scholarly journals In the Eye of the Beholder: The Effect of Rater Variability and Different Rating Scales on QTL Mapping

2011 ◽  
Vol 101 (2) ◽  
pp. 290-298 ◽  
Author(s):  
Jesse A. Poland ◽  
Rebecca J. Nelson
Keyword(s):  
Disease Resistance ◽  
Qtl Mapping ◽  
Disease Severity ◽  
Rating Scales ◽  
Ordinal Scale ◽  
Disease Assessment ◽  
True Value ◽  
Accuracy And Precision ◽  
Rater Variability ◽  
The Impact

The agronomic importance of developing durably resistant cultivars has led to substantial research in the field of quantitative disease resistance (QDR) and, in particular, mapping quantitative trait loci (QTL) for disease resistance. The assessment of QDR is typically conducted by visual estimation of disease severity, which raises concern over the accuracy and precision of visual estimates. Although previous studies have examined the factors affecting the accuracy and precision of visual disease assessment in relation to the true value of disease severity, the impact of this variability on the identification of disease resistance QTL has not been assessed. In this study, the effects of rater variability and rating scales on mapping QTL for northern leaf blight resistance in maize were evaluated in a recombinant inbred line population grown under field conditions. The population of 191 lines was evaluated by 22 different raters using a direct percentage estimate, a 0-to-9 ordinal rating scale, or both. It was found that more experienced raters had higher precision and that using a direct percentage estimation of diseased leaf area produced higher precision than using an ordinal scale. QTL mapping was then conducted using the disease estimates from each rater using stepwise general linear model selection (GLM) and inclusive composite interval mapping (ICIM). For GLM, the same QTL were largely found across raters, though some QTL were only identified by a subset of raters. The magnitudes of estimated allele effects at identified QTL varied drastically, sometimes by as much as threefold. ICIM produced highly consistent results across raters and for the different rating scales in identifying the location of QTL. We conclude that, despite variability between raters, the identification of QTL was largely consistent among raters, particularly when using ICIM. However, care should be taken in estimating QTL allele effects, because this was highly variable and rater dependent.

scholarly journals Proportional odds model applied to mapping of disease resistance genes in plants

2000 ◽  
Vol 23 (1) ◽  
pp. 223-227 ◽  
Author(s):  
Maria Helena Spyrides-Cunha ◽  
Clarice G.B. Demétrio ◽  
Luis E.A. Camargo
Keyword(s):  
Disease Resistance ◽  
Disease Severity ◽  
Resistance Genes ◽  
Proportional Odds Model ◽  
Disease Resistance Genes ◽  
Ordinal Scale ◽  
Proportional Odds ◽  
Response Variable ◽  
Resistance Qtl ◽  
Single Marker

Molecular markers have been used extensively to map quantitative trait loci (QTL) controlling disease resistance in plants. Mapping is usually done by establishing a statistical association between molecular marker genotypes and quantitative variations in disease resistance. However, most statistical approaches require a continuous distribution of the response variable, a requirement not always met since evaluation of disease resistance is often done using visual ratings based on an ordinal scale of disease severity. This paper discusses the application of the proportional odds model to the mapping of disease resistance genes in plants amenable to expression as ordinal data. The model was used to map two resistance QTL of maize to Puccinia sorghi. The microsatellite markers bngl166 and bngl669, located on chromosomes 2 and 8, respectively, were used to genotype F2 individuals from a segregating population. Genotypes at each marker locus were then compared by assessing disease severity in F3 plants derived from the selfing of each genotyped F2 plant based on an ordinal scale severity. The residual deviance and the chi-square score statistic indicated a good fit of the model to the data and the odds had a constant proportionality at each threshold. Single-marker analyses detected significant differences among marker genotypes at both marker loci, indicating that these markers were linked to disease resistance QTL. The inclusion of the interaction term after single-marker analysis provided strong evidence of an epistatic interaction between the two QTL. These results indicate that the proportional odds model can be used as an alternative to traditional methods in cases where the response variable consists of an ordinal scale, thus eliminating the problems of heterocedasticity, non-linearity, and the non-normality of residuals often associated with this type of data.

scholarly journals Accuracy and Precision of Social Relationship Indices

2021 ◽  
Author(s):  
Alexander Mielke ◽  
Liran Samuni
Keyword(s):  
Social Relationships ◽  
Social Relationship ◽  
Social Systems ◽  
Small Sample ◽  
Interaction Type ◽  
True Value ◽  
Accuracy And Precision ◽  
Interaction Types ◽  
Highly Correlated ◽  
The Impact

AbstractCombining interaction rates of different social behaviours into social relationship indices to represent the structure of dyadic relationships on one underlying dimension is common practice in animal sociality studies. However, the properties of these relationship indices are not well explored – mainly because, for real-world social systems, the ‘true’ value of relationships is unobservable. Here, we use simulation studies to estimate the accuracy and precision of three relationship indices: the Dyadic Composite Sociality Index, the Composite Relationship Index, and the Dynamic Dyadic Sociality Index. We simulated one year of social interactions for multiple groups of 25 individuals and 4 interaction types with different properties, and tested the impact of different focal follow regimes, data densities and sampling conditions on the representation of social relationships. Accuracy and precision of social relationship indices were strongly driven by sample size, similar to simple interaction rates. Under the assumption that there was a clear, one-dimensional relationship underlying interactions, and that different interaction types constituting an index were highly correlated, indices indeed increased accuracy over single interaction rates for small sample sizes. Including uninformative constituting behaviours (i.e., those not highly correlated with the underlying relationship dimension) reduced the accuracy of all indices. The precision of each index (i.e., whether multiple simulated focal follow regimes achieve the same dyadic values for the same data) was generally poor and was driven by the precision of the least precise constituting behaviour, making them less precise than some single interaction rates. Our results showed that social relationship indices do not remove the need to have sufficient data for each individual constituting interaction type. Index quality was defined by the least accurate and precise constituting interaction type. Indices might only be useful if all constituting interaction rates are highly correlated and if there are clear indications that one dimension is sufficient to represent social relationships in a group.

scholarly journals Effect of Different Hormones on Disease Resistance against Bacterial Blight in Pomegranate

2021 ◽  
Vol 10 (10) ◽  
pp. 565-571
Author(s):  
Mahesh S. Dashyal M. P. Basavarajappa ◽  
G. Manjunath D. P. Prakash ◽  
Sayeed Wajeed R. Mulla Anita Rajkumar Ghandhe
Keyword(s):  
Salicylic Acid ◽  
Disease Resistance ◽  
Jasmonic Acid ◽  
Disease Severity ◽  
Bacterial Blight ◽  
Economic Losses ◽  
Greenhouse Condition ◽  
Xanthomonas Axonopodis ◽  
Novel Approach ◽  
The Impact

Bacterial blight in pomegranate is a major disease caused by Xanthomonas axonopodis pv. punicae, which has resulted in significant economic losses in terms of both quality and quantity. The ineffectiveness of most chemicals in controlling this disease has shifted grower attention to the quest for a new molecule and hence the use of plant growth regulators and signaling molecules is a novel approach to control the disease as well as improving quality and quantity attributes of pomegranate. Hence, the aim of present study was to determine the impact of plant hormones like ethylene, jasmonic acid and salicylic acid on bacterial blight of pomegranate. Among different hormones applied, ethrel application shown maximum disease severity (33.2%) and salicylic acid shown lowest disease severity (15.08%) under greenhouse condition.

scholarly journals Effects of Quantitative Ordinal Scale Design on the Accuracy of Estimates of Mean Disease Severity

Agronomy ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 565 ◽  
Author(s):  
Hung I. Liu ◽  
Jia Ren Tsai ◽  
Wen Hsin Chung ◽  
Clive H. Bock ◽  
Kuo Szu Chiang
Keyword(s):  
Disease Severity ◽  
Plant Disease ◽  
Mean Squared Error ◽  
Simulation Method ◽  
Ordinal Scale ◽  
Disease Assessment ◽  
The Mean ◽  
Scale Design ◽  
Number Of Classes ◽  
Assessment Scales

