Integrated Land Use-Transport Model System with Dynamic Time-Dependent Activity-Travel Microsimulation

The development of integrated land use-transport model systems has long been of interest because of the complex interrelationships between land use, transport demand, and network supply. This paper describes the design and prototype implementation of an integrated model system that involves the microsimulation of location choices in the land use domain, activity-travel choices in the travel demand domain, and individual vehicles on networks in the network supply modeling domain. Although many previous applications of integrated transport demand-supply models have relied on a sequential coupling of the models, the system presented in this paper involves a dynamic integration of the activity-travel demand model and the dynamic traffic assignment and simulation model with appropriate feedback to the land use model system. The system has been fully implemented, and initial results of model system runs in a case study test application suggest that the proposed model design provides a robust behavioral framework for simulation of human activity-travel behavior in space, time, and networks. The paper provides a detailed description of the design, together with results from initial test runs

The prognostic significance of low-frequency somatic mutations in metastatic cutaneous melanoma

Background: Little is known about the prognostic significance of somatically mutated genes in metastatic melanoma (MM). We have employed a combined clinical and bioinformatics approach on tumor samples from cutaneous melanoma (SKCM) as part of The Cancer Genome Atlas project (TCGA) to identify mutated genes with potential clinical relevance. Methods: After limiting our DNA sequencing analysis to MM samples (n = 356) and to the CANCER CENSUS gene list, we filtered out mutations with low functional significance (snpEFF). We performed Cox analysis on 53 genes that were mutated in ≥3% of samples, and had ≥50% difference in incidence of mutations in deceased subjects versus alive subjects. Results: Four genes were potentially prognostic [RAC1, FGFR1, CARD11, CIITA; false discovery rate (FDR) 75% of the samples that exhibited corresponding DNA mutations. The low frequency, UV signature type and RNA expression of the 22 genes in MM samples were confirmed in a separate multi-institution validation cohort (n = 413). An underpowered analysis within a subset of this validation cohort with available patient follow-up (n = 224) showed that somatic mutations in SPEN and RAC1 reached borderline prognostic significance [log-rank favorable (p = 0.09) and adverse (p = 0.07), respectively]. Somatic mutations in SPEN, and to a lesser extent RAC1, were not associated with definite gene copy number or RNA expression alterations. High (>2+) nuclear plus cytoplasmic expression intensity for SPEN was associated with longer melanoma-specific overall survival (OS) compared to lower (≤ 2+) nuclear intensity (p = 0.048). We conclude that expressed somatic mutations in infrequently mutated genes beyond the well-characterized ones (e.g., BRAF, RAS, CDKN2A, PTEN, TP53), such as RAC1 and SPEN, may have prognostic significance in MM

Global Retinoblastoma Presentation and Analysis by National Income Level

Importance: Early diagnosis of retinoblastoma, the most common intraocular cancer, can save both a child's life and vision. However, anecdotal evidence suggests that many children across the world are diagnosed late. To our knowledge, the clinical presentation of retinoblastoma has never been assessed on a global scale. Objectives: To report the retinoblastoma stage at diagnosis in patients across the world during a single year, to investigate associations between clinical variables and national income level, and to investigate risk factors for advanced disease at diagnosis. Design, Setting, and Participants: A total of 278 retinoblastoma treatment centers were recruited from June 2017 through December 2018 to participate in a cross-sectional analysis of treatment-naive patients with retinoblastoma who were diagnosed in 2017. Main Outcomes and Measures: Age at presentation, proportion of familial history of retinoblastoma, and tumor stage and metastasis. Results: The cohort included 4351 new patients from 153 countries; the median age at diagnosis was 30.5 (interquartile range, 18.3-45.9) months, and 1976 patients (45.4) were female. Most patients (n = 3685 84.7%) were from low-and middle-income countries (LMICs). Globally, the most common indication for referral was leukocoria (n = 2638 62.8%), followed by strabismus (n = 429 10.2%) and proptosis (n = 309 7.4%). Patients from high-income countries (HICs) were diagnosed at a median age of 14.1 months, with 656 of 666 (98.5%) patients having intraocular retinoblastoma and 2 (0.3%) having metastasis. Patients from low-income countries were diagnosed at a median age of 30.5 months, with 256 of 521 (49.1%) having extraocular retinoblastoma and 94 of 498 (18.9%) having metastasis. Lower national income level was associated with older presentation age, higher proportion of locally advanced disease and distant metastasis, and smaller proportion of familial history of retinoblastoma. Advanced disease at diagnosis was more common in LMICs even after adjusting for age (odds ratio for low-income countries vs upper-middle-income countries and HICs, 17.92 95% CI, 12.94-24.80, and for lower-middle-income countries vs upper-middle-income countries and HICs, 5.74 95% CI, 4.30-7.68). Conclusions and Relevance: This study is estimated to have included more than half of all new retinoblastoma cases worldwide in 2017. Children from LMICs, where the main global retinoblastoma burden lies, presented at an older age with more advanced disease and demonstrated a smaller proportion of familial history of retinoblastoma, likely because many do not reach a childbearing age. Given that retinoblastoma is curable, these data are concerning and mandate intervention at national and international levels. Further studies are needed to investigate factors, other than age at presentation, that may be associated with advanced disease in LMICs. © 2020 American Medical Association. All rights reserved

Comparison of algorithm-based estimates of occupational diesel exhaust exposure to those of multiple independent raters in a population-based case-control study

