Osteology of the Crow Creek Massacre

About 1325 AD in south-central South Dakota nearly 500 American Indians were massacred at the Crow Creek Site. They were mutilated, exposed above ground, then buried in the fortification ditch which surrounded the Crow Creek Village. Their remains were discovered, excavated, and cleaned in 1978 and were available for study the first 5 months of 1979. The general purposes of the Crow Creek osteological study were to describe the remains as fully as time permitted and compare these results with those of other samples. This dissertation presents information concerning the Crow Creek bone elements, paleodemography, cranial affiliations, mutilations, and stature. It emphasizes the unique features of the sample and compares the Crow Creek sample with other skeletal samples from the Plains. The major findings can be summarized as follows: At least 486 Arikara were buried, that number probably constituting roughly 60 percent of the village inhabitants. Many of the smaller, more distal and more cancellous bone elements are under-represented, and many bones show indications of chewing, snapping, and splintering. There are some indications that some of the elements were preferentially placed in the ditch though these indications are slight. There are fewer young adult females and old adult males present in the sample than expected. A number of explanations for their absence are possible, but the raiders taking captives seems a most likely explanation for the missing young women. There are many mutilations on the bones. Scalping, skull fractures, evulsions, and decapitations are common. Cranial measurements indicate the Crow Creek sample were Arikara Indians and otherwise most similar to the Pawnee and St. Helena samples. There appear to be no morphologically alien skulls in the sample and no kin affiliated burial placement of the skulls. The Crow Creek sample was shorter than subsequent Arikara samples, but only the females were significantly shorter. Their stature may indicate dietary insufficiencies and illnesses, but additional testing of this hypothesis is necessary

MARCKS regulates growth and radiation sensitivity and is a novel prognostic factor for glioma

Purpose This study assessed whether Myristoylated Alanine Rich C-Kinase Substrate (MARCKS) can regulate glioblastoma (GBM) growth, radiation sensitivity and clinical outcome. Experimental Design MARCKS protein levels were analyzed in five GBM explant cell lines and eight patient-derived xenograft tumors by immunoblot, and these levels were correlated to proliferation rates and intracranial growth rates, respectively. Manipulation of MARCKS protein levels was assessed by lentiviral-mediated shRNA knockdown in the U251 cell line and MARCKS over-expression in the U87 cell line. The effect of manipulation of MARCKS on proliferation, radiation sensitivity and senescence was assessed. MARCKS gene expression was correlated with survival outcomes in the Repository of Molecular Brain Neoplasia Data (REMBRANDT) Database and The Cancer Genome Atlas (TCGA). Results MARCKS protein expression was inversely correlated with GBM proliferation and intracranial xenograft growth rates. Genetic silencing of MARCKS promoted GBM proliferation and radiation resistance, while MARCKS overexpression greatly reduced GBM growth potential and induced senescence. We found MARCKS gene expression to be directly correlated with survival in both the REMBRANDT and TCGA databases. Specifically, patients with high MARCKS expressing tumors of the Proneural molecular subtype had significantly increased survival rates. This effect was most pronounced in tumors with unmethylated O6-methylguanine DNA methyltransferase (MGMT) promoters, a traditionally poor prognostic factor. Conclusions MARCKS levels impact GBM growth and radiation sensitivity. High MARCKS expressing GBM tumors are associated with improved survival, particularly with unmethylated MGMT promoters. These findings suggest the use of MARCKS as a novel target and biomarker for prognosis in the Proneural subtype of GBM

The Dark Side of the Electroweak Phase Transition

Recent data from cosmic ray experiments may be explained by a new GeV scale of physics. In addition the fine-tuning of supersymmetric models may be alleviated by new O(GeV) states into which the Higgs boson could decay. The presence of these new, light states can affect early universe cosmology. We explore the consequences of a light (~ GeV) scalar on the electroweak phase transition. We find that trilinear interactions between the light state and the Higgs can allow a first order electroweak phase transition and a Higgs mass consistent with experimental bounds, which may allow electroweak baryogenesis to explain the cosmological baryon asymmetry. We show, within the context of a specific supersymmetric model, how the physics responsible for the first order phase transition may also be responsible for the recent cosmic ray excesses of PAMELA, FERMI etc. We consider the production of gravity waves from this transition and the possible detectability at LISA and BBO

