BackgroundNeutrophil extracellular traps (NETs), extracellular structures composed of decondensed chromatin and antimicrobial molecules, are released in a process called NETosis. NETs, which are part of normal host defense, have also been implicated in multiple human diseases. Unfortunately, methods for quantifying NETs have limitations which constrain the study of NETs in disease. Establishing optimal methods for NET quantification holds the potential to further elucidate the role of NETs in normal and pathologic processes.ResultsTo better quantify NETs and NET-like structures, we created DNA Area and NETosis Analysis (DANA), a novel ImageJ/Java based program which provides a simