Ancient technology and punctuated change: Detecting the emergence of the Edomite Kingdom in the Southern Levant.

While the punctuated equilibrium model has been employed in paleontological and archaeological research, it has rarely been applied for technological and social evolution in the Holocene. Using metallurgical technologies from the Wadi Arabah (Jordan/Israel) as a case study, we demonstrate a gradual technological development (13th-10th c. BCE) followed by a human agency-triggered punctuated "leap" (late-10th c. BCE) simultaneously across the entire region (an area of ~2000 km2). Here, we present an unparalleled, diachronic archaeometallurgical dataset focusing on elemental analysis of dozens of well-dated slag samples. Based on the results, we suggest punctuated equilibrium provides an innovative theoretical model for exploring ancient technological changes in relation to larger sociopolitical conditions-in the case at hand the emergence of biblical Edom-, exemplifying its potential for more general cross-cultural applications

A study of diabetes mellitus within a large sample of Australian twins.

Udgivelsesdato: 2008-FebTwin studies of diabetes mellitus can help elucidate genetic and environmental factors in etiology and can provide valuable biological samples for testing functional hypotheses, for example using expression and methylation studies of discordant pairs. We searched the volunteer Australian Twin Registry (19,387 pairs) for twins with diabetes using disease checklists from nine different surveys conducted from 1980-2000. After follow-up questionnaires to the twins and their doctors to confirm diagnoses, we eventually identified 46 pairs where one or both had type 1 diabetes (T1D), 113 pairs with type 2 diabetes (T2D), 41 female pairs with gestational diabetes (GD), 5 pairs with impaired glucose tolerance (IGT) and one pair with MODY. Heritabilities of T1D, T2D and GD were all high, but our samples did not have the power to detect effects of shared environment unless they were very large. Weight differences between affected and unaffected cotwins from monozygotic (MZ) discordant pairs were large for T2D and GD, but much larger again for discordant dizygotic (DZ) pairs. The bivariate genetic analysis (under the multifactorial threshold model) estimated the genetic correlation between body mass index (BMI) and T2D to be 0.46, and the environmental correlation at only 0.06

Synthetic lethal screening in the mammalian central nervous system identifies Gpx6 as a modulator of Huntington’s disease

Huntington’s disease, the most common inherited neurodegenerative disease, is characterized by a dramatic loss of deep-layer cortical and striatal neurons, as well as morbidity in midlife. Human genetic studies led to the identification of the causative gene, huntingtin. Recent genomic advances have also led to the identification of hundreds of potential interacting partners for huntingtin protein and many hypotheses as to the molecular mechanisms whereby mutant huntingtin leads to cellular dysfunction and death. However, the multitude of possible interacting partners and cellular pathways affected by mutant huntingtin has complicated efforts to understand the etiology of this disease, and to date no curative therapeutic exists. To address the general problem of identifying the disease-phenotype contributing genes from a large number of correlative studies, here we develop a synthetic lethal screening methodology for the mammalian central nervous system, called SLIC, for synthetic lethal in the central nervous system. Applying SLIC to the study of Huntington’s disease, we identify the age-regulated glutathione peroxidase 6 (Gpx6) gene as a modulator of mutant huntingtin toxicity and show that overexpression of Gpx6 can dramatically alleviate both behavioral and molecular phenotypes associated with a mouse model of Huntington’s disease. SLIC can, in principle, be used in the study of any neurodegenerative disease for which a mouse model exists, promising to reveal modulators of neurodegenerative disease in an unbiased fashion, akin to screens in simpler model organisms.National Institute of Neurological Disorders and Stroke (U.S.) (Award R01NS085880)William N. and Bernice E. Bumpus Foundation (Early Career Investigator Innovation Award)JPB FoundationEuropean Molecular Biology Organization (Long-term Fellowship

Using resource graphs to represent conceptual change

We introduce resource graphs, a representation of linked ideas used when reasoning about specific contexts in physics. Our model is consistent with previous descriptions of resources and coordination classes. It can represent mesoscopic scales that are neither knowledge-in-pieces or large-scale concepts. We use resource graphs to describe several forms of conceptual change: incremental, cascade, wholesale, and dual construction. For each, we give evidence from the physics education research literature to show examples of each form of conceptual change. Where possible, we compare our representation to models used by other researchers. Building on our representation, we introduce a new form of conceptual change, differentiation, and suggest several experimental studies that would help understand the differences between reform-based curricula.Comment: 27 pages, 14 figures, no tables. Submitted for publication to the Physical Review Special Topics Physics Education Research on March 8, 200

Evidence-based decision support for pediatric rheumatology reduces diagnostic errors.

BACKGROUND: The number of trained specialists world-wide is insufficient to serve all children with pediatric rheumatologic disorders, even in the countries with robust medical resources. We evaluated the potential of diagnostic decision support software (DDSS) to alleviate this shortage by assessing the ability of such software to improve the diagnostic accuracy of non-specialists. METHODS: Using vignettes of actual clinical cases, clinician testers generated a differential diagnosis before and after using diagnostic decision support software. The evaluation used the SimulConsult® DDSS tool, based on Bayesian pattern matching with temporal onset of each finding in each disease. The tool covered 5405 diseases (averaging 22 findings per disease). Rheumatology content in the database was developed using both primary references and textbooks. The frequency, timing, age of onset and age of disappearance of findings, as well as their incidence, treatability, and heritability were taken into account in order to guide diagnostic decision making. These capabilities allowed key information such as pertinent negatives and evolution over time to be used in the computations. Efficacy was measured by comparing whether the correct condition was included in the differential diagnosis generated by clinicians before using the software ( unaided ), versus after use of the DDSS ( aided ). RESULTS: The 26 clinicians demonstrated a significant reduction in diagnostic errors following introduction of the software, from 28% errors while unaided to 15% using decision support (p \u3c 0.0001). Improvement was greatest for emergency medicine physicians (p = 0.013) and clinicians in practice for less than 10 years (p = 0.012). This error reduction occurred despite the fact that testers employed an open book approach to generate their initial lists of potential diagnoses, spending an average of 8.6 min using printed and electronic sources of medical information before using the diagnostic software. CONCLUSIONS: These findings suggest that decision support can reduce diagnostic errors and improve use of relevant information by generalists. Such assistance could potentially help relieve the shortage of experts in pediatric rheumatology and similarly underserved specialties by improving generalists\u27 ability to evaluate and diagnose patients presenting with musculoskeletal complaints. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT02205086

Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma

Human cancers are complex ecosystems composed of cells with distinct phenotypes, genotypes, and epigenetic states, but current models do not adequately reflect tumor composition in patients. We used single-cell RNA sequencing (RNA-seq) to profile 430 cells from five primary glioblastomas, which we found to be inherently variable in their expression of diverse transcriptional programs related to oncogenic signaling, proliferation, complement/immune response, and hypoxia. We also observed a continuum of stemness-related expression states that enabled us to identify putative regulators of stemness in vivo. Finally, we show that established glioblastoma subtype classifiers are variably expressed across individual cells within a tumor and demonstrate the potential prognostic implications of such intratumoral heterogeneity. Thus, we reveal previously unappreciated heterogeneity in diverse regulatory programs central to glioblastoma biology, prognosis, and therapy.National Institutes of Health (U.S.) (U24 CA180922

Development of intuitive rules: Evaluating the application of the dual-system framework to understanding children's intuitive reasoning

This is an author-created version of this article. The original source of publication is Psychon Bull Rev. 2006 Dec;13(6):935-53 The final publication is available at www.springerlink.com Published version: http://dx.doi.org/10.3758/BF0321390

A Genome-Wide Analysis of Promoter-Mediated Phenotypic Noise in Escherichia coli

Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as “phenotypic noise.” In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alon

Hsp90 orchestrates transcriptional regulation by Hsf1 and cell wall remodelling by MAPK signalling during thermal adaptation in a pathogenic yeast

Acknowledgments We thank Rebecca Shapiro for creating CaLC1819, CaLC1855 and CaLC1875, Gillian Milne for help with EM, Aaron Mitchell for generously providing the transposon insertion mutant library, Jesus Pla for generously providing the hog1 hst7 mutant, and Cathy Collins for technical assistance.Peer reviewedPublisher PD

Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma

Although human tumours are shaped by the genetic evolution of cancer cells, evidence also suggests that they display hierarchies related to developmental pathways and epigenetic programs in which cancer stem cells (CSCs) can drive tumour growth and give rise to differentiated progeny. Yet, unbiased evidence for CSCs in solid human malignancies remains elusive. Here we profile 4,347 single cells from six IDH1 or IDH2 mutant human oligodendrogliomas by RNA sequencing (RNA-seq) and reconstruct their developmental programs from genome-wide expression signatures. We infer that most cancer cells are differentiated along two specialized glial programs, whereas a rare subpopulation of cells is undifferentiated and associated with a neural stem cell expression program. Cells with expression signatures for proliferation are highly enriched in this rare subpopulation, consistent with a model in which CSCs are primarily responsible for fuelling the growth of oligodendroglioma in humans. Analysis of copy number variation (CNV) shows that distinct CNV sub-clones within tumours display similar cellular hierarchies, suggesting that the architecture of oligodendroglioma is primarily dictated by developmental programs. Subclonal point mutation analysis supports a similar model, although a full phylogenetic tree would be required to definitively determine the effect of genetic evolution on the inferred hierarchies. Our single-cell analyses provide insight into the cellular architecture of oligodendrogliomas at single-cell resolution and support the cancer stem cell model, with substantial implications for disease management