293 research outputs found

    Phosphorylation on PstP controls cell wall metabolism and antibiotic tolerance in Mycobacterium smegmatis [preprint]

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    The mycobacterial cell wall is a dynamic structure that protects Mycobacterium tuberculosis and its relatives from environmental stresses. Modulation of cell wall metabolism under stress is thought to be responsible for decreased cell wall permeability and increased tolerance to antibiotics. The signaling pathways that control cell wall metabolism under stress, however, are poorly understood. Here, we examine the signaling capacity of a cell wall master regulator, the Serine Threonine Phosphatase PstP, in the model organism Mycobacterium smegmatis. We studied how interference with a regulatory phosphorylation site on PstP affects growth, cell wall metabolism and antibiotic tolerance. We find that a phospho-mimetic mutation, pstP T171E, slows growth, misregulates both mycolic acid and peptidoglycan metabolism in different conditions, and interferes with antibiotic tolerance. These data suggest that phosphorylation on PstP controls its substrate specificity and is important in the transition between growth and stasis

    Acceptance of Behavior Guidance Techniques Used in Pediatric Dentistry by Parents From Diverse Backgrounds

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    Objective. To investigate if parental background affects acceptance of behavior guidance techniques. Background. Behavior guidance techniques are used for the safe and effective treatment of pediatric patients. Acceptance of these techniques may vary by racial and ethnic background. Methods. A total of 142 parents were recruited and asked to rate videos showing: active restraint/protective stabilization (AR), general anesthesia (GA), nitrous oxide sedation (N2O), oral premedication/sedation (OP), passive restraint/protective stabilization (PR), tell-show-do (TSD), and voice control (VC) techniques. Results. Hispanic parents rated VC most acceptable, followed by TSD, PR, and pharmacologic techniques. Black and white parents rated TSD, followed by N2O, as most acceptable, and AR and PR as least favorable. Hispanics found GA significantly less acceptable than whites or blacks. Hispanics were less accepting of AR than blacks; but more accepting of PR than whites. TSD was highly rated among all 3 cohorts. Parental background affected acceptance of the techniques in this study

    Evaluation of a Pharmacist Led Oral Chemotherapy Clinic: A Pilot Program in the Gastrointestinal Oncology Clinic at an Academic Medical Center

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    Oral chemotherapy represents a major patient-centric advancement in therapy convenience. However, ownership of safe and correct administration of these agents requires significant patient education. To address this challenge, an in-person pharmacist-led oral chemotherapy education clinic in gastrointestinal oncology patients within an academic medical center was created and assessed. In this pilot program, a medication-specific quiz was administered to patients before and after education performed by a pharmacist to assess patient understanding of their new oral chemotherapy. A five-question satisfaction survey was also administered at the conclusion of the pharmacist clinic visit. Primary outcome was the percentage difference between pre-and post-education quiz scores. Secondary outcomes included patient satisfaction, time to treatment initiation, and number of pharmacist interventions. Frequencies and medians were used to describe categorical and continuous variables, respectively. Of the 18 patients analyzed, 50% were male and median age was 59.5 years. Approximately 28% had colon cancer, and 61% were treated with capecitabine. The median post-education scores improved from a pre-education score of 75% to 100%. Overall, seventeen of the eighteen patients responded with "strongly agree" to all satisfaction survey statements. An in-person oncology pharmacist-led oral chemotherapy education session demonstrated an improvement in patients' understanding of their new oral chemotherapy treatment

    Probing the extragalactic fast transient sky at minute timescales with DECam

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    Searches for optical transients are usually performed with a cadence of days to weeks, optimised for supernova discovery. The optical fast transient sky is still largely unexplored, with only a few surveys to date having placed meaningful constraints on the detection of extragalactic transients evolving at sub-hour timescales. Here, we present the results of deep searches for dim, minute-timescale extragalactic fast transients using the Dark Energy Camera, a core facility of our all-wavelength and all-messenger Deeper, Wider, Faster programme. We used continuous 20s exposures to systematically probe timescales down to 1.17 minutes at magnitude limits g>23g > 23 (AB), detecting hundreds of transient and variable sources. Nine candidates passed our strict criteria on duration and non-stellarity, all of which could be classified as flare stars based on deep multi-band imaging. Searches for fast radio burst and gamma-ray counterparts during simultaneous multi-facility observations yielded no counterparts to the optical transients. Also, no long-term variability was detected with pre-imaging and follow-up observations using the SkyMapper optical telescope. We place upper limits for minute-timescale fast optical transient rates for a range of depths and timescales. Finally, we demonstrate that optical gg-band light curve behaviour alone cannot discriminate between confirmed extragalactic fast transients such as prompt GRB flashes and Galactic stellar flares.Comment: Published in MNRA

