Fate and preservation of the late pleistocene cave bears from Niedzwiedzia Cave in Poland, through taphonomy, pathology, and geochemistry.

This comprehensive study examines fossil remains from Niedzwiedzia Cave in the Eastern Sudetes, offering detailed insights into the palaeobiology and adversities encountered by the Pleistocene cave bear Ursus spelaeus ingressus. Emphasising habitual cave use for hibernation and a primarily herbivorous diet, the findings attribute mortality to resource scarcity during hibernation and habitat fragmentation amid climate shifts. Taphonomic analysis indicates that the cave was extensively used by successive generations of bears, virtually unexposed to the impact of predators. The study also reveals that alkaline conditions developed in the cave during the post-depositional taphonomic processes. Mortality patterns, notably among juveniles, imply dwindling resources, indicative of environmental instability. Skeletal examination reveals a high incidence of forelimb fractures, indicating risks during activities like digging or confrontations. Palaeopathological evidence unveils vulnerabilities to tuberculosis, abscesses, rickets, and injuries, elucidating mobility challenges. The cave's silts exhibit a high zinc concentration, potentially derived from successive bear generations consuming zinc-rich plants. This study illuminates the lives of late cave bears, elucidating unique environmental hurdles faced near their species' end.

A side-specific nomogram for extraprostatic extension may reduce the positive surgical margin rate in radical prostatectomy.

PURPOSE: Nomograms predicting side-specific extraprostatic extension (EPE) may be applied to reduce positive surgical margin (PSM) rates in patients planned for radical prostatectomy (RP). This study evaluates the impact of implementing an externally validated nomogram for side-specific EPE on PSM rate and degree of nerve-sparing. METHODS: In patients planned for RP, the side-specific nomogram predictions (based on MRI, ISUP grade group, and PSA density), with an advised threshold of 20% for safe nerve-sparing, were presented preoperatively to the urological surgeon. The surgeon completed a survey before RP about the planning with respect to side-specific nerve-sparing and change of management due to the result of the nomogram. PSM rates and degree of nerve-sparing were compared to a retrospective control group treated in the months prior to the introduction of the nomogram. RESULTS: A total of 100 patients were included, 50 patients in both groups representing 200 prostate lobes. Of the patients, 37% had histologically confirmed EPE, and 40% a PSM. In 12% of the 100 lobes planned after nomogram presentation, a change in management due to the nomogram was reported. A per-prostate lobe analysis of all the lobes showed comparable rates of full nerve-sparing (45% vs. 30%; p = 0.083) and lower rates of PSM on the lobes with histological EPE (45% vs. 85%; p < 0.05) in the intervention (nomogram) group versus the control group. CONCLUSION: Implementing a predictive nomogram for side-specific EPE in the surgical planning for nerve-sparing leads to lower rates PSM on the side of the histological EPE without compromising nerve-sparing.

Natural Occurrence of Maize Gibberella Ear Rot and Contamination of Grain with Mycotoxins in Association with Weather Variables.

Gibberella ear rot (GER) severity (percent area of the ear diseased) and associated grain contamination with mycotoxins were quantified in plots of 15 to 16 maize hybrids planted at 10 Ohio locations from 2015 to 2018. Deoxynivalenol (DON) was quantified in grain samples in all 4 years, whereas nivalenol, 3-acetyldeoxynivalenol, and 15-acetyldeoxynivalenol (15ADON) were quantified only in the last 2 years. Only DON and 15ADON were detected. The highest levels of GER and DON contamination were observed for 2018, followed by 2016 and 2017. No GER symptoms or DON were detected in 2015. Approximately 41% of the samples from asymptomatic ears had detectable levels of DON, and 7% of these samples from 2016 had DON > 5 ppm. Associations between DON contamination and 43 variables representing summaries of temperature (T), relative humidity (RH), rainfall (R), surface wetness, and T-RH combinations for different window lengths and positions relative to R1 growth stage were quantified with Spearman correlation coefficients (r). Fifteen-day window lengths tended to show the highest correlations. Most of the variables based on T, R, RH, and T-RH were significantly correlated with DON for the 15-day window, as well as other windows. For moisture-related variables, there generally was a negative correlation before R1, changing to a positive correlation after R1. Results showed that GER and DON can be frequently found in Ohio maize fields, with the risk of DON being associated with multiple weather variables, particularly those representing combinations of T between 15 and 30°C and RH > 80 summarized during the 3 weeks after R1.

Tar Spot: An Understudied Disease Threatening Corn Production in the Americas.

Tar spot of corn has been a major foliar disease in several Latin American countries since 1904. In 2015, tar spot was first documented in the United States and has led to significant yield losses of approximately 4.5 million t. Tar spot is caused by an obligate pathogen, Phyllachora maydis, and thus requires a living host to grow and reproduce. Due to its obligate nature, biological and epidemiological studies are limited and impact of disease in corn production has been understudied. Here we present the current literature and gaps in knowledge of tar spot of corn in the Americas, its etiology, distribution, impact and known management strategies as a resource for understanding the pathosystem. This will in tern guide current and future research and aid in the development of effective management strategies for this disease.

Stability of Hybrid Maize Reaction to Gibberella Ear Rot and Deoxynivalenol Contamination of Grain.

Trials were conducted to quantify the stability (or lack of G × E interaction) of 15 maize hybrids to Gibberella ear rot (GER; caused by Fusarium graminearum) and deoxynivalenol (DON) contamination of grain across 30 Ohio environments (3 years × 10 locations). In each environment, one plot of each hybrid was planted and 10 ears per plot were inoculated via the silk channel. GER severity (proportion of ear area diseased) and DON contamination of grain (ppm) were quantified. Multiple rank-based methods, including Kendall's concordance coefficient (W) and Piepho's U, were used to quantify hybrid stability. The results found insufficient evidence to suggest crossover G × E interaction of ranks, with W greater than zero for GER (W = 0.28) and DON (W = 0.26), and U not statistically significant for either variable (P > 0.20). Linear mixed models (LMMs) were also used to quantify hybrid stability, accounting for crossover or noncrossover G × E interaction of transformed observed data. Based on information criteria and likelihood ratio tests for GER and DON response variables, the models with more complex variance-covariance structures-heterogeneous compound symmetry and factor-analytic-provided a better fit than the model with the simpler compound symmetry structure, indicating that one or more hybrids differed in stability. Overall, hybrids were stable based on rank-based methods, which indicated a lack of crossover G × E interaction, but the LMMs identified a few hybrids that were sensitive to environment. Resistant hybrids were generally more stable than susceptible hybrids.

Identification of a Divergent Isolate of Ryegrass Mosaic Virus in Ohio Wheat.

A divergent isolate of ryegrass mosaic virus (RGMV) has been identified that is associated with wheat samples collected in Ohio. The complete genome of the virus is 9,570 nucleotides, with a polyprotein open reading frame that shares 77.2% nucleotide sequence identity with the reference ryegrass mosaic virus sequence.

Occurrence and High-Throughput Sequencing of Viruses in Ohio Wheat.

Ohio is a leading producer of soft red winter wheat in the United States. Many viruses impact wheat production, but there is a lack of contemporary information on the distribution and potential impact of wheat viruses in Ohio. To address this knowledge gap, we created a comprehensive dataset of viruses identified by high-throughput sequencing (HTS) and their incidence in field sites sampled across the state. Samples were collected from 103 field sites in surveys conducted in 2012, 2016, and 2017 and subjected to RNA HTS, reverse transcription (RT) PCR, or enzyme-linked immunosorbent assay to assess virus sequence diversity, prevalence, and incidence within fields. Partial and complete virus sequences were assembled and detection validated by RT-PCR. Assembled sequences were compared with previously known virus sequences, and novel sequences were validated by Sanger sequencing. The viruses detected most often included barley yellow dwarf virus (BYDV), cereal yellow dwarf virus (CYDV), wheat streak mosaic virus (WSMV), and wheat spindle streak mosaic virus (WSSMV). These viruses were detected at 67, 69, 55, and 28% of the field sites sampled, with mean incidences of 18, 19, 20, and 49%, respectively, within fields where they were detected. Brome mosaic virus (BMV) and cocksfoot mottle virus (CfMV) were also viruses of potential importance detected in Ohio, found in 26 and 17% of the field sites sampled, respectively. Based on results from logistic regression analyses, the presence of BYDV, CYDV, WSMV, and WSSMV was associated with the presence of volunteer wheat, BYDV and CfMV with monocots as the previous crop, and BMV with the presence of nearby corn fields (P < 0.10). For six viruses, there was evidence of spatial clustering in at least one field site and the variance of mean incidence was higher at the county level than at the regional spatial level. This finding suggests that county- and site-specific factors influenced the incidence and spatial pattern of some viruses. The results of this study provide a snapshot of viruses present in Ohio wheat and insights into their biology, potential risks to wheat production, and possible management strategies.

