Reciprocal regulation of the basic helix-loop-helix/Per-Arnt-Sim partner proteins, Arnt and Arnt2, during neuronal differentiation

Basic helix–loop–helix/Per–Arnt–Sim (bHLH/PAS) transcription factors function broadly in development, homeostasis and stress response. Active bHLH/PAS heterodimers consist of a ubiquitous signal-regulated subunit (e.g., hypoxia-inducible factors, HIF-1α/2α/3α; the aryl hydrocarbon receptor, AhR) or tissue-restricted subunit (e.g., NPAS1/3/4, Single Minded 1/2), paired with a general partner protein, aryl hydrocarbon receptor nuclear translocator (Arnt or Arnt2). We have investigated regulation of the neuron-enriched Arnt paralogue, Arnt2. We find high Arnt/Arnt2 ratios in P19 embryonic carcinoma cells and ES cells are dramatically reversed to high Arnt2/Arnt on neuronal differentiation. mRNA half-lives of Arnt and Arnt2 remain similar in both parent and neuronal differentiated cells. The GC-rich Arnt2 promoter, while heavily methylated in Arnt only expressing hepatoma cells, is methylation free in P19 and ES cells, where it is bivalent with respect to active H3K4me3 and repressive H3K27me3 histone marks. Typical of a ‘transcription poised’ developmental gene, H3K27me3 repressive marks are removed from Arnt2 during neuronal differentiation. Our data are consistent with a switch to predominant Arnt2 expression in neurons to allow specific functions of neuronal bHLH/PAS factors and/or to avoid neuronal bHLH/PAS factors from interfering with AhR/Arnt signalling.Nan Hao, Veronica L. D. Bhakti, Daniel J. Peet and Murray L. Whitela

Predictive Power Estimation Algorithm (PPEA) - A New Algorithm to Reduce Overfitting for Genomic Biomarker Discovery

Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA), which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1) PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2) the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3) using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4) more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses

BRAF V600E Mutations Are Common in Pleomorphic Xanthoastrocytoma: Diagnostic and Therapeutic Implications

Pleomorphic xanthoastrocytoma (PXA) is low-grade glial neoplasm principally affecting children and young adults. Approximately 40% of PXA are reported to recur within 10 years of primary resection. Upon recurrence, patients receive radiation therapy and conventional chemotherapeutics designed for high-grade gliomas. Genetic changes that can be targeted by selective therapeutics have not been extensively evaluated in PXA and ancillary diagnostic tests to help discriminate PXA from other pleomorphic and often more aggressive astrocytic malignancies are limited. In this study, we apply the SNaPshot multiplexed targeted sequencing platform in the analysis of brain tumors to interrogate 60 genetic loci that are frequently mutated in 15 cancer genes. In our analysis we detect BRAF V600E mutations in 12 of 20 (60%) WHO grade II PXA, in 1 of 6 (17%) PXA with anaplasia and in 1 glioblastoma arising in a PXA. Phospho-ERK was detected in all tumors independent of the BRAF mutation status. BRAF duplication was not detected in any of the PXA cases. BRAF V600E mutations were identified in only 2 of 71 (2.8%) glioblastoma (GBM) analyzed, including 1 of 9 (11.1%) giant cell GBM (gcGBM). The finding that BRAF V600E mutations are common in the majority of PXA has important therapeutic implications and may help in differentiating less aggressive PXAs from lethal gcGBMs and GBMs

BRAF V600E Mutations Are Common in Pleomorphic Xanthoastrocytoma: Diagnostic and Therapeutic Implications

