The influence of location, source, and emission type in estimates of the human health benefits of reducing a ton of air pollution

The benefit per ton ($/ton) of reducing PM2.5 varies by the location of the emission reduction, the type of source emitting the precursor, and the specific precursor controlled. This paper examines how each of these factors influences the magnitude of the$/ton estimate. We employ a reduced-form air quality model to predict changes in ambient PM2.5 resulting from an array of emission control scenarios affecting 12 different combinations of sources emitting carbonaceous particles, NOx, SOx, NH3, and volatile organic compounds. We perform this modeling for each of nine urban areas and one nationwide area. Upon modeling the air quality change, we then divide the total monetized health benefits by the PM2.5 precursor emission reductions to generate $/ton metrics. The resulting$/ton estimates exhibit the greatest variability across certain precursors and sources such as area source SOx, point source SOx, and mobile source NH3. Certain $/ton estimates, including mobile source NOx, exhibit significant variability across urban areas. Reductions in carbonaceous particles generate the largest$/ton across all locations

Salt-related knowledge, attitudes and behaviors (KABs) among Victorian adults following 22-Months of a consumer awareness campaign

The Australian population consumes more salt than recommended and this increases the risk of raised blood pressure and cardiovascular disease. In 2015, a state-wide initiative was launched in the Australian state of Victoria to reduce population salt intake. This study examines whether salt-related knowledge, attitudes and behaviors (KABs) of Victorian adults changed following the first 22 months of a consumer awareness campaign targeting parents. Repeated cross-sectional surveys of adults (18-65 years) recruited from research panels. Analyses were weighted to reflect the Victorian population. In both surveys mean age of participants (1584 in 2015 and 2141 in 2018) was 41 years, and 51% were female. This includes 554 parents/caregivers in 2015 and 799 in 2018. Most indicators of KAB remained unchanged. Among parents/caregivers the percentage who agreed limiting salt in their child's diet was important increased by 8% (p = 0.001), and there was a 10% reduction in the percentage who reported placing a saltshaker on the table and a 9% reduction in those who reported their child added salt at the table (both p < 0.001). Some small adverse effects on other indicators were also observed. During the first 22 months of a salt reduction consumer awareness campaign, there were limited changes in KAB overall, however the target audience reported positive changes regarding their children, which aligned with the campaign messages

Cardiorenal Biomarkers, Canagliflozin, and Outcomes in Diabetic Kidney Disease: The CREDENCE Trial

BACKGROUND: People with type 2 diabetes and albuminuria are at an elevated risk for cardiac and renal events. The optimal biomarkers to aid disease prediction and to understand the benefits of sodium-glucose cotransporter-2 inhibition remain unclear. METHODS: Among 2627 study participants in the CREDENCE trial (Canagliflozin and Renal Events in Diabetes With Established Nephropathy Clinical Evaluation), concentrations of NT-proBNP (N-terminal pro-B-type natriuretic peptide), high-sensitivity cardiac troponin T, growth differentiation factor-15, and IGFBP7 (insulin-like growth factor binding protein 7) were measured. The effect of canagliflozin on biomarker concentrations was evaluated. The prognostic potential of each biomarker on the primary outcome (a composite of end-stage kidney disease [dialysis, transplantation, or a sustained estimated glomerular filtration rate of <15 mL·min-1·1.73 m-2], doubling of the serum creatinine level, or renal death or cardiovascular death) was assessed. RESULTS: The median (quartiles 1 and 3) concentration of each biomarker was generally elevated: NT-proBNP, 180 ng/L (82, 442 ng/L); high-sensitivity cardiac troponin T, 19 ng/L (12, 29 ng/L); growth differentiation factor-15, 2595 ng/L (1852, 3775 ng/L); and IGFBP7, 121.8 ng/mL (105.4, 141.5 ng/mL). At 1 year, the biomarkers all rose by 6% to 29% in the placebo arm but only by 3% to 10% in the canagliflozin arm (all P<0.01 in multivariable linear mixed-effect models). Baseline concentrations of each biomarker were strongly predictive of cardiac and renal outcomes. When the biomarkers were analyzed together in a multimarker panel, individuals with high risk scores (hazard ratio [HR], 4.01 [95% CI, 2.52-6.35]) and moderate risk scores (HR, 2.39 [95% CI, 1.48-3.87]) showed a higher risk for the primary outcome compared with those with low risk scores. By 1 year, a 50% increase in NT-proBNP (HR, 1.11 [95% CI, 1.08-1.15]), high-sensitivity cardiac troponin T (HR, 1.86 [95% CI, 1.64-2.10]), growth differentiation factor-15 (HR, 1.45 [95% CI, 1.24-1.70]), and IGFBP7 (HR, 3.76 [95% CI, 2.54-5.56]) was associated with risk of the primary outcome. CONCLUSIONS: Multiple cardiorenal stress biomarkers are strongly prognostic in people with type 2 diabetes and albuminuria. Canagliflozin modestly reduced the longitudinal trajectory of rise in each biomarker. Change in the biomarker level in addition to the baseline level augments the primary outcome prediction. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT02065791

Symptoms and signs of lung cancer prior to diagnosis: case-control study using electronic health records from ambulatory care within a large US-based tertiary care centre.