The Reproducibility of Lists of Differentially Expressed Genes in Microarray Studies

Reproducibility is a fundamental requirement in scientific experiments and clinical contexts. Recent publications raise concerns about the reliability of microarray technology because of the apparent lack of agreement between lists of differentially expressed genes (DEGs). In this study we demonstrate that (1) such discordance may stem from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion, the lists become much more reproducible, especially when fewer genes are selected; and (3) the instability of short DEG lists based on P cutoffs is an expected mathematical consequence of the high variability of the t-values. We recommend the use of FC ranking plus a non-stringent P cutoff as a baseline practice in order to generate more reproducible DEG lists. The FC criterion enhances reproducibility while the P criterion balances sensitivity and specificity

RNAseq analysis of bronchial epithelial cells to identify COPD-associated genes and SNPs

Abstract Background There is a need for more powerful methods to identify low-effect SNPs that contribute to hereditary COPD pathogenesis. We hypothesized that SNPs contributing to COPD risk through cis-regulatory effects are enriched in genes comprised by bronchial epithelial cell (BEC) expression patterns associated with COPD. Methods To test this hypothesis, normal BEC specimens were obtained by bronchoscopy from 60 subjects: 30 subjects with COPD defined by spirometry (FEV1/FVC < 0.7, FEV1% < 80%), and 30 non-COPD controls. Targeted next generation sequencing was used to measure total and allele-specific expression of 35 genes in genome maintenance (GM) genes pathways linked to COPD pathogenesis, including seven TP53 and CEBP transcription factor family members. Shrinkage linear discriminant analysis (SLDA) was used to identify COPD-classification models. COPD GWAS were queried for putative cis-regulatory SNPs in the targeted genes. Results On a network basis, TP53 and CEBP transcription factor pathway gene pair network connections, including key DNA repair gene ERCC5, were significantly different in COPD subjects (e.g., Wilcoxon rank sum test for closeness, p-value = 5.0E-11). ERCC5 SNP rs4150275 association with chronic bronchitis was identified in a set of Lung Health Study (LHS) COPD GWAS SNPs restricted to those in putative regulatory regions within the targeted genes, and this association was validated in the COPDgene non-hispanic white (NHW) GWAS. ERCC5 SNP rs4150275 is linked (D’ = 1) to ERCC5 SNP rs17655 which displayed differential allelic expression (DAE) in BEC and is an expression quantitative trait locus (eQTL) in lung tissue (p = 3.2E-7). SNPs in linkage (D’ = 1) with rs17655 were predicted to alter miRNA binding (rs873601). A classifier model that comprised gene features CAT, CEBPG, GPX1, KEAP1, TP73, and XPA had pooled 10-fold cross-validation receiver operator characteristic area under the curve of 75.4% (95% CI: 66.3%–89.3%). The prevalence of DAE was higher than expected (p = 0.0023) in the classifier genes. Conclusions GM genes comprised by COPD-associated BEC expression patterns were enriched for SNPs with cis-regulatory function, including a putative cis-rSNP in ERCC5 that was associated with COPD risk. These findings support additional total and allele-specific expression analysis of gene pathways with high prior likelihood for involvement in COPD pathogenesis.https://deepblue.lib.umich.edu/bitstream/2027.42/142723/1/12890_2018_Article_603.pd

Estimates of Burden and Consequences of Infants Born Small for Gestational Age in Low and Middle Income Countries with INTERGROWTH-21(st) Standard: Analysis of CHERG Datasets.

