Modern American populism: Analyzing the economics behind the Silent Majority, the Tea Party and Trumpism

This article researches populism, more specifically, Modern American Populism (MAP), constructed of white, rural, and economically oppressed reactionarianism, which was borne out of the political upheaval of the 1960’s Civil Rights movement. The research looks to explain the causes of populism and what leads voters to support populist movements and politicians. The research focuses on economic anxiety as the main cause but also examines an alternative theory of racial resentment. In an effort to answer the question, what causes populist movements and motivations, I apply a research approach that utilizes qualitative and quantitative methods. There is an examination of literature that defines populism, its causes and a detailed discussion of the case studies, including the 1972 election of Richard Nixon; the Tea Party election of 2010; and the 2016 election of Donald Trump. In addition, statistical data analysis was run using American National Election Studies (ANES) surveys associated with each specific case study. These case studies were chosen because they most represent forms of populist movements in modern American history. While ample qualitative evidence suggested support for the hypothesis that economic anxiety is a necessary condition for populist voting patterns that elected Nixon, the Tea Party and Trump, the statistical data only supported the hypothesis in two cases, 2010 and 2016, with 1972 coming back inconclusive. The data also suggested that both economic anxiety and racial resentment played a role in 2010 and 2016, while having no significant effect in 1972 in either case. This suggests that further research needs to be conducted into additional populist case studies, as well as an examination into the role economic anxiety and economic crises play on racial resentment and racially motivated voting behavior

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding ‘big data’ that is conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

Plasma modification of microporous polymer membranes for application in biomimetic dissolution studies

Abstract Biorelevant dissolution is an indispensable tool utilized during formulation development and optimization for the prediction of in vivo bioavailability of pharmaceutical agents. Within that framework, membrane-permeation dissolution methodologies are widely used to model drug absorption. The current work evaluates polymer membrane surface modifications for production of biomimetic membranes to be employed in biorelevant dissolution studies. Biomimetic membranes exhibit hydrophilic and hydrophobic properties to simulate the intestinal membrane environment. Low temperature plasma treatment of microporous polyethersulfone (PES), nylon and polypropylene (PP) polymer membranes was applied to produce low energy surface layers with permanent hydrophobic and hydrophilic functionalities. Surface modifications on microporous polymer membranes were achieved by plasma treatments using tetrafluoromethane (CF4), perfluorohexane (C6F14), dichloromethane (DCM) and water (H2O). Surface characterization of treated membranes was evaluated using scanning electron microscopy energy dispersive x-ray spectroscopy (SEM-EDS), water contact angle (CA) and x-ray photoelectron spectroscopy (XPS) techniques. SEM-EDS analysis of polymer membranes treated with fluorinated and chlorinated solvents/gases depicts altered surface morphologies with enriched porosity. SEM-EDS and XPS analyses demonstrate the chemical modification at the surface of treated membranes is strongly influenced by the type of treatment gas or solvent. Results show fluorination as a more effective and less destructive treatment technique. XPS confirmed the presence of elemental fluorine functional groups at the surface of the PES and nylon membranes. Evaluating elemental changes (F/C ratio) from multiple techniques confirms fluorinated plasma treatments are localized to the surface of the membrane and do not significantly affect the bulk properties. In a supplemental study, a detailed comparison of the plasma treated polymer membranes and porcine intestines revealed the biomimetic nature of the modified membranes

Dissolution Enhancement of a Drug Exhibiting Thermal and Acidic Decomposition Characteristics by Fusion Processing: A Comparative Study of Hot Melt Extrusion and KinetiSol® Dispersing

In this study, hot melt extrusion (HME) and KinetiSol® Dispersing (KSD) were utilized to prepare dissolution-enhanced solid dispersions of Roche Research Compound A (ROA), a BCS class II drug. Preformulation characterization studies showed that ROA was chemically unstable at elevated temperatures and acidic pH values. Eudragit® L100-55 and AQOAT® LF (HPMCAS) were evaluated as carrier polymers. Dispersions were characterized for ROA recovery, crystallinity, homogeneity, and non-sink dissolution. Eudragit® L100-55 dispersions prepared by HME required the use of micronized ROA and reduced residence times in order to become substantially amorphous. Compositions containing HPMCAS were also prepared by HME, but an amorphous dispersion could not be obtained. All HME compositions contained ROA-related impurities. KSD was investigated as a method to reduce the decomposition of ROA while rendering compositions amorphous. Substantially amorphous, plasticizer free compositions were processed successfully by KSD with significantly higher ROA recovery values and amorphous character than those achieved by HME. A near-infrared chemical imaging analysis was conducted on the solid dispersions as a measure of homogeneity. A statistical analysis showed similar levels of homogeneity in compositions containing Eudragit® L100-55, while differences were observed in those containing HMPCAS. Non-sink dissolution analysis of all compositions showed rapid supersaturation after pH adjustment to approximately two to three times the equilibrium solubility of ROA, which was maintained for at least 24 h. The results of the study demonstrated that KSD is an effective method of forming dissolution-enhanced amorphous solid solutions in cases where HME is not a feasible technique