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Indigeneity and mestizaje in Luis Alberto Urrea's The Hummingbird's Daughter and Leslie Marmon Silko's Almanac of the Dead
textIn an attempt to narrow a perceived gap between two literary fields, this thesis provides a comparative analysis of Luis Alberto Urrea’s The Humminbird’s Daughter, and Leslie Marmon Silko’s Almanac of the Dead. I explore and critique the ways in which Luis Alberto Urrea mobilizes mestizaje and Chicana/o nationalist rhetoric. I argue that mestizaje stems from colonial representations that inscribe indigenous people into a narrative of erasure. Furthermore, I address Leslie Marmon Silko’s critique of mestizaje within Almanac of the Dead.Mexican American Studie
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Ancestry-Dependent Enrichment of Deleterious Homozygotes in Runs of Homozygosity.
Runs of homozygosity (ROH) are important genomic features that manifest when an individual inherits two haplotypes that are identical by descent. Their length distributions are informative about population history, and their genomic locations are useful for mapping recessive loci contributing to both Mendelian and complex disease risk. We have previously shown that ROH, and especially long ROH that are likely the result of recent parental relatedness, are enriched for homozygous deleterious coding variation in a worldwide sample of outbred individuals. However, the distribution of ROH in admixed populations and their relationship to deleterious homozygous genotypes is understudied. Here we analyze whole-genome sequencing data from 1,441 unrelated individuals from self-identified African American, Puerto Rican, and Mexican American populations. These populations are three-way admixed between European, African, and Native American ancestries and provide an opportunity to study the distribution of deleterious alleles partitioned by local ancestry and ROH. We re-capitulate previous findings that long ROH are enriched for deleterious variation genome-wide. We then partition by local ancestry and show that deleterious homozygotes arise at a higher rate when ROH overlap African ancestry segments than when they overlap European or Native American ancestry segments of the genome. These results suggest that, while ROH on any haplotype background are associated with an inflation of deleterious homozygous variation, African haplotype backgrounds may play a particularly important role in the genetic architecture of complex diseases for admixed individuals, highlighting the need for further study of these populations
When is it Safe for Patients to Drive after Right Total Hip Arthroplasty?
Introduction: Driving restrictions after total hip arthroplasty (THA) can be inconvenient and burdensome for patients. When patients may safely be allowed to drive remains controversial. Most studies recommend 6 weeks but recent advances in surgical approach, pain management and rapid recovery may have changed this time frame. The purpose of this study was to prospectively evaluate driving safety after THA through brake reaction time
Do We Still Need Clinical Language Models?
Although recent advances in scaling large language models (LLMs) have
resulted in improvements on many NLP tasks, it remains unclear whether these
models trained primarily with general web text are the right tool in highly
specialized, safety critical domains such as clinical text. Recent results have
suggested that LLMs encode a surprising amount of medical knowledge. This
raises an important question regarding the utility of smaller domain-specific
language models. With the success of general-domain LLMs, is there still a need
for specialized clinical models? To investigate this question, we conduct an
extensive empirical analysis of 12 language models, ranging from 220M to 175B
parameters, measuring their performance on 3 different clinical tasks that test
their ability to parse and reason over electronic health records. As part of
our experiments, we train T5-Base and T5-Large models from scratch on clinical
notes from MIMIC III and IV to directly investigate the efficiency of clinical
tokens. We show that relatively small specialized clinical models substantially
outperform all in-context learning approaches, even when finetuned on limited
annotated data. Further, we find that pretraining on clinical tokens allows for
smaller, more parameter-efficient models that either match or outperform much
larger language models trained on general text. We release the code and the
models used under the PhysioNet Credentialed Health Data license and data use
agreement
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