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 & Laser. The organization has 31430 authors who have published 69040 publications receiving 2724463 citations. The organization is also known as: CSU & Colorado Agricultural College.

Community readiness: Research to practice

Abstract: Communities are at many different stages of readiness for implementing programs, and this readiness is to be a major factor in determining whether a local program can be effectively implemented and supported by the community. The Community Readiness Model was developed to meet research needs, (e.g., matching treatment and control communities for an experimental intervention) as well as to provide a practical tool to help communities mobile for change. The model defines nine stages of community readiness ranging from “no awareness” of the problem to “professionalization” in the response to the problem within the community. Assessment of the stage of readiness is accomplished using key informant interviews, with questions on six different dimensions related to a community's readiness to mobilize to address a specific issue. Based on experiences in working directly with communities, strategies for successful effort implementation have been developed for each stage of readiness. Once a community has achieved a stage of readiness where local efforts can be initiated, community teams can be trained in use of the community readiness model. These teams can then develop specific, culturally appropriate efforts that use local resources to guide the community to more advanced levels of readiness, eventually leading to long-term sustainability of local community efforts. This article presents the history of the development of the model, the stages of readiness, dimensions used to assess readiness, how readiness is assessed and strategies for change at each level of readiness. © 2000 John Wiley & Sons, Inc.

Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system

Abstract: The effect of an increase in atmospheric aerosol concentrations on the distribution and radiative properties of Earth’s clouds is the most uncertain component of the overall global radiative forcing from preindustrial time. General circulation models (GCMs) are the tool for predicting future climate, but the treatment of aerosols, clouds, and aerosol−cloud radiative effects carries large uncertainties that directly affect GCM predictions, such as climate sensitivity. Predictions are hampered by the large range of scales of interaction between various components that need to be captured. Observation systems (remote sensing, in situ) are increasingly being used to constrain predictions, but significant challenges exist, to some extent because of the large range of scales and the fact that the various measuring systems tend to address different scales. Fine-scale models represent clouds, aerosols, and aerosol−cloud interactions with high fidelity but do not include interactions with the larger scale and are therefore limited from a climatic point of view. We suggest strategies for improving estimates of aerosol−cloud relationships in climate models, for new remote sensing and in situ measurements, and for quantifying and reducing model uncertainty.

The ACOS CO 2 retrieval algorithm – Part 1: Description and validation against synthetic observations

Abstract: . This work describes the NASA Atmospheric CO2 Observations from Space (ACOS) XCO2 retrieval algorithm, and its performance on highly realistic, simulated observations. These tests, restricted to observations over land, are used to evaluate retrieval errors in the face of realistic clouds and aerosols, polarized non-Lambertian surfaces, imperfect meteorology, and uncorrelated instrument noise. We find that post-retrieval filters are essential to eliminate the poorest retrievals, which arise primarily due to imperfect cloud screening. The remaining retrievals have RMS errors of approximately 1 ppm. Modeled instrument noise, based on the Greenhouse Gases Observing SATellite (GOSAT) in-flight performance, accounts for less than half the total error in these retrievals. A small fraction of unfiltered clouds, particularly thin cirrus, lead to a small positive bias of ~0.3 ppm. Overall, systematic errors due to imperfect characterization of clouds and aerosols dominate the error budget, while errors due to other simplifying assumptions, in particular those related to the prior meteorological fields, appear small.

Discovery of Q203, a potent clinical candidate for the treatment of tuberculosis

Abstract: New therapeutic strategies are needed to combat the tuberculosis pandemic and the spread of multidrug-resistant (MDR) and extensively drug-resistant (XDR) forms of the disease, which remain a serious public health challenge worldwide. The most urgent clinical need is to discover potent agents capable of reducing the duration of MDR and XDR tuberculosis therapy with a success rate comparable to that of current therapies for drug-susceptible tuberculosis. The last decade has seen the discovery of new agent classes for the management of tuberculosis, several of which are currently in clinical trials. However, given the high attrition rate of drug candidates during clinical development and the emergence of drug resistance, the discovery of additional clinical candidates is clearly needed. Here, we report on a promising class of imidazopyridine amide (IPA) compounds that block Mycobacterium tuberculosis growth by targeting the respiratory cytochrome bc1 complex. The optimized IPA compound Q203 inhibited the growth of MDR and XDR M. tuberculosis clinical isolates in culture broth medium in the low nanomolar range and was efficacious in a mouse model of tuberculosis at a dose less than 1 mg per kg body weight, which highlights the potency of this compound. In addition, Q203 displays pharmacokinetic and safety profiles compatible with once-daily dosing. Together, our data indicate that Q203 is a promising new clinical candidate for the treatment of tuberculosis.

Soil biodiversity and carbon cycling: A review and synthesis of studies examining diversity-function relationships

Abstract: Biodiversity and carbon (C) cycling have been the focus of much research in recent decades, partly because both change as a result of anthropogenic activities that are likely to continue. Soils are extremely species-rich and store approximately 80% of global terrestrial C. Soil organisms play a key role in C dynamics and a loss of species through global changes could influence global C dynamics. Here, we synthesize findings from published studies that have manipulated soil species richness and measured the response in terms of ecosystem functions related to C cycling (such as decomposition, respiration and the abundance or biomass of decomposer biota) to evaluate the impact of biodiversity loss on C dynamics. We grouped studies where one or more biotic groups had been manipulated to include a richness of 10 species in order to reflect 'low' and 'high' extents of diversity manipulations. There was a positive relationship between species richness and C cycling in 77-100% of low-diversity experiments, even when the richness of just one biotic group was manipulated, whereas positive relationships occurred less frequently in studies with greater richness (35-64%). Moreover, when positive relationships were observed, these often indicated functional redundancy at low extents of diversity or that community composition had a stronger influence on C cycling than did species richness. Initial reductions in soil species richness resulting from global changes are unlikely to alter C dynamics significantly unless particularly influential species are lost. However, changes in community composition, and the loss of species with an ability to facilitate specialized soil processes related to C cycling, as a result of global changes, may have larger impacts on C dynamics.