    Prevalence and Diversity of Avian Hematozoan Parasites in Asia: A Regional Study

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    Tissue samples from 699 birds from three regions of Asia (Myanmar, India, and South Korea) were screened for evidence of infection by avian parasites in the genera Plasmodium and Haemoproteus. Samples were collected from November 1994 to October 2004. We identified 241 infected birds (34.0%). Base-on-sequence data for the cytochrome b gene from 221 positive samples, 34 distinct lineages of Plasmodium, and 41 of Haemoproteus were detected. Parasite diversity was highest in Myanmar followed by India and South Korea. Parasite prevalence differed among regions but not among host families. There were four lineages of Plasmodium and one of Haemoproteus shared between Myanmar and India and only one lineage of Plasmodium shared between Myanmar and South Korea. No lineages were shared between India and South Korea, although an equal number of distinct lineages were recovered from each region. Migratory birds in South Korea and India originate from two different migratory flyways; therefore cross-transmission of parasite lineages may be less likely. India and Myanmar shared more host species and habitat types compared to South Korea. Comparison between low-elevation habitat in India and Myanmar showed a difference in prevalence of haematozoans

    Pharmacogenomics driven decision support prototype with machine learning: A framework for improving patient care

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    Introduction: A growing number of healthcare providers make complex treatment decisions guided by electronic health record (EHR) software interfaces. Many interfaces integrate multiple sources of data (e.g., labs, pharmacy, diagnoses) successfully, though relatively few have incorporated genetic data. Method: This study utilizes informatics methods with predictive modeling to create and validate algorithms to enable informed pharmacogenomic decision-making at the point of care in near real-time. The proposed framework integrates EHR and genetic data relevant to the patient's current medications including decision support mechanisms based on predictive modeling. We created a prototype with EHR and linked genetic data from the Department of Veterans Affairs (VA), the largest integrated healthcare system in the US. The EHR data included diagnoses, medication fills, and outpatient clinic visits for 2,600 people with HIV and matched uninfected controls linked to prototypic genetic data (variations in single or multiple positions in the DNA sequence). We then mapped the medications that patients were prescribed to medications defined in the drug-gene interaction mapping of the Clinical Pharmacogenomics Implementation Consortium's (CPIC) level A (i.e., sufficient evidence for at least one prescribing action) guidelines that predict adverse events. CPIC is a National Institute of Health funded group of experts who develop evidence based pharmacogenomic guidelines. Preventable adverse events (PAE) can be defined as a harmful outcome from an intervention that could have been prevented. For this study, we focused on potential PAEs resulting from a medication-gene interaction. Results: The final model showed AUC scores of 0.972 with an F1 score of 0.97 with genetic data as compared to 0.766 and 0.73 respectively, without genetic data integration. Discussion: Over 98% of people in the cohort were on at least one medication with CPIC level a guideline in their lifetime. We compared predictive power of machine learning models to detect a PAE between five modeling methods: Random Forest, Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), K Nearest neighbors (KNN), and Decision Tree. We found that XGBoost performed best for the prototype when genetic data was added to the framework and improved prediction of PAE. We compared area under the curve (AUC) between the models in the testing dataset

    Covid-19 Testing, Hospital Admission, and Intensive Care Among 2,026,227 United States Veterans Aged 54-75 Years.

