Unpacking estimates of task duration: The role of typicality and temporality

Research in task duration judgment has shown that unpacking a multifaceted task into components prior to estimating its duration increases estimates. In three studies, we find that unpacking a complex task can increase, decrease, or leave unaffected task duration estimates depending on the typicality of the unpacked components and their temporal position in the task sequence. Unpacking atypical long components increases task duration estimates, while unpacking atypical short components decreases estimates (Study 1). Unpacking atypical early components increases task duration estimates, while unpacking atypical late components decreases estimates (Study 2). Unpacking typical early or late components leaves estimates unaffected (Study 3). We explain these results based on the idea that task duration estimation involves a mental simulation process, and by drawing on theories of unpacking in probability judgment that emphasize the role of the typicality of the unpacked components. These findings hint at a deep conceptual link between probability judgment and task duration estimation but also show differences, such as the influence that temporality exerts on estimated duration. © 2013 Elsevier Inc

The effectiveness of convalescent plasma and hyperimmune immunoglobulin for the treatment of severe acute respiratory infections of viral etiology: a systematic review

Background: Administration of convalescent plasma, serum, or hyperimmune immunoglobulin may be of clinical benefit for treatment of severe acute respiratory infections (SARIs) of viral etiology. We conducted a systematic review and exploratory meta-analysis to assess the overall evidence. Methods: Healthcare databases and sources of grey literature were searched in July 2013. All records were screened against the protocol eligibility criteria, using a 3-stage process. Data extraction and risk of bias assessments were undertaken. Results: We identified 32 studies of SARS coronavirus infection and severe influenza. Narrative analyses revealed consistent evidence for a reduction in mortality, especially when convalescent plasma is administered early after symptom onset. Exploratory post hoc meta-analysis showed a statistically significant reduction in the pooled odds of mortality following treatment, compared with placebo or no therapy (odds ratio, 0.25; 95% confidence interval, .14–.45; I(2) = 0%). Studies were commonly of low or very low quality, lacked control groups, and at moderate or high risk of bias. Sources of clinical and methodological heterogeneity were identified. Conclusions: Convalescent plasma may reduce mortality and appears safe. This therapy should be studied within the context of a well-designed clinical trial or other formal evaluation, including for treatment of Middle East respiratory syndrome coronavirus CoV infection

Does the Degree of Hepatocellular Carcinoma Tumor Necrosis following Transarterial Chemoembolization Impact Patient Survival?

Purpose. The association between transarterial chemoembolization- (TACE-) induced HCC tumor necrosis measured by the modified Response Evaluation Criteria In Solid Tumors (mRECIST) and patient survival is poorly defined. We hypothesize that survival will be superior in HCC patients with increased TACE-induced tumor necrosis. Materials and Methods. TACE interventions were retrospectively reviewed. Tumor response was quantified via dichotomized (responders and nonresponders) and the four defined mRECIST categories. Results. Median survival following TACE was significantly greater in responders compared to nonresponders (20.8 months versus 14.9 months, p=0.011). Survival outcomes also significantly varied among the four mRECIST categories (p=0.0003): complete, 21.4 months; partial, 20.8; stable, 16.8; and progressive, 7.73. Only progressive disease demonstrated significantly worse survival when compared to complete response. Multivariable analysis showed that progressive disease, increasing total tumor diameter, and non-Child-Pugh class A were independent predictors of post-TACE mortality. Conclusions. Both dichotomized (responders and nonresponders) and the four defined mRECIST responses to TACE in patients with HCC were predictive of survival. The main driver of the survival analysis was poor survival in the progressive disease group. Surprisingly, there was small nonsignificant survival benefit between complete, partial, and stable disease groups. These findings may inform HCC treatment decisions following first TACE

Cutaneous neurofibromas in Neurofibromatosis type I: a quantitative natural history study

Abstract Background Neurofibromatosis type 1 (NF1) is a genetic disorder characterized by a predisposition to develop multiple benign tumors. A major feature of NF1 is the development of localized cutaneous neurofibromas. Cutaneous neurofibromas manifest in > 99% of adults with NF1 and are responsible for major negative effects on quality of life. Previous reports have correlated increased burden of cutaneous neurofibromas with age and pregnancy, but longitudinal data are not available to establish a quantitative natural history of these lesions. The purpose of this study is to conduct a prospective natural history study of 22 adults with NF1 over an 8-year period to quantify cutaneous neurofibroma number and size. Results The average monthly increase in volume for cutaneous neurofibromas was 0.37 mm3 in the back region (95% CI (0.23, 0.51), p < 0.0001), 0.28 mm3 in the abdominal region (95% CI (0.16, 0.41), p < 0.0001), and 0.21 mm3 in the arm/leg region (95% CI (0.08, 0.34), p = 0.0022). The number of cutaneous neurofibromas significantly increased in the back (slope = 0.032, p = 0.011) and abdominal (slope = 0.018, p = 0.026) regions, while the leg/arm regions retained a positive trend (slope = 0.004, p = 0.055). Conclusions The number and volume of cutaneous neurofibromas significantly increased over an 8-year timespan; however, the rate of increase is variable by individual and body region. These findings may provide insight into cutaneous neurofibroma development and benefit researchers considering clinical trials targeting cutaneous neurofibromas

Pea (Pisum sativum L.) in the Genomic Era

Pea (Pisum sativum L.) was the original model organism used in Mendel’s discovery (1866) of the laws of inheritance, making it the foundation of modern plant genetics. However, subsequent progress in pea genomics has lagged behind many other plant species. Although the size and repetitive nature of the pea genome has so far restricted its sequencing, comprehensive genomic and post genomic resources already exist. These include BAC libraries, several types of molecular marker sets, both transcriptome and proteome datasets and mutant populations for reverse genetics. The availability of the full genome sequences of three legume species has offered significant opportunities for genome wide comparison revealing synteny and co-linearity to pea. A combination of a candidate gene and colinearity approach has successfully led to the identification of genes underlying agronomically important traits including virus resistances and plant architecture. Some of this knowledge has already been applied to marker assisted selection (MAS) programs, increasing precision and shortening the breeding cycle. Yet, complete translation of marker discovery to pea breeding is still to be achieved. Molecular analysis of pea collections has shown that although substantial variation is present within the cultivated genepool, wild material offers the possibility to incorporate novel traits that may have been inadvertently eliminated. Association mapping analysis of diverse pea germplasm promises to identify genetic variation related to desirable agronomic traits, which are historically difficult to breed for in a traditional manner. The availability of high throughput ‘omics’ methodologies offers great promise for the development of novel, highly accurate selective breeding tools for improved pea genotypes that are sustainable under current and future climates and farming systems.P.S. acknowledges financial support from the Ministry of Education of Czech Republic ME1006, ME10062, LA08011 and the Bioversity International AEGIS LOA 10/048 projects. J.M. acknowledges financial support from the Academy of Sciences of the Czech Republic (AVOZ50510513). T.D.W. acknowledges financial support from the Saskatchewan Pulse Growers and the Saskatchewan Ministry of Agriculture. C.J.C. acknowledges financial support from the United States Department of Agricultural, Agricultural Research Service

Additional file 1: of Cutaneous neurofibromas in Neurofibromatosis type I: a quantitative natural history study

Investigator guide for manual cutaneous neurofibroma measurement. (PDF 354 kb

Pea (Pisum sativum L.) in the Genomic Era

Pea (Pisum sativum L.) was the original model organism used in Mendel’s discovery (1866) of the laws of inheritance, making it the foundation of modern plant genetics. However, subsequent progress in pea genomics has lagged behind many other plant species. Although the size and repetitive nature of the pea genome has so far restricted its sequencing, comprehensive genomic and post genomic resources already exist. These include BAC libraries, several types of molecular marker sets, both transcriptome and proteome datasets and mutant populations for reverse genetics. The availability of the full genome sequences of three legume species has offered significant opportunities for genome wide comparison revealing synteny and co-linearity to pea. A combination of a candidate gene and colinearity approach has successfully led to the identification of genes underlying agronomically important traits including virus resistances and plant architecture. Some of this knowledge has already been applied to marker assisted selection (MAS) programs, increasing precision and shortening the breeding cycle. Yet, complete translation of marker discovery to pea breeding is still to be achieved. Molecular analysis of pea collections has shown that although substantial variation is present within the cultivated genepool, wild material offers the possibility to incorporate novel traits that may have been inadvertently eliminated. Association mapping analysis of diverse pea germplasm promises to identify genetic variation related to desirable agronomic traits, which are historically difficult to breed for in a traditional manner. The availability of high throughput ‘omics’ methodologies offers great promise for the development of novel, highly accurate selective breeding tools for improved pea genotypes that are sustainable under current and future climates and farming systems