Understanding a Care Management System's Role in Influencing a Transitional-Aged Youth Program's Practice: Mixed Methods Study.

BACKGROUND: Extended foster care programs help prepare transitional-aged youth (TAY) to step into adulthood and live independent lives. Aspiranet, one of California's largest social service organizations, used a social care management solution (SCMS) to meet TAY's needs. OBJECTIVE: We aimed to investigate the impact of an SCMS, IBM Watson Care Manager (WCM), in transforming foster program service delivery and improving TAY outcomes. METHODS: We used a mixed methods study design by collecting primary data from stakeholders through semistructured interviews in 2021 and by pulling secondary data from annual reports, system use logs, and data repositories from 2014 to 2021. Thematic analysis based on grounded theory was used to analyze qualitative data using NVivo software. Descriptive analysis of aggregated outcome metrics in the quantitative data was performed and compared across 2 periods: pre-SCMS implementation (before October 31, 2016) and post-SCMS implementation (November 1, 2016, and March 31, 2021). RESULTS: In total, 6 Aspiranet employees (4 leaders and 2 life coaches) were interviewed, with a median time of 56 (IQR 53-67) minutes. The majority (5/6, 83%) were female, over 30 years of age (median 37, IQR 32-39) with a median of 6 (IQR 5-10) years of experience at Aspiranet and overall field experience of 10 (IQR 7-14) years. Most (4/6, 67%) participants rated their technological skills as expert. Thematic analysis of participants' interview transcripts yielded 24 subthemes that were grouped into 6 superordinate themes: study context, the impact of the new tool, key strengths, commonly used features, expectations with WCM, and limitations and recommendations. The tool met users' initial expectations of streamlining tasks and adopting essential functionalities. Median satisfaction scores around pre- and post-WCM workflow processes remained constant between 2 life coaches (3.25, IQR 2.5-4); however, among leaders, post-WCM scores (median 4, IQR 4-5) were higher than pre-WCM scores (median 3, IQR 3-3). Across the 2 study phases, Aspiranet served 1641 TAY having consistent population demographics (median age of 18, IQR 18-19 years; female: 903/1641, 55.03%; race and ethnicity: Hispanic or Latino: 621/1641, 37.84%; Black: 470/1641, 28.64%; White: 397/1641, 24.19%; Other: 153/1641, 9.32%). Between the pre- and post-WCM period, there was an increase in full-time school enrollment (359/531, 67.6% to 833/1110, 75.04%) and a reduction in part-time school enrollment (61/531, 11.5% to 91/1110, 8.2%). The median number of days spent in the foster care program remained the same (247, IQR 125-468 years); however, the number of incidents reported monthly per hundred youth showed a steady decline, even with an exponentially increasing number of enrolled youth and incidents. CONCLUSIONS: The SCMS for coordinating care and delivering tailored services to TAY streamlined Aspiranet's workflows and processes and positively impacted youth outcomes. Further enhancements are needed to better align with user and youth needs.

Digital Health Interventions to Enhance Prevention in Primary Care: Scoping Review.

BACKGROUND: Disease prevention is a central aspect of primary care practice and is comprised of primary (eg, vaccinations), secondary (eg, screenings), tertiary (eg, chronic condition monitoring), and quaternary (eg, prevention of overmedicalization) levels. Despite rapid digital transformation of primary care practices, digital health interventions (DHIs) in preventive care have yet to be systematically evaluated. OBJECTIVE: This review aimed to identify and describe the scope and use of current DHIs for preventive care in primary care settings. METHODS: A scoping review to identify literature published from 2014 to 2020 was conducted across multiple databases using keywords and Medical Subject Headings terms covering primary care professionals, prevention and care management, and digital health. A subgroup analysis identified relevant studies conducted in US primary care settings, excluding DHIs that use the electronic health record (EHR) as a retrospective data capture tool. Technology descriptions, outcomes (eg, health care performance and implementation science), and study quality as per Oxford levels of evidence were abstracted. RESULTS: The search yielded 5274 citations, of which 1060 full-text articles were identified. Following a subgroup analysis, 241 articles met the inclusion criteria. Studies primarily examined DHIs among health information technologies, including EHRs (166/241, 68.9%), clinical decision support (88/241, 36.5%), telehealth (88/241, 36.5%), and multiple technologies (154/241, 63.9%). DHIs were predominantly used for tertiary prevention (131/241, 54.4%). Of the core primary care functions, comprehensiveness was addressed most frequently (213/241, 88.4%). DHI users were providers (205/241, 85.1%), patients (111/241, 46.1%), or multiple types (89/241, 36.9%). Reported outcomes were primarily clinical (179/241, 70.1%), and statistically significant improvements were common (192/241, 79.7%). Results were summarized across the following 5 topics for the most novel/distinct DHIs: population-centered, patient-centered, care access expansion, panel-centered (dashboarding), and application-driven DHIs. The quality of the included studies was moderate to low. CONCLUSIONS: Preventive DHIs in primary care settings demonstrated meaningful improvements in both clinical and nonclinical outcomes, and across user types; however, adoption and implementation in the US were limited primarily to EHR platforms, and users were mainly clinicians receiving alerts regarding care management for their patients. Evaluations of negative results, effects on health disparities, and many other gaps remain to be explored.

Clinical insights into hematologic malignancies and comparative analysis of molecular signatures of acute myeloid leukemia in different ethnicities using an artificial intelligence offering.

ABSTRACT: Next generation sequencing generates copious amounts of genomics data, causing manual interpretation to be laborious and non-scalable while remaining subjective (even for highly trained specialists). We evaluated the performance of the artificial intelligence-based offering Watson for Genomics (WfG), a variant interpretation platform, in hematologic malignancies for the first time.Next generation sequencing was performed for patients treated for various hematological malignancies at Hallym University Sacred Heart Hospital, South Korea, between December 2017 and August 2020 using a 54-gene panel. Both WfG and expert manual curation were used to evaluate the performance of WfG. Acute myeloid leukemia (AML) molecular profiles were compared between Koreans and other ethnic groups using a publicly available dataset.Seventy-seven patients were analyzed (AML: 45, myeloproliferative neoplasms: 12, multiple myeloma: 7, myelodysplastic syndromes: 6, and others: 7). The concordance between the manual and WfG interpretations of 35 variants in 11 random patients was 94%. Among all patients, WfG identified 39 (51%) with at least 1 clinically actionable therapeutic alteration (i.e., a variant targeted by a United States Food and Drug Administration [US FDA]-approved drug, off-label drug, or clinical trial). Moreover, 46% of these patients (18/39) had genes that were targeted by a US FDA-approved therapy. WfG identified diagnostic or prognostic insights in 65% of the patients with no targetable alterations. In those with AML, FLT3-internal tandem duplications or tyrosine kinase domain mutations were less frequent among Koreans than among Caucasians (6.7% vs 30.2%, P < .001) or Hispanics (6.7% vs 28.3%, P = .005), suggesting ethnic differences.Variant interpretation using WfG correlated well with manually curated expert opinions. WfG provided therapeutic insights (including variant-specific drugs and clinical trials that cannot easily be provided by expert manual curation), as well as diagnostic and/or prognostic information.

Effectiveness of Contact Tracing for Viral Disease Mitigation and Suppression: Evidence-Based Review.

BACKGROUND: Contact tracing in association with quarantine and isolation is an important public health tool to control outbreaks of infectious diseases. This strategy has been widely implemented during the current COVID-19 pandemic. The effectiveness of this nonpharmaceutical intervention is largely dependent on social interactions within the population and its combination with other interventions. Given the high transmissibility of SARS-CoV-2, short serial intervals, and asymptomatic transmission patterns, the effectiveness of contact tracing for this novel viral agent is largely unknown. OBJECTIVE: This study aims to identify and synthesize evidence regarding the effectiveness of contact tracing on infectious viral disease outcomes based on prior scientific literature. METHODS: An evidence-based review was conducted to identify studies from the PubMed database, including preprint medRxiv server content, related to the effectiveness of contact tracing in viral outbreaks. The search dates were from database inception to July 24, 2020. Outcomes of interest included measures of incidence, transmission, hospitalization, and mortality. RESULTS: Out of 159 unique records retrieved, 45 (28.3%) records were reviewed at the full-text level, and 24 (15.1%) records met all inclusion criteria. The studies included utilized mathematical modeling (n=14), observational (n=8), and systematic review (n=2) approaches. Only 2 studies considered digital contact tracing. Contact tracing was mostly evaluated in combination with other nonpharmaceutical interventions and/or pharmaceutical interventions. Although some degree of effectiveness in decreasing viral disease incidence, transmission, and resulting hospitalizations and mortality was observed, these results were highly dependent on epidemic severity (R0 value), number of contacts traced (including presymptomatic and asymptomatic cases), timeliness, duration, and compliance with combined interventions (eg, isolation, quarantine, and treatment). Contact tracing effectiveness was particularly limited by logistical challenges associated with increased outbreak size and speed of infection spread. CONCLUSIONS: Timely deployment of contact tracing strategically layered with other nonpharmaceutical interventions could be an effective public health tool for mitigating and suppressing infectious outbreaks by decreasing viral disease incidence, transmission, and resulting hospitalizations and mortality.

