A person-centered approach to behaving badly at work: An examination of workplace deviance patterns.

To investigate research questions surrounding workplace deviance, scholars have primarily applied variable-centered approaches, such as overall deviance measures or those that separate interpersonal deviance and organizational deviance. These approaches, however, ignore that individuals might employ more complex combinations of deviance behaviors that do not fit neatly within the existing variable frameworks. The present study explores whether person-centered deviance classes emerge in a comprehensive database of the prior studies. We then investigated whether these classes showed differences in antecedents and correlates in an independent sample of working adults from multiple industries. In Study 1, a multilevel latent class analysis of 20 independent samples and 6,218 individuals revealed five classes of workplace deviance, thus providing preliminary support for a person-centered approach. In Study 2, a time-lagged sample of 553 individuals showed the emergence of five classes that largely reflected the patterns found in Study 1. Study 2 points to meaningful differences between classes of deviance behaviors and antecedents, including abusive supervision, Openness, Conscientiousness, Agreeableness, Emotional Stability, and psychological entitlement; classes are also uniquely associated with correlates such as organizational citizenship behaviors, turnover intentions, job performance, and job satisfaction. Altogether, this work is an important first step toward understanding workplace deviance with a person-centered lens. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Protecting Privacy of Pregnant and LGBTQ+ Research Participants.

This Viewpoint summarizes existing federal regulations aimed at protecting research data, describes the challenges of enforcing these regulations, and discusses how evolving privacy technologies could be used to reduce health disparities and advance health equity among pregnant and LGBTQ+ research participants.

Genetic sex validation for sample tracking in next-generation sequencing clinical testing.

OBJECTIVE: Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups. RESULTS: Precise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors (49.09%), samples from transgender participants (3.64%) and stem cell or bone marrow transplant patients (7.27%) along with undetermined sample mix-ups (40%) for which sample swaps occurred prior to arrival at genome centers, however the exact cause of the events at the sampling sites resulting in the mix-ups were not able to be determined.

Genetic Sex Validation for Sample Tracking in Clinical Testing.

Objective: Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups. Results: Precise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors, samples from transgender participants and stem cell or bone marrow transplant patients along with undetermined sample mix-ups.

Histologic Inflammation can Predict Future Clinical Relapse in Ulcerative Colitis Patients in Endoscopic Remission.

Background: In ulcerative colitis (UC), endoscopic improvement, defined as a Mayo Endoscopic Score (MES) of 0 or 1, is a target of treatment. The aim of our study was to evaluate the risk of clinical relapse between patients with an MES of 0 or 1 and determine if histologic activity using the Robarts Histopathologic Index (RHI) was predictive of clinical relapse. Methods: UC patients with an MES score of 0 or 1, no prior colectomy, and at least 1 year of outpatient follow-up after colonoscopy were included. Demographic, clinical characteristics, and clinical relapse were retrospectively collected. Biopsy specimens were read by a gastrointestinal pathologist. Primary outcome was defined as a composite of relapse requiring change in medical therapy, new steroid use, UC-related hospitalization, and/or colectomy. Results: Four hundred and forty-five UC patients were identified. Ninety-five percent of patients with MES 0 were in histologic remission by the RHI whereas only 35% of patients with MES 1 were in histologic remission. Twenty-six percent of patients experienced a clinical relapse; patients with MES 1 or RHI > 3 were significantly more likely to relapse (P < .01) compared to patients with MES 0 or RHI ≤ 3. When patients were stratified into 4 groups (MES 0, RHI ≤ 3; MES 0, RHI > 3; MES 1, RHI ≤ 3; MES 1, RHI > 3) and adjusted for age and sex, RHI > 3 was predictive of relapse (P = .008). Conclusions: UC patients with endoscopic improvement have a high rate of clinical relapse over time. Histologic activity is a predictor of clinical relapse.

Conducting inclusive research in genetics for transgender, gender-diverse, and sex-diverse individuals: Case analyses and recommendations from a clinical genomics study.

A person's phenotypic sex (i.e., endogenous expression of primary, secondary, and endocrinological sex characteristics) can impact crucial aspects of genetic assessment and resulting clinical care recommendations. In studies with genetics components, it is critical to collect phenotypic sex, information about current organ/tissue inventory and hormonal milieu, and gender identity. If researchers do not carefully construct data models, transgender, gender diverse, and sex diverse (TGSD) individuals may be given inappropriate care recommendations and/or be subjected to misgendering, inflicting medical and psychosocial harms. The recognized need for an inclusive care experience should not be limited to clinical practice but should extend to the research setting, where researchers must build an inclusive experience for TGSD participants. Here, we review three TGSD participants in the Family History and Cancer Risk Study (FOREST) to critically evaluate sex- and gender-related survey measures and associated data models in a study seeking to identify patients at risk for hereditary cancer syndromes. Furthermore, we leverage these participants' responses to sex- and gender identity-related questions in FOREST to inform needed changes to the FOREST data model and to make recommendations for TGSD-inclusive genetics research design, data models, and processes.

Impact of a novel multilayer imager on metal artifacts in MV-CBCT.

Objective. Megavoltage cone-beam computed tomography (MV-CBCT) imaging offers several advantages including reduced metal artifacts and accurate electron density mapping for adaptive or emergent situations. However, MV-CBCT imaging is limited by the poor efficiency of current detectors. Here we examine a new MV imager and compare CBCT reconstructions under clinically relevant scenarios.Approach. A multilayer imager (MLI), consisting of four vertically stacked standard flat-panel imagers, was mounted to a clinical linear accelerator. A custom anthropomorphic pelvis phantom with replaceable femoral heads was imaged using MV-CBCT and kilovoltage CBCT (kV-CBCT). Bone, aluminum, and titanium were used as femoral head inserts. 8 MU 2.5 MV scans were acquired for all four layers and (as reference) the top layer. Prostate and bladder were contoured on a reference CT and transferred to the other scans after rigid registration, from which the structural similarity index measure (SSIM) was calculated. Prostate and bladder were also contoured on CBCT scans without guidance, and Dice coefficients were compared to CT contours.Main results. kV-CBCT demonstrated the highest SSIMs with bone inserts (prostate: 0.86, bladder: 0.94) and lowest with titanium inserts (0.32, 0.37). Four-layer MV-CBCT SSIMs were preserved with bone (0.75, 0.80) as compared to titanium (0.67, 0.74), outperforming kV-CBCT when metal is present. One-layer MV-CBCT consistently underperformed four-layer results across all phantom configurations. Unilateral titanium inserts and bilateral aluminum insert results fell between the bone and bilateral titanium results. Dice coefficients trended similarly, with four-layer MV-CBCT reducing metal artifact impact relative to KV-CBCT to provide better soft-tissue identification.Significance. MV-CBCT with a four-layer MLI showed improvement over single-layer MV scans, approaching kV-CBCT quality for soft-tissue contrast. In the presence of artifact-producing metal implants, four-layer MV-CBCT scans outperformed kV-CBCT by eliminating artifacts and single-layer MV-CBCT by reducing noise. MV-CBCT with a novel multi-layer imager may be a valuable alternative to kV-CBCT, particularly in the presence of metal.

Permanent Porosity in the Room-Temperature Magnet and Magnonic Material V(TCNE)2.

Materials that simultaneously exhibit permanent porosity and high-temperature magnetic order could lead to advances in fundamental physics and numerous emerging technologies. Herein, we show that the archetypal molecule-based magnet and magnonic material V(TCNE)2 (TCNE = tetracyanoethylene) can be desolvated to generate a room-temperature microporous magnet. The solution-phase reaction of V(CO)6 with TCNE yields V(TCNE)2·0.95CH2Cl2, for which a characteristic temperature of T* = 646 K is estimated from a Bloch fit to variable-temperature magnetization data. Removal of the solvent under reduced pressure affords the activated compound V(TCNE)2, which exhibits a T* value of 590 K and permanent microporosity (Langmuir surface area of 850 m2/g). The porous structure of V(TCNE)2 is accessible to the small gas molecules H2, N2, O2, CO2, ethane, and ethylene. While V(TCNE)2 exhibits thermally activated electron transfer with O2, all the other studied gases engage in physisorption. The T* value of V(TCNE)2 is slightly modulated upon adsorption of H2 (T* = 583 K) or CO2 (T* = 596 K), while it decreases more significantly upon ethylene insertion (T* = 459 K). These results provide an initial demonstration of microporosity in a room-temperature magnet and highlight the possibility of further incorporation of small-molecule guests, potentially even molecular qubits, toward future applications.

Education and electronic medical records and genomics network, challenges, and lessons learned from a large-scale clinical trial using polygenic risk scores.

Polygenic risk scores (PRS) have potential to improve health care by identifying individuals that have elevated risk for common complex conditions. Use of PRS in clinical practice, however, requires careful assessment of the needs and capabilities of patients, providers, and health care systems. The electronic Medical Records and Genomics (eMERGE) network is conducting a collaborative study which will return PRS to 25,000 pediatric and adult participants. All participants will receive a risk report, potentially classifying them as high risk (∼2-10% per condition) for 1 or more of 10 conditions based on PRS. The study population is enriched by participants from racial and ethnic minority populations, underserved populations, and populations who experience poorer medical outcomes. All 10 eMERGE clinical sites conducted focus groups, interviews, and/or surveys to understand educational needs among key stakeholders-participants, providers, and/or study staff. Together, these studies highlighted the need for tools that address the perceived benefit/value of PRS, types of education/support needed, accessibility, and PRS-related knowledge and understanding. Based on findings from these preliminary studies, the network harmonized training initiatives and formal/informal educational resources. This paper summarizes eMERGE's collective approach to assessing educational needs and developing educational approaches for primary stakeholders. It discusses challenges encountered and solutions provided.

Returning integrated genomic risk and clinical recommendations: The eMERGE study.

PURPOSE: Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk. METHODS: To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results. RESULTS: GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022. CONCLUSION: Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

Metal-organic frameworks as O2-selective adsorbents for air separations.

Oxygen is a critical gas in numerous industries and is produced globally on a gigatonne scale, primarily through energy-intensive cryogenic distillation of air. The realization of large-scale adsorption-based air separations could enable a significant reduction in associated worldwide energy consumption and would constitute an important component of broader efforts to combat climate change. Certain small-scale air separations are carried out using N2-selective adsorbents, although the low capacities, poor selectivities, and high regeneration energies associated with these materials limit the extent of their usage. In contrast, the realization of O2-selective adsorbents may facilitate more widespread adoption of adsorptive air separations, which could enable the decentralization of O2 production and utilization and advance new uses for O2. Here, we present a detailed evaluation of the potential of metal-organic frameworks (MOFs) to serve as O2-selective adsorbents for air separations. Drawing insights from biological and molecular systems that selectively bind O2, we survey the field of O2-selective MOFs, highlighting progress and identifying promising areas for future exploration. As a guide for further research, the importance of moving beyond the traditional evaluation of O2 adsorption enthalpy, ΔH, is emphasized, and the free energy of O2 adsorption, ΔG, is discussed as the key metric for understanding and predicting MOF performance under practical conditions. Based on a proof-of-concept assessment of O2 binding carried out for eight different MOFs using experimentally derived capacities and thermodynamic parameters, we identify two existing materials and one proposed framework with nearly optimal ΔG values for operation under user-defined conditions. While enhancements are still needed in other material properties, the insights from the assessments herein serve as a guide for future materials design and evaluation. Computational approaches based on density functional theory with periodic boundary conditions are also discussed as complementary to experimental efforts, and new predictions enable identification of additional promising MOF systems for investigation.

In Silico analysis of the sequence and structure of plant microRNAs packaged in extracellular vesicles.

Small RNA (sRNA)-mediated RNA interference (RNAi) is a conserved eukaryotic cellular process associated with immune defense and pathogen virulence. The cross-kingdom transfer of noncoding regulatory sRNAs between host and pathogen can be mediated via lipid, membrane-bound extracellular vesicles (EVs). Several studies have reported in mammalian and plant systems there is selective packaging of sRNAs into EVs. In mammals, sequence patterns and structural motifs are implicated in signaling pathways related to EV cargo sorting. However, in the emerging plant EV field, there is a lack of knowledge of the mechanisms involved in selecting sRNAs for EV transport. In this study, we accessed publicly available databases where the sRNA content of plant EVs has been characterized from control plants and those released in response to fungal pathogen infection. An in-depth analysis revealed 158 sRNAs are EV packaged, with ∼60 % sharing a sequence motif and 98.1 % forming a secondary hairpin stem-loop structure. Many of the predicted plant targets for the EV sRNAs were associated with biological pathways involved in metabolism and regulation processes. Overall, our in silico analysis of sRNAs packaged in plant EVs highlight that a computational approach can offer valuable insights into the cross-kingdom EV transport of sRNAs.

The reckoning: The return of genomic results to 1444 participants across the eMERGE3 Network.

PURPOSE: The goal of Electronic Medical Records and Genomics (eMERGE) Phase III Network was to return actionable sequence variants to 25,084 consenting participants from 10 different health care institutions across the United States. The purpose of this study was to evaluate system-based issues relating to the return of results (RoR) disclosure process for clinical grade research genomic tests to eMERGE3 participants. METHODS: RoR processes were developed and approved by each eMERGE institution's internal review board. Investigators at each eMERGE3 site were surveyed for RoR processes related to the participant's disclosure of pathogenic or likely pathogenic variants and engagement with genetic counseling. Standard statistical analysis was performed. RESULTS: Of the 25,084 eMERGE participants, 1444 had a pathogenic or likely pathogenic variant identified on the eMERGEseq panel of 67 genes and 14 single nucleotide variants. Of these, 1077 (74.6%) participants had results disclosed, with 562 (38.9%) participants provided with variant-specific genetic counseling. Site-specific processes that either offered or required genetic counseling in their RoR process had an effect on whether a participant ultimately engaged with genetic counseling (P = .0052). CONCLUSION: The real-life experience of the multiarm eMERGE3 RoR study for returning actionable genomic results to consented research participants showed the impact of consent, method of disclosure, and genetic counseling on RoR.

Associations between ethnicity and admission to intensive care among women giving birth: a cohort study.

OBJECTIVE: To determine the association between ethnic group and likelihood of admission to intensive care in pregnancy and the postnatal period. DESIGN: Cohort study. SETTING: Maternity and intensive care units in England and Wales. POPULATION OR SAMPLE: A total of 631 851 women who had a record of a registerable birth between 1 April 2015 and 31 March 2016 in a database used for national audit. METHODS: Logistic regression analyses of linked maternity and intensive care records, with multiple imputation to account for missing data. MAIN OUTCOME MEASURES: Admission to intensive care in pregnancy or postnatal period to 6 weeks after birth. RESULTS: In all, 2.24 per 1000 maternities were associated with intensive care admission. Black women were more than twice as likely as women from other ethnic groups to be admitted (odds ratio [OR] 2.21, 95% CI 1.82-2.68). This association was only partially explained by demographic, lifestyle, pregnancy and birth factors (adjusted OR 1.69, 95% CI 1.37-2.09). A higher proportion of intensive care admissions in Black women were for obstetric haemorrhage than in women from other ethnic groups. CONCLUSIONS: Black women have an increased risk of intensive care admission that cannot be explained by demographic, health, lifestyle, pregnancy and birth factors. Clinical and policy intervention should focus on the early identification and management of severe illness, particularly obstetric haemorrhage, in Black women, in order to reduce inequalities in intensive care admission. TWEETABLE ABSTRACT: Black women are almost twice as likely as White women to be admitted to intensive care during pregnancy and the postpartum period; this risk remains after accounting for demographic, health, lifestyle, pregnancy and birth factors.

First impression effects in organizational psychology.

The study of first impressions, which consistently demonstrate meaningful and surprisingly durable impacts on attitudes, behaviors, and cognitions, is pervasive across psychological disciplines. In this integrative conceptual review, we focus on first impressions within the organizational psychology literature, which have been explored across an impressive variety of topical domains (e.g., selection, socialization, leader-subordinate relationships, job performance, and teams) though largely in fragmented ways. Our review attempts to resolve major differences in how researchers have approached first impression effects to build consensus on what first impression effects are, how they occur, and how long they take to develop. In synthesizing this seemingly disparate body of research, we develop an integrative framework of first impression effects comprising four fundamental elements-cues, motives, processes, and outcomes-that must be considered both individually and collectively to understand first impression effects in organizational settings in their entirety. Using this framework, we take stock of the existing literature and identify important through lines, including the focus on displayer- or perceiver-centric effects and whether first impression effects are presumed to be biased or valid. Our fundamental elements framework can be used to systematically catalog and reconcile prior work, as well as develop stronger, more theoretically cohesive studies in the future. We outline major implications for theory and practice on first impressions in the workplace. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Arrhythmia Variant Associations and Reclassifications in the eMERGE-III Sequencing Study.

BACKGROUND: Sequencing Mendelian arrhythmia genes in individuals without an indication for arrhythmia genetic testing can identify carriers of pathogenic or likely pathogenic (P/LP) variants. However, the extent to which these variants are associated with clinically meaningful phenotypes before or after return of variant results is unclear. In addition, the majority of discovered variants are currently classified as variants of uncertain significance, limiting clinical actionability. METHODS: The eMERGE-III study (Electronic Medical Records and Genomics Phase III) is a multicenter prospective cohort that included 21 846 participants without previous indication for cardiac genetic testing. Participants were sequenced for 109 Mendelian disease genes, including 10 linked to arrhythmia syndromes. Variant carriers were assessed with electronic health record-derived phenotypes and follow-up clinical examination. Selected variants of uncertain significance (n=50) were characterized in vitro with automated electrophysiology experiments in HEK293 cells. RESULTS: As previously reported, 3.0% of participants had P/LP variants in the 109 genes. Herein, we report 120 participants (0.6%) with P/LP arrhythmia variants. Compared with noncarriers, arrhythmia P/LP carriers had a significantly higher burden of arrhythmia phenotypes in their electronic health records. Fifty-four participants had variant results returned. Nineteen of these 54 participants had inherited arrhythmia syndrome diagnoses (primarily long-QT syndrome), and 12 of these 19 diagnoses were made only after variant results were returned (0.05%). After in vitro functional evaluation of 50 variants of uncertain significance, we reclassified 11 variants: 3 to likely benign and 8 to P/LP. CONCLUSIONS: Genome sequencing in a large population without indication for arrhythmia genetic testing identified phenotype-positive carriers of variants in congenital arrhythmia syndrome disease genes. As the genomes of large numbers of people are sequenced, the disease risk from rare variants in arrhythmia genes can be assessed by integrating genomic screening, electronic health record phenotypes, and in vitro functional studies. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier; NCT03394859.

Improvements in beam's eye view fiducial tracking using a novel multilayer imager.

Purpose.Electronic portal image devices (EPIDs) have been investigated previously for beams-eye view (BEV) applications such as tumor tracking but are limited by low contrast-to-noise ratio and detective quantum efficiency. A novel multilayer imager (MLI), consisting of four stacked flat-panels was used to measure improvements in fiducial tracking during liver stereotactic body radiation therapy (SBRT) procedures compared to a single layer EPID.Methods.The prototype MLI was installed on a clinical TrueBeam linac in place of the conventional DMI single-layer EPID. The panel was extended during volumetric modulated arc therapy SBRT treatments in order to passively acquire data during therapy. Images were acquired for six patients receiving SBRT to liver metastases over two fractions each, one with the MLI using all 4 layers and one with the MLI using the top layer only, representing a standard EPID. The acquired frames were processed by a previously published tracking algorithm modified to identify implanted radiopaque fiducials. Truth data was determined using respiratory traces combined with partial manual tracking. Results for 4- and 1-layer mode were compared against truth data for tracking accuracy and efficiency. Tracking and noise improvements as a function of gantry angle were determined.Results. Tracking efficiency with 4-layers improved to 82.8% versus 58.4% for the 1-layer mode, a relative improvement of 41.7%. Fiducial tracking with 1-layer returned a root mean square error (RMSE) of 2.1 mm compared to 4-layer RMSE of 1.5 mm, a statistically significant (p < 0.001) improvement of 0.6 mm. The reduction in noise correlated with an increase in successfully tracked frames (r = 0.913) and with increased tracking accuracy (0.927).Conclusion. Increases in MV photon detection efficiency by utilization of a MLI results in improved fiducial tracking for liver SBRT treatments. Future clinical applications utilizing BEV imaging may be enhanced by including similar noise reduction strategies.

Phenotyping coronavirus disease 2019 during a global health pandemic: Lessons learned from the characterization of an early cohort.

From the start of the coronavirus disease 2019 (COVID-19) pandemic, researchers have looked to electronic health record (EHR) data as a way to study possible risk factors and outcomes. To ensure the validity and accuracy of research using these data, investigators need to be confident that the phenotypes they construct are reliable and accurate, reflecting the healthcare settings from which they are ascertained. We developed a COVID-19 registry at a single academic medical center and used data from March 1 to June 5, 2020 to assess differences in population-level characteristics in pandemic and non-pandemic years respectively. Median EHR length, previously shown to impact phenotype performance in type 2 diabetes, was significantly shorter in the SARS-CoV-2 positive group relative to a 2019 influenza tested group (median 3.1 years vs 8.7; Wilcoxon rank sum P = 1.3e-52). Using three phenotyping methods of increasing complexity (billing codes alone and domain-specific algorithms provided by an EHR vendor and clinical experts), common medical comorbidities were abstracted from COVID-19 EHRs, defined by the presence of a positive laboratory test (positive predictive value 100%, recall 93%). After combining performance data across phenotyping methods, we observed significantly lower false negative rates for those records billed for a comprehensive care visit (p = 4e-11) and those with complete demographics data recorded (p = 7e-5). In an early COVID-19 cohort, we found that phenotyping performance of nine common comorbidities was influenced by median EHR length, consistent with previous studies, as well as by data density, which can be measured using portable metrics including CPT codes. Here we present those challenges and potential solutions to creating deeply phenotyped, acute COVID-19 cohorts.