Belonging: A Phenomenological Study of Systemic Racism Experienced Among Black Students in Occupational Therapy Programs

Belonging, a crucial aspect of humanity and justice, is negated by racism. Formal analyses have shown that racial and ethnic minorities experience significantly higher rates of racial discrimination, with the greatest disparity being among Blacks. Incidences of racism toward healthcare professionals of color indicate that comprehensive and unbiased academic content is warranted in occupational therapy education. This study explored the lived experiences of systemic racism among Black occupational therapy students and their preparation to deal with racism and bias within didactic and clinical settings. This study featured a phenomenological design with data collection through semi-structured interviews and focus groups. Transcripts were coded and inductively analyzed using Qualitative Data Analysis (QDA) Miner software, and intercoder agreement was established. Themes were organized using Wilcock\u27s Occupational Perspective of Health (OPH) framework (Doing, Being, Becoming, and Belonging). The results revealed that the prevailing themes that emerged were Anxiety from Lack of Black Representation, Education through Lived Experience, including family, media, and self-education, and Initiating Change as the Diversity Person. Participants’ sense of Belonging was most affected of all the constructs in the OPH. In conclusion, the tapestry of occupational therapy curricula may benefit from incorporating explicit threads addressing the lasting effects of historic and current systemic racism, thus severely limiting students’ awareness and comprehension of occupational injustices. Recommendations are outlined to identify gaps in current occupational therapy curricula and to guide occupational therapy administrators (Chairs/Program Directors) in developing programs that acknowledge, educate, and combat the effects of systemic racism, thereby enhancing the sense of belonging for all

Reconstructing and Classifying SDSS DR16 Galaxy Spectra with Machine-Learning and Dimensionality Reduction Algorithms

Optical spectra of galaxies and quasars from large cosmological surveys are used to measure redshifts and infer distances. They are also rich with information on the intrinsic properties of these astronomical objects. However, their physical interpretation can be challenging due to the substantial number of degrees of freedom, various sources of noise, and degeneracies between physical parameters that cause similar spectral characteristics. To gain deeper insights into these degeneracies, we apply two unsupervised machine learning frameworks to a sample from the Sloan Digital Sky Survey data release 16 (SDSS DR16). The first framework is a Probabilistic Auto-Encoder (PAE), a two-stage deep learning framework consisting of a data compression stage from 1000 elements to 10 parameters and a density estimation stage. The second framework is a Uniform Manifold Approximation and Projection (UMAP), which we apply to both the uncompressed and compressed data. Exploring across regions on the compressed data UMAP, we construct sequences of stacked spectra which show a gradual transition from star-forming galaxies with narrow emission lines and blue spectra to passive galaxies with absorption lines and red spectra. Focusing on galaxies with broad emission lines produced by quasars, we find a sequence with varying levels of obscuration caused by cosmic dust. The experiments we present here inform future applications of neural networks and dimensionality reduction algorithms for large astronomical spectroscopic surveys.Comment: ASP Conference Series, Compendium of Undergraduate Research in Astronomy and Space Science (accepted), 24 pages, 14 figure

Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads.

As metagenomic studies move to increasing numbers of samples, communities like the human gut may benefit more from the assembly of abundant microbes in many samples, rather than the exhaustive assembly of fewer samples. We term this approach leaderboard metagenome sequencing. To explore protocol optimization for leaderboard metagenomics in real samples, we introduce a benchmark of library prep and sequencing using internal references generated by synthetic long-read technology, allowing us to evaluate high-throughput library preparation methods against gold-standard reference genomes derived from the samples themselves. We introduce a low-cost protocol for high-throughput library preparation and sequencing

A Genome-Wide Assessment of the Ancestral Neural Crest Gene Regulatory Network

The neural crest (NC) is an embryonic cell population that contributes to key vertebrate-specific features including the craniofacial skeleton and peripheral nervous system. Here we examine the transcriptional and epigenomic profiles of NC cells in the sea lamprey, in order to gain insight into the ancestral state of the NC gene regulatory network (GRN). Transcriptome analyses identify clusters of co-regulated genes during NC specification and migration that show high conservation across vertebrates but also identify transcription factors (TFs) and cell-adhesion molecules not previously implicated in NC migration. ATAC-seq analysis uncovers an ensemble of cis-regulatory elements, including enhancers of Tfap2B, SoxE1 and Hox-α2 validated in the embryo. Cross-species deployment of lamprey elements identifies the deep conservation of lamprey SoxE1 enhancer activity, mediating homologous expression in jawed vertebrates. Our data provide insight into the core GRN elements conserved to the base of the vertebrates and expose others that are unique to lampreys

Educational Priorities for Children with Cri-Du-Chat Syndrome

There are few data on the educational needs of children with cri-du-chat syndrome: a neurodevelopmental disorder that affects learning and development. We therefore designed an Internet survey to identify parents’ educational priorities in relation to children’s level of need/ability. The survey listed 54 skills/behaviors (e.g., toileting, expresses wants and needs, and tantrums) representing 10 adaptive behavior domains (e.g., self-care, communication, and problem behavior). Parents rated their child’s current level of ability/performance with respect to each skill/behavior and indicated the extent to which training/treatment was a priority. Fifty-four surveys were completed during the 3-month data collection period. Parents identified nine high priority skills/behaviors. Results supported the view that parent priorities are often based on the child’s deficits and emergent skills, rather than on child strengths. Implications for educational practice include the need for competence to develop high priority skills/behaviors and the value of assessing children’s deficits and emergent skills to inform the content of individualized education plans

Individual common variants exert weak effects on the risk for autism spectrum disorders.

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest

Communication in Individuals with Rett Syndrome: an Assessment of Forms and Functions

In the present study we assessed the forms and functions of prelinguistic communicative behaviors for 120 children and adults with Rett syndrome using the Inventory of Potential Communicative Acts (IPCA) (Sigafoos et al. Communication Disorders Quarterly 21:77–86, 2000a). Informants completed the IPCA and the results were analysed to provide a systematic inventory and objective description of the communicative forms and functions present in each individual’s repertoire. Results show that respondents reported a wide variety of communicative forms and functions. By far most girls used prelinguistic communicative behaviors of which eye contact/gazing was the most common form. The most often endorsed communicative functions were social convention, commenting, answering, requesting and choice-making. Problematic topographies (e.g., self-injury, screaming, non-compliance) were being used for communicative purposes in 10 to 41% of the sample. Exploratory analyses revealed that several communicative forms and functions were related to living environment, presence/absence of epilepsy, and age. That is, higher percentages of girls who showed some forms/functions were found in those who lived at home, who had no epilepsy and who were relatively young