Objectives: Algorithm-based exposure assessments based on patterns in questionnaire responses and professional judgment can readily apply transparent exposure decision rules to thousands of jobs quickly. However, we need to better understand how algorithms compare to a one-by-one job review by an exposure assessor. We compared algorithm-based estimates of diesel exhaust exposure to those of three independent raters within the New England Bladder Cancer Study, a population-based case-control study, and identified conditions under which disparities occurred in the assessments of the algorithm and the raters.Methods: Occupational diesel exhaust exposure was assessed previously using an algorithm and a single rater for all 14 983 jobs reported by 2631 study participants during personal interviews conducted from 2001 to 2004. Two additional raters independently assessed a random subset of 324 jobs that were selected based on strata defined by the cross-tabulations of the algorithm and the first rater's probability assessments for each job, oversampling their disagreements. The algorithm and each rater assessed the probability, intensity and frequency of occupational diesel exhaust exposure, as well as a confidence rating for each metric. Agreement among the raters, their aggregate rating (average of the three raters' ratings) and the algorithm were evaluated using proportion of agreement, kappa and weighted kappa (κw). Agreement analyses on the subset used inverse probability weighting to extrapolate the subset to estimate agreement for all jobs. Classification and Regression Tree (CART) models were used to identify patterns in questionnaire responses that predicted disparities in exposure status (i.e., unexposed versus exposed) between the first rater and the algorithm-based estimates.Results: For the probability, intensity and frequency exposure metrics, moderate to moderately high agreement was observed among raters (κw = 0.50-0.76) and between the algorithm and the individual raters (κw = 0.58-0.81). For these metrics, the algorithm estimates had consistently higher agreement with the aggregate rating (κw = 0.82) than with the individual raters. For all metrics, the agreement between the algorithm and the aggregate ratings was highest for the unexposed category (90-93%) and was poor to moderate for the exposed categories (9-64%). Lower agreement was observed for jobs with a start year <1965 versus ≥1965. For the confidence metrics, the agreement was poor to moderate among raters (κw = 0.17-0.45) and between the algorithm and the individual raters (κw = 0.24-0.61). CART models identified patterns in the questionnaire responses that predicted a fair-to-moderate (33-89%) proportion of the disagreements between the raters' and the algorithm estimates.Discussion: The agreement between any two raters was similar to the agreement between an algorithm-based approach and individual raters, providing additional support for using the more efficient and transparent algorithm-based approach. CART models identified some patterns in disagreements between the first rater and the algorithm. Given the absence of a gold standard for estimating exposure, these patterns can be reviewed by a team of exposure assessors to determine whether the algorithm should be revised for future studies. © 2012 The Author

Interaction of Shiga toxin from Escherichia coli with human intestinal epithelial cell lines and explants: Stx2 induces epithelial damage in organ culture

Shiga toxins (Stx) produced by Escherichia coli are associated with systemic complications such as haemolytic-uraemic syndrome. The mechanism of Stx translocation across the epithelial barrier is unknown as human intestinal epithelium lacks receptor Gb3. In this study, we have examined the interaction of purified Stx1 and 2 with Caco-2 (Gb3(+)) and T84 (Gb3(-)) cell lines, and determined the effects of Stx on human intestine using in vitro organ culture (IVOC). Stx exposure caused inhibition of protein synthesis and apoptosis in Caco-2 but not in T84 cells. However, both Stx1 and 2 were transported to the endoplasmic reticulum, and the Stx1 A-subunit was cleaved in a furin-dependent manner in both cell lines. Thus, a Gb3-independent retrograde transport route exists in T84 cells for Stx that does not induce cell damage. IVOC demonstrated increased epithelial cell extrusion in response to exposure to Stx2, but not Stx1, in both small intestine and colon. Pretreatment of Stx2 with Stx2-specific antibody abrogated this effect. Overlaying frozen sections with Stx showed lamina propria, but not epithelial, cell binding that paralleled Gb3 localization, and included endothelium and pericryptal myofibroblasts. This indicates that human intestinal epithelium may evince Stx2-induced damage in the absence of Gb3 receptors, by an as yet unrecognized mechanism

Read, think, do!: A method for fitting research evidence into practice

Aim. This paper discusses a process for research utilization that overcomes well known barriers in order to influence clinical decision-making and practice change. Read, Think, Do! is a problem-solving approach to research utilization and practice development which has the potential to overcome barriers to research utilization. Background. Any process for research utilization at the practice level needs to overcome numerous barriers in order to influence clinical decision-making and practice change. Access to research-based knowledge is an obvious first step in the evidence-based approach to care delivery, but is clearly inadequate alone in influencing the improvement of practice. Discussion. Read, Think, Do! acknowledges the complexity of problem-solving processes from the outset by looking for (1) the evidence, (2) assessing the value to practice, and (3) addressing the social and cultural milieu of the practice setting to ascertain the best strategies for initiating and sustaining practice change. This approach draws distal forms of empirical knowledge that have the capacity to improve patient outcomes into the proximal knowledge base of the clinical nurse. This is achieved by collaboration, planning and evaluation involving all levels of staff and a specialist facilitator, the Clinical Nurse Consultant in evidence-based practice. Conclusion. Read, Think, Do! is a method of research utilization and practice development that has the potential to overcome barriers to research utilization and avoid the "misplaced concreteness" that can occur when trying to fit empiricism into practice. By addressing the breadth and diversity of issues surrounding research utilization in a systematic manner it presents a sustainable method for practice change informed by evidence