OBJECTIVE: Lung cancer is the most common cause of cancer-related death in the USA. While most patients are diagnosed following symptomatic presentation, no studies have compared symptoms and physical examination signs at or prior to diagnosis from electronic health records (EHRs) in the USA. We aimed to identify symptoms and signs in patients prior to diagnosis in EHR data. DESIGN: Case-control study. SETTING: Ambulatory care clinics at a large tertiary care academic health centre in the USA. PARTICIPANTS, OUTCOMES: We studied 698 primary lung cancer cases in adults diagnosed between 1 January 2012 and 31 December 2019, and 6841 controls matched by age, sex, smoking status and type of clinic. Coded and free-text data from the EHR were extracted from 2 years prior to diagnosis date for cases and index date for controls. Univariate and multivariable conditional logistic regression were used to identify symptoms and signs associated with lung cancer at time of diagnosis, and 1, 3, 6 and 12 months before the diagnosis/index dates. RESULTS: Eleven symptoms and signs recorded during the study period were associated with a significantly higher chance of being a lung cancer case in multivariable analyses. Of these, seven were significantly associated with lung cancer 6 months prior to diagnosis: haemoptysis (OR 3.2, 95% CI 1.9 to 5.3), cough (OR 3.1, 95% CI 2.4 to 4.0), chest crackles or wheeze (OR 3.1, 95% CI 2.3 to 4.1), bone pain (OR 2.7, 95% CI 2.1 to 3.6), back pain (OR 2.5, 95% CI 1.9 to 3.2), weight loss (OR 2.1, 95% CI 1.5 to 2.8) and fatigue (OR 1.6, 95% CI 1.3 to 2.1). CONCLUSIONS: Patients diagnosed with lung cancer appear to have symptoms and signs recorded in the EHR that distinguish them from similar matched patients in ambulatory care, often 6 months or more before diagnosis. These findings suggest opportunities to improve the diagnostic process for lung cancer

Evaluation of a Salt-Reduction Consumer Awareness Campaign Targeted at Parents Residing in the State of Victoria, Australia

From 2015 to 2020 a state-wide salt-reduction initiative was launched in Victoria, Australia, including an awareness campaign focused on parents with children <18 years of age. To evaluate the impact of the campaign on salt-related knowledge, attitudes and behaviors (KABs) we have assessed trends in salt-related KAB pre- and post-delivery of the campaign in parents, as well as within the wider adult population. Cross-sectional surveys of adults aged 18–65 years were undertaken pre- (2015: n = 821 parents; n = 1527 general sample) and post-campaign (2019: n = 935 parents; n = 1747 general sample). KABs were assessed via an online survey. Data were analyzed with regression models and adjusted for covariates. Among parents, around one-quarter of salt-related KABs shifted in a positive direction, but changes were small: there was a 6% (95% CI 2, 11%) increase in the percentage who knew the main source of salt in the diet and reductions in the percentage who reported placing a salt shaker on the table (−8% (95%CI −12, −3)) and that their child added salt at the table (−5% (95% −9, −0.2)). Among the wider adult sample, even fewer shifts in KAB were observed, with some behaviors worsening at follow-up. These findings indicate that this consumer awareness campaign had minimum impact

Robust estimation of microbial diversity in theory and in practice

Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao's estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics ("Hill diversities"), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao's estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.Comment: To be published in The ISME Journal. Main text: 16 pages, 5 figures. Supplement: 16 pages, 4 figure

Risk Model-Based Lung Cancer Screening and Racial and Ethnic Disparities in the US

Importance The revised 2021 US Preventive Services Task Force (USPSTF) guidelines for lung cancer screening have been shown to reduce disparities in screening eligibility and performance between African American and White individuals vs the 2013 guidelines. However, potential disparities across other racial and ethnic groups in the US remain unknown. Risk model–based screening may reduce racial and ethnic disparities and improve screening performance, but neither validation of key risk prediction models nor their screening performance has been examined by race and ethnicity.Objective To validate and recalibrate the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 2012 (PLCOm2012) model—a well-established risk prediction model based on a predominantly White population—across races and ethnicities in the US and evaluate racial and ethnic disparities and screening performance through risk-based screening using PLCOm2012 vs the USPSTF 2021 criteria.Design, Setting, and Participants In a population-based cohort design, the Multiethnic Cohort Study enrolled participants in 1993-1996, followed up through December 31, 2018. Data analysis was conducted from April 1, 2022, to May 19. 2023. A total of 105 261 adults with a smoking history were included.Exposures The 6-year lung cancer risk was calculated through recalibrated PLCOm2012 (ie, PLCOm2012-Update) and screening eligibility based on a 6-year risk threshold greater than or equal to 1.3%, yielding similar eligibility as the USPSTF 2021 guidelines.Outcomes Predictive accuracy, screening eligibility-incidence (E-I) ratio (ie, ratio of the number of eligible to incident cases), and screening performance (sensitivity, specificity, and number needed to screen to detect 1 lung cancer).Results Of 105 261 participants (60 011 [57.0%] men; mean [SD] age, 59.8 [8.7] years), consisting of 19 258 (18.3%) African American, 27 227 (25.9%) Japanese American, 21 383 (20.3%) Latino, 8368 (7.9%) Native Hawaiian/Other Pacific Islander, and 29 025 (27.6%) White individuals, 1464 (1.4%) developed lung cancer within 6 years from enrollment. The PLCOm2012-Update showed good predictive accuracy across races and ethnicities (area under the curve, 0.72-0.82). The USPSTF 2021 criteria yielded a large disparity among African American individuals, whose E-I ratio was 53% lower vs White individuals (E-I ratio: 9.5 vs 20.3; P &lt; .001). Under the risk-based screening (PLCOm2012-Update 6-year risk ≥1.3%), the disparity between African American and White individuals was substantially reduced (E-I ratio: 15.9 vs 18.4; P &lt; .001), with minimal disparities observed in persons of other minoritized groups, including Japanese American, Latino, and Native Hawaiian/Other Pacific Islander. Risk-based screening yielded superior overall and race and ethnicity–specific performance to the USPSTF 2021 criteria, with higher overall sensitivity (67.2% vs 57.7%) and lower number needed to screen (26 vs 30) at similar specificity (76.6%).Conclusions The findings of this cohort study suggest that risk-based lung cancer screening can reduce racial and ethnic disparities and improve screening performance across races and ethnicities vs the USPSTF 2021 criteria

Neurospora from natural populations: Population genomics insights into the Life history of a model microbial Eukaryote

The ascomycete filamentous fungus Neurospora crassa played a historic role in experimental biology and became a model system for genetic research. Stimulated by a systematic effort to collect wild strains initiated by Stanford geneticist David Perkins, the genus Neurospora has also become a basic model for the study of evolutionary processes, speciation, and population biology. In this chapter, we will first trace the history that brought Neurospora into the era of population genomics. We will then cover the major contributions of population genomic investigations using Neurospora to our understanding of microbial biogeography and speciation, and review recent work using population genomics and genome-wide association mapping that illustrates the unique potential of Neurospora as a model for identifying the genetic basis of (potentially adaptive) phenotypes in filamentous fungi. The advent of population genomics has contributed to firmly establish Neurospora as a complete model system and we hope our review will entice biologists to include Neurospora in their research

Haplotype inference in crossbred populations without pedigree information

<p>Abstract</p> <p>Background</p> <p>Current methods for haplotype inference without pedigree information assume random mating populations. In animal and plant breeding, however, mating is often not random. A particular form of nonrandom mating occurs when parental individuals of opposite sex originate from distinct populations. In animal breeding this is called <it>crossbreeding </it>and <it>hybridization </it>in plant breeding. In these situations, association between marker and putative gene alleles might differ between the founding populations and origin of alleles should be accounted for in studies which estimate breeding values with marker data. The sequence of alleles from one parent constitutes one haplotype of an individual. Haplotypes thus reveal allele origin in data of crossbred individuals.</p> <p>Results</p> <p>We introduce a new method for haplotype inference without pedigree that allows nonrandom mating and that can use genotype data of the parental populations and of a crossbred population. The aim of the method is to estimate line origin of alleles. The method has a Bayesian set up with a Dirichlet Process as prior for the haplotypes in the two parental populations. The basic idea is that only a subset of the complete set of possible haplotypes is present in the population.</p> <p>Conclusion</p> <p>Line origin of approximately 95% of the alleles at heterozygous sites was assessed correctly in both simulated and real data. Comparing accuracy of haplotype frequencies inferred with the new algorithm to the accuracy of haplotype frequencies inferred with PHASE, an existing algorithm for haplotype inference, showed that the DP algorithm outperformed PHASE in situations of crossbreeding and that PHASE performed better in situations of random mating.</p