Case series demonstrating in vivo MR safety of stainless steel (Chinese/Ring) IUDs

Intrauterine devices (IUDs) are one of the most common forms of long-term contraception used by patients around the world. Many studies have been performed over the past few decades demonstrating the safety of many common hormonal and metallic intrauterine devices in Magnetic Resonance (MR) imaging; however, the stainless steel ring IUD (often termed the “Chinese” IUD) is still considered MR Unsafe. This device was used in the 1980s and 1990s in China, where as many as 60 million women in China were using an IUD by 1988, and approximately 90% of those were stainless steel ring IUDs. In a major metropolitan area hospital such as ours with a large immigrant population, we encounter females with this ring IUD several times a year. As this population ages, the need for medical care (and concomitantly, MR imaging) is projected to increase. The purpose of this case review is to examine the imaging and clinical course of patients with stainless-steel ring intrauterine devices who safely received 1.5T Brain MR scans at our institution for clinically necessary diagnostic imaging.

Homophily and Social Capital in a Network of Religious Congregations

This article investigates the relationship between homophily, the tendency for relationships to be more common among similar actors, and social capital in a social network of religious congregations from eight counties encompassing and surrounding a major metropolitan area in the southeastern United States. This network is inter-congregational, consisting of congregations and the relationships between them. Two types of social capital are investigated: the first involves the extent to which congregations bridge across structural holes, or bridge together otherwise disconnected congregations within the network; secondly, network closure involves the extent to which congregations are embedded in tight-knit clusters. Analyses use two types of homophily (religious and racial) to predict both outcomes, and they test linear and curvilinear relationships between both forms of homophily and the outcomes. Results indicate that congregations with moderate levels of religious homophily are more likely to bridge between otherwise disconnected congregations; however, congregations with low or high religious homophily as well as congregations with high racial homophily are more likely to be embedded in tight-knit relational clusters. This article contributes additional social network research on congregations and evidence of curvilinear relationships between homophily and social capital to the fields of social network analysis and sociology of religion.

Identification and trajectory of growth of concerning SARS-CoV-2 variants in Houston, Texas, January through April 2021 based on 11,568 genome sequences

Genetic variants of the SARS-CoV-2 virus are of substantial concern because they can detrimentally alter the trajectory of the ongoing pandemic, and disease course in individual patients. Here we report genome sequences from 11,568 COVID-19 patients in the Houston Methodist healthcare system dispersed throughout the metroplex that were diagnosed from January 1, 2021 through April 30, 2021. This sample represents 94% of Houston Methodist cases and 4.6% of all reported cases in the metropolitan area during this period. The SARS-CoV-2 variant designated UK B.1.1.7 increased very rapidly, and now causes 75%-90% of all new cases in the Houston area. Five of the 2,543 B.1.1.7 genomes had an E484K change in spike protein. Compared with non-B.1.1.7 patients, individuals infected with B.1.1.7 had a significantly lower cycle threshold value (considered to be a proxy for higher virus load) and higher rate of hospitalization. Other variants (e.g., B.1.429, B.1.427, P.1, P.2, and R.1) also increased rapidly in frequency, although the magnitude was less than for B.1.1.7. We also identified 42 patients with a recently described R.1 variant that has an E484K amino acid replacement, and seven patients with the B.1.617 "India" variants. In the aggregate, our study shows the occurrence of a diverse array of concerning SARS-CoV-2 variants circulating in a major metropolitan area, documents B.1.1.7 as the major cause of new cases in Houston and heralds the arrival and spread of B.1.617 variants in the metroplex.

Voice of the Victims: Accounts of Secondary Victimization With the Court System Among Homicide Co-victims

The treatment homicide co-victims receive from the criminal justice system often leaves them aggrieved and feeling alienated. A neglected but important area of investigation is the courtroom workgroup’s handling of murder cases. This exploratory study examines the nature and extent to which varying secondary victimization experiences are common among co-victims as the murder cases are processed through the court system. The sample consists of 27 co-victims connected to 24 separate cases where the murders occurred in a major metropolitan area in the southeastern United States. Drawing upon focus group data, Nvivo 10 was employed to identify themes that illustrate common secondary victimization experiences among co-victims along with positive and mixed reactions to court processes and personnel. The findings indicate that court requirements to provide notifications are infrequently met and attorney’s practice to supply information about case progress and counseling to family members regarding plea-bargaining and sentencing decisions are greatly restrictive. When information is offered, it is often perceived as highly technical and when assistance is provided, it is frequently limited or intermittent. Despite the prevalence of negative experiences, there also were reports of positive interactions with the district attorney and victim advocates. The study concludes by identifying ways in which the courtroom workgroup can uphold the rights afforded to co-victims while at the same time meeting the duties and responsibilities of the workgroup.

Geographic Differences in Lung Cancer Incidence: A Study of a Major Metropolitan Area within Southeastern Pennsylvania

This study investigated the geographic variation and the clustering of lung cancer incidence rates in Philadelphia and the surrounding areas using addresses at the time of diagnosis. Using 60,844 cases from Pennsylvania Cancer Registry, we calculated and mapped the age-adjusted incidence rates for five Pennsylvania (PA) counties near Philadelphia between 1998–2007 and 2008–2017. We identified ZIP codes with significantly higher incidence rates than the state rates and examined their demographic and exposure characteristics. Further, we tested for spatial autocorrelation and identified spatial clusters using Moran’s I statistic. Our results showed that approximately one in four ZIP codes had an incidence rate that was significantly higher than the PA state rate in each period studied. Clusters of higher incidences were detected in the southeastern part of PA bordering New Jersey. These areas tended to be more populated, of lower socioeconomic status, and closer to manufacturing facilities and major highways. Possibly driven by the community and environmental factors, the observed differences in disease incidence suggest the importance of including residential location in risk assessment tools for lung cancer.

Unsupervised identification of crime problems from police free-text data

We present a novel exploratory application of unsupervised machine-learning methods to identify clusters of specific crime problems from unstructured modus operandi free-text data within a single administrative crime classification. To illustrate our proposed approach, we analyse police recorded free-text narrative descriptions of residential burglaries occurring over a two-year period in a major metropolitan area of the UK. Results of our analyses demonstrate that topic modelling algorithms are capable of clustering substantively different burglary problems without prior knowledge of such groupings. Subsequently, we describe a prototype dashboard that allows replication of our analytical workflow and could be applied to support operational decision making in the identification of specific crime problems. This approach to grouping distinct types of offences within existing offence categories, we argue, has the potential to support crime analysts in proactively analysing large volumes of modus operandi free-text data—with the ultimate aims of developing a greater understanding of crime problems and supporting the design of tailored crime reduction interventions.