Evaluation of the Combined Effect of Heterodera glycines and Macrophomina phaseolina on Soybean Yield in Naturally Infested Fields with Spatial Regression Analysis and in Greenhouse Studies.

Heterodera glycines, the soybean cyst nematode, and Macrophomina phaseolina, causal agent of charcoal rot, are economically important soybean pathogens. The impact and effect of these pathogens on soybean yield in coinfested fields in the Midwest production region is not known. Both pathogens are soilborne, with spatially aggregated distribution and effects. Spatial regression analysis, therefore, is an appropriate method to account for the spatial dependency in either the dependent variable or regression error term from data produced in fields naturally infested with H. glycines and M. phaseolina. The objectives of this study were twofold: to evaluate the combined effect of H. glycines and M. phaseolina on soybean yield in naturally infested commercial fields with ordinary least squares and spatial regression models; and to evaluate, under environmentally controlled conditions, the combined effect of H. glycines and M. phaseolina through nematode reproduction and plant tissue fungal colonization. Six trials were conducted in fields naturally infested with H. glycines and M. phaseolina in Ohio. Systematic-grid sampling was used to determine the population densities of H. glycines and M. phaseolina, and soybean yield estimates. Though not used in any statistical analysis, M. phaseolina colony forming units from plant tissue, charcoal rot severity, and H. glycines type were also recorded and summarized. In two greenhouse experiments, treatments consisted of H. glycines alone, M. phaseolina alone, and coinfestation of soybean with both pathogens. Moran's I test indicated that the yield from five fields was spatially correlated (P < 0.05) and aggregated. In these fields, to account for spatial dependence, spatial regression models were fitted to the data. Spatial regression analyses revealed a significant interaction effect between H. glycines and M. phaseolina on soybean yield for fields with high initial population densities of both pathogens. In the greenhouse experiments, H. glycines reproduction was significantly (P < 0.05) reduced in the presence of M. phaseolina; however, soybean tissue fungal colonization was not affected by the presence of H. glycines. The direct mechanisms by which H. glycines and M. phaseolina interact were not demonstrated in this study. Future studies must be conducted in the field and greenhouse to better understand this interaction effect.

Predicting plant disease epidemics from functionally represented weather series.

Epidemics are often triggered by specific weather patterns favouring the pathogen on susceptible hosts. For plant diseases, models predicting epidemics have therefore often emphasized the identification of early season weather patterns that are correlated with a disease outcome at some later point. Toward that end, window-pane analysis is an exhaustive search algorithm traditionally used in plant pathology for mining correlations in a weather series with respect to a disease endpoint. Here we show, with reference to Fusarium head blight (FHB) of wheat, that a functional approach is a more principled analytical method for understanding the relationship between disease epidemics and environmental conditions over an extended time series. We used scalar-on-function regression to model a binary outcome (FHB epidemic or non-epidemic) relative to weather time series spanning 140 days relative to flowering (when FHB infection primarily occurs). The functional models overall fit the data better than previously described standard logistic regression (lr) models. Periods much earlier than heretofore realized were associated with FHB epidemics. The findings were used to create novel weather summary variables which, when incorporated into lr models, yielded a new set of models that performed as well as existing lr models for real-time predictions of disease risk. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.

Characterization of an Ohio Isolate of Brome Mosaic Virus and Its Impact on the Development and Yield of Soft Red Winter Wheat.

Brome mosaic virus (BMV) is generally thought to be of little economic importance to crops; consequently, there is little information about its impact on wheat production under field conditions. After repeated detection of BMV in Ohio wheat fields at incidences up to 25%, the virus was isolated, sequenced, characterized, and tested for its impact on soft red winter wheat (SRWW). The Ohio isolate of brome mosaic virus (BMV-OH) was found to be >99% identical to a BMV-Fescue isolate (accession no. DQ530423-25) and capable of systemically infecting multiple monocot and dicot species, including cowpea and soybean, in experimental inoculations. BMV-OH was used in field experiments during the 2016 and 2017 growing seasons to quantify its effect on SRWW grain yield and development when inoculated at Feekes 1, 5, 8, and 10 in two to four cultivars. Cultivar and timing of inoculation had statistically significant (P < 0.05) main and interaction effects on grain yield, wheat growth, and multiple components of yield. Compared with noninoculated controls, BMV-OH reduced grain yield by up to 61% when inoculated at Feekes 1 and by as much as 25, 36, and 31% for inoculations at Feekes 5, 8, and 10, respectively. The magnitude of the yield reduction varied among cultivars and was associated with reductions in grain size and weight or plant population. These findings suggest that BMV could impact wheat productivity in Ohio and will serve as the basis for more large-scale investigations of the effects of this virus in commercial fields.