A System to Support Diverse Social Program Management.

BACKGROUND: Social programs are services provided by governments, nonprofits, and other organizations to help improve the health and well-being of individuals, families, and communities. Social programs aim to deliver services effectively and efficiently, but they are challenged by information silos, limited resources, and the need to deliver frequently changing mandated benefits. OBJECTIVE: We aim to explore how an information system designed for social programs helps deliver services effectively and efficiently across diverse programs. METHODS: This viewpoint describes the configurable and modular architecture of Social Program Management (SPM), a system to support efficient and effective delivery of services through a wide range of social programs and lessons learned from implementing SPM across diverse settings. We explored usage data to inform the engagement and impact of SPM on the efficient and effective delivery of services. RESULTS: The features and functionalities of SPM seem to support the goals of social programs. We found that SPM provides fundamental management processes and configurable program-specific components to support social program administration; has been used by more than 280,000 caseworkers serving more than 30 million people in 13 countries; contains features designed to meet specific user requirements; supports secure information sharing and collaboration through data standardization and aggregation; and offers configurability and flexibility, which are important for digital transformation and organizational change. CONCLUSIONS: SPM is a user-centered, configurable, and flexible system for managing social program workflows.

Variations in breast cancer surgical treatment and timing: determinants and disparities.

PURPOSE: To describe clinical and non-clinical factors associated with receipt of breast conserving surgery (BCS) versus mastectomy and time to surgical intervention. METHODS: Cross-sectional retrospective study of January 1, 2012 through March 31, 2018 data from the IBM MarketScan Commercial Claims and Encounter and Medicare Supplemental Databases. Area Health Resource Files provided non-clinical characteristics and sociodemographic data. Eligibility: Female sex, claim(s) with ICD-9-CM or ICD-10-CM diagnosis of non-metastatic invasive breast cancer, > 6 months of continuous insurance pre- and post-diagnosis, evidence of BCS or mastectomy following initial ICD9/10 code diagnosis. Logistic and quantile multivariable regression models assessed the association between clinical and non-clinical factors and the outcome of BCS and time to surgery, respectively. RESULTS: A total of 53,060 women were included in the study. Compared to mastectomy, BCS was significantly associated with older age (ORs: 1.54 to 2.99, 95% CIs 1.45 to 3.38; ps < .0001) and higher community density of medical genetics (OR: 5.88, 95% CIs 1.38 to 25.00; p = 0.02) or obstetrics and gynecology (OR: 1.13, 95% CI 1.02 to 1.25; p = .02) physicians. Shorter time-to-BCS was associated with living in the South (-2.96, 95% CI -4.39 to -1.33; p < .0001). Longer time-to-BCS was associated with residence in more urban (4.18, 95% CI 0.08 to 8.29; p = 0. 05), educated (9.02, 95% CI 0.13 to 17.91; p = 0.05), or plastic-surgeon-dense (4.62, 95% CI 0.50 to 8.73; p = 0.03) communities. CONCLUSIONS: Clinical and non-clinical factors are associated with adoption of BCS and time to treatment, suggesting opportunities to ensure equitable and timely care.

The burden of the digital environment: a systematic review on organization-directed workplace interventions to mitigate physician burnout.

OBJECTIVE: To conduct a systematic review identifying workplace interventions that mitigate physician burnout related to the digital environment including health information technologies (eg, electronic health records) and decision support systems) with or without the application of advanced analytics for clinical care. MATERIALS AND METHODS: Literature published from January 1, 2007 to June 3, 2020 was systematically reviewed from multiple databases and hand searches. Subgroup analysis identified relevant physician burnout studies with interventions examining digital tool burden, related workflow inefficiencies, and measures of burnout, stress, or job satisfaction in all practice settings. RESULTS: The search strategy identified 4806 citations of which 81 met inclusion criteria. Thirty-eight studies reported interventions to decrease digital tool burden. Sixty-eight percent of these studies reported improvement in burnout and/or its proxy measures. Burnout was decreased by interventions that optimized technologies (primarily electronic health records), provided training, reduced documentation and task time, expanded the care team, and leveraged quality improvement processes in workflows. DISCUSSION: The contribution of digital tools to physician burnout can be mitigated by careful examination of usability, introducing technologies to save or optimize time, and applying quality improvement to workflows. CONCLUSION: Physician burnout is not reduced by technology implementation but can be mitigated by technology and workflow optimization, training, team expansion, and careful consideration of factors affecting burnout, including specialty, practice setting, regulatory pressures, and how physicians spend their time.

Predictive article recommendation using natural language processing and machine learning to support evidence updates in domain-specific knowledge graphs.

OBJECTIVES: Describe an augmented intelligence approach to facilitate the update of evidence for associations in knowledge graphs. METHODS: New publications are filtered through multiple machine learning study classifiers, and filtered publications are combined with articles already included as evidence in the knowledge graph. The corpus is then subjected to named entity recognition, semantic dictionary mapping, term vector space modeling, pairwise similarity, and focal entity match to identify highly related publications. Subject matter experts review recommended articles to assess inclusion in the knowledge graph; discrepancies are resolved by consensus. RESULTS: Study classifiers achieved F-scores from 0.88 to 0.94, and similarity thresholds for each study type were determined by experimentation. Our approach reduces human literature review load by 99%, and over the past 12 months, 41% of recommendations were accepted to update the knowledge graph. CONCLUSION: Integrated search and recommendation exploiting current evidence in a knowledge graph is useful for reducing human cognition load.

Clinical Decision Support for High-Risk Stage II Colon Cancer: A Real-World Study of Treatment Concordance and Survival.

BACKGROUND: Prognostic and pathologic risk factors typically guide clinicians and patients in their choice of surveillance or adjuvant chemotherapy when managing high-risk stage II colon cancer. However, variations in treatment and outcomes in patients with stage II colon cancer remain. OBJECTIVE: This study aimed to assess the survival benefits of treatments concordant with suggested therapeutic options from Watson for Oncology, a clinical decision support system. DESIGN: This is a retrospective observational study of concordance between actual treatment and Watson for Oncology therapeutic options. SETTING: This study was conducted at a top-tier cancer center in China. PATIENTS: Postoperative treatment data were retrieved from the electronic health records of 306 patients with high-risk stage II colon adenocarcinoma. MAIN OUTCOME MEASURES: The primary outcomes measured were the treatment patterns plus 3- and 5-year overall and disease-free survival for concordant and nonconcordant cases. RESULTS: Overall concordance was 90%. Most nonconcordant care resulted from adjuvant chemotherapy use (rather than surveillance) in patients with high-level microsatellite instability and ≥70 years old. No difference in overall survival (p = 0.56) or disease-free survival (p = 0.19) was observed between concordance groups. Patients receiving adjuvant chemotherapy had significantly higher 5-year overall survival than those undergoing surveillance (94% vs 84%, p = 0.01). LIMITATIONS: This study was limited by the use of retrospective cases drawn from patients presenting for surgery, the lack of complete follow-up data for 58% of patients who could not be included in the analysis, and a survival analysis that assumes no unmeasured correlation between survival and censoring. CONCLUSIONS: Watson for Oncology produced therapeutic options highly concordant with human decisions at a top-tier cancer center in China. Treatment patterns suggest that Watson for Oncology may be able to guide clinicians to minimize overtreatment of patients with high-risk stage II colon cancer with chemotherapy. Survival analyses suggest the need for further investigation to specifically assess the association between surveillance, single-agent and multiagent chemotherapy, and survival outcomes in this population. See Video Abstract at http://links.lww.com/DCR/B291. APOYO A LA DECISIÓN CLÍNICA DEL CÁNCER DE COLON EN ESTADIO II DE ALTO RIESGO: UN ESTUDIO DEL MUNDO REAL SOBRE LA CONCORDANCIA DEL TRATAMIENTO Y LA SUPERVIVENCIA: Los factores de riesgo pronósticos y patológicos generalmente guían a los médicos y pacientes en su elección de vigilancia o quimioterapia adyuvante cuando se trata el cáncer de colon en estadio II de alto riesgo. Sin embargo, las variaciones en el tratamiento y los resultados en pacientes con cáncer de colon en estadio II permanecen.Evaluar los beneficios de supervivencia de los tratamientos concordantes con las opciones terapéuticas sugeridas por "Watson for Oncology" (Watson para la oncología), un sistema de apoyo a la decisión clínica.Estudio observacional retrospectivo de concordancia entre el tratamiento real y las opciones terapéuticas de Watson para oncología.Un centro oncológico de primer nivel en China.Datos de tratamiento postoperatorio de registros de salud electrónicos de 306 pacientes con adenocarcinoma de colon en estadio II de alto riesgo.Patrones de tratamiento más supervivencia global y libre de enfermedad a 3 y 5 años para casos concordantes y no concordantes.La concordancia general fue del 90%. La mayoría de la atención no concordante resultó del uso de quimioterapia adyuvante (en lugar de vigilancia) en pacientes de alto nivel con inestabilidad de microsatélites y pacientes ≥70 años. No se observaron diferencias en la supervivencia global (p = 0,56) o la supervivencia libre de enfermedad (p = 0,19) entre los grupos de concordancia. Los pacientes que recibieron quimioterapia adyuvante tuvieron una supervivencia global a los 5 años significativamente más alta que los que fueron sometidos a vigilancia (94% frente a 84%, p = 0,01).Uso de casos retrospectivos extraídos de pacientes que se presentan para cirugía, falta de datos de seguimiento completos para el 58% de los pacientes que no pudieron ser incluidos en el análisis, y análisis de supervivencia que asume que no exite una correlación no medida entre supervivencia y censura.Watson para Oncología produjo opciones terapéuticas altamente concordantes con las decisiones humanas en un centro oncológico de primer nivel en China. Los patrones de tratamiento sugieren que Watson para Oncología puede guiar a los médicos para minimizar el sobretratamiento de pacientes con cáncer de colon en estadio II de alto riesgo con quimioterapia. Los análisis de supervivencia sugieren la necesidad de realizar mas investigaciónes para evaluar específicamente la asociación entre la vigilancia, la quimioterapia con uno solo o múltiples agentes y los resultados de supervivencia en esta población. Consulte Video Resumen en http://links.lww.com/DCR/B291. (Traducción-Dr. Gonzalo Hagerman).

A Narrative Review of Emerging Therapeutics for COVID-19.

The novel severe acute respiratory syndrome coronavirus 2, the causal agent of coronavirus disease 2019 (COVID-19), quickly spread around the world, resulting in the most aggressive pandemic experienced in more than 100 years. Research on targeted therapies and vaccines has been initiated on an unprecedented scale and speed but will take months and even years to come to fruition. Meanwhile, the efficacy of emerging therapeutics for use in treating COVID-19 is feverishly being investigated to identify the best available treatment options for dealing with the current wave of disease. This review of publications with a "treatment" tag through June 29, 2020 in the National Library of Medicine's LitCovid literature hub, provides frontline clinicians with a pragmatic summary of the current state of the rapidly evolving evidence supporting emerging candidate therapeutics for COVID-19. Two main categories of pharmaceutical therapeutics are showing promise: those with antiviral activity directly addressing infection and those that counteract the inflammatory cytokine storm induced by severe disease. Preliminary results suggest that other approaches such as convalescent plasma therapy and lung radiation therapy may have some efficacy. The current clinical evidence for potential treatments is preliminary-often small retrospective series or early results of randomized trials-and the science is evolving rapidly. The long-term results from large, well-designed randomized controlled trials will provide definitive evidence for therapeutic effectiveness and are likely months away. The trial landscape for promising therapies is described.

Rapid review: Identification of digital health interventions in atherosclerotic-related cardiovascular disease populations to address racial, ethnic, and socioeconomic health disparities.

