Meta-Analysis in Plant Pathology: Publication Patterns, Methodological Trends, and Potential Future Directions.

Meta-analysis (MA) is increasingly adopted in agricultural and ecological sciences, fields at the interface with plant pathology. Our review of the use of MA in the field since 1999 identified 79 original research papers. Fifty percent of these works were published in two American Phytopathological Society journals, emphasizing their central role in disseminating MA research. Analysis of the number of authors per study and the authorship network revealed a tightly knit field. The network shows a few "hub" authors or groups that significantly influence research directions, with a clear geographical clustering in North and South America. Most of the MA papers focused on the effects of disease control, where fungicide was the main product. The MA investigations often focus on response variables like yield and disease severity for which the analyzed effect sizes differ, but the log of the ratio of means and untransformed means are predominant. The study selection to be included in the MA often follows systematic review standards or when clear quantitative criteria are used for study inclusion. Yet, the inclusion of data from reports, newsletters, and research trials adds breadth. Frequentist rather than Bayesian inference is most common, and SAS and R are the preferred software. Our review underscores the escalating importance of MA in plant pathology, especially for determining the mean and variability of the effects of different control methods on disease and yield. Efforts should continue to improve the detailed reporting of MA methods used, data sharing, and reporting of measures of heterogeneity among studies.

The use of fixed study main effects in arm-based network meta-analysis.

Methods of network meta-analysis (NMA) can be classified as arm-based and contrast-based approaches. There are several arm-based approaches, and some of these have been criticized because they recover inter-study information and hence do not obey the principle of concurrent control. Here, we point out that recovery of inter-study information in arm-based NMA can be prevented by fitting a fixed main effect for studies. Advantages of arm-based NMA are discussed.

Open Access and Reproducibility in Plant Pathology Research: Guidelines and Best Practices.

The landscape of scientific publishing is experiencing a transformative shift toward open access, a paradigm that mandates the availability of research outputs such as data, code, materials, and publications. Open access provides increased reproducibility and allows for reuse of these resources. This article provides guidance for best publishing practices of scientific research, data, and associated resources, including code, in The American Phytopathological Society journals. Key areas such as diagnostic assays, experimental design, data sharing, and code deposition are explored in detail. This guidance aligns with that observed by other leading journals. We hope the information assembled in this paper will raise awareness of best practices and enable greater appraisal of the true effects of biological phenomena in plant pathology.

Into the Trees: Random Forests for Predicting Fusarium Head Blight Epidemics of Wheat in the United States.

Constructing models that accurately predict Fusarium head blight (FHB) epidemics and are also amenable to large-scale deployment is a challenging task. In the United States, the emphasis has been on simple logistic regression (LR) models, which are easy to implement but may suffer from lower accuracies when compared with more complicated, harder-to-deploy (over large geographies) model frameworks such as functional or boosted regressions. This article examined the plausibility of random forests (RFs) for the binary prediction of FHB epidemics as a possible mediation between model simplicity and complexity without sacrificing accuracy. A minimalist set of predictors was also desirable rather than having the RF model use all 90 candidate variables as predictors. The input predictor set was filtered with the aid of three RF variable selection algorithms (Boruta, varSelRF, and VSURF), using resampling techniques to quantify the variability and stability of selected variable sets. Post-selection filtering produced 58 competitive RF models with no more than 14 predictors each. One variable representing temperature stability in the 20 days before anthesis was the most frequently selected predictor. This was a departure from the prominence of relative humidity-based variables previously reported in LR models for FHB. The RF models had overall superior predictive performance over the LR models and may be suitable candidates for use by the Fusarium Head Blight Prediction Center.

Semi-field evaluation of the space spray efficacy of Fludora Co-Max EW against wild insecticide-resistant Aedes aegypti and Culex quinquefasciatus mosquito populations from Abidjan, Côte d'Ivoire.

BACKGROUND: Space spraying of insecticides is still an important means of controlling Aedes and Culex mosquitoes and arboviral diseases. This study evaluated the space spray efficacy of Fludora Co-Max EW, (water-based insecticide space spray combining flupyradifurone and transfluthrin with film forming aqueous spray technology (FFAST)), against wild insecticide-resistant Aedes aegypti and Culex quinquefasciatus mosquitoes from Abidjan, Côte d'Ivoire, compared with K-Othrine EC (deltamethrin-only product), in small-scale field trials. METHODS: Wild Ae. aegypti and Cx. quinquefasciatus mosquito larvae were collected in Abidjan, Côte d'Ivoire from August to December 2020. Mosquito larvae were reared in the laboratory until the adult stage. Fludora Co-Max EW and K-Othrine EC were tested against emerged adult females (F0 generation) using ultra-low volume cold fogging (ULV) and thermal fogging (TF) delivery technology, both outdoors and indoors in Agboville, Côte d'Ivoire. Specifically, cages containing 20 mosquitoes each were placed at distances of 10, 25, 50, 75 and 100 m from the spraying line for outdoor spraying, and at ceiling, mid-height and floor levels for indoor house spraying. Knockdown and mortality were recorded at each checkpoint and compared by treatments. RESULTS: Overall, Fludora Co-Max EW induced significantly higher knockdown and mortality effects in the wild insecticide-resistant Ae. aegypti and Cx. quinquefasciatus compared with K-Othrine EC. In both species, mortality rates with Fludora Co-Max EW were > 80% (up to 100%) with the ULV spray outdoors at each distance checkpoint (i.e. 10-100 m), and 100% with the ULV and TF sprays indoors at all checkpoints (i.e. ceiling, mid-height and floor). K-Othrine EC induced high mortality indoors (97.9-100%), whereas mortality outdoors rapidly declined in Ae. aegypti from 96.7% (10 m) to 36.7% (100 m) with the ULV spray, and from 85.0% (10 m) to 38.3% (100 m) with the TF spray. Fludora Co-Max EW spray applied as ULV spray outdoors had higher knockdown and higher killing effects on Ae. aegypti and Cx. quinquefasciatus than when applied as TF spray. Fludora Co-Max EW performed better against Cx. quinquefasciatus than against Ae. aegypti. CONCLUSIONS: Fludora Co-Max EW induced high mortality and knockdown effects against wild insecticide-resistant Ae. aegypti and Cx. quinquefasciatus Abidjan strains and performed better than K-Othrine EC. The presence of flupyradifurone and transfluthrin (with new and independent modes of action) and FFAST technology in the current Fludora Co-Max EW formulation appears to have broadened its killing capacity. Fludora Co-Max EW is thus an effective adulticide and may be a useful tool for Aedes and Culex mosquito and arbovirus control in endemic areas.

Environmental Conditions After Fusarium Head Blight Visual Symptom Development Affect Contamination of Wheat Grain with Deoxynivalenol and Deoxynivalenol-3-Glucoside.

Fusarium head blight (FHB) of wheat, caused by the fungus Fusarium graminearum, is associated with grain contamination with mycotoxins such as deoxynivalenol (DON). Although FHB is often positively correlated with DON, this relationship can break down under certain conditions. One possible explanation for this could be the conversion of DON to DON-3-glucoside (D3G), which is typically missed by common DON testing methods. The objective of this study was to quantify the effects of temperature, relative humidity (RH), and preharvest rainfall on DON, D3G, and the D3D/DON relationship. D3G levels were higher in grain from spikes exposed to 100% RH than to 70, 80, or 90% RH at 20 and 25°C across all tested levels of mean FHB index (percentage of diseased spikelets per spike). Mean D3G contamination was higher at 20°C than at 25 or 30°C. There were significantly positive linear relationships between DON and D3G. Rainfall treatments resulted in significantly higher mean D3G than the rain-free check and induced preharvest sprouting, as indicated by low falling numbers (FNs). There were significant positive relationships between the rate of increase in D3G per unit increase in DON (a measure of conversion) and sprouting. As FN decreased, the rate of D3G conversion increased, and this rate of conversion per unit decrease in FN was greater at relatively low than at high mean DON levels. These results provide strong evidence that moisture after FHB visual symptom development was associated with DON-to-D3G conversion and constitute valuable new information for understanding this complex disease-mycotoxin system.

Environment, Grain Development, and Harvesting Strategy Effects on Zearalenone Contamination of Grain from Fusarium Head Blight-Affected Wheat Spikes.

Fusarium head blight (FHB), caused by the fungus Fusarium graminearum, is associated with grain contamination with mycotoxins such as deoxynivalenol (DON) and zearalenone (ZEA). Unlike DON, less is known about factors affecting ZEA production during FHB epidemics. The objective of this study was to quantify ZEA contamination of wheat grain as influenced by temperature, relative humidity, FHB index (IND), grain maturation, simulated late-season rainfall, and harvest timing. Mean ZEA concentrations were low (<1.1 ppm) during the early stages of grain development (25 to 31 days after anthesis [DAA]) but rapidly increased 35 to 51 DAA in field experiments, particularly under rainy conditions. Five or ten consecutive days with simulated rainfall shortly before harvest greatly increased ZEA contamination. Similarly, extremely high levels of ZEA (51.8 to 468.6 ppm) were observed in grain from spikes exposed to 100% relative humidity (RH) at all tested temperatures and mean IND levels under controlled conditions. Interestingly, at RH ≤ 90%, ZEA concentrations were very low (0.1 to 3.6 ppm) at all tested temperatures, even at IND above 90%. At 100% RH, mean ZEA contamination was significantly higher at 20 and 25°C (235.1 and 278.2 ppm) than at 30°C (104.7 ppm). Grain harvested early and not exposed to rainfall had lower mean ZEA than grain harvested late and/or subjected to preharvest rainfall. This study was the first to associate ZEA contamination of grain from FHB-affected wheat spikes with temperature and moisture and show through designed experiments that early harvest could be a useful strategy for reducing ZEA contamination.

Impact of Gibberella Ear Rot on Grain Quality and Yield Components in Maize as Influenced by Hybrid Reaction.

The impact of Gibberella ear rot (GER; caused by Fusarium graminearum) on deoxynivalenol (DON) contamination of grain and yield components in maize were investigated using data from 30 environments in Ohio (3 years by 10 locations). Fifteen hybrids, later classified as susceptible (SU), moderately susceptible (MS), or moderately resistant (MR), based on the magnitude of differences in mean arcsine square-root-transformed GER severity (arcSEV) and log-transformed DON (logDON) relative to a reference SU check, were planted in each environment, and 10 ears per hybrid were inoculated with a spore suspension of F. graminearum. Relationships between GER severity and DON were well described by a Kono-Sugino-type nonlinear equation. Estimated parameters representing height (A) and steepness (ß) of the curves were significantly higher for SU than MS and MR hybrids but A was not significantly different between MS and MR. Results from a surrogacy analysis showed that GER was a moderate trial- and individual-level surrogate for DON. Both grain weight per ear and ear diameter decreased with increasing arcSEV but the regression slopes varied among resistance classes. The rates of reduction in both yield components per unit increase in arcSEV were significantly greater for SU than for MS and MR. An estimated 50% reduction in grain weight occurred at 62% GER severity for SU, compared with 77% severity for MS and 83% for MR. These results show that GER severity can be used as a surrogate for early estimation of DON contamination and yield loss to help guide grain handling and marketing decisions.

How to observe the principle of concurrent control in an arm-based meta-analysis using SAS procedures GLIMMIX and BGLIMM.

Network meta-analysis is a popular method to synthesize the information obtained in a systematic review of studies (e.g., randomized clinical trials) involving subsets of multiple treatments of interest. The dominant method of analysis employs within-study information on treatment contrasts and integrates this over a network of studies. One advantage of this approach is that all inference is protected by within-study randomization. By contrast, arm-based analyses have been criticized in the past because they may also recover inter-study information when studies are modeled as random, which is the dominant practice, hence violating the principle of concurrent control, requiring treated individuals to only be compared directly with randomized controls. This issue arises regardless of whether analysis is implemented within a frequentist or a Bayesian framework. Here, we argue that recovery of inter-study information can be prevented in an arm-based analysis by adding a fixed study main effect. This simple device means that it is possible to honor the principle of concurrent control in a two-way analysis-of-variance approach that is very easy to implement using generalized linear mixed model procedures and hence may be particularly welcome to those not well versed in the more intricate coding required for a contrast-based analysis.

Efficacy of Genetic Resistance and Fungicide Application Against Fusarium Head Blight and Mycotoxins in Wheat Under Persistent Pre- and Postanthesis Moisture.

Field experiments were conducted to investigate the efficacy of fungicide treatments in combination with genetic resistance against Fusarium head blight (FHB) and its associated mycotoxins under persistently wet pre- and postanthesis conditions in plots inoculated with Fusarium graminearum-colonized corn spawn. Treatments consisted of a single application of prothioconazole + tebuconazole at early anthesis (PA), or at 3 (P3), 6 (P6), or 9 (P9) days after early anthesis, or PA followed by a single application of metconazole at 3 (PA+C3), 6 (PA+C6), or 9 (PA+C9) days after early anthesis. PA and P3 were the most efficacious of the single-application treatments in terms of mean percentage control of FHB index (IND), deoxynivalenol (DON), zearalenone (ZEA), and mean increase in grain yield and test weight (TW) relative to the nontreated susceptible check (S_CK). The double-application treatments (PA+C3, PA+C6, and PA+C9) were the most effective of all tested fungicide programs. However, relative to S_CK, the highest overall mean percentage reduction in IND, DON, and ZEA and increase in grain yield and TW were observed when the double-application fungicide programs were integrated with genetic resistance. The estimated net cash income (NCI) of the integrated management (IM) programs was consistently higher than the NCI of other tested programs across different grain prices and fungicide application costs. Thus, the benefits of the two-treatment IM programs under highly favorable conditions for FHB development were enough to offset the cost of two applications, making these programs profitable.

Patterns of care and outcomes of 417 patients with METAstatic SYNovial sarcoma (METASYN): real-life data from the French Sarcoma Group (FSG).

BACKGROUND: Synovial sarcoma (SS) occurs in both adult and pediatric patients. The primary aim of this study is to describe the outcomes, prognostic factors, and treatment of patients with metastatic SS within a nationwide cohort. PATIENTS AND METHODS: All pediatric and adult patients with metastatic SS are registered in the French Sarcoma Group database. Data were collected from the national database https://conticabase.sarcomabcb.org/ up to March 2020. Descriptive and comparative analyses were conducted using SAS 9.4 and Stata Special Edition 16.1 software. RESULTS: Between January 1981 and December 2019, 417 patients with metastatic SS from 17 French sarcoma centers were included, including 64 (15.3%) under the age of 26 years. Median age was 42.5 years (range 9-87 years). The metastases were synchronous (cohort 1) or metachronous (cohort 2) in 18.9% (N = 79) and 81.1% (N = 338) patients, respectively. Median overall survival (OS) from the date of metastasis was 22.3 months (95% confidence interval 19.7-24.1 months). First-line chemotherapy without ifosfamide and/or doxorubicin was unfavorable for progression-free survival and OS (P < 0.001). Concerning cohort 1, young age, surgery of the primary tumor, and single metastatic site were independent favorable prognostic factors for OS. In cohort 2, surgery within an expert French Sarcoma Group center, absence of chemotherapy in the perioperative setting, the lungs as a single metastatic site, time to first metastasis >12 months, local therapy, and ifosfamide in the first metastatic line were independent favorable prognostic factors. CONCLUSIONS: The outcome of patients with metastatic SS is influenced by local treatment, management in reference centers, and cytotoxic treatments given in the perioperative and metastatic setting.

Characterizing Heterogeneity and Determining Sample Sizes for Accurately Estimating Wheat Fusarium Head Blight Index in Research Plots.