Estimates of plant disease severity are crucial to various practical and research-related needs in agriculture. Ordinal scales are used for categorizing severity into ordered classes. Certain characteristics of quantitative ordinal scale design may affect the accuracy of the specimen estimates and, consequently, affect the accuracy of the resulting mean disease severity for the sample. The aim of this study was to compare mean estimates based on various quantitative ordinal scale designs to the nearest percent estimates, and to investigate the effect of the number of classes in an ordinal scale on the accuracy of that mean. A simulation method was employed. The criterion for comparison was the mean squared error of the mean disease severity for each of the different scale designs used. The results indicate that scales with seven or more classes are preferable when actual mean disease severities of 50% or less are involved. Moreover, use of an amended 10% quantitative ordinal scale with additional classes at low severities resulted in a more accurate mean severity compared to most other scale designs at most mean disease severities. To further verify the simulation results, estimates of mean severity of pear scab on samples of leaves from orchards in Taiwan demonstrated similar results. These observations contribute to the development of plant disease assessment scales to improve the accuracy of estimates of mean disease severities.

scholarly journals Understanding the ramifications of quantitative ordinal scales on accuracy of estimates of disease severity and data analysis in plant pathology

2021 ◽  
Author(s):  
Kuo-Szu Chiang ◽  
Clive H. Bock
Keyword(s):  
Plant Pathology ◽  
Disease Severity ◽  
Statistical Power ◽  
Plant Diseases ◽  
Ordinal Scale ◽  
Disease Assessment ◽  
Ordinal Scales ◽  
Scale Design ◽  
Data Design ◽  
Scale Data

AbstractThe severity of plant diseases, traditionally defined as the proportion of the plant tissue exhibiting symptoms, is a key quantitative variable to know for many diseases but is prone to error. Plant pathologists face many situations in which the measurement by nearest percent estimates (NPEs) of disease severity is time-consuming or impractical. Moreover, rater NPEs of disease severity are notoriously variable. Therefore, NPEs of disease may be of questionable value if severity cannot be determined accurately and reliably. In such situations, researchers have often used a quantitative ordinal scale of measurement—often alleging the time saved, and the ease with which the scale can be learned. Because quantitative ordinal disease scales lack the resolution of the 0 to 100% scale, they are inherently less accurate. We contend that scale design and structure have ramifications for the resulting analysis of data from the ordinal scale data. To minimize inaccuracy and ensure that there is equivalent statistical power when using quantitative ordinal scale data, design of the scales can be optimized for use in the discipline of plant pathology. In this review, we focus on the nature of quantitative ordinal scales used in plant disease assessment. Subsequently, their application and effects will be discussed. Finally, we will review how to optimize quantitative ordinal scales design to allow sufficient accuracy of estimation while maximizing power for hypothesis testing.

scholarly journals THU0466 EARLY DIAGNOSIS IS ASSOCIATED WITH LESS DISEASE SEVERITY AND BETTER OUTCOME IN FIBROMYALGIA SYNDROME: A TRICENTRIC PROSPECTIVE ANALYSIS OF A COHORT OF 370 PATIENTS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 470.2-470
Author(s):  
A. Moshrif ◽  
W. Gouda ◽  
M. H. Abu-Zaid
Keyword(s):  
Early Diagnosis ◽  
Disease Severity ◽  
Diagnostic Delay ◽  
Late Diagnosis ◽  
Response To Treatment ◽  
Disease Assessment ◽  
Severity Scale ◽  
Tender Points ◽  
The Mean ◽  
The Impact

Background:Delayed diagnosis of fibromyalgia (FM) has been reported to be associated with more economic burden, healthcare utilization and worse response to treatment1,2. However, its impact on the patients’ symptomatology and disease severity is still underestimated.Objectives:to evaluate the effect of diagnostic delay (DD) on FM severity and disease assessment parameters.Methods:in this cross sectional study, 370 FM patients were prospectively interviewed. Information about DD, widespread pain index (WPI), symptom severity scale (SSS), total severity scale (SSS+WPI) and number of tender points were collected. We proposed to classify our patients into 3 categories; early diagnosis (ED ≤ 2 years; 83 patients), late diagnosis (LD: >2-7 years; 198) and very late diagnosis (VLD >7 years; 89 patients).Results:the mean age of patients was 33.9 (±9.8) and 79.4 % were female. The mean for DD was 5.6 (±3.6) while the means for SSS, total scale and tender points were 7.8 (±1.6), 16.46 (±4.1), 14.31 (±2.3) respectively. A significant correlation has been found for DD with SSS (r = 0.14), total scale (r = 0.37) and tender points (r = 0.16) but not with WPI (r = 0.059).Comparing the three categories, the mean for SSS was 7.54 (±1.6), 7.73 (±1.4) and 8.25 (±1.7) in the groups of ED, LD and VLD respectively (P =0.008) while the mean for the total scale was 15 (±3.8), 15.95 (±3.8) and 18.96 (±4.4) respectively (P = 0.000) and the mean for tender points was 13.7 (±2.3), 14.35 (±2.1) and 14.77 (±2.8) respectively (P = 0.011). The mean for WPI did not significantly differ as it was 7.45 (±2.8), 7.8 (±3.6) and 7.18 (±4.8) in the groups of ED, LD and VLD respectively (P = 0.415).Conclusion:early diagnosis of FM is associated with low SSS, total severity scale and tender points reflecting a better outcome and a less disease severity.References:[1]Hughes G, Martinez C, Myon E, Taïeb C, Wessely S: The impact of a diagnosis of fibromyalgia on health care resource use by primary care patients in the UK: an observational study based on clinical practice.Arthritis Rheum 2006, 54(1):177-83.[2]Choy et al., A patient survey of the impact of fibromyalgia and the journey to diagnosis BMC Health Services Research 2010, 10:102.Disclosure of Interests: :None declared

Childbirth and Posttraumatic Stress Responses

2006 ◽  
Vol 22 (4) ◽  
pp. 259-267 ◽  
Author(s):  
Eelco Olde ◽  
Rolf J. Kleber ◽  
Onno van der Hart ◽  
Victor J.M. Pop
Keyword(s):  
Posttraumatic Stress Disorder ◽  
Posttraumatic Stress ◽  
Stress Responses ◽  
Rating Scales ◽  
Rating Scale ◽  
Stress Disorder ◽  
Traumatic Experience ◽  
Event Scale ◽  
Self Rating ◽  
The Impact

Childbirth has been identified as a possible traumatic experience, leading to traumatic stress responses and even to the development of posttraumatic stress disorder (PTSD). The current study investigated the psychometric properties of the Dutch version of the Impact of Event Scale-Revised (IES-R) in a group of women who recently gave birth (N = 435). In addition, a comparison was made between the original IES and the IES-R. The scale showed high internal consistency (α = 0.88). Using confirmatory factor analysis no support was found for a three-factor structure of an intrusion, an avoidance, and a hyperarousal factor. Goodness of fit was only reasonable, even after fitting one intrusion item on the hyperarousal scale. The IES-R correlated significantly with scores on depression and anxiety self-rating scales, as well as with scores on a self-rating scale of posttraumatic stress disorder. Although the IES-R can be used for studying posttraumatic stress reactions in women who recently gave birth, the original IES proved to be a better instrument compared to the IES-R. It is concluded that adding the hyperarousal scale to the IES-R did not make the scale stronger.

Impact of influenza virus during pregnancy: from disease severity to vaccine efficacy

2020 ◽  
Vol 15 (7) ◽  
pp. 441-453
Author(s):  
Ana Vazquez-Pagan ◽  
Rebekah Honce ◽  
Stacey Schultz-Cherry
Keyword(s):  
Influenza Virus ◽  
Virus Infection ◽  
Immune Responses ◽  
Pregnant Women ◽  
Disease Severity ◽  
Influenza A ◽  
Antiviral Treatment ◽  
Influenza Virus Infection ◽  
Severe Influenza ◽  
The Impact

Pregnant women are among the individuals at the highest risk for severe influenza virus infection. Infection of the mother during pregnancy increases the probability of adverse fetal outcomes such as small for gestational age, preterm birth and fetal death. Animal models of syngeneic and allogeneic mating can recapitulate the increased disease severity observed in pregnant women and are used to define the mechanism(s) of that increased severity. This review focuses on influenza A virus pathogenesis, the unique immunological landscape during pregnancy, the impact of maternal influenza virus infection on the fetus and the immune responses at the maternal–fetal interface. Finally, we summarize the importance of immunization and antiviral treatment in this population and highlight issues that warrant further investigation.

scholarly journals Use of Anti-Cytokine Therapy in Kidney Transplant Recipients with COVID-19

2021 ◽  
Vol 10 (8) ◽  
pp. 1551
Author(s):  
Marta Bodro ◽  
Frederic Cofan ◽  
Jose Ríos ◽  
Sabina Herrera ◽  
Laura Linares ◽  
...  
Keyword(s):  
Kidney Transplant ◽  
Ordinal Scale ◽  
Transplant Recipients ◽  
Kidney Transplant Recipients ◽  
Kidney Recipients ◽  
Secondary Infections ◽  
Statistical Effect ◽  
Randomized Control ◽  
The Impact ◽  
To Receive

In the context of the coronavirus disease 2019 (COVID-19) pandemic, we aimed to evaluate the impact of anti-cytokine therapies (AT) in kidney transplant recipients requiring hospitalization due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. This is an observational retrospective study, which included patients from March to May 2020. An inverse probability of treatment weighting from a propensity score to receive AT was used in all statistical analyses, and we applied a bootstrap procedure in order to calculate an estimation of the 2.5th and 97.5th percentiles of odds ratio (OR). outcomes were measured using an ordinal scale determination (OSD). A total of 33 kidney recipients required hospitalization and 54% of them received at least one AT, mainly tocilizumab (42%), followed by anakinra (12%). There was no statistical effect in terms of intensive care unit (ICU) admission, respiratory secondary infections (35% vs. 7%) or mortality (16% vs. 13%) comparing patients that received AT with those who did not. Nevertheless, patients who received AT presented better outcomes during hospitalization in terms of OSD ≥5 ((OR 0.31; 2.5th, 97.5th percentiles (0.10; 0.72)). These analyses indicate, as a plausible hypothesis, that the use of AT in kidney transplant recipients presenting with COVID-19 could be beneficial, even though multicenter randomized control trials using these therapies in transplanted patients are needed.

scholarly journals Updated overview on the interplay between obesity and COVID-19

Diagnosis ◽  
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Diletta Onorato ◽  
Giovanni Carpenè ◽  
Giuseppe Lippi ◽  
Mairi Pucci
Keyword(s):  
Disease Severity ◽  
Clinical Characteristics ◽  
Literature Search ◽  
Scientific Literature ◽  
Population Sample ◽  
Obese Patients ◽  
Health Crisis ◽  
Keywords Obesity ◽  
Negative Prognostic Factor ◽  
The Impact

AbstractThe worldwide spread of coronavirus disease 2019 (COVID-19) has generated a global health crisis and more than a million deaths so far. Epidemiological and clinical characteristics of COVID-19 are increasingly reported, along with its potential relationship with overweight and/or obesity. Therefore, we aim here to review the current scientific literature on the impact of overweight and/or obesity among hospitalized patients who have developed severe or critical forms of COVID-19. Following PRISMA guidelines, our literature search identified over 300 scientific articles using the keywords “obesity” and “COVID-19”, 22 of which were finally selected for reporting useful information on the association between overweight/obesity and disease severity. In particular, in 11 out of the 14 studies (79%) which evaluated the association between obesity and disease severity providing also a risk estimate (i.e., the odd ratio; OR), the OR value was constantly >2. Although the studies were found to be heterogeneous in terms of design, population, sample size and endpoints, in most cases a significant association was found between obesity and the risk of progressing to severe COVID-19 illness, intensive care unit admission and/or death. We can hence conclude that an increased body mass index shall be considered a negative prognostic factor in patients with COVID-19, and more aggressive prevention or treatment shall hence be reserved to overweight and/or obese patients.

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