmed, CINAHL, Embase, Popline and the Cochrane Library for articles from inception of database through December 2015. For outcomes specific to IUD use (IUD expulsion and perforation), we examined effect measures for IUD users generally aged 25 years or younger compared with older IUD users. For outcomes of pregnancy, infection, pelvic inflammatory disease (PID), and heavy bleeding or anemia, we examined young IUD users compared with young users of other contraceptive methods or no method. RESULTS: We identified 3169 articles of which 16 articles from 14 studies met our inclusion criteria. Six studies (Level II-2, good to poor) reported increased risk of expulsion among younger age groups compared with older age groups using Cu-IUDs. Two studies (Level II-2, fair) examined risks of expulsion among younger compared with older women using LNG-IUDs; one reported no difference in expulsion, while the other reported increased odds for younger women. Four studies (Level II-2, good to poor) examined risk of expulsion among Cu- and LNG-IUD users combined and reported no significant differences between younger and older women. For perforation, four studies (Level II-2, fair to poor) found very low perforation rates (range 0-0.1%), with no significant differences between younger and older women. Pregnancies were generally rare among young IUD users in nine studies (Level I to II-2, fair to poor) and no differences were reported for young IUD users compared with young combined oral contraceptive (COC) or etonogestrel (ENG) implant users. PID was rare among young IUD users; one study reported no cases among COC or IUD users and one reported no difference in PID among LNG-IUD users compared with ENG implant users from nationwide insurance claims data (Level I to II-2, fair). One study reported decreased odds of bleeding with LNG-IUD compared with COC use among young women, while one study of young women reported decreased odds of removal for bleeding with LNG-IUD compared with ENG implant (Level I to II-2, fair). CONCLUSION: Overall evidence suggests that the risk of adverse outcomes related to pregnancy, perforation, infection, heavy bleeding or removals for bleeding among young IUD users is low and may not be clinically meaningful. However, the risk of expulsion, especially for Cu-IUDs is higher for younger women compared with older women. If IUD expulsion occurs, a young woman is exposed to an increased risk of unintended pregnancy if replacement contraception is not initiated. IUDs are safe for young women and provide highly effective reversible contraception.

Information that details use and supply of respirators in acute care hospitals is vital to prevent disease transmission, assure the safety of health care personnel, and inform national guidelines and regulations. OBJECTIVE: To develop measures of respirator use and supply in the acute care hospital setting to aid evaluation of respirator programs, allow benchmarking among hospitals, and serve as a foundation for national surveillance to enhance effective Personal Protective Equipment (PPE) use and management. METHODS: We identified existing regulations and guidelines that govern respirator use and supply at Vanderbilt University Medical Center (VUMC). Related routine and emergency hospital practices were documented through an investigation of hospital administrative policies, protocols, and programs. Respirator dependent practices were categorized based on hospital workflow: Prevention (preparation), patient care (response), and infection surveillance (outcomes). Associated data in information systems were extracted and their quality evaluated. Finally, measures representing major factors and components of respirator use and supply were developed. RESULTS: Various directives affecting multiple stakeholders govern respirator use and supply in hospitals. Forty-seven primary and secondary measures representing factors of respirator use and supply in the acute care hospital setting were derived from existing information systems associated with the implementation of these directives. CONCLUSION: Adequate PPE supply and effective use that limit disease transmission and protect health care personnel are dependent on multiple factors associated with routine and emergency hospital practices. We developed forty-seven measures that may serve as the basis for a national PPE surveillance system, beginning with standardized measures of respirator use and supply for collection across different hospital types, sizes, and locations to inform hospitals, government agencies, manufacturers, and distributors. Despite involvement of multiple hospital stakeholders, regulatory guidance prescribes workplace practices that are likely to result in similar workflows across hospitals. Future work will explore the feasibility of implementing the collection and reporting of standardized measures in multiple facilities.

OBJECTIVES: To investigate levonorgestrel (LNG)-releasing and copper-bearing (Cu) intrauterine device (IUD) safety among breastfeeding women and, for Cu-IUD use, breastfeeding performance and infant health. STUDY DESIGN: Systematic review METHODS: We searched PubMed, Embase, Cochrane Library and clinicaltrials.gov for articles through January 2016. We included studies of Cu-IUD or LNG-IUD users comparing IUD-specific (perforation, expulsion) and other contraceptive-related (infection, removal/cessation due to bleeding/pain, and other adverse events) outcomes for breastfeeding versus non-breastfeeding women. We also included studies of breastfeeding women comparing contraceptive-related outcome for IUD-users versus other contraceptive-method users. Finally, we included studies comparing breastfeeding outcomes among Cu-IUD users to users of other non-hormonal contraceptives or no contraception. RESULTS: Of 548 articles identified, 23 (16 studies) met inclusion criteria. Two studies suggested the risk of IUD perforation was 6-10 times higher among breastfeeding versus non-breastfeeding women. Seven studies suggested risks for other adverse events were similar or lower among breastfeeding versus non-breastfeeding women. Three studies among breastfeeding women found no increased risk of adverse events in IUD users versus non-users. Breastfeeding performance and infant growth were similar for Cu-IUD users and users of other non-hormonal methods or no contraception. CONCLUSION: Overall, risks for adverse events among IUD users, including expulsion, pain and removals were similar or lower for breastfeeding women versus non-breastfeeding women. Uterine perforation with IUDs, while rare, appeared more frequent among breastfeeding women. No evidence indicated Cu-IUD use in breastfeeding women influences breastfeeding performance or infant growth.