Because Fusarium head blight (FHB) intensity is usually highly variable within a plot, the number of spikes rated for FHB index (IND) quantification must be considered when designing experiments. In addition, quantification of sources of IND heterogeneity is crucial for defining sampling protocols. Field experiments were conducted to quantify the variability of IND ("field severity") at different spatial scales and to investigate the effects of sample size on estimated plot-level mean IND and its accuracy. A total of 216 7-row × 6-m-long plots of a moderately resistant and a susceptible cultivar were spray-inoculated with different Fusarium graminearum spore concentrations at anthesis to generate a range of IND levels. A one-stage cluster sampling approach was used to estimate IND, with an average of 32 spikes rated at each of 10 equally spaced points per plot. Plot-level mean IND ranged from 0.9 to 37.9%. Heterogeneity of IND, quantified by fitting unconditional hierarchical linear models, was higher among spikes within clusters than among clusters within plots or among plots. The projected relative error of mean IND increased as mean IND decreased, and as sample size decreased to <100 spikes per plot. Simple random samples were drawn with replacement 50,000 times from the original dataset for each plot and used to estimate the effects of sample sizes on mean IND. Samples of 100 or more spikes resulted in more precise estimates of mean IND than smaller samples. Poor sampling may result in inaccurate estimates of IND and poor interpretation of results.

Logistic Models Derived via LASSO Methods for Quantifying the Risk of Natural Contamination of Maize Grain with Deoxynivalenol.

Models were developed to quantify the risk of deoxynivalenol (DON) contamination of maize grain based on weather, cultural practices, hybrid resistance, and Gibberella ear rot (GER) intensity. Data on natural DON contamination of 15 to 16 hybrids and weather were collected from 10 Ohio locations over 4 years. Logistic regression with 10-fold cross-validation was used to develop models to predict the risk of DON ≥1 ppm. The presence and severity of GER predicted DON risk with an accuracy of 0.81 and 0.87, respectively. Temperature, relative humidity, surface wetness, and rainfall were used to generate 37 weather-based predictor variables summarized over each of six 15-day windows relative to maize silking (R1). With these variables, least absolute shrinkage and selection operator (LASSO) followed by all-subsets variable selection and logistic regression with 10-fold cross-validation were used to build single-window weather-based models, from which 11 with one or two predictors were selected based on performance metrics and simplicity. LASSO logistic regression was also used to build more complex multiwindow models with up to 22 predictors. The performance of the best single-window models was comparable to that of the best multiwindow models, with accuracy ranging from 0.81 to 0.83 for the former and 0.83 to 0.87 for the latter group of models. These results indicated that the risk of DON ≥1 ppm can be accurately predicted with simple models built using temperature- and moisture-based predictors from a single window. These models will be the foundation for developing tools to predict the risk of DON contamination of maize grain.

Adolescents and young adults (AYA) with cancer: a position paper from the AYA Working Group of the European Society for Medical Oncology (ESMO) and the European Society for Paediatric Oncology (SIOPE).

It is well recognised that adolescents and young adults (AYA) with cancer have inequitable access to oncology services that provide expert cancer care and consider their unique needs. Subsequently, survival gains in this patient population have improved only modestly compared with older adults and children with cancer. In 2015, the European Society for Medical Oncology (ESMO) and the European Society for Paediatric Oncology (SIOPE) established the joint Cancer in AYA Working Group in order to increase awareness among adult and paediatric oncology communities, enhance knowledge on specific issues in AYA and ultimately improve the standard of care for AYA with cancer across Europe. This manuscript reflects the position of this working group regarding current AYA cancer care, the challenges to be addressed and possible solutions. Key challenges include the lack of specific biological understanding of AYA cancers, the lack of access to specialised centres with age-appropriate multidisciplinary care and the lack of available clinical trials with novel therapeutics. Key recommendations include diversifying interprofessional cooperation in AYA care and specific measures to improve trial accrual, including centralising care where that is the best means to achieve trial accrual. This defines a common vision that can lead to improved outcomes for AYA with cancer in Europe.

Accuracy in the prediction of disease epidemics when ensembling simple but highly correlated models.