Pleomorphic xanthoastrocytoma (PXA) is low-grade glial neoplasm principally affecting children and young adults. Approximately 40% of PXA are reported to recur within 10 years of primary resection. Upon recurrence, patients receive radiation therapy and conventional chemotherapeutics designed for high-grade gliomas. Genetic changes that can be targeted by selective therapeutics have not been extensively evaluated in PXA and ancillary diagnostic tests to help discriminate PXA from other pleomorphic and often more aggressive astrocytic malignancies are limited. In this study, we apply the SNaPshot multiplexed targeted sequencing platform in the analysis of brain tumors to interrogate 60 genetic loci that are frequently mutated in 15 cancer genes. In our analysis we detect BRAF V600E mutations in 12 of 20 (60%) WHO grade II PXA, in 1 of 6 (17%) PXA with anaplasia and in 1 glioblastoma arising in a PXA. Phospho-ERK was detected in all tumors independent of the BRAF mutation status. BRAF duplication was not detected in any of the PXA cases. BRAF V600E mutations were identified in only 2 of 71 (2.8%) glioblastoma (GBM) analyzed, including 1 of 9 (11.1%) giant cell GBM (gcGBM). The finding that BRAF V600E mutations are common in the majority of PXA has important therapeutic implications and may help in differentiating less aggressive PXAs from lethal gcGBMs and GBMs

Genomic reconstruction of the SARS-CoV-2 epidemic in England.

The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance data generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. The Alpha variant grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed the Alpha variant and eliminated nearly all other lineages in early 2021. Yet a series of variants (most of which contained the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. However, by accounting for sustained introductions, we found that the transmissibility of these variants is unlikely to have exceeded the transmissibility of the Alpha variant. Finally, B.1.617.2/Delta was repeatedly introduced in England and grew rapidly in early summer 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on 26 June 2021

The Properties of Simple Vs. Absolute Majority Rule: Cases Where Absences and Abstentions Are Important

Little attention has been paid to the differences between absolute majority rule and simple majority rule, which differ in their treatment of absences and ‘votes to abstain’. This article fills that gap by undertaking a probabilistic analysis of the two voting rules assuming two alternatives and a quorum requirement for simple majority rule. The rules are compared in both a modified sincere setting and a strategic setting using five criteria: (1) the Pareto criterion, (2) the BT criterion (Buchanan and Tullock, 1962), (3) the Expected Social Gain criterion, (4) the Responsiveness criterion, and (5) a modified version of Rae’s criterion. In the sincere setting, we find that simple majority rule (with and without a quorum) outperforms absolute majority rule under most conditions for four out of the five criteria. In the strategic setting, we find that the voting rules perform much more similarly.absolute majority rule; simple majority rule; social choice; voter turnout

A Nonequilibrium Analysis of Unanimity Rule, Majority Rule, and Pareto

It is widely held that in the absence of transaction costs unanimity rule is more effective at producing Pareto improvements and Pareto optimal outcomes than majority rule. We compare unanimity rule and majority rule in their ability to adhere to the Pareto criterion and to select Pareto-optimal alternatives using a single-dimensional spatial voting model without rational proposals. This produces two interesting results. First, if proposals are random, then majority rule is almost always more adept at selecting Pareto-optimal alternatives than unanimity rule. Second, if individuals propose their ideal points, then majority rule selects Pareto-optimal outcomes at least as well as unanimity rule. These results contrast with equilibrium analyses, which typically show that unanimity rule is the best voting procedure for maintaining Pareto optimality. (JEL D7, C61) Copyright 2005, Oxford University Press.

Majority Rule versus Supermajority Rules: Their Effects on Narrow and Broad Taxes

Buchanan and Tullock argue that larger supermajority rules reduce tyranny of the majority but should have no effect on the passage of mutually advantageous policies. The authors test this argument by separately analyzing the effect of supermajority requirements on taxes that are targeted toward narrow groups (more redistributive) and taxes targeted toward a broader base (less redistributive), in a panel of fifty states from 1970 to 2008. Regression analysis reveals an inverse relationship between narrow taxes and the size of the majority rule requirement and no relationship between broad taxes and the size of the majority requirement—consistent with the claim of Buchanan and Tullock. The authors also find that Democratic controlled governments have significantly higher tax rates on narrow taxes than Republican controlled governments. The reverse is found for broad taxes, but the result is not as strong.taxation; majority rule; constitutional economics; redistribution