Low-cost sensing strategies hold the promise of denser air quality monitoring networks, which could significantly improve our understanding of personal air pollution exposure. Additionally, low-cost ...air quality sensors could be deployed to areas where limited monitoring exists. However, low-cost sensors are frequently sensitive to environmental conditions and pollutant cross-sensitivities, which have historically been poorly addressed by laboratory calibrations, limiting their utility for monitoring. In this study, we investigated different calibration models for the Real-time Affordable Multi-Pollutant (RAMP) sensor package, which measures CO, NO2, O3, and CO2. We explored three methods: (1) laboratory univariate linear regression, (2) empirical multiple linear regression, and (3) machine-learning-based calibration models using random forests (RF). Calibration models were developed for 16–19 RAMP monitors (varied by pollutant) using training and testing windows spanning August 2016 through February 2017 in Pittsburgh, PA, US. The random forest models matched (CO) or significantly outperformed (NO2, CO2, O3) the other calibration models, and their accuracy and precision were robust over time for testing windows of up to 16 weeks. Following calibration, average mean absolute error on the testing data set from the random forest models was 38 ppb for CO (14 % relative error), 10 ppm for CO2 (2 % relative error), 3.5 ppb for NO2 (29 % relative error), and 3.4 ppb for O3 (15 % relative error), and Pearson r versus the reference monitors exceeded 0.8 for most units. Model performance is explored in detail, including a quantification of model variable importance, accuracy across different concentration ranges, and performance in a range of monitoring contexts including the National Ambient Air Quality Standards (NAAQS) and the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. A key strength of the RF approach is that it accounts for pollutant cross-sensitivities. This highlights the importance of developing multipollutant sensor packages (as opposed to single-pollutant monitors); we determined this is especially critical for NO2 and CO2. The evaluation reveals that only the RF-calibrated sensors meet the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. We also demonstrate that the RF-model-calibrated sensors could detect differences in NO2 concentrations between a near-road site and a suburban site less than 1.5 km away. From this study, we conclude that combining RF models with carefully controlled state-of-the-art multipollutant sensor packages as in the RAMP monitors appears to be a very promising approach to address the poor performance that has plagued low-cost air quality sensors.
Short-term studies indicate that bempedoic acid, an ATP citrate lyase inhibitor, reduces LDL cholesterol levels. In a 1-year trial, bempedoic acid added to maximally tolerated statin therapy did not ...lead to a higher incidence of adverse events than placebo and led to significantly lower LDL cholesterol levels.
Plastic waste is a distinctive indicator of the world-wide impact of anthropogenic activities. Both macro- and micro-plastics are found in the ocean, but as yet little is known about their ultimate ...fate and their impact on marine ecosystems. In this study we present the first evidence that microplastics are already becoming integrated into deep-water organisms. By examining organisms that live on the deep-sea floor we show that plastic microfibres are ingested and internalised by members of at least three major phyla with different feeding mechanisms. These results demonstrate that, despite its remote location, the deep sea and its fragile habitats are already being exposed to human waste to the extent that diverse organisms are ingesting microplastics.
Emissions from mobile sources are important contributors to both
primary and secondary organic aerosols (POA and SOA) in urban environments.
We compiled recently published data to create ...comprehensive model-ready
organic emission profiles for on- and off-road gasoline, gas-turbine, and
diesel engines. The profiles span the entire volatility range, including
volatile organic compounds (VOCs, effective saturation concentration
C*=107–1011 µg m−3),
intermediate-volatile organic compounds (IVOCs,
C*=103–106 µg m−3), semi-volatile organic compounds
(SVOCs, C*=1–102 µg m−3), low-volatile organic
compounds (LVOCs, C*≤0.1 µg m−3) and non-volatile
organic compounds (NVOCs). Although our profiles are comprehensive, this
paper focuses on the IVOC and SVOC fractions to improve predictions of SOA
formation. Organic emissions from all three source categories feature
tri-modal volatility distributions (“by-product” mode, “fuel” mode, and
“lubricant oil” mode). Despite wide variations in emission factors for
total organics, the mass fractions of IVOCs and SVOCs are relatively
consistent across sources using the same fuel type, for example, contributing
4.5 % (2.4 %–9.6 % as 10th to 90th percentiles) and
1.1 % (0.4 %–3.6 %) for a diverse fleet of light duty gasoline
vehicles tested over the cold-start unified cycle, respectively. This
consistency indicates that a limited number of profiles are needed to
construct emissions inventories. We define five distinct profiles:
(i) cold-start and off-road gasoline, (ii) hot-operation gasoline,
(iii) gas-turbine, (iv) traditional diesel and (v) diesel-particulate-filter
equipped diesel. These profiles are designed to be directly implemented into
chemical transport models and inventories. We compare emissions to unburned
fuel; gasoline and gas-turbine emissions are enriched in IVOCs relative to
unburned fuel. The new profiles predict that IVOCs and SVOC vapour will
contribute significantly to SOA production. We compare our new profiles to
traditional source profiles and various scaling approaches used previously to
estimate IVOC emissions. These comparisons reveal large errors in these
different approaches, ranging from failure to account for IVOC emissions
(traditional source profiles) to assuming source-invariant scaling ratios
(most IVOC scaling approaches).
