•Comparison of ANOCOVA and remote sensing (RS) approaches for mapping soil salinity.•Cross validation confirmed robustness of ANOCOVA and RS salinity assessment.•RS salinity assessment approach was ...most cost effective for landscape to regional scales.•ANOCOVA approach proved more appropriate for multiple-field to landscape scales.•The study provides guidelines, strengths, and weaknesses for ANOCOVA and RS approaches.
Soil salinity is recognized worldwide as a major threat to agriculture, particularly in arid and semi-arid regions. Producers and decision makers need updated and accurate maps of salinity in agronomically and environmentally relevant ranges (i.e., <20dSm−1, when salinity is measured as electrical conductivity of the saturation extract, ECe). State-of-the-art approaches for creating accurate ECe maps beyond field scale (i.e., 1km2) include: (i) Analysis Of Covariance (ANOCOVA) of near-ground measurements of apparent soil electrical conductivity (ECa) and (ii) regression modeling of multi-year remote sensing canopy reflectance and other co-variates (e.g., crop type, annual rainfall). This study presents a comparison of the two approaches to establish their viability and utility. The approaches were tested using 22 fields (total 542ha) located in California’s western San Joaquin Valley. In 2013 ECa-directed soil sampling resulted in the collection of 267 soil samples across the 22 fields, which were analyzed for ECe, ranging from 0 to 38.6dSm−1. The ANOCOVA ECa-ECe model returned a coefficient of determination (R2) of 0.87 and root mean square prediction error (RMSPE) of 3.05dSm−1. For the remote sensing approach seven years (2007–2013) of Landsat 7 reflectance were considered. The remote sensing salinity model had R2=0.73 and RMSPE=3.63dSm−1. The robustness of the models was tested with a leave-one-field-out (lofo) cross-validation to assure maximum independence between training and validation datasets. For the ANOCOVA model, lofo cross-validation provided a range of scenarios in terms of RMSPE. The worst, median, and best fit scenarios provided global cross-validation R2 of 0.52, 0.80, and 0.81, respectively. The lofo cross-validation for the remote sensing approach returned a R2 of 0.65. The ANOCOVA approach performs particularly well at ECe values <10dSm−1, but requires extensive field work. Field work is reduced considerably with the remote sensing approach, but due to the larger errors at low ECe values, the methodology is less suitable for crop selection, and other practices that require accurate knowledge of salinity variation within a field, making it more useful for assessing trends in salinity across a regional scale. The two models proved to be viable solutions at large spatial scales, with the ANOCOVA approach more appropriate for multiple-field to landscape scales (1–10km2) and the remote sensing approach best for landscape to regional scales (>10km2).
Due in large measure to the prodigious research efforts of Rhoades and his colleagues at the George E. Brown, Jr., Salinity Laboratory over the past two decades, soil electrical conductivity (EC), ...measured using electrical resistivity and electromagnetic induction (EM), is among the most useful and easily obtained spatial properties of soil that influences crop productivity. As a result, soil EC has become one of the most frequently used measurements to characterize field variability for application to precision agriculture. The value of spatial measurements of soil EC to precision agriculture is widely acknowledged, but soil EC is still often misunderstood and misinterpreted. To help clarify misconceptions, a general overview of the application of soil EC to precision agriculture is presented. The following areas are discussed with particular emphasis on spatial EC measurements: a brief history of the measurement of soil salinity with EC, the basic theories and principles of the soil EC measurement and what it actually measures, an overview of the measurement of soil salinity with various EC measurement techniques and equipment (specifically, electrical resistivity with the Wenner array and EM), examples of spatial EC surveys and their interpretation, applications and value of spatial measurements of soil EC to precision agriculture, and current and future developments. Precision agriculture is an outgrowth of technological developments, such as the soil EC measurement, which facilitate a spatial understanding of soil-water-plant relationships. The future of precision agriculture rests on the reliability, reproducibility, and understanding of these technologies.