Objectives To estimate small for gestational age birth prevalence and attributable neonatal mortality in low and middle income countries with the INTERGROWTH-21st birth weight standard. Design Secondary analysis of data from the Child Health Epidemiology Reference Group (CHERG), including 14 birth cohorts with gestational age, birth weight, and neonatal follow-up. Small for gestational age was defined as infants weighing less than the 10th centile birth weight for gestational age and sex with the multiethnic, INTERGROWTH-21st birth weight standard. Prevalence of small for gestational age and neonatal mortality risk ratios were calculated and pooled among these datasets at the regional level. With available national level data, prevalence of small for gestational age and population attributable fractions of neonatal mortality attributable to small for gestational age were estimated. Setting CHERG birth cohorts from 14 population based sites in low and middle income countries. Main outcome measures In low and middle income countries in the year 2012, the number and proportion of infants born small for gestational age; number and proportion of neonatal deaths attributable to small for gestational age; the number and proportion of neonatal deaths that could be prevented by reducing the prevalence of small for gestational age to 10%. Results In 2012, an estimated 23.3 million infants (uncertainty range 17.6 to 31.9; 19.3% of live births) were born small for gestational age in low and middle income countries. Among these, 11.2 million (0.8 to 15.8) were term and not low birth weight (≥2500 g), 10.7 million (7.6 to 15.0) were term and low birth weight (\u3c2500 g) and 1.5 million (0.9 to 2.6) were preterm. In low and middle income countries, an estimated 606 500 (495 000 to 773 000) neonatal deaths were attributable to infants born small for gestational age, 21.9% of all neonatal deaths. The largest burden was in South Asia, where the prevalence was the highest (34%); about 26% of neonatal deaths were attributable to infants born small for gestational age. Reduction of the prevalence of small for gestational age from 19.3% to 10.0% in these countries could reduce neonatal deaths by 9.2% (254 600 neonatal deaths; 164 800 to 449 700). Conclusions In low and middle income countries, about one in five infants are born small for gestational age, and one in four neonatal deaths are among such infants. Increased efforts are required to improve the quality of care for and survival of these high risk infants in low and middle income countrie

The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies

<p>Abstract</p> <p>Background</p> <p>Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature. The resultant variety of existing and emerging methods exacerbates confusion and continuing debate in the microarray community on the appropriate choice of methods for identifying reliable DEG lists.</p> <p>Results</p> <p>Using the data sets generated by the MicroArray Quality Control (MAQC) project, we investigated the impact on the reproducibility of DEG lists of a few widely used gene selection procedures. We present comprehensive results from inter-site comparisons using the same microarray platform, cross-platform comparisons using multiple microarray platforms, and comparisons between microarray results and those from TaqMan – the widely regarded "standard" gene expression platform. Our results demonstrate that (1) previously reported discordance between DEG lists could simply result from ranking and selecting DEGs solely by statistical significance (<it>P</it>) derived from widely used simple <it>t</it>-tests; (2) when fold change (FC) is used as the ranking criterion with a non-stringent <it>P</it>-value cutoff filtering, the DEG lists become much more reproducible, especially when fewer genes are selected as differentially expressed, as is the case in most microarray studies; and (3) the instability of short DEG lists solely based on <it>P</it>-value ranking is an expected mathematical consequence of the high variability of the <it>t</it>-values; the more stringent the <it>P</it>-value threshold, the less reproducible the DEG list is. These observations are also consistent with results from extensive simulation calculations.</p> <p>Conclusion</p> <p>We recommend the use of FC-ranking plus a non-stringent <it>P </it>cutoff as a straightforward and baseline practice in order to generate more reproducible DEG lists. Specifically, the <it>P</it>-value cutoff should not be stringent (too small) and FC should be as large as possible. Our results provide practical guidance to choose the appropriate FC and <it>P</it>-value cutoffs when selecting a given number of DEGs. The FC criterion enhances reproducibility, whereas the <it>P </it>criterion balances sensitivity and specificity.</p

Up, down, near, far: an online vestibular contribution to distance judgement

Whether a visual stimulus seems near or far away depends partly on its vertical elevation. Contrasting theories suggest either that perception of distance could vary with elevation, because of memory of previous upwards efforts in climbing to overcome gravity, or because of fear of falling associated with the downwards direction. The vestibular system provides a fundamental signal for the downward direction of gravity, but the relation between this signal and depth perception remains unexplored. Here we report an experiment on vestibular contributions to depth perception, using Virtual Reality. We asked participants to judge the absolute distance of an object presented on a plane at different elevations during brief artificial vestibular inputs. Relative to distance estimates collected with the object at the level of horizon, participants tended to overestimate distances when the object was presented above the level of horizon and the head was tilted upward and underestimate them when the object was presented below the level of horizon. Interestingly, adding artificial vestibular inputs strengthened these distance biases, showing that online multisensory signals, and not only stored information, contribute to such distance illusions. Our results support the gravity theory of depth perception, and show that vestibular signals make an on-line contribution to the perception of effort, and thus of distance