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This article is based on feedback I submitted in response to the Office of Management and Budget’s (OMB’s) April 2023 request for comments on its draft revisions to Circular A-4, “Regulatory Analysis.” Much has changed since I submitted my comments in June 2023. OMB issued a final circular in November 2023 and subsequently rescinded it in February 2025. This article includes my comments as submitted, along with an introductory “prologue” and an “epilogue” that reflects on the decision to abandon the 2023 revisions and return to the 2003 Circular. My comment addressed key elements of regulatory analysis, suggested areas where OMB could provide more guidance, and identified several aspects of the 2023 Circular that appeared to be internally inconsistent or contradictory. It concluded that some of the 2023 revisions were worthwhile, while others would have obfuscated for policymakers important information on the welfare effects of regulatory actions.
Objectives/Goals: The goal of this work is to understand the physiological profile of phage susceptibility and identify candidate phage defense mechanisms. Additionally, it aims to determine the host receptors targeted by bacteriophages to infect E. coli O157:H7 through random bar code transposon-site sequencing (RB-TnSeq). Methods/Study Population: A collection of 109 E. coli O157:H7 strains from environmental, food, and animal sources were analyzed, representing phylogenetic lineages corresponding to clades 2, 3, 5, 6, 7, and 8. Phage susceptibility profiles were determined using 23 bacteriophages, assessing plaque morphology. Using the O157:H7 genomes, a genomic analysis was conducted with the Prokaryotic Antiviral Defense Locator (PADLOC), which identified putative phage defense systems through sequence homology. Additionally, 5 RB-TnSeq libraries were generated in representative strains to study loss-of-function mutations. These libraries will be screened against a subset of diverse phage to identify the receptors involved in phage adsorption. Results/Anticipated Results: The phage resistance patterns showed susceptibility varied across clades, suggesting distinct mechanisms. Several defense systems were identified using PADLOC, including restriction-modification, Cas, Lamassu, and Druantia. Phage defense candidate (PDC) systems were identified, showing homology to known systems, though their specific function remains unknown. Clade 7.2 exhibited higher phage resistance and a greater presence of PDCs compared to the other clades. Five saturated RB-TnSeq libraries were constructed in O157:H7, achieving 84.5–89% gene coverage. These libraries will facilitate the identification of receptors involved in phage adsorption and resistance. Discussion/Significance of Impact: This study deepens our understanding of phage resistance in E. coli O157:H7 by identifying key defense systems and receptors. The discovery of novel antiviral mechanisms offers promising targets for phage-based interventions, potentially enhancing strategies for controlling this dangerous pathogen.
Symptoms of complex post-traumatic stress disorder (cPTSD) may play a role in the maintenance of psychotic symptoms. Network analyses have shown interrelationships between post-traumatic sequelae and psychosis, but the temporal dynamics of these relationships in people with psychosis and a history of trauma remain unclear. We aimed to explore, using network analysis, the temporal order of relationships between symptoms of cPTSD (i.e. core PTSD and disturbances of self-organization [DSOs]) and psychosis in the flow of daily life.
Methods
Participants with psychosis and comorbid PTSD (N = 153) completed an experience-sampling study involving multiple daily assessments of psychosis (paranoia, voices, and visions), core PTSD (trauma-related intrusions, avoidance, hyperarousal), and DSOs (emotional dysregulation, interpersonal difficulties, negative self-concept) over six consecutive days. Multilevel vector autoregressive modeling was used to estimate three complementary networks representing different timescales.
Results
Our between-subjects network suggested that, on average over the testing period, most cPTSD symptoms related to at least one positive psychotic symptom. Many average relationships persist in the contemporaneous network, indicating symptoms of cPTSD and psychosis co-occur, especially paranoia with hyperarousal and negative self-concept. The temporal network suggested that paranoia reciprocally predicted, and was predicted by, hyperarousal, negative self-concept, and emotional dysregulation from moment to moment. cPTSD did not directly relate to voices in the temporal network.
Conclusions
cPTSD and positive psychosis symptoms mutually maintain each other in trauma-exposed people with psychosis via the maintenance of current threat, consistent with cognitive models of PTSD. Current threat, therefore, represents a valuable treatment target in phased-based trauma-focused psychosis interventions.
This chapter reviews the development and implementation of English school education policy following an exploratory report by the Department for Education and Skills on the future of primary school collaboration and three major Blair (Labour) government initiatives focused on inter-school collaboration: the New Labour Academies; the Secondary Leadership Incentive Grant programme; and the Networked Learning Communities programme (and their further evolution under Brown (Labour)) until 2010. It traces the dramatic intensification of these policies under the Conservative–Liberal Coalition including incentives to create new academies and Teaching Schools. The Conservative policy also revolutionised school administration and performance by removing the remaining state schools from local government control. The stated aim of a 2016 White Paper ‘Education Excellence Everywhere’ was that, by 2022, every English state school would be in a multi academy trust. It is now past 2022 and, while this goal has not been attained, there is no doubt that ten years of a combination of policy and austerity have transformed England’s state school systems.
Research on campaign finance suggests that Americans prefer candidates who are not funded by Political Action Committees (PACs). However, prior research has not examined how perceptions of a candidate who is PAC-funded vs. PAC-free might differ for racial minority and female candidates compared to White, male candidates. Using experimental vignettes, we test the causal impact of PAC funding, race, and gender on voter perceptions of the candidate. We find that refusing PAC funds, for example, is associated with appearing more ethical and more likely to work for voters’ interests over special interests, less corrupt, and more capable of winning elections. However, we show that race, more than gender, interacts with PAC funding to impact voter perceptions. We find that White female and male candidates benefit the most from PAC refusal. While Black female and male candidates receive little or no significant change in perceptions, Black PAC-funded candidates are perceived favorably compared to White PAC-funded candidates. Our results have implications for White and Black political candidates considering their funding strategies. Additionally, we contribute to existing literature by showing that refusing PAC funds status does not signal the same qualities for all candidates.
This special issue of the Journal of Benefit–Cost Analysis is dedicated to the memory of Jerry Ellig, a brilliant economist whose untimely death in 2021 cut short a productive and influential career in government and academia. Jerry was adept at applying economic concepts and empirical analysis to improve public policy, and he enjoyed not only studying real policy problems, but finding practical solutions to them. He was also a generous mentor, supporting and collaborating with graduate students and colleagues to publish prolifically in peer-reviewed economics, public administration, and political science journals, as well as law reviews and more popular outlets. He was a great communicator, able to take his academic work and translate it for different audiences, including through testimony, seminars, op-eds, short presentations, and classroom teaching. In addition to these immense talents, Jerry was genuinely kind and unpretentious; he wore Wal-Mart suits and garish ties. And he was laugh-out-loud funny, a master at diffusing difficult situations with a witty, but never mean, quip.
Over the last century, the United States has witnessed three approaches to achieving better regulatory outcomes: the removal of “economic” regulations in certain sectors; regulatory impact analysis (RIA) of new “social” regulations; and retrospective analysis of existing regulations. This article reviews the rationale for each approach, the results to date, and the remaining challenges. It finds that both institutional and technical factors influence the success of reform efforts.
Post-traumatic stress disorder (PTSD) has been shown to predict psychotic symptomology. However, few studies have examined the relative contribution of PTSD compared to broader post-traumatic sequelae in maintaining psychosis. Complex PTSD (cPTSD), operationalized using ICD-11 criteria, includes core PTSD (intrusions, avoidance, hyperarousal) as well as additional “disturbances of self-organisation” (DSO; emotional dysregulation, interpersonal difficulties, negative self-concept) symptoms, more likely to be associated with complex trauma histories. It was hypothesized that DSOs would be associated with positive psychotic symptoms (paranoia, voices, and visions) in daily life, over and above core PTSD symptoms.
Methods
This study (N = 153) employed a baseline subsample of the Study of Trauma And Recovery (STAR), a clinical sample of participants with comorbid post-traumatic stress and psychosis symptoms. Core PTSD, DSO and psychosis symptoms were assessed up to 10 times per day at quasi-random intervals over six consecutive days using Experience Sampling Methodology.
Results
DSOs within the preceding 90 min predicted paranoia, voices, and visions at subsequent moments. These relationships persisted when controlling for core PTSD symptoms within this timeframe, which were themselves significant. The associations between DSOs and paranoia but not voices or visions, were significantly stronger than those between psychosis and core PTSD symptoms.
Conclusions
Consistent with an affective pathway to psychosis, the findings suggest that DSOs may be more important than core PTSD symptoms in maintaining psychotic experiences in daily life among people with comorbid psychosis and cPTSD, and indicate the potential importance of addressing broad post-traumatic sequelae in trauma-focused psychosis interventions.
Background: Sellar and suprasellar pediatric lesions are uncommon. Endoscopic transnasal transphenoidal surgery (ETTS) is the preferred treatment, but early post-op MRI is hindered by sphenoidal packing. This study aims to assess iMRI safety and efficacy in pediatric ETTS cases. Methods: We performed a retrospective review from Jan 01, 2015 to Dec 31, 2022, evaluating use of iMRI. We determined if the goals of the surgery (biopsy, cyst decompression, subtotal resection, gross total resection) were met, and iMRI’s influence on surgery outcomes. We examined patient age, surgery duration, length of stay, histopathology results, surgical complications, post-op MRIs within 1 month, and tumor progression/recurrence. Results: Over eight years, 20 pediatric ETTS procedures, 14 with iMRI, were conducted. Achieving goals in 13 cases, iMRI prompted extra surgery once. Two adenomas progressed, requiring a second surgery, and craniopharyngioma cases had complications, needing further interventions. Hospital stays varied (1-9 days), with a mean surgery duration of 6 hours and 47 minutes. The study underscores iMRI’s potential impact, stressing the necessity for more research in pediatric transsphenoidal surgeries. Conclusions: While intraoperative MRI in pediatric transsphenoidal surgeries may aid goal verification, this small study doesn’t conclusively demonstrate improved outcomes. Complication rates align with non-IMRI procedures, highlighting the need for further research.
OBJECTIVES/GOALS: 1. Identify candidate AN-SAD-causing variants. 2. Estimate the variant effect size of and genotypic relative risk for arrhythmias and AN-SAD. METHODS/STUDY POPULATION: We performed whole genome sequencing (WGS) on 59 Thoroughbred AN-SAD cases and 58 controls. WGS was mapped and variants identified using a modified version of the Genome Analysis Toolkit best practices. Variants will be selected based on case-control analysis using SnpSift and presence in candidate genes. The top 400 candidate AN-SAD-causing variants will be selected based on being common in cases and rare or absent in controls, and uncommon (allele frequency less than 10%) in a catalog of genetic variation for the horse. The 400 variants will be genotyped in our cohort of 1,200 racehorses to determine variant effect size and genotypic relative risk. RESULTS/ANTICIPATED RESULTS: 17,182,003 variants were identified. 230 variants had significantly different allele frequencies (AF) between cases and controls (SnpSift). 723 high and 4,824 moderate impact variants were identified in 1,072 candidate genes. 3,681 variants were present at an AF 10% in the equine variant catalog. Variant effect prediction is ongoing to select the final 400 variants. Cardiac phenotyping (cardiac auscultation and ECG before, during, and after exercise) was performed on 790 racehorses and we will have 1,200 racehorses with cardiac phenotypes and/or AN-SAD. We will genotype the top 400 candidate AN-SAD-causing variants in these 1,200 horses to identify variants of large effect size. DISCUSSION/SIGNIFICANCE: Identification of candidate AN-SAD variants in a spontaneous animal model can facilitate interpretation of candidate variants in humans and horses. This project will provide further support for the racehorse AN-SAD model and will support future work exploring the genetic and environmental risk factors contributing to AN-SAD in this animal model.