Grasping at straws: a re-evaluation of sweepstakes colonisation of islands by mammals.

Natural rafting is an easy, non-evidence-based solution often used to explain the presence of a variety of species on isolated islands. The question arises as to whether this solution is based on solid scientific grounds. It is a plausible colonisation route only if intricate networks of variables are considered and many different conditions satisfied. This review provides a descriptive account of some of the most critical issues underlying the theory of natural rafting that should be addressed by its supporters. These include: (i) biological variables; (ii) characteristics of the vessels; and (iii) physical variables. Natural rafting may explain the dispersal of poikilotherms with low metabolic rates and low resource requirements that could withstand trans-oceanic crossings, but explaining the transport of homeothermic terrestrial mammals to oceanic islands is more problematic. Drifting at sea exposes organisms to high concentrations of salt, high temperature and humidity excursions, starvation, and above all to dehydration. A sufficiently large group of healthy reproductive individuals of the two sexes should either be transported together, or be able to reassemble after separate crossings, to prevent inbreeding, genetic drift and ultimately extinction. Any vessels of flotsam occupied must minimally provide the animals they transport with sufficient provisions to survive the journey, offer minimum friction and drag through water, and be transported by appropriately directed, sustained, high-speed currents. Thus, a 'sweepstakes colonisation' event would be the result of a lucky combination of all, or at least the majority, of these factors. Some cases throw doubt on the use of a natural rafting model to explain known animal colonisations, with one of the most striking examples being Madagascar. This island is far from the nearest mainland coasts and the sea currents in the Mozambique Channel are directed towards Africa rather than Madagascar, yet, the island was colonised by terrestrial mammals (e.g. extinct hippopotamuses, lemurs, carnivores, rodents and tenrecs) unable to swim and to survive long journeys at sea. In order to assess the feasibility of the natural rafting model in a case such as Madagascar, tests were performed using three variables for which enough information could be obtained from the literature: length of survival without food, survival without water, and sea current speed. The distributions of these variables appear to be log-normal and multiplicative, or follow a power-law, rather than being Gaussian. The tests suggest that a distributional analysis is a more suitable approach than the use of geometric probability to calculate the probabilities associated with the examined data. Such non-linear and self-organising systems may reach a critical point governed by different competing factors. Mammals with high survival requirements, such as lemurs and hippopotamuses, thus may have a virtually zero probability of reaching distant islands by natural rafting. Our results raise doubts as to the validity of a natural rafting model, and we urge a rethinking of the modes in which numerous islands were colonised by land mammals and a careful revision of past geological and phylogeographic work.

Functional Data Analysis of Weather Variables Linked to Fusarium Head Blight Epidemics in the United States.

In past efforts, input weather variables for Fusarium head blight (FHB) prediction models in the United States were identified after following some version of the window-pane algorithm, which discretizes a continuous weather time series into fixed-length windows before searching for summary variables associated with FHB risk. Functional data analysis, on the other hand, reconstructs the assumed continuous process (represented by a series of recorded weather data) by using smoothing functions, and is an alternative way of working with time series data with respect to FHB risk. Our objective was to functionally model weather-based time series data linked to 865 observations of FHB (covering 16 states and 31 years in total), classified as epidemics (FHB disease index ≥ 10%) and nonepidemics (FHB disease index < 10%). Altogether, 94 different time series variables were modeled by penalized cubic B-splines for the smoothing function, from 120 days pre-anthesis to 20 days post-anthesis. Functional mean curves, standard deviations, and first derivatives were plotted for FHB epidemics relative to nonepidemics. Function-on-scalar regressions assessed the temporal trends of the magnitude and significance of the mean difference between functionally represented weather time series associated with FHB epidemics and nonepidemics. The mean functional weather-variable curve for epidemics started to deviate, in general, from that for nonepidemics as early as 40 days pre-anthesis for several weather variables. The greatest deviations were often near anthesis, the period of maximum susceptibility of wheat to FHB-causing fungi. The most consistent separations between the mean functional curves were seen with the daily averages of moisture-related variables (such as average relative humidity) and with variables summarizing the daily variation in temperature (as opposed to the daily mean). Functional data analysis was useful for extending our knowledge of relationships between weather variables and FHB epidemics.

