The Trauma of Broad-Based Inclusion for Students with Autism

Inclusion is a model where students with disabilities spend most/all of their time in an educational setting with non-disabled students. This model has led many countries to pass laws requiring disabled students be educated in the least restrictive environment: they should be educated with students without disabilities to the maximum extent possible. However, this model ignores the very nature of Autism Spectrum Disorder (ASD). The autistic brain is different in both function and structure, making deficits in social interaction, inherent and appropriate for their development. This paper explores research on the autistic brain, comorbidities, child development, and trauma associated with forced inclusion for this population. Research on brain function indicates inclusion can be very stressful and can produce anxiety and post-traumatic stress in children with ASD

Do Virtual Classrooms Encroach on Family Privacy Rights?

On August 27, a 12-year-old boy in Colorado flashed a toy gun, emblazoned with the words “Zombie Hunter,” across the screen during his virtual art class.1 The school’s vice principal later called the boy’s mother to inform her that a police officer was on the way to her house.2 The boy was suspended from school for a week, and now has a record with the El Paso County Sherriff’s Office and a mark on his school paperwork saying that he brought a “facsimile of a firearm to school.”3 The boy’s mother, in an interview with The Washington Post, noted that the school had been recording the students in class without parental consent, although the school claimed the recording function was only used for the first week of classes.4 Further privacy concerns have arisen from such incidents as an 11-year-old at a different Colorado school was suspended for four days over handling an Airsoft gun during a Zoom session,5 as well as a multitude of incidents involving outsiders interrupting classes by doing such things as shouting the teacher’s home address or exposing themselves to the students in the class. This post was originally published on the Cardozo Arts & Entertainment Law Journal website on September 29, 2020. The original post can be accessed via the Archived Link button above

Estimating Stellar Parameters from Spectra using a Hierarchical Bayesian Approach

A method is developed for fitting theoretically predicted astronomical spectra to an observed spectrum. Using a hierarchical Bayesian principle, the method takes both systematic and statistical measurement errors into account, which has not been done before in the astronomical literature. The goal is to estimate fundamental stellar parameters and their associated uncertainties. The non-availability of a convenient deterministic relation between stellar parameters and the observed spectrum, combined with the computational complexities this entails, necessitate the curtailment of the continuous Bayesian model to a reduced model based on a grid of synthetic spectra. A criterion for model selection based on the so-called predictive squared error loss function is proposed, together with a measure for the goodness-of-fit between observed and synthetic spectra. The proposed method is applied to the infrared 2.38--2.60 \mic ISO-SWS data (Infrared Space Observatory - Short Wavelength Spectrometer) of the star $\alpha$ Bootis, yielding estimates for the stellar parameters: effective temperature \Teff = 4230 $\pm$ 83 K, gravity $\log$ g = 1.50 $\pm$ 0.15 dex, and metallicity [Fe/H] = $-0.30 \pm 0.21$ dex.Comment: 15 pages, 8 figures, 5 tables. Accepted for publication in MNRA

Simultaneous mapping of multiple gene loci with pooled segregants

The analysis of polygenic, phenotypic characteristics such as quantitative traits or inheritable diseases remains an important challenge. It requires reliable scoring of many genetic markers covering the entire genome. The advent of high-throughput sequencing technologies provides a new way to evaluate large numbers of single nucleotide polymorphisms (SNPs) as genetic markers. Combining the technologies with pooling of segregants, as performed in bulked segregant analysis (BSA), should, in principle, allow the simultaneous mapping of multiple genetic loci present throughout the genome. The gene mapping process, applied here, consists of three steps: First, a controlled crossing of parents with and without a trait. Second, selection based on phenotypic screening of the offspring, followed by the mapping of short offspring sequences against the parental reference. The final step aims at detecting genetic markers such as SNPs, insertions and deletions with next generation sequencing (NGS). Markers in close proximity of genomic loci that are associated to the trait have a higher probability to be inherited together. Hence, these markers are very useful for discovering the loci and the genetic mechanism underlying the characteristic of interest. Within this context, NGS produces binomial counts along the genome, i.e., the number of sequenced reads that matches with the SNP of the parental reference strain, which is a proxy for the number of individuals in the offspring that share the SNP with the parent. Genomic loci associated with the trait can thus be discovered by analyzing trends in the counts along the genome. We exploit the link between smoothing splines and generalized mixed models for estimating the underlying structure present in the SNP scatterplots

beadarrayFilter : an R package to filter beads

Microarrays enable the expression levels of thousands of genes to be measured simultaneously. However, only a small fraction of these genes are expected to be expressed under different experimental conditions. Nowadays, filtering has been introduced as a step in the microarray preprocessing pipeline. Gene filtering aims at reducing the dimensionality of data by filtering redundant features prior to the actual statistical analysis. Previous filtering methods focus on the Affymetrix platform and can not be easily ported to the Illumina platform. As such, we developed a filtering method for Illumina bead arrays. We developed an R package, beadarrayFilter, to implement the latter method. In this paper, the main functions in the package are highlighted and using many examples, we illustrate how beadarrayFilter can be used to filter bead arrays