High-affinity MHC I-peptide interactions are considered essential for immunogenicity. However, some neo-epitopes with low affinity for MHC I have been reported to elicit CD8 T cell dependent tumor ...rejection in immunization-challenge studies. Here we show in a mouse model that a neo-epitope that poorly binds to MHC I is able to enhance the immunogenicity of a tumor in the absence of immunization. Fibrosarcoma cells with a naturally occurring mutation are edited to their wild type counterpart; the mutation is then re-introduced in order to obtain a cell line that is genetically identical to the wild type except for the neo-epitope-encoding mutation. Upon transplantation into syngeneic mice, all three cell lines form tumors that are infiltrated with activated T cells. However, lymphocytes from the two tumors that harbor the mutation show significantly stronger transcriptional signatures of cytotoxicity and TCR engagement, and induce greater breadth of TCR reactivity than those of the wild type tumors. Structural modeling of the neo-epitope peptide/MHC I pairs suggests increased hydrophobicity of the neo-epitope surface, consistent with higher TCR reactivity. These results confirm the in vivo immunogenicity of low affinity or 'non-binding' epitopes that do not follow the canonical concept of MHC I-peptide recognition.
Purpose: To describe and evaluate behavioral models of binge-type eating.
Data identification: Studies were identified using Medline and hand searches of bibliographies of identified articles.
Study ...selection: Isomorphic studies were selected that were judged to have some measure of construct validity.
Data extraction: Face and construct validity were assessed, as well as simplicity and cost of use.
Results of data synthesis: Several different models of binge-type eating exist, each with different strengths of validity and use. These include models using sham feeding, restriction/refeeding cycles and/or stress, limited access (LA) to optional foods, and eating induced by operant schedules of behavior.
Conclusions: We concur with Harry Harlow, who was quoted by Gerry Smith as saying: “You'd be crazy to use animal models, but you'd also be crazy not to use them.”
Intraoperative stopcock contamination is a frequent event associated with increased patient mortality. In the current study we examined the relative contributions of anesthesia provider hands, the ...patient, and the patient environment to stopcock contamination. Our secondary aims were to identify risk factors for stopcock contamination and to examine the prior association of stopcock contamination with 30-day postoperative infection and mortality. Additional microbiological analyses were completed to determine the prevalence of bacterial pathogens within intraoperative bacterial reservoirs. Pulsed-field gel electrophoresis was used to assess the contribution of reservoir bacterial pathogens to 30-day postoperative infections.
In a multicenter study, stopcock transmission events were observed in 274 operating rooms, with the first and second cases of the day in each operating room studied in series to identify within- and between-case transmission events. Reservoir bacterial cultures were obtained and compared with stopcock set isolates to determine the origin of stopcock contamination. Between-case transmission was defined by the isolation of 1 or more bacterial isolates from the stopcock set of a subsequent case (case 2) that were identical to reservoir isolates from the preceding case (case 1). Within-case transmission was defined by the isolation of 1 or more bacterial isolates from a stopcock set that were identical to bacterial reservoirs from the same case. Bacterial pathogens within these reservoirs were identified, and their potential contribution to postoperative infections was evaluated. All patients were followed for 30 days postoperatively for the development of infection and all-cause mortality.
Stopcock contamination was detected in 23% (126 out of 548) of cases with 14 between-case and 30 within-case transmission events confirmed. All 3 reservoirs contributed to between-case (64% environment, 14% patient, and 21% provider) and within-case (47% environment, 23% patient, and 30% provider) stopcock transmission. The environment was a more likely source of stopcock contamination than provider hands (relative risk RR 1.91, confidence interval CI 1.09 to 3.35, P = 0.029) or patients (RR 2.56, CI 1.34 to 4.89, P = 0.002). Hospital site (odds ratio OR 5.09, CI 2.02 to 12.86, P = 0.001) and case 2 (OR 6.82, CI 4.03 to 11.5, P < 0.001) were significant predictors of stopcock contamination. Stopcock contamination was associated with increased mortality (OR 58.5, CI 2.32 to 1477, P = 0.014). Intraoperative bacterial contamination of patients and provider hands was linked to 30-day postoperative infections.