Disparities in cardiovascular disease (CVD) and associated health and healthcare delivery outcomes have been partially attributed to differential risk factors, and to prevention and treatment inequities within racial and ethnic (including language) minority groups and low socioeconomic status (SES) populations in urban and rural settings. Digital health interventions (DHIs) show promise in promoting equitable access to high-quality care, optimal utilization, and improved outcomes; however, their potential role and impact has not been fully explored. The role of DHIs to mitigate drivers of the health disparities listed above in populations disproportionately affected by atherosclerotic-related CVD was systematically reviewed using published literature (January 2008-July 2020) from multiple databases. Study design, type and description of the technology, health disparities information, type of CVD, outcomes, and notable barriers and innovations associated with the technology utilized were abstracted. Study quality was assessed using the Oxford Levels of Evidence. Included studies described digital health technologies in a disparity population with CVD and reported outcomes. DHIs significantly improved health (eg, clinical, intermediate, and patient-reported) and healthcare delivery (eg, access, quality, and utilization of care) outcomes in populations disproportionately affected by CVD in 24 of 38 included studies identified from 2104 citations. Hypertension control was the most frequently improved clinical outcome. Telemedicine, mobile health, and clinical decision support systems were the most common types of DHIs identified. DHIs improved CVD-related health and healthcare delivery outcomes in racial/ethnic groups and low SES populations in both rural and urban geographies globally.

Identification of pharmacodynamic biomarker hypotheses through literature analysis with IBM Watson.

BACKGROUND: Pharmacodynamic biomarkers are becoming increasingly valuable for assessing drug activity and target modulation in clinical trials. However, identifying quality biomarkers is challenging due to the increasing volume and heterogeneity of relevant data describing the biological networks that underlie disease mechanisms. A biological pathway network typically includes entities (e.g. genes, proteins and chemicals/drugs) as well as the relationships between these and is typically curated or mined from structured databases and textual co-occurrence data. We propose a hybrid Natural Language Processing and directed relationships-based network analysis approach using IBM Watson for Drug Discovery to rank all human genes and identify potential candidate biomarkers, requiring only an initial determination of a specific target-disease relationship. METHODS: Through natural language processing of scientific literature, Watson for Drug Discovery creates a network of semantic relationships between biological concepts such as genes, drugs, and diseases. Using Bruton's tyrosine kinase as a case study, Watson for Drug Discovery's automatically extracted relationship network was compared with a prominent manually curated physical interaction network. Additionally, potential biomarkers for Bruton's tyrosine kinase inhibition were predicted using a matrix factorization approach and subsequently compared with expert-generated biomarkers. RESULTS: Watson's natural language processing generated a relationship network matching 55 (86%) genes upstream of BTK and 98 (95%) genes downstream of Bruton's tyrosine kinase in a prominent manually curated physical interaction network. Matrix factorization analysis predicted 11 of 13 genes identified by Merck subject matter experts in the top 20% of Watson for Drug Discovery's 13,595 ranked genes, with 7 in the top 5%. CONCLUSION: Taken together, these results suggest that Watson for Drug Discovery's automatic relationship network identifies the majority of upstream and downstream genes in biological pathway networks and can be used to help with the identification and prioritization of pharmacodynamic biomarker evaluation, accelerating the early phases of disease hypothesis generation.

A new mouse anti-mouse complement receptor type 2 and 1 (CR2/CR1) monoclonal antibody as a tool to study receptor involvement in chronic models of immune responses and disease.

Although reagents are available to block mouse complement receptor type 2 and/or type 1 (CR2/CR1, CD21/CD35) function in acute or short term models of human disease, a mouse anti-rat antibody response limits their use in chronic models. We have addressed this problem by generating in Cr2−/− mice a mouse monoclonal antibody (mAb 4B2) to mouse CR2/CR1. The binding of murine mAb 4B2 to CR2/CR1 directly blocked C3dg (C3d) ligand binding. In vivo injection of mAb 4B2 induced substantial down regulation of CR2 and CR1 from the B cell surface, an effect that lasted six weeks after a single injection of 2 mg of mAb. The 4B2 mAb was studied in vivo for the capability to affect immunological responses to model antigens. Pre-injection of mAb 4B2 before immunization of C57BL/6 mice reduced the IgG1 antibody response to the T-dependent antigen sheep red blood cells (SRBC) to a level comparable to that found in Cr2−/− mice. We also used the collagen-induced arthritis (CIA) model, a CR2/CR1-dependent autoimmune disease model, and found that mice pre-injected with mAb 4B2 demonstrated substantially reduced levels of pathogenic IgG2a antibodies to both the bovine type II collagen (CII) used to induce arthritis and to endogenous mouse CII. Consistent with this result, mice pre-injected with mAb 4B2 demonstrated only very mild arthritis. This reduction in disease, together with published data in CII-immunized Cr2−/− mice, confirm both that the arthritis development depends on CR2/CR1 receptors and that mAb 4B2 can be used to induce biologically relevant receptor blockade. Thus mAb 4B2 is an excellent candidate for use in chronic murine models to determine how receptor blockage at different points modifies disease activity and autoantibody responses.