Ensembling combines the predictions made by individual component base models with the goal of achieving a predictive accuracy that is better than that of any one of the constituent member models. Diversity among the base models in terms of predictions is a crucial criterion in ensembling. However, there are practical instances when the available base models produce highly correlated predictions, because they may have been developed within the same research group or may have been built from the same underlying algorithm. We investigated, via a case study on Fusarium head blight (FHB) on wheat in the U.S., whether ensembles of simple yet highly correlated models for predicting the risk of FHB epidemics, all generated from logistic regression, provided any benefit to predictive performance, despite relatively low levels of base model diversity. Three ensembling methods were explored: soft voting, weighted averaging of smaller subsets of the base models, and penalized regression as a stacking algorithm. Soft voting and weighted model averages were generally better at classification than the base models, though not universally so. The performances of stacked regressions were superior to those of the other two ensembling methods we analyzed in this study. Ensembling simple yet correlated models is computationally feasible and is therefore worth pursuing for models of epidemic risk.

A Meta-Analytical Assessment of the Aggregation Parameter of the Binary Power Law for Characterizing Spatial Heterogeneity of Plant Disease Incidence.

The binary power law (BPL) is often used to characterize spatial heterogeneity of disease incidence. A hierarchical mixed model, coupled with multiple imputation to randomly generate any missing standard errors, was used to conduct a meta-analysis of >200 published values of the estimated aggregation (b) parameter of the BPL. Approximately 50% of estimated b values ranged from 1.1 to 1.3. Moderator variable analysis showed that the number of individuals per sampling unit (n) had a strong positive effect on b, with a linear relation between estimated b and ln(n). Estimated expected value of b for the population of published regressions at a reference n of 15 was 1.22. The increase in the variance due to the imputations was only 0.03, and the efficiency exceeded 0.98. Results were confirmed with an alternative mixed model that considered a range of possible within-trial correlations of the estimated b values and with a random-coefficient mixed model fitted to the subset of the data. Cropping system, dispersal mode, and pathogen type all had significant effects on b, with annuals having larger expected value than woody perennials, soilborne and rain-splashed dispersed pathogens having the largest expected values for dispersal mode, and bacteria and oomycetes having the largest expected values for pathogen type. However, there was considerable variation within each of the levels of the moderators, and the differences of expected values from smallest to largest were small, ≤0.16. Results are discussed in relation to previously published findings from stochastic simulations.

Comparing the Temporal Development of Wheat Spike Blast Epidemics in a Region of Bolivia Where the Disease Is Endemic.

Epidemics of wheat blast, caused the Triticum pathotype of Magnaporthe oryzae, were studied in the Santa Cruz del la Sierra region of Bolivia to quantify and compare the temporal dynamics of the disease under different growing conditions. Six plots of a susceptible wheat cultivar were planted at Cuatro Cañadas (CC), Okinawa 1 (OK1), and Okinawa 2 (OK2) in 2015. Spike blast incidence (INC) and severity (SEV) and leaf blast severity (LEAF) were quantified in each plot at regular intervals on a 10 × 10 grid (n = 100 clusters of spikes), beginning at head emergence (Feekes growth stage 10.5), for a total of nine assessments at CC, six at OK1, and six at OK2. Spike blast increased over time for 20 to 30 days before approaching a mean INC of 100% and a mean SEV of 60 to 75%. The logistic model was the most appropriate for describing the temporal dynamics of spike blast. The highest absolute rates of disease increase occurred earliest at OK1 and latest at OK2, and in all cases it coincided with major rain events. Estimated y0 values (initial blast intensity) were significantly (P < 0.05) higher at OK1 than at CC or OK2, whereas rL values (the logistic rate parameter) were significantly higher at OK2 than at CC or OK1. It took about 10 fewer days for SEV to reach 10, 15, or 20% at OK1 compared with OK2 and CC. Based on survival analyses, the survivor functions for time to 10, 15 and 20% SEV (ts) were significantly different between OK1 and the other locations, with the probabilities of SEV reaching the thresholds being highest at OK1. LEAF at 21 days after Feekes 10.5 had a significant effect on ts at OK1. For every 5% increase in LEAF, the chance of SEV reaching the thresholds by day 21 increased by 30 to 55%.

Quantifying the Effects of Temperature and Relative Humidity on the Development of Wheat Blast Incited by the Lolium Pathotype of Magnaporthe oryzae.