As the venues for professional training and education, universities have always shaped the future of the archaeological discipline—for better but also, in important ways, for worse. Historically, university structures promoted practitioner homogeneity and social inequity and, at the largest research-intensive universities, even managed to turn “service” into a dirty word. However, using the same structures that perpetuated damaging practices in the past, universities can just as readily transform archaeology into the inclusive, community-engaged discipline it should always have been—while serving communities in ways that matter to them. This article explains and illustrates how and why we have tried to do this through the founding and operation of the Oklahoma Public Archaeology Network (OKPAN) at the University of Oklahoma. OKPAN seeks to improve relationships among diverse Oklahoma communities by framing archaeology as a tool that that can serve communities’ interests while creating pathways within universities for members of historically excluded groups to join and help further transform the discipline.
This accessible and practical textbook gives students the perfect guide to the use of regression models in testing and evaluating hypotheses dealing with social relationships. A range of statistical methods suited to a wide variety of dependent variables is explained, which will allow students to read, understand, and interpret complex statistical analyses of social data. Each chapter contains example applications using relevant statistical methods in both Stata and R, giving students direct experience of applying their knowledge. A full suite of online resources - including statistical command files, datasets and results files, homework assignments, class discussion topics, PowerPoint slides, and exam questions - supports the student to work independently with the data, and the instructor to deliver the most effective possible course. This is the ideal textbook for advanced undergraduate and beginning graduate students taking courses in applied social statistics.
In Chapter 12 we discussed the modeling and fitting of a logistic regression equation with a dependent variable with three or more ordered categories. In this chapter we discuss the modelling and fitting of a logistic regression equation with a multi-categorical dependent variable, but here the dependent variable will have response categories that are not ordered, that is, they are nominal. The most frequently used method for estimating a nominal categorical dependent variable is the multinomial logistic regression model, the subject of this chapter. This model is a natural extension of logistic regression for a binary dependent variable.
Many of the dependent variables analyzed in the social sciences involve a time period of nonoccurrence prior to their occurrence. Demographers study death; but one cannot die without being born. Thus, one’s death is preceded by a time period after the person has been born during which time they do not die. Such a dependent variable is referred to as a time-to-event variable because there must be a time period of nonoccurrence before the event occurs. Such analyses have several names. The broadest ones are survival analysis or hazard analysis, owing to their early development in biostatistics and epidemiology, where researchers modeled the occurrence of death. The event of death was referred to as a hazard. Persons over a time interval not experiencing the hazard, that is, not dying, were referred to as surviving the hazard. There are two main types of survival models, continuous-time models and discrete-time methods. We direct most of our attention in this chapter to continuous-time models of survival analysis, and specifically to the Cox proportional hazard model. In the last section of the chapter, we focus on discrete-time survival models.
Many dependent variables analyzed in the social sciences are not continuous, but are dichotomous, with a yes/no response. A dichotomous dependent variable takes on only two values; the value 1 represents yes, and the value 0, no. The independent variables in the regression model are then used to predict whether the subjects fall into one of the two dependent variable categories. In this chapter we discuss the modeling of a dichotomous dependent variable and show why ordinary least squares regression is not appropriate. We discuss the logistic regression model. We fit a logistic regression equation and address several statistical concepts and issues: log likelihoods, the likelihood ratio chi-squared statistic, Pseudo R2, model adequacy, and statistical significance. We then discuss the interpretation of logit coefficients, odds ratios, standardized logit coefficients, and standardized odds ratios. We show how to use “margins” in the interpretation of logit models with predicted probabilities. The last sections deal with testing and evaluating nested logit models, and with comparing logit models with probit models.