Protein Kinase C α Modulates Estrogen-Receptor-Dependent Transcription and Proliferation in Endometrial Cancer Cells.

Endometrial cancer is the most common invasive gynecologic malignancy in developed countries. The most prevalent endometrioid tumors are linked to excessive estrogen exposure and hyperplasia. However, molecular mechanisms and signaling pathways underlying their etiology and pathophysiology remain poorly understood. We have shown that protein kinase C α (PKC α ) is aberrantly expressed in endometrioid tumors and is an important mediator of endometrial cancer cell survival, proliferation, and invasion. In this study, we demonstrate that expression of active, myristoylated PKC α conferred ligand-independent activation of estrogen-receptor- (ER-) dependent promoters and enhanced responses to estrogen. Conversely, knockdown of PKC α reduced ER-dependent gene expression and inhibited estrogen-induced proliferation of endometrial cancer cells. The ability of PKC α to potentiate estrogen activation of ER-dependent transcription was attenuated by inhibitors of phosphoinositide 3-kinase (PI3K) and Akt. Evidence suggests that PKC α and estrogen signal transduction pathways functionally interact, to modulate ER-dependent growth and transcription. Thus, PKC α signaling, via PI3K/Akt, may be a critical element of the hyperestrogenic environment and activation of ER that is thought to underlie the development of estrogen-dependent endometrial hyperplasia and malignancy. PKC α -dependent pathways may provide much needed prognostic markers of aggressive disease and novel therapeutic targets in ER positive tumors.

Sputum autoantibodies in patients with established rheumatoid arthritis and subjects at risk of future clinically apparent disease.

OBJECTIVE: To evaluate the generation of rheumatoid arthritis (RA)-related autoantibodies in the lung. METHODS: Simultaneous collection of serum and induced sputum was performed in 21 healthy controls, 49 at-risk subjects without inflammatory arthritis but at risk of RA due to family history or seropositivity for anti-citrullinated protein antibodies, and 14 subjects with early RA. Samples were tested for anti-cyclic citrullinated peptide 2 (anti-CCP2), anti-CCP3, anti-CCP3.1, rheumatoid factor isotypes IgM, IgG, and IgA, and total IgM, IgG, and IgA. RESULTS: One or more autoantibodies were present in sputum of 39% of at-risk seronegative subjects, 65% of at-risk seropositive subjects, and 86% of subjects with early RA. In at-risk seronegative subjects, the rate of anti-CCP3.1 positivity and the median number of autoantibodies were elevated in sputum versus serum. In subjects with early RA, the rate of positivity for several individual autoantibodies and the median number of autoantibodies were higher in serum than in sputum. Results in at-risk seropositive subjects were intermediate between these groups. In at-risk subjects with autoantibody positivity in sputum, the ratios of autoantibody to total Ig were higher in sputum than in serum, suggesting that these autoantibodies are generated or sequestered in the lung. CONCLUSION: RA-related autoantibodies are detectable in sputum in subjects at risk of RA and in subjects with early RA. In a subset of at-risk subjects, the presence of sputum autoantibodies in the absence of seropositivity, and the increased autoantibody-to-total Ig ratios in sputum, suggest that the lung may be a site of autoantibody generation in the early development of RA. These findings suggest an important role of the lung in the pathogenesis of RA.

A citrullinated fibrinogen-specific T cell line enhances autoimmune arthritis in a mouse model of rheumatoid arthritis.

Citrullinated proteins, derived from the conversion of peptidyl-arginine to peptidyl-citrulline, are present in the joints of patients with rheumatoid arthritis (RA), who also uniquely produce high levels of anti-citrullinated protein Abs. Citrullinated fibrinogen (CF) is abundant in rheumatoid synovial tissue, and anti-citrullinated protein Ab-positive RA patients exhibit circulating immune complexes containing CF. Thus, CF is a potential major target of pathogenic autoimmunity in RA. T cells are believed to be involved in this process by initiating, controlling, and driving Ag-specific immune responses in RA. In this study, we isolated a CD4 T cell line specific for CF that produces inflammatory cytokines. When transferred into mice with collagen-induced arthritis (CIA), this T cell line specifically enhanced the severity of autoimmune arthritis. Additionally, pathogenic IgG2a autoantibody levels to mouse type II collagen were increased in mice that received the T cells in CIA, and levels of these T cells were increased in the synovium, suggesting the T cells may have had systemic effects on the B cell response as well as local effects on the inflammatory environment. This work demonstrates that CD4 T cells specific for CF can amplify disease severity after onset of CIA.