Integrated Effects of Genetic Resistance and Prothioconazole + Tebuconazole Application Timing on Fusarium Head Blight in Wheat.

Integrated Fusarium head blight (FHB) management programs consisting of different combinations of cultivar resistance class and an application of the fungicide prothioconazole + tebuconazole at or after 50% early anthesis were evaluated for efficacy against FHB incidence (INC; percentage of diseased spikes), index (IND; percentage of diseased spikelets per spike), Fusarium damaged kernel (FDK), deoxynivalenol (DON) toxin contamination, grain yield, and test weight (TW) in inoculated field trials conducted in 11 U.S. states in 2014 and 2015. Mean log response ratios and corresponding percent control values for INC, IND, FDK, and DON, and mean differences in yield and TW relative to a nontreated, inoculated susceptible check (S_CK), were estimated through network meta-analyses as measures of efficacy. Results from the analyses were then used to estimate the economic benefit of each management program for a range of grain prices and fungicide applications costs. Management programs consisting of a moderately resistant (MR) cultivar treated with the fungicide were the most efficacious, reducing INC by 60 to 69%, IND by 71 to 76%, FDK by 66 to 72%, and DON by 60 to 64% relative to S_CK, compared with 56 to 62% for INC, 68 to 72% for IND, 66 to 68% for FDK, and 58 to 61% for DON for programs with a moderately susceptible (MS) cultivar. The least efficacious programs were those with a fungicide application to a susceptible (S) cultivar, with less than a 45% reduction of INC, IND, FDK, or DON. All programs were more efficacious under conditions favorable for FHB compared with less favorable conditions, with applications made at 50% early anthesis being of comparable efficacy to those made 2 to 7 days later. Programs with an MS cultivar resulted in the highest mean yield increases relative to S_CK (541 to 753 kg/ha), followed by programs with an S cultivar (386 to 498 kg/ha) and programs with an MR cultivar (250 to 337 kg/ha). Integrated management programs with an MS or MR cultivar treated with the fungicide at or after 50% early anthesis were the most likely to result in a 50 or 75% control of IND, FDK, or DON in a future trial. At a fixed fungicide application cost, these programs were $4 to $319/MT more economically beneficial than corresponding fungicide-only programs, depending on the cultivar and grain price. These findings demonstrate the benefits of combining genetic resistance with a prothioconazole + tebuconazole treatment to manage FHB, even if that treatment is applied a few days after 50% early anthesis.

Meta-Analysis of the Effects of QoI and DMI Fungicide Combinations on Fusarium Head Blight and Deoxynivalenol in Wheat.

Field trials were conducted in 17 U.S. states to evaluate the effects of quinone outside inhibitor (QoI) and demethylation inhibitor (DMI) fungicide programs on Fusarium head blight index (IND) and deoxynivalenol (DON) toxin in wheat. Four DMI-only treatments applied at Feekes 10.5.1, five QoI-only treatments applied between Feekes 9 or Feekes 10.5, three QoI+DMI mixtures applied at Feekes 10.5, and three treatments consisting of a QoI at Feekes 9 followed by a DMI at Feekes 10.5.1 were evaluated. Network meta-analytical models were fitted to log-transformed mean IND and DON data and estimated contrasts of log means were used to obtain estimates of mean percent controls relative to the nontreated check as measures of efficacy. Results from the meta-analyses were also used to assess the risk of DON increase in future trials. DMI at Feekes 10.5.1 were the most effective programs against IND and DON and the least likely to increase DON in future trials. QoI-only programs increased mean DON over the nontreated checks and were the most likely to do so in future trials, particularly when applied at Feekes 10.5. The effects of QoI+DMI combinations depended on the active ingredients and whether the two were applied as a mixture at heading or sequentially. Following a Feekes 9 QoI application with a Feekes 10.5.1 application of a DMI reduced the negative effect of the QoI on DON but was not sufficient to achieve the efficacy of the Feekes 10.5.1 DMI-only treatments. Our results suggest that one must be prudent when using QoI treatments under moderate to high risk of FHB, particularly where the QoI is used without an effective DMI applied in combination or in sequence.

