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Institution

Colorado State University

EducationFort Collins, Colorado, United States
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 & Laser. The organization has 31430 authors who have published 69040 publications receiving 2724463 citations. The organization is also known as: CSU & Colorado Agricultural College.
Topics: Population, Laser, Radar, Poison control, Soil water


Papers
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Journal ArticleDOI
11 Mar 2020-Nature
TL;DR: Microbial nucleic acids are detected in samples of tissues and blood from more than 10,000 patients with cancer, and machine learning is used to show that these can be used to discriminate between and among different types of cancer, suggesting a new microbiome-based diagnostic approach.
Abstract: Systematic characterization of the cancer microbiome provides the opportunity to develop techniques that exploit non-human, microorganism-derived molecules in the diagnosis of a major human disease. Following recent demonstrations that some types of cancer show substantial microbial contributions1–10, we re-examined whole-genome and whole-transcriptome sequencing studies in The Cancer Genome Atlas11 (TCGA) of 33 types of cancer from treatment-naive patients (a total of 18,116 samples) for microbial reads, and found unique microbial signatures in tissue and blood within and between most major types of cancer. These TCGA blood signatures remained predictive when applied to patients with stage Ia–IIc cancer and cancers lacking any genomic alterations currently measured on two commercial-grade cell-free tumour DNA platforms, despite the use of very stringent decontamination analyses that discarded up to 92.3% of total sequence data. In addition, we could discriminate among samples from healthy, cancer-free individuals (n = 69) and those from patients with multiple types of cancer (prostate, lung, and melanoma; 100 samples in total) solely using plasma-derived, cell-free microbial nucleic acids. This potential microbiome-based oncology diagnostic tool warrants further exploration. Microbial nucleic acids are detected in samples of tissues and blood from more than 10,000 patients with cancer, and machine learning is used to show that these can be used to discriminate between and among different types of cancer, suggesting a new microbiome-based diagnostic approach.

524 citations

Journal ArticleDOI
TL;DR: In this article, the authors identify four key elements required to make this model succeed: existing and planned water projects represent opportunities to conduct ecosystem-scale experiments through controlled river flow manipulations; more cooperative interactions among scientists, managers, and other stakeholders are critical; experimental results must be synthesized across studies to allow broader generalization; and new, innovative funding partnerships are needed to engage scientists and to broadly involve the government, the private sector, and NGOs.
Abstract: Real and apparent conflicts between ecosystem and human needs for fresh water are contributing to the emergence of an alternative model for conducting river science around the world. The core of this new paradigm emphasizes the need to forge new partnerships between scientists and other stakeholders where shared ecological goals and river visions are developed, and the need for new experimental approaches to advance scientific understanding at the scales relevant to whole-river management. We identify four key elements required to make this model succeed: existing and planned water projects represent opportunities to conduct ecosystem-scale experiments through controlled river flow manipulations; more cooperative interactions among scientists, managers, and other stakeholders are critical; experimental results must be synthesized across studies to allow broader generalization; and new, innovative funding partnerships are needed to engage scientists and to broadly involve the government, the private sector, and NGOs.

523 citations

Journal ArticleDOI
TL;DR: In this article, a satellite-based 1° by 1° normalized difference vegetation index (NDVI) data set has been processed to derive land surface parameters for general circulation models of the atmosphere (GCMs).
Abstract: A satellite-based 1° by 1° normalized difference vegetation index (NDVI) data set has been processed to derive land surface parameters for general circulation models of the atmosphere (GCMs). Prior to calculation of the land surface parameters, corrections were applied to the source NDVI data set to account for (i) obvious anomalies in the data time-series, (ii) the effect of variations in solar zenith angle, (iii) data dropouts in cold regions where a temperature threshold procedure designed to screen for clouds also eliminates cold land surface points, and (iv) persistent cloud cover in the tropics. An outline of the procedures for calculating land surface parameters from the corrected NDVI data set is given, and a brief description is provided of source material that was used in addition to the NDVI data. The data sets summarized in this paper should represent improvements over prescriptions currently used in land surface parameterizations in that the spatial and temporal dynamics of key land ...

522 citations

Journal ArticleDOI
TL;DR: In this article, the authors examine the future of citizen science in terms of its research processes, program and participant cultures, and scientific communities, and offer recommendations to help prepare project managers for impending challenges.
Abstract: Citizen science creates a nexus between science and education that, when coupled with emerging technologies, expands the frontiers of ecological research and public engagement. Using representative technologies and other examples, we examine the future of citizen science in terms of its research processes, program and participant cultures, and scientific communities. Future citizen-science projects will likely be influenced by sociocultural issues related to new technologies and will continue to face practical programmatic challenges. We foresee networked, open science and the use of online computer/video gaming as important tools to engage non-traditional audiences, and offer recommendations to help prepare project managers for impending challenges. A more formalized citizen-science enterprise, complete with networked organizations, associations, journals, and cyberinfrastructure, will advance scientific research, including ecology, and further public education.

521 citations

Journal ArticleDOI
TL;DR: Conceptualizing SOM into POM versus MAOM is a feasible, well-supported, and useful framework that will allow scientists to move beyond studies of bulk SOM, but also use a consistent separation scheme across studies.
Abstract: Managing soil organic matter (SOM) stocks to address global change challenges requires well-substantiated knowledge of SOM behavior that can be clearly communicated between scientists, management practitioners, and policy makers. However, SOM is incredibly complex and requires separation into multiple components with contrasting behavior in order to study and predict its dynamics. Numerous diverse SOM separation schemes are currently used, making cross-study comparisons difficult and hindering broad-scale generalizations. Here, we recommend separating SOM into particulate (POM) and mineral-associated (MAOM) forms, two SOM components that are fundamentally different in terms of their formation, persistence, and functioning. We provide evidence of their highly contrasting physical and chemical properties, mean residence times in soil, and responses to land use change, plant litter inputs, warming, CO2 enrichment, and N fertilization. Conceptualizing SOM into POM versus MAOM is a feasible, well-supported, and useful framework that will allow scientists to move beyond studies of bulk SOM, but also use a consistent separation scheme across studies. Ultimately, we propose the POM versus MAOM framework as the best way forward to understand and predict broad-scale SOM dynamics in the context of global change challenges and provide necessary recommendations to managers and policy makers.

521 citations


Authors

Showing all 31766 results

NameH-indexPapersCitations
Mark P. Mattson200980138033
Stephen J. O'Brien153106293025
Ad Bax13848697112
David Price138168793535
Georgios B. Giannakis137132173517
James Mueller134119487738
Christopher B. Field13340888930
Steven W. Running12635576265
Simon Lin12675469084
Jitender P. Dubey124134477275
Gregory P. Asner12361360547
Steven P. DenBaars118136660343
Peter Molnar11844653480
William R. Jacobs11849048638
C. Patrignani1171754110008
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023159
2022500
20213,596
20203,492
20193,340
20183,136