The Triticum pathotype of Magnaporthe oryzae (MoT) that causes wheat blast has not yet been reported in the U.S., but the closely related M. oryzae Lolium pathotype (MoL), also capable of inciting blast, is found in several wheat growing regions. Since the epidemiology of MoL-incited wheat blast is unknown, it is difficult to project where and under what conditions this pathogen may be of importance. To quantify conditions favorable for MoL infection and temporal development of wheat blast, separate cohorts of wheat spikes were spray or point inoculated at anthesis and immediately subjected to different combinations of temperature (TEMP; 20, 25, and 30°C) and 100% relative humidity (RH) duration (0, 3, 6, 12, 24, and 48 h). Blast developed under all tested conditions, with both incidence (INC) and severity (SEV) increasing over time. The effects of TEMP on angular-transformed INC and SEV (arcINC and arcSEV) were significant (P < 0.05) in most cases, with the magnitude of the TEMP effect influenced by RH duration when spikes were spray-inoculated. Between 12 and 21 days after inoculation (DAI), there were significant, positive linear relationships between hours of high RH and arcINC and arcSEV at 25 and 30°C, but not at 20°C. The estimated rates of increase in transformed INC or SEV per hour increase in high RH duration were significantly higher at 30°C than at 25°C at 12 to 14 DAI, but not at 19 to 21 DAI. The highest estimated temporal rates of increase in INC and SEV and the shortest estimated incubation periods (5 to 8 days) occurred at 25 and 30°C, with 24 and 48 h of high RH immediately after inoculation. These results will contribute to ongoing efforts to better understand the epidemiology of wheat blast incited by MoL as well as MoT.

Is Disease Intensity a Good Surrogate for Yield Loss or Toxin Contamination? A Case Study with Fusarium Head Blight of Wheat.

Sometimes plant pathologists assess disease intensity when they are primarily interested in other response variables, such as yield loss or toxin concentration in harvested products. In these situations, disease intensity potentially could be considered a surrogate of yield or toxin. A surrogate is a variable which can be used instead of the variable of interest in the evaluation of experimental treatments or in making predictions. Surrogates can be measured earlier, more conveniently, or more cheaply than the variable of primary interest, but the reliability or validity of the surrogate must be shown. We demonstrate ways of quantifying two facets of surrogacy by using a protocol originally developed by Buyse and colleagues for medical research. Coefficient-of-determination type statistics can be used to conveniently assess the strength of surrogacy on a unitless scale. As a case study, we evaluated whether field severity of Fusarium head blight (i.e., FHB index) can be used as a surrogate for yield loss and deoxynivalenol (DON) toxin concentration in harvested wheat grain. Bivariate mixed models and corresponding approximations were fitted to data from 82 uniform fungicide trials conducted from 2008 to 2013. Individual-level surrogacy-for predicting the variable of interest (yield or DON) from the surrogate (index) in plots with the same treatment-was very low. Trial-level surrogacy-for predicting the effect of treatment (e.g., mean difference) for the variable of interest based on the effect of the treatment on the surrogate (index)-was moderate for yield, and only low for DON. Challenges in using disease severity as a surrogate for yield and toxin are discussed.

Association of Mycoplasma Hominis and head and neck cancer with unknown primary.

INTRODUCTION: Beside HPV infection, there is currently no evidence of association between head and neck squamous cell carcinomas and microbial infections. We report the case of a cervical squamous cell carcinoma by Mycoplasma hominis. CASE SUMMARY: A 20-year-old woman, consulted for a swelling on the left cervical side. Clinical examination found a large fixed mass. Biological tests found no evidence of infection. Biopsies of the cervical lesion diagnosed an HPV negative squamous cell carcinoma. Microbiological tests of 16sRNA identification showed the presence of Mycoplasma hominis in the 3 specimens. The patient was treated by induction chemotherapy associated to antibiotherapy, followed by chemo-radiotherapy. DISCUSSION: The present case suggests that oropharyngeal infection by Mycoplasma hominis might be more frequent than expected, that 16sRNA is an efficient technique to isolate this pathogen and finally that further studies are required to document its potential oncogenic role in head and neck squamous cell carcinomas.