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    IMPORTANCE: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes coronavirus disease 2019 (Covid-19), an evolving pandemic. Limited data are available characterizing SARS-Cov-2 infection in the United States. OBJECTIVE: To determine associations between demographic and clinical factors and testing positive for coronavirus 2019 (Covid-19+), and among Covid-19+ subsequent hospitalization and intensive care. DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort study including all patients tested for Covid-19 between February 8 and March 30, 2020, inclusive. We extracted electronic health record data from the national Veterans Affairs Healthcare System, the largest integrated healthcare system in the United States, on 2,026,227 patients born between 1945 and 1965 and active in care. Exposures: Demographic data, comorbidities, medication history, substance use, vital signs, and laboratory measures. Laboratory tests were analyzed first individually and then grouped into a validated summary measure of physiologic injury (VACS Index). Main Outcomes and Measures: We evaluated which factors were associated with Covid-19+ among all who tested. Among Covid-19+ we identified factors associated with hospitalization or intensive care. We identified independent associations using multivariable and conditional multivariable logistic regression with multiple imputation of missing values. RESULTS: Among Veterans aged 54-75 years, 585/3,789 (15.4%) tested Covid-19+. In adjusted analysis (C-statistic=0.806) black race was associated with Covid-19+ (OR 4.68, 95% CI 3.79-5.78) and the association remained in analyses conditional on site (OR 2.56, 95% CI 1.89-3.46). In adjusted models, laboratory abnormalities (especially fibrosis-4 score [FIB-4] >3.25 OR 8.73, 95% CI 4.11-18.56), and VACS Index (per 5-point increase OR 1.62, 95% CI 1.43-1.84) were strongly associated with hospitalization. Associations were similar for intensive care. Although significant in unadjusted analyses, associations with comorbid conditions and medications were substantially reduced and, in most cases, no longer significant after adjustment. CONCLUSIONS AND RELEVANCE: Black race was strongly associated with Covid-19+, but not with hospitalization or intensive care. Among Covid-19+, risk of hospitalization and intensive care may be better characterized by laboratory measures and vital signs than by comorbid conditions or prior medication exposure

    Patterns of COVID-19 testing and mortality by race and ethnicity among United States veterans: A nationwide cohort study.

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    BACKGROUND: There is growing concern that racial and ethnic minority communities around the world are experiencing a disproportionate burden of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19). We investigated racial and ethnic disparities in patterns of COVID-19 testing (i.e., who received testing and who tested positive) and subsequent mortality in the largest integrated healthcare system in the United States. METHODS AND FINDINGS: This retrospective cohort study included 5,834,543 individuals receiving care in the US Department of Veterans Affairs; most (91%) were men, 74% were non-Hispanic White (White), 19% were non-Hispanic Black (Black), and 7% were Hispanic. We evaluated associations between race/ethnicity and receipt of COVID-19 testing, a positive test result, and 30-day mortality, with multivariable adjustment for a wide range of demographic and clinical characteristics including comorbid conditions, health behaviors, medication history, site of care, and urban versus rural residence. Between February 8 and July 22, 2020, 254,595 individuals were tested for COVID-19, of whom 16,317 tested positive and 1,057 died. Black individuals were more likely to be tested (rate per 1,000 individuals: 60.0, 95% CI 59.6-60.5) than Hispanic (52.7, 95% CI 52.1-53.4) and White individuals (38.6, 95% CI 38.4-38.7). While individuals from minority backgrounds were more likely to test positive (Black versus White: odds ratio [OR] 1.93, 95% CI 1.85-2.01, p < 0.001; Hispanic versus White: OR 1.84, 95% CI 1.74-1.94, p < 0.001), 30-day mortality did not differ by race/ethnicity (Black versus White: OR 0.97, 95% CI 0.80-1.17, p = 0.74; Hispanic versus White: OR 0.99, 95% CI 0.73-1.34, p = 0.94). The disparity between Black and White individuals in testing positive for COVID-19 was stronger in the Midwest (OR 2.66, 95% CI 2.41-2.95, p < 0.001) than the West (OR 1.24, 95% CI 1.11-1.39, p < 0.001). The disparity in testing positive for COVID-19 between Hispanic and White individuals was consistent across region, calendar time, and outbreak pattern. Study limitations include underrepresentation of women and a lack of detailed information on social determinants of health. CONCLUSIONS: In this nationwide study, we found that Black and Hispanic individuals are experiencing an excess burden of SARS-CoV-2 infection not entirely explained by underlying medical conditions or where they live or receive care. There is an urgent need to proactively tailor strategies to contain and prevent further outbreaks in racial and ethnic minority communities

    Utility of Nontraditional Risk Markers in Atherosclerotic Cardiovascular Disease Risk Assessment

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    AbstractBackgroundThe improvement in discrimination gained by adding nontraditional cardiovascular risk markers cited in the 2013 American College of Cardiology/American Heart Association cholesterol guidelines to the atherosclerotic cardiovascular disease (ASCVD) risk estimator (pooled cohort equation [PCE]) is untested.ObjectivesThis study assessed the predictive accuracy and improvement in reclassification gained by the addition of the coronary artery calcium (CAC) score, the ankle–brachial index (ABI), high-sensitivity C-reactive protein (hsCRP) levels, and family history (FH) of ASCVD to the PCE in participants of MESA (Multi-Ethnic Study of Atherosclerosis).MethodsThe PCE was calibrated (cPCE) and used for this analysis. The Cox proportional hazards survival model, Harrell’s C statistics, and net reclassification improvement analyses were used. ASCVD was defined as myocardial infarction, coronary heart disease–related death, or fatal or nonfatal stroke.ResultsOf 6,814 MESA participants not prescribed statins at baseline, 5,185 had complete data and were included in this analysis. Their mean age was 61 years; 53.1% were women, 9.8% had diabetes, and 13.6% were current smokers. After 10 years of follow-up, 320 (6.2%) ASCVD events occurred. CAC score, ABI, and FH were independent predictors of ASCVD events in the multivariable Cox models. CAC score modestly improved the Harrell’s C statistic (0.74 vs. 0.76; p = 0.04); ABI, hsCRP levels, and FH produced no improvement in Harrell’s C statistic when added to the cPCE.ConclusionsCAC score, ABI, and FH were independent predictors of ASCVD events. CAC score modestly improved the discriminative ability of the cPCE compared with other nontraditional risk markers

    Development and validation of a 30-day mortality index based on pre-existing medical administrative data from 13,323 COVID-19 patients: The Veterans Health Administration COVID-19 (VACO) Index.

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    BACKGROUND: Available COVID-19 mortality indices are limited to acute inpatient data. Using nationwide medical administrative data available prior to SARS-CoV-2 infection from the US Veterans Health Administration (VA), we developed the VA COVID-19 (VACO) 30-day mortality index and validated the index in two independent, prospective samples. METHODS AND FINDINGS: We reviewed SARS-CoV-2 testing results within the VA between February 8 and August 18, 2020. The sample was split into a development cohort (test positive between March 2 and April 15, 2020), an early validation cohort (test positive between April 16 and May 18, 2020), and a late validation cohort (test positive between May 19 and July 19, 2020). Our logistic regression model in the development cohort considered demographics (age, sex, race/ethnicity), and pre-existing medical conditions and the Charlson Comorbidity Index (CCI) derived from ICD-10 diagnosis codes. Weights were fixed to create the VACO Index that was then validated by comparing area under receiver operating characteristic curves (AUC) in the early and late validation cohorts and among important validation cohort subgroups defined by sex, race/ethnicity, and geographic region. We also evaluated calibration curves and the range of predictions generated within age categories. 13,323 individuals tested positive for SARS-CoV-2 (median age: 63 years; 91% male; 42% non-Hispanic Black). We observed 480/3,681 (13%) deaths in development, 253/2,151 (12%) deaths in the early validation cohort, and 403/7,491 (5%) deaths in the late validation cohort. Age, multimorbidity described with CCI, and a history of myocardial infarction or peripheral vascular disease were independently associated with mortality-no other individual comorbid diagnosis provided additional information. The VACO Index discriminated mortality in development (AUC = 0.79, 95% CI: 0.77-0.81), and in early (AUC = 0.81 95% CI: 0.78-0.83) and late (AUC = 0.84, 95% CI: 0.78-0.86) validation. The VACO Index allows personalized estimates of 30-day mortality after COVID-19 infection. For example, among those aged 60-64 years, overall mortality was estimated at 9% (95% CI: 6-11%). The Index further discriminated risk in this age stratum from 4% (95% CI: 3-7%) to 21% (95% CI: 12-31%), depending on sex and comorbid disease. CONCLUSION: Prior to infection, demographics and comorbid conditions can discriminate COVID-19 mortality risk overall and within age strata. The VACO Index reproducibly identified individuals at substantial risk of COVID-19 mortality who might consider continuing social distancing, despite relaxed state and local guidelines
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