Multi-state models for the analysis of time-to-treatment modification among HIV patients under highly active antiretroviral therapy in Southwest Ethiopia

Background Highly active antiretroviral therapy (HAART) has shown a dramatic change in controlling the burden of HIV/AIDS. However, the new challenge of HAART is to allow long-term sustainability. Toxicities, comorbidity, pregnancy, and treatment failure, among others, would result in frequent initial HAART regimen change. The aim of this study was to evaluate the durability of first line antiretroviral therapy and to assess the causes of initial highly active antiretroviral therapeutic regimen changes among patients on HAART. Methods A Hospital based retrospective study was conducted from January 2007 to August 2013 at Jimma University Hospital, Southwest Ethiopia. Data on the prescribed ARV along with start date, switching date, and reason for change was collected. The primary outcome was defined as the time-to-treatment change. We adopted a multi-state survival modeling approach assuming each treatment regimen as state. We estimate the transition probability of patients to move from one regimen to another. Result A total of 1284 ART naive patients were included in the study. Almost half of the patients (41.2%) changed their treatment during follow up for various reasons; 442 (34.4%) changed once and 86 (6.69%) changed more than once. Toxicity was the most common reason for treatment changes accounting for 48.94% of the changes, followed by comorbidity (New TB) 14.31%. The HAART combinations that were robust to treatment changes were tenofovir (TDF) + lamivudine (3TC)+ efavirenz (EFV), tenofovir + lamivudine (3TC) + nevirapine (NVP) and zidovudine (AZT) + lamivudine (3TC) + nevirapine (NVP) with 3.6%, 4.5% and 11% treatment changes, respectively. Conclusion Moving away from drugs with poor safety profiles, such as stavudine(d4T), could reduce modification rates and this would improve regimen tolerability, while preserving future treatment options

Using transcriptomics to guide lead optimization in drug discovery projects : lessons learned from the QSTAR project

The pharmaceutical industry is faced with steadily declining R&D efficiency which results in fewer drugs reaching the market despite increased investment. A major cause for this low efficiency is the failure of drug candidates in late-stage development owing to safety issues or previously undiscovered side-effects. We analyzed to what extent gene expression data can help to de-risk drug development in early phases by detecting the biological effects of compounds across disease areas, targets and scaffolds. For eight drug discovery projects within a global pharmaceutical company, gene expression data were informative and able to support go/no-go decisions. Our studies show that gene expression profiling can detect adverse effects of compounds, and is a valuable tool in early-stage drug discovery decision making

Choice of initial antiretroviral drugs and treatment outcomes among HIV-infected patients in sub-Saharan Africa: systematic review and meta-analysis of observational studies

Background: The effectiveness of antiretroviral therapy (ART) depends on the choice of regimens during initiation. Most evidences from developed countries indicated that there is difference between efavirenz (EFV) and nevirapine (NVP). However, the evidences are limited in resource poor countries particularly in Africa. Thus, this systematic review and meta-analysis was carried out to summarize reported long-term treatment outcomes among people on first line therapy in sub-Saharan Africa. Methods: Observational studies that reported odds ratio, relative risk, hazard ratio, or standardized incidence ratio to compare risk of treatment failure among HIV/AIDS patients who initiated ART with EFV versus NVP were systematically searched. Searches were conducted using the MEDLINE database within PubMed, Google Scholar, HINARI, and Research Gates between 2007 and 2016. Information was extracted using standardized form. Pooled risk ratios (RR) and 95% confidence intervals (CI) were calculated using random-effect, generic inverse variance method. Result: A total of 6394 articles were identified, of which, 29 were eligible for review and abstraction in sub-Saharan Africa. Seventeen articles were used for the meta-analysis. Of a total of 121,092 independent study participants, 76,719 (63.36%) were females. Of these, 40,480 (33.43%) initiated with NVP containing regimen. Two studies did not report the median CD4 cell counts at initiation. Patients who have low CD4 cell counts initiated with EFV containing regimen. The pooled effect size indicated that treatment failure was reduced by 15%, 0.85 (95%CI: 0.75–0.98), and non-nucleoside reverse transcriptase inhibitor (NNRTI) switch was reduced by 43%, 0.57 (95%CI: 0.37–0.89). Conclusion: The risk of treatment failure and NNRTI switch were lower in patients who initiated with EFV than NVP-containing regimen. The review suggests that initiation of patients with EFV-containing regimen will reduce treatment failure and NNRTI switch