Bacterial contamination of patients, provider hands, and the environment contributes to stopcock transmission events, but the surrounding patient environment is the most likely source. Stopcock contamination is associated with increased patient mortality. Patient and provider bacterial reservoirs contribute to 30-day postoperative infections. Multimodal programs designed to target each of these reservoirs in parallel should be studied intensely as a comprehensive approach to reducing intraoperative bacterial transmission.
Soil salinization is widely recognized to be a major threat to worldwide agriculture. Despite decades of research in soil mapping, no reliable and up-to-date salinity maps are available for large ...geographical regions, especially for the salinity ranges that are most relevant to agricultural productivity (i.e., salinities less than 20dSm−1, when measured as the electrical conductivity of the soil saturation extract). This paper explores the potentials and limitations of assessing and mapping soil salinity via linear modeling of remote sensing vegetation indices. A case study is presented for western San Joaquin Valley, California, USA using multi-year Landsat 7 ETM+ canopy reflectance and the Canopy Response Salinity Index (CRSI). Highly detailed salinity maps for 22 fields comprising 542ha were used for ground-truthing. Re-gridded to 30×30m, the ground-truth data totaled over 5000pixels with salinity values in the range 0 to 35.2dSm−1. Multi-year maximum values of CRSI were used to model soil salinity. Soil type, meteorological data, and crop type were evaluated as covariates. All considered models were evaluated for their fit to the whole data set as well as their performance in a leave-one-field-out spatial cross-validation. The best performing model was a function of CRSI, crop type (i.e., cropped or fallow), rainfall, and average minimum temperature, with R2=0.728 when evaluated against all data and R2=0.611 for the cross-validation predictions. Broken out by salinity classes, the mean absolute errors (MAE) for the cross-validation predictions were (all units dSm−1): 2.94 for the 0–2 interval (non-saline), 2.12 for 2–4 (slightly saline), 2.35 for 4–8 (moderately saline), 3.23 for 8–16 (strongly saline), and 5.64 for >16 (extremely saline). On a per-field basis, the validation predictions had good agreement with the field average (R2=0.79, MAE=2.46dSm−1), minimum (R2=0.76, MAE=2.25dSm−1), and maximum (R2=0.76, MAE=3.09dSm−1) observed salinity. Overall, reasonably accurate and precise high resolution, regional-scale remote sensing of soil salinity is possible, even over the critical range of 0 to 20dSm−1, where researchers and policy makers must focus to prevent loss of agricultural productivity and ecosystem health.
Regional scale soil salinity assessment can successfully be carried out using multi-year Landsat ETM+ canopy reflectance and information on crop cover and meteorological settings. Display omitted
•Multi-year maxima of Landsat ETM+ vegetation indices correlates with soil salinity.•Linear regressions provide reliable salinity estimates at the regional scale.•Crop and meteorological covariates increase accuracy of soil salinity predictions.•Salinity assessment models are validated through a spatial cross-validation.
The ability to inventory and map soil salinity at regional scales remains a significant challenge to scientists concerned with the salinization of agricultural soils throughout the world. Previous ...attempts to use satellite or aerial imagery to assess soil salinity have found limited success in part because of the inability of methods to isolate the effects of soil salinity on vegetative growth from other factors. This study evaluated the use of Moderate Resolution Imaging Spectroradiometer (MODIS) imagery in conjunction with directed soil sampling to assess and map soil salinity at a regional scale (i.e., 10–10⁵ km2) in a parsimonious manner. Correlations with three soil salinity ground truth datasets differing in scale were made in Kittson County within the Red River Valley (RRV) of North Dakota and Minnesota, an area where soil salinity assessment is a top priority for the Natural Resource Conservation Service (NRCS). Multi-year MODIS imagery was used to mitigate the influence of temporally dynamic factors such as weather, pests, disease, and management influences. The average of the MODIS enhanced vegetation index (EVI) for a 7-yr period exhibited a strong relationship with soil salinity in all three datasets, and outperformed the normalized difference vegetation index (NDVI). One-third to one-half of the spatial variability in soil salinity could be captured by measuring average MODIS EVI and whether the land qualified for the Conservation Reserve Program (a USDA program that sets aside marginally productive land based on conservation principles). The approach has the practical simplicity to allow broad application in areas where limited resources are available for salinity assessment.
Water scarcity and increased frequency of drought conditions, resulting from erratic weather attributable to climatic change or alterations in historical weather patterns, have caused greater ...scrutiny of irrigated agriculture's demand on water resources. The traditional guidelines for the calculation of the crop-specific leaching requirement (LR) of irrigated soils have fallen under the microscope of scrutiny and criticism because the commonly used traditional method is believed to erroneously estimate LR due to its assumption of steady-state flow and disregard for processes such as salt precipitation and preferential flow. An over-estimation of the LR would result in the application of excessive amounts of irrigation water and increased salt loads in drainage systems, which can detrimentally impact the environment and reduce water supplies. The objectives of this study are (i) to evaluate the appropriateness of the traditional steady-state method for estimating LR in comparison to the transient method and (ii) to discuss the implications these findings could have on irrigation guidelines and recommendations, particularly with respect to California's Imperial Valley. Steady-state models for calculating LR including the traditional model, which is an extension of the original U.S. Salinity Laboratory LR model, WATSUIT model, and water-production-function model were compared to transient models including TETrans and UNSATCHEM. The calculated LR was lower when determined using a transient approach than when using a steady-state approach. Transient conditions and the influence of preferential flow did not have as significant an effect on lowering the LR as salt precipitation for a representative study of the Imperial Valley using Colorado River water (EC
=
1.23
dS/m) for irrigation. A valley-wide LR of 0.08 for a crop rotation of alfalfa/alfalfa/alfalfa/alfalfa/wheat/lettuce, as calculated by both WATSUIT and UNSATCHEM, was concluded to be the most reasonable estimate for the entire Imperial Valley as compared to a LR of 0.13 by the commonly used traditional method. The reduced LR for the Imperial Valley would result in a diminished drainage volume of approximately 1.23
×
10
8
m
3 (i.e., 100,000
ac-ft). The most significant conclusion derived from the comparison is that the use of the traditional steady-state model for estimating LR needs to be reevaluated.
Intermittent excessive behaviors (IEB) characterize a variety human disorders including binge eating, drug abuse, alcoholism, aberrant sexual conduct, and compulsive gambling. Clinical co-morbidity ...exists among IEB, and limited treatment options are available. The use of behavioral models of bingeing and other feeding protocols is beginning to clarify neural similarities and differences that exist between IEB directed toward obtaining and consuming food and IEB directed toward obtaining and consuming drugs of abuse. Research from this laboratory using a limited access binge-type eating protocol may provide new insight into IEB.
Objective
The objective of this study was to describe oral health literacy (OHL) among periodontal patients and to examine its association with periodontal health status.
Methods
This cross‐sectional ...study included new and referred patients presenting to the University of North Carolina Graduate Periodontology Clinic. Sociodemographic and dental history information were collected. OHL was measured using a dental word recognition instrument, Rapid Estimate of Adult Literacy‐30 (REALD‐30). Clinical periodontal examinations were completed.
Results
One hundred and twenty‐eight participants enrolled and 121 completed all study examinations and instruments. Despite a high level of education among participants in our study, low levels of OHL were found in one‐third (33 percent) of the study population. Thirty‐one percent had moderate OHL (score of 22‐25), 37 percent had high OHL (score ≥ 26). The mean REALD‐30 score was 23. Fifty‐three percent of participants had severe periodontitis, 29 percent had moderate periodontitis, and 18 percent had mild or no periodontitis. Bivariate analysis showed a significant association between OHL and periodontal status (P < 0.05). The effect of OHL on periodontal health status remained statistically significant (P < 0.002) even after controlling for smoking, race, and dental insurance.
Conclusion
Lower OHL was associated with more severe periodontal disease among new and referred patients presenting to the University of North Carolina Graduate Periodontology Clinics.
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