Potentially autoreactive naturally occurring transitional T3 B lymphocytes exhibit a unique signaling profile.

B lymphocytes exhibit phenotypic differences that correlate with their developmental or functional stages and affect humoral immune responses. One recently described subset of naturally occurring immature transitional type 3 (T3) B lymphocytes is believed to consist of potentially autoimmune cells whose signaling properties have not been studied in detail. This study characterizes intracellular signaling in T3 B cells in wildtype C57BL/6 mice. Protein phosphorylation and Ca(2+) responses upon B-cell antigen receptor (BCR) engagement were measured by multicolor flow cytometry. We observed high baseline signaling activity and reduced BCR-mediated responses in T3 cells, which confirmed their anergy - a functional state in which lymphocytes recognize chronically present self-antigens but cannot produce immune response due to intrinsic signaling inhibition. Our results also revealed a previously unknown T3-specific phosphorylation pattern of 24 key signaling molecules involved in BCR signal transduction. These characteristics reflect the balance between stimulatory and inhibitory BCR signaling pathways in anergy. Results obtained in the collagen-induced arthritis model demonstrate the loss of anergy in T3 B cells during the onset of the disease. Our findings provide rationale for further investigating alterations in B-cell signaling patterns as earliest functional biomarkers of changes in the immune tolerance of autoreactive B cells.

N-α-benzoyl-N5-(2-chloro-1-iminoethyl)-L-ornithine amide, a protein arginine deiminase inhibitor, reduces the severity of murine collagen-induced arthritis.

Rheumatoid arthritis is associated with the development of autoantibodies to citrullinated self-proteins. Citrullinated synovial proteins, which are generated via the actions of the protein arginine deiminases (PADs), are known to develop in the murine collagen-induced arthritis (CIA) model of inflammatory arthritis. Given these findings, we evaluated whether N-α-benzoyl-N5-(2-chloro-1-iminoethyl)-L-ornithine amide (Cl-amidine), a recently described pan-PAD inhibitor, could affect the development of arthritis and autoimmunity by treating mice in the CIA model with Cl-amidine on days 0-35. Cl-amidine treatment reduced total synovial and serum citrullination, decreased clinical disease activity by ∼50%, and significantly decreased IgG2a anti-mouse type II collagen Abs. Additionally, histopathology scores and total complement C3 deposition were significantly lower in Cl-amidine-treated mice compared with vehicle controls. Synovial microarray analyses demonstrated decreased IgG reactivity to several native and citrullinated epitopes compared with vehicle controls. Cl-amidine treatment had no ameliorative effect on collagen Ab-induced arthritis, suggesting its primary protective mechanism was not mediated through effector pathways. Reduced levels of citrullinated synovial proteins observed in mice treated with Cl-amidine are consistent with the notion that Cl-amidine derives its efficacy from its ability to inhibit the deiminating activity of PADs. In total, these results suggested that PADs are necessary participants in the autoimmune and subsequent inflammatory processes in CIA. Cl-amidine may represent a novel class of disease-modifying agents that modulate aberrant citrullination, and perhaps other immune processes, necessary for the development of inflammatory arthritis.

Western blot analysis to illustrate relative control levels of the lac and ara promoters in Escherichia coli.

The lactose operon and its control is a fundamental transcriptional regulatory concept presented in introductory and many advanced molecular biology courses. Much is known about the positive and negative control mechanisms that govern levels of expression of this operon. One basic principle that is taught about the lac operon is that it is "leaky," meaning that the transcriptional control of the operon is not 100% efficient and that in wild-type cells, transcription from the promoter is never completely "off," but there is always some basal transcription. In contrast, the arabinose operon is often used as an example of a tightly controlled operon, and transcription from the ara promoter is very low in the absence of inducer. The relative levels of control of these two operons can be illustrated using Western blots of proteins expressed in the presence and absence of the appropriate inducers and antibodies against the gene products. Different times of growth and the addition of inducer can also be examined. The results are very dramatic and help to reinforce the principles of promoter control.