High-Precision In Situ 87Sr/86Sr Analyses through Microsampling on Solid Samples: Applications to Earth and Life Sciences.

An analytical protocol for high-precision, in situ microscale isotopic investigations is presented here, which combines the use of a high-performing mechanical microsampling device and high-precision TIMS measurements on micro-Sr samples, allowing for excellent results both in accuracy and precision. The present paper is a detailed methodological description of the whole analytical procedure from sampling to elemental purification and Sr-isotope measurements. The method offers the potential to attain isotope data at the microscale on a wide range of solid materials with the use of minimally invasive sampling. In addition, we present three significant case studies for geological and life sciences, as examples of the various applications of microscale 87Sr/86Sr isotope ratios, concerning (i) the pre-eruptive mechanisms triggering recent eruptions at Nisyros volcano (Greece), (ii) the dynamics involved with the initial magma ascent during Eyjafjallajökull volcano's (Iceland) 2010 eruption, which are usually related to the precursory signals of the eruption, and (iii) the environmental context of a MIS 3 cave bear, Ursus spelaeus. The studied cases show the robustness of the methods, which can be also be applied in other areas, such as cultural heritage, archaeology, petrology, and forensic sciences.

Perceptions of Midwestern Crop Advisors and Growers on Foliar Fungicide Adoption and Use in Maize.

Foliar fungicide use in hybrid maize in the United States was rare before 2000. The decade from 2000 to 2010 saw foliar fungicides increasingly applied to maize in the absence of appreciable disease pressure, a practice seemingly at odds with integrated pest management philosophy. Yet, it is commonly believed that growers do not employ management strategies unless there are perceived benefits. Maize (corn) growers (CGs) and certified crop advisors (CCAs) across four Midwestern states (Iowa, Illinois, Ohio, and Wisconsin) were surveyed to better understand their practices, values and perceptions concerning the use of foliar fungicides during 2005 to 2009. The survey results demonstrated the rapid rise in maize foliar fungicide applications from 2000 through 2008, with 84% of CGs who sprayed having used a foliar fungicide in maize production for the very first time during 2005 to 2009. During 2005 to 2009, 73% of CCAs had recommended using a foliar fungicide, but only 35% of CGs sprayed. Perceived yield gains, conditional on having sprayed, were above the break-even point on average. However, negative yield responses were also observed by almost half of CCAs and a quarter of CGs. Hybrid disease resistance was a more important factor to economically successful maize production than foliar fungicides. Diseases as a yield-limiting factor were more important to CGs than CCAs. As a group, CGs were not as embracing of foliar fungicide as were CCAs, and remained more conservative about the perceived benefits to yield.

The tangled cases of Deinogalerix (Late Miocene endemic erinaceid of Gargano) and Galericini (Eulipotyphla, Erinaceidae): a cladistic perspective.

The Late Miocene giant erinaceid Deinogalerix from Scontrone and Gargano (Italy) is associated with many other vertebrates in deposits of a past island, the "Abruzzo-Apulia Platform". At Gargano, Deinogalerix is accompanied by the moderately endemized Galericini Apulogalerix. This first extensive cladistic analysis is aimed at defining the relationships of Deinogalerix with characteristic members of the tribe Galericini. The analysis was performed on a matrix of 30 characters and 19 taxa and identified some smaller clades, nested within three major ones. The latter include: (i) a pentatomy of Galerix species, (ii) a polytomy of "transitional" Galerix-Parasorex species and (iii) a large clade with Parasorex, Schizogalerix and Gargano representatives. Galerix and Parasorex proved to be paraphyletic and Schizogalerix monophyletic. Based on the results of the analysis, Deinogalerix and Apulogalerix have distinct origins, which supports an asynchronous colonization of the island. The line of Deinogalerix possibly stemmed from some eastern species transitional between Galerix and Parasorex around Mammal Neogene (MN) zone 2. Conversely, the line of Apulogalerix originated from a primitive Parasorex ibericus, or a close relative, around MN 9-10. Another important result was detecting an impressive early Miocene (MN 2?) radiation of Galericini. Moreover, Schizogalerix and Parasorex originated from eastern Galericini morphologically transitional between Galerix and Parasorex.

Painless swollen calf muscles of a 75-year-old patient caused by bilateral venous malformations.

A 75-year-old man presented with knee pain due to medial osteoarthritis of the knee in the orthopedic outpatient clinic. Conservative treatment was started with steroid infiltration. Besides his knee complaint reported a bilateral painless swollen calf muscle without traumatic cause, and also without any pain at night, fever or medical illness. On physical examination the soleus muscle had a swollen aspect in both calfs. The skin appeared normal without deformities and the arterial pulsations were intact. An X-ray did not show abnormalities in the tibia. Magnetic resonance imaging of the legs revealed bilateral multiple saccular intramuscular venous malformations involving the soleus muscle. Intramuscular venous malformations in skeletal muscles are rare, especially when the occurrence is bilateral. Bilateral venous malformations have the potential to be missed because of the intramuscular localization. Symptoms of intramuscular venous malformation can be often mild and overlap with non-exercise related compartment syndrome, claudication, lymphedema and post thrombotic syndrome or muscle strains.

Statistical Models and Methods for Network Meta-Analysis.

Meta-analysis, the methodology for analyzing the results from multiple independent studies, has grown tremendously in popularity over the last four decades. Although most meta-analyses involve a single effect size (summary result, such as a treatment difference) from each study, there are often multiple treatments of interest across the network of studies in the analysis. Multi-treatment (or network) meta-analysis can be used for simultaneously analyzing the results from all the treatments. However, the methodology is considerably more complicated than for the analysis of a single effect size, and there have not been adequate explanations of the approach for agricultural investigations. We review the methods and models for conducting a network meta-analysis based on frequentist statistical principles, and demonstrate the procedures using a published multi-treatment plant pathology data set. A major advantage of network meta-analysis is that correlations of estimated treatment effects are automatically taken into account when an appropriate model is used. Moreover, treatment comparisons may be possible in a network meta-analysis that are not possible in a single study because all treatments of interest may not be included in any given study. We review several models that consider the study effect as either fixed or random, and show how to interpret model-fitting output. We further show how to model the effect of moderator variables (study-level characteristics) on treatment effects, and present one approach to test for the consistency of treatment effects across the network. Online supplemental files give explanations on fitting the network meta-analytical models using SAS.

Revisiting Fungicide-Based Management Guidelines for Leaf Blotch Diseases in Soft Red Winter Wheat.

Standard foliar fungicide applications in wheat are usually made between flag leaf emergence (Feekes [FK] 8) and heading (FK10.5) to minimize damage to the flag leaf. However, over the last few years, new fungicide programs such as applications prior to FK8 and split half-rate applications have been implemented, although there are few data pertaining to the efficacy of these programs. Eight experiments were conducted in Illinois, Indiana, Ohio, and Wisconsin from 2010 to 2012 to compare new programs to standard FK8 and FK10 programs in terms of disease control and yield response. The programs evaluated consisted of single full-rate applications of 19% tebuconazole + 19% prothioconazole (Prosaro) or 23.6% pyraclostrobin (Headline) at FK5 (pseudostem strongly erected), FK8, or FK10, or split half rates at FK5 and 8 (FK5+8), plus an untreated check (CK). Leaf blotch (LB) severity and yield data were collected and random effects meta-analytical models fitted to estimate the overall log odds ratio of disease reaching the flag leaf ( L¯OR ) and mean yield increase ( D¯ ) for each fungicide program relative to CK. For all programs, L¯OR was significantly different from zero (P < 0.05). Based on estimated odds ratios (OR = exp[ L¯OR ]), the two FK8 programs reduced the risk of LB reaching the flag leaf by 55 and 75%, compared with 62 and 69% and 67 and 70% for the two FK10 and FK5+8 programs, respectively, and only 32 and 37% for the two FK5 programs. D¯ was significantly different from zero (P ≤ 0.003) for all FK8, FK10, and FK5+8 programs, with values of 233 and 245, 175 and 220, and 175 and 187 kg ha-1 for the FK10, FK5+8, and FK8 programs, respectively. Differences in mean yield response between Headline and Prosaro were not statistically significant (P > 0.05). The probability of profitability was estimated for each program for a range of grain prices and fungicide application costs. All FK8, FK10, and FK5+8 programs had more than an 80% chance of resulting in a positive yield response, compared with 63 and 67% for the two FK5 programs. The chance of obtaining a yield increase of 200 kg ha-1, required to offset an application cost of $36 ha-1 at a grain price of $0.18 kg-1, ranged from 44 to 60% for FK8, FK10 and FK5+8 programs compared with 22 and 25% for the two FK5 programs. These findings could be used to help inform fungicide application decisions for LB diseases in soft red winter wheat.