The Effects of the Online Remediation of Phonological Processing Deficits on Functional Reading Abilities in Students With Dyslexia

Dyslexia affects between 5% and 18% of Americans and is caused by difficulty with phonological processing. This study investigates the impact of an online intervention designed to remediate phonological processing deficits on reading accuracy, fluency, and comprehension. It also investigates changes to student self-concept and parent perceptions of their children’s reading attitudes and abilities as a result of the online intervention. Ten students participated in the intervention; assessments were administered at the beginning and at the midpoint of the treatment. Scores in Phonological Processing and Alternate Phonological Processing, as measured by the CTOPP-2, demonstrated large to very large effect sizes, indicating that the intervention improves students’ abilities to perceive and manipulate the individual sounds in words, which is the foundation of good reading. Functional reading abilities (accuracy, fluency, and comprehension) were measured using the WIAT-IV. At the midpoint of the intervention, these scores demonstrated effect sizes that were small to moderate. Parents noted qualitative changes in their children\u27s attitudes toward reading, including a greater willingness to read in general. The Piers-Harris SelfConcept Scale did not demonstrate significant changes to student self-concept

Apraxia of Speech: Change in Error Consistency Following a Multimodal intensive Treatment (MMiT)

Historically, error inconsistency has been considered a defining feature of AOS. While recent studies have demonstrated consistency of certain errors over time, changes following intervention have not been reported. Therefore, we examined error consistency across successive repetitions of the same utterance following 120 hours of Multimodal intensive Treatment (MMiT). Three males with AOS and aphasia produced three repetitions of 10 target words before and after treatment. SLP evaluations of transcribed responses revealed increased consistency of error location across all participants and increased consistency in error number across successive responses. Further investigation of MMiT in relation to these findings is warranted

Predictors of chronic breathlessness: a large population study

<p>Abstract</p> <p>Background</p> <p>Breathlessness causes significant burden in our community but the underlying socio-demographic and lifestyle factors that may influence it are not well quantified. This study aims to define these predictors of chronic breathlessness at a population level.</p> <p>Methods</p> <p>Data were collected from adult South Australians in 2007 and 2008 (n = 5331) as part of a face-to-face, cross-sectional, whole-of-population, multi-stage, systematic area sampling population health survey. The main outcome variable was breathlessness in logistic regression models. Lifestyle factors examined included smoking history, smoke-free housing, level of physical activity and body mass index (obesity).</p> <p>Results</p> <p>The participation rate was 64.1%, and 11.1% of individuals (15.0% if aged ≥50 years) chronically had breathlessness that limited exertion. Significant bivariate associations with chronic breathlessness for the whole population and only those ≥50 included: increasing age; female gender; being separated/divorced/widowed; social disadvantage; smoking status; those without a smoke-free home; low levels of physical activity; and obesity. In multi-variate analyses adjusted for age, marital status (p < 0.001), physical activity (p < 0.001), obesity (p < 0.001), gender (p < 0.05) and social disadvantage (p < 0.05) remained significant factors. Smoking history was <it>not </it>a significant contributor to the model.</p> <p>Conclusions</p> <p>There is potential benefit in addressing reversible lifestyle causes of breathlessness including high body mass index (obesity) and low levels of physical activity in order to decrease the prevalence of chronic breathlessness. Clinical intervention studies for chronic breathlessness should consider stratification by body mass index.</p

Predicting ore content throughout a machine learning procedure – An Sn-W enrichment case study

The distribution patterns of trace elements are a very useful tool for the prediction of mineral deposits occurrence and possible future exploitation. Machine learning techniques were used for the computation of adequate models in trace elements’ prediction. The main subject of this research is to define an adequate model to predict the amounts of Sn and W in the abandoned mine area of Lardosa (Central Portugal). The geochemical composition of 333 stream sediment samples collected in the study area was used. Total concentrations of As, B, Be, Cd, Co, Cr, Cu, Fe, Ni, P, Sn, U, V, W, Y, and Zn were used to define the best prediction model. Different machine learning techniques were tested: decision trees (CART), multilayer perceptron (MLP) and support vector machines (SVM) For regression and clustering, CART, MLP and SVM for the classification problem. These algorithms were used with six different inputs – N1 to N6 - to pick out the best-performing model. The results indicate that CART achieves the best predictions for Sn and W. In the regression process, correlation coefficients of 0.67 for Sn (with Input N1) and 0.70 28 for W (with Input N3) were obtained. Regarding the classification problem, an error rate of 0.10 for both Sn (Input N1) and W (Input N2) was reached. The classification process is the best methodology to use in the prediction of Sn and W using the trace element concentration of stream sediments from Lardosa area.Thanks are due to Prof. M.R. Machado Leite for the use of data on stream sediments from Instituto Geológico e Mineiro, S. Mamede de Infesta (Portugal). C. Iglesias acknowledges the Spanish Ministry of Education, Culture and Sports for FPU 12/02283 grant. This research was carried out under the CERENA/FEUP (Natural resources and Environment Center), Portugal. The author acknowledges the funding provided by the Institute of Earth Sciences (ICT), under contracts UID/ GEO/04683/2013 with FCT (the Portuguese Science and Technology Foundation) and COMPETE POCI-01-0145-FEDER-007690

