Colorado State University

About: Colorado State University is a education organization based out in Fort Collins, Colorado, United States. It is known for research contribution in the topics: Population & Radar. The organization has 31430 authors who have published 69040 publications receiving 2724463 citations. The organization is also known as: CSU & Colorado Agricultural College.

Applying the Bradford Hill criteria in the 21st century: how data integration has changed causal inference in molecular epidemiology.

Abstract: In 1965, Sir Austin Bradford Hill published nine “viewpoints” to help determine if observed epidemiologic associations are causal. Since then, the “Bradford Hill Criteria” have become the most frequently cited framework for causal inference in epidemiologic studies. However, when Hill published his causal guidelines—just 12 years after the double-helix model for DNA was first suggested and 25 years before the Human Genome Project began—disease causation was understood on a more elementary level than it is today. Advancements in genetics, molecular biology, toxicology, exposure science, and statistics have increased our analytical capabilities for exploring potential cause-and-effect relationships, and have resulted in a greater understanding of the complexity behind human disease onset and progression. These additional tools for causal inference necessitate a re-evaluation of how each Bradford Hill criterion should be interpreted when considering a variety of data types beyond classic epidemiology studies. Herein, we explore the implications of data integration on the interpretation and application of the criteria. Using examples of recently discovered exposure–response associations in human disease, we discuss novel ways by which researchers can apply and interpret the Bradford Hill criteria when considering data gathered using modern molecular techniques, such as epigenetics, biomarkers, mechanistic toxicology, and genotoxicology.

Tree growth and soil acidification in response to 30 years of experimental nitrogen loading on boreal forest

Abstract: Relations among nitrogen load, soil acidification and forest growth have been evaluated based on short-term (o15 years) experiments, or on surveys across gradients of N deposition that may also include variations in edaphic conditions and other pollutants, which confound the interpretation of effects of N per se. We report effects on trees and soils in a uniquely long-term (30 years) experiment with annual N loading on an unpolluted boreal forest. Ammonium nitrate was added to replicated (N 53) 0.09ha plots at two doses, N1 and N2, 34 and 68kgNha � 1 yr � 1 , respectively. A third treatment, N3, 108kgNha � 1 yr � 1 , was terminated after 20 years, allowing assessment of recovery during 10 years. Tree growth initially responded positively to all N treatments, but the longer term response was highly rate dependent with no gain in N3, a gain of 50m 3 ha � 1 stemwood in N2 and a gain of 100m 3 ha � 1 stemwood in excess of the control (N0) in N1. High N treatments caused losses of up to 70% of exchangeable base cations (Ca 2 1 ,M g 2 1 , K 1 ) in the mineral soil, along with decreases in pH and increases in exchangeable Al 3 1 . In contrast, the organic mor-layer (forest floor) in the N-treated plots had similar amounts per hectare of exchangeable base cations as in the N0 treatment. Magnesium was even higher in the mor of N-treated plots, providing evidence of up-lift by the trees from the mineral soil. Tree growth did not correlate with the soil Ca/Al ratio (a suggested predictor of effects of soil acidity on tree growth). A boron deficiency occurred on N-treated plots, but was corrected at an early stage. Extractable NH4 1 and NO3 were high in mor and mineral soils of on-going N treatments, while NH4 1 was elevated in the mor only in N3 plots. Ten years after termination of N addition in the N3 treatment, the pH had increased significantly in the mineral soil; there were also tendencies of higher soil base status and concentrations of base cations in the foliage. Our data suggest the recovery of soil chemical properties, notably pH, may be quicker after removal of the N-load than predicted. Our long-term experiment demonstrated the fundamental importance of the rate of N application relative to the total amount of N applied, in particular with regard to tree growth and C sequestration. Hence, experiments adding high doses of N over short periods do not mimic the long-term effects of N deposition at lower rates.

Toxicology of selenium: A review

Abstract: (1980). Toxicology of selenium: A review. Clinical Toxicology: Vol. 17, No. 2, pp. 171-230.

Metabolomics enables precision medicine: "A White Paper, Community Perspective"

Abstract: Metabolomics is the comprehensive study of the metabolome, the repertoire of biochemicals (or small molecules) present in cells, tissues, and body fluids. The study of metabolism at the global or “-omics” level is a rapidly growing field that has the potential to have a profound impact upon medical practice. At the center of metabolomics, is the concept that a person’s metabolic state provides a close representation of that individual’s overall health status. This metabolic state reflects what has been encoded by the genome, and modified by diet, environmental factors, and the gut microbiome. The metabolic profile provides a quantifiable readout of biochemical state from normal physiology to diverse pathophysiologies in a manner that is often not obvious from gene expression analyses. Today, clinicians capture only a very small part of the information contained in the metabolome, as they routinely measure only a narrow set of blood chemistry analytes to assess health and disease states. Examples include measuring glucose to monitor diabetes, measuring cholesterol and high density lipoprotein/low density lipoprotein ratio to assess cardiovascular health, BUN and creatinine for renal disorders, and measuring a panel of metabolites to diagnose potential inborn errors of metabolism in neonates. We anticipate that the narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature. This signature is expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis. Such future metabolic signatures will: (1) provide predictive, prognostic, diagnostic, and surrogate markers of diverse disease states; (2) inform on underlying molecular mechanisms of diseases; (3) allow for sub-classification of diseases, and stratification of patients based on metabolic pathways impacted; (4) reveal biomarkers for drug response phenotypes, providing an effective means to predict variation in a subject’s response to treatment (pharmacometabolomics); (5) define a metabotype for each specific genotype, offering a functional read-out for genetic variants: (6) provide a means to monitor response and recurrence of diseases, such as cancers: (7) describe the molecular landscape in human performance applications and extreme environments. Importantly, sophisticated metabolomic analytical platforms and informatics tools have recently been developed that make it possible to measure thousands of metabolites in blood, other body fluids, and tissues. Such tools also enable more robust analysis of response to treatment. New insights have been gained about mechanisms of diseases, including neuropsychiatric disorders, cardiovascular disease, cancers, diabetes and a range of pathologies. A series of ground breaking studies supported by National Institute of Health (NIH) through the Pharmacometabolomics Research Network and its partnership with the Pharmacogenomics Research Network illustrate how a patient’s metabotype at baseline, prior to treatment, during treatment, and post-treatment, can inform about treatment outcomes and variations in responsiveness to drugs (e.g., statins, antidepressants, antihypertensives and antiplatelet therapies). These studies along with several others also exemplify how metabolomics data can complement and inform genetic data in defining ethnic, sex, and gender basis for variation in responses to treatment, which illustrates how pharmacometabolomics and pharmacogenomics are complementary and powerful tools for precision medicine. Our metabolomics community believes that inclusion of metabolomics data in precision medicine initiatives is timely and will provide an extremely valuable layer of data that compliments and informs other data obtained by these important initiatives. Our Metabolomics Society, through its “Precision Medicine and Pharmacometabolomics Task Group”, with input from our metabolomics community at large, has developed this White Paper where we discuss the value and approaches for including metabolomics data in large precision medicine initiatives. This White Paper offers recommendations for the selection of state of-the-art metabolomics platforms and approaches that offer the widest biochemical coverage, considers critical sample collection and preservation, as well as standardization of measurements, among other important topics. We anticipate that our metabolomics community will have representation in large precision medicine initiatives to provide input with regard to sample acquisition/preservation, selection of optimal omics technologies, and key issues regarding data collection, interpretation, and dissemination. We strongly recommend the collection and biobanking of samples for precision medicine initiatives that will take into consideration needs for large-scale metabolic phenotyping studies.