Covering: up to 2021
Metagenomics has yielded massive amounts of sequencing data offering a glimpse into the biosynthetic potential of the uncultivated microbial majority. While genome-resolved ...information about microbial communities from nearly every environment on earth is now available, the ability to accurately predict biocatalytic functions directly from sequencing data remains challenging. Compared to primary metabolic pathways, enzymes involved in secondary metabolism often catalyze specialized reactions with diverse substrates, making these pathways rich resources for the discovery of new enzymology. To date, functional insights gained from studies on environmental DNA (eDNA) have largely relied on PCR- or activity-based screening of eDNA fragments cloned in fosmid or cosmid libraries. As an alternative, shotgun metagenomics holds underexplored potential for the discovery of new enzymes directly from eDNA by avoiding common biases introduced through PCR- or activity-guided functional metagenomics workflows. However, inferring new enzyme functions directly from eDNA is similar to searching for a 'needle in a haystack' without direct links between genotype and phenotype. The goal of this review is to provide a roadmap to navigate shotgun metagenomic sequencing data and identify new candidate biosynthetic enzymes. We cover both computational and experimental strategies to mine metagenomes and explore protein sequence space with a spotlight on natural product biosynthesis. Specifically, we compare
in silico
methods for enzyme discovery including phylogenetics, sequence similarity networks, genomic context, 3D structure-based approaches, and machine learning techniques. We also discuss various experimental strategies to test computational predictions including heterologous expression and screening. Finally, we provide an outlook for future directions in the field with an emphasis on meta-omics, single-cell genomics, cell-free expression systems, and sequence-independent methods.
Shotgun metagenomic approaches to uncover new enzymes are underdeveloped relative to PCR- or activity-based functional metagenomics. Here we review computational and experimental strategies to discover biosynthetic enzymes from metagenomes.
Androgen receptor (AR) signaling exerts an antiestrogenic, growth-inhibitory influence in normal breast tissue, and this role may be sustained in estrogen receptor α (ERα)-positive luminal breast ...cancers. Conversely, AR signaling may promote growth of a subset of ERα-negative, AR-positive breast cancers with a molecular apocrine phenotype. Understanding the molecular mechanisms whereby androgens can elicit distinct gene expression programs and opposing proliferative responses in these two breast cancer phenotypes is critical to the development of new therapeutic strategies to target the AR in breast cancer.
Diet modulates the gut microbiome, which in turn can impact the immune system. Here, we determined how two microbiota-targeted dietary interventions, plant-based fiber and fermented foods, influence ...the human microbiome and immune system in healthy adults. Using a 17-week randomized, prospective study (n = 18/arm) combined with -omics measurements of microbiome and host, including extensive immune profiling, we found diet-specific effects. The high-fiber diet increased microbiome-encoded glycan-degrading carbohydrate active enzymes (CAZymes) despite stable microbial community diversity. Although cytokine response score (primary outcome) was unchanged, three distinct immunological trajectories in high-fiber consumers corresponded to baseline microbiota diversity. Alternatively, the high-fermented-food diet steadily increased microbiota diversity and decreased inflammatory markers. The data highlight how coupling dietary interventions to deep and longitudinal immune and microbiome profiling can provide individualized and population-wide insight. Fermented foods may be valuable in countering the decreased microbiome diversity and increased inflammation pervasive in industrialized society.
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•Diet intervention with systems profiling reveals links in diet-microbiome-immune axis•High-fiber diet changes microbiome function and elicits personalized immune responses•Fermented-food diet increases microbiome diversity and decreases markers of inflammation
A prospective randomized multiomics study in humans investigating the longitudinal effects of a high-fiber or fermented-food diet shows their differential effects on the diversity of the microbiome, with the latter having a noticeable impact on reducing inflammatory markers and modulating immune responses.
Initiating your coronation Woods, Letha; Robinson, Jr, Douglas L
American journal of physiology. Heart and circulatory physiology,
03/2024, Letnik:
326, Številka:
3
Journal Article
Recenzirano
Earning an advanced degree in biomedical sciences can be a challenging experience, and recent data indicate high levels of stress and anxiety among the current generation of learners. We propose here ...a new illustration for all graduate students to visualize their didactic journey as a coronation process. Before their coronation, trainees must undergo rigorous preparation. During the training, four key attributes, best described by the acronym COST (Credibility, Opportunity, Strength, and Tenacity), are cultivated. Throughout their academic journey, which is a critical period of intellectual and personal growth, the trainees will enhance their understanding of the responsibility of wearing a CROWN, which requires accepting the Cost of earning a diadem, Revolutionizing their thought construct, being Open to innovation and research, acknowledging that Wealth is intrinsically connected to their health, and Never forsaking their aspiration and pursuits. Executing these principles daily will provide a mechanism on which to rise to the stature of achieving individual career goals (i.e., being a Regent of your life). Actualization of this process requires sacrifice, maturity, and a sense of fearlessness. The results of taking this approach will lead to an educational legacy that establishes a pattern of academic success that can be emulated by future learners.
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