A Digital Repository and Execution Platform for Interactive Scholarly Publications in Neuroscience

The CARMEN Virtual Laboratory (VL) is a cloud-based platform which allows neuroscientists to store, share, develop, execute, reproduce and publicise their work. This paper describes new functionality in the CARMEN VL: an interactive publications repository. This new facility allows users to link data and software to publications. This enables other users to examine data and software associated with the publication and execute the associated software within the VL using the same data as the authors used in the publication. The cloud-based architecture and SaaS (Software as a Service) framework allows vast data sets to be uploaded and analysed using software services. Thus, this new interactive publications facility allows others to build on research results through reuse. This aligns with recent developments by funding agencies, institutions, and publishers with a move to open access research. Open access provides reproducibility and verification of research resources and results. Publications and their associated data and software will be assured of long-term preservation and curation in the repository. Further, analysing research data and the evaluations described in publications frequently requires a number of execution stages many of which are iterative. The VL provides a scientific workflow environment to combine software services into a processing tree. These workflows can also be associated with publications and executed by users. The VL also provides a secure environment where users can decide the access rights for each resource to ensure copyright and privacy restrictions are met

Estimating Marginal Healthcare Costs Using Genetic Variants as Instrumental Variables: Mendelian Randomization in Economic Evaluation

Accurate measurement of the marginal healthcare costs associated with different diseases and health conditions is important, especially for increasingly prevalent conditions such as obesity. However, existing observational study designs cannot identify the causal impact of disease on healthcare costs. This paper explores the possibilities for causal inference offered by Mendelian Randomization, a form of instrumental variable analysis that uses genetic variation as a proxy for modifiable risk exposures, to estimate the effect of health conditions on cost. Well-conducted genome-wide association studies provide robust evidence of the associations of genetic variants with health conditions or disease risk factors. The subsequent causal effects of these health conditions on cost can be estimated by using genetic variants as instruments for the health conditions. This is because the approximately random allocation of genotypes at conception means that many genetic variants are orthogonal to observable and unobservable confounders. Datasets with linked genotypic and resource use information obtained from electronic medical records or from routinely collected administrative data are now becoming available, and will facilitate this form of analysis. We describe some of the methodological issues that arise in this type of analysis, which we illustrate by considering how Mendelian Randomization could be used to estimate the causal impact of obesity, a complex trait, on healthcare costs. We describe some of the data sources that could be used for this type of analysis. We conclude by considering the challenges and opportunities offered by Mendelian Randomization for economic evaluation

Dearth and the English revolution : the harvest crisis of 1647-50

This article reconstructs the nature and scale of dearth in the late 1640s, emphasizing the coincidence of economic distress with constitutional crisis. It reconsiders the parish register evidence for subsistence crisis; examines the responses of central and local government; analyses the role of popular agency, especially though petitioning campaigns, in prompting reluctant magistrates to regulate the grain markets along lines stipulated by the late Elizabethan and early Stuart dearth orders, which had not been proclaimed since 1630; and accordingly suggests that the late 1640s represents a missing link in the historiography of responses to harvest failure

Second Language Processing Shows Increased Native-Like Neural Responses after Months of No Exposure

Although learning a second language (L2) as an adult is notoriously difficult, research has shown that adults can indeed attain native language-like brain processing and high proficiency levels. However, it is important to then retain what has been attained, even in the absence of continued exposure to the L2—particularly since periods of minimal or no L2 exposure are common. This event-related potential (ERP) study of an artificial language tested performance and neural processing following a substantial period of no exposure. Adults learned to speak and comprehend the artificial language to high proficiency with either explicit, classroom-like, or implicit, immersion-like training, and then underwent several months of no exposure to the language. Surprisingly, proficiency did not decrease during this delay. Instead, it remained unchanged, and there was an increase in native-like neural processing of syntax, as evidenced by several ERP changes—including earlier, more reliable, and more left-lateralized anterior negativities, and more robust P600s, in response to word-order violations. Moreover, both the explicitly and implicitly trained groups showed increased native-like ERP patterns over the delay, indicating that such changes can hold independently of L2 training type. The results demonstrate that substantial periods with no L2 exposure are not necessarily detrimental. Rather, benefits may ensue from such periods of time even when there is no L2 exposure. Interestingly, both before and after the delay the implicitly trained group showed more native-like processing than the explicitly trained group, indicating that type of training also affects the attainment of native-like processing in the brain. Overall, the findings may be largely explained by a combination of forgetting and consolidation in declarative and procedural memory, on which L2 grammar learning appears to depend. The study has a range of implications, and suggests a research program with potentially important consequences for second language acquisition and related fields

Elective cancer surgery in COVID-19-free surgical pathways during the SARS-CoV-2 pandemic: An international, multicenter, comparative cohort study

PURPOSE As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19–free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19–free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19–free surgical pathways. Patients who underwent surgery within COVID-19–free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19–free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score–matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19–free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION Within available resources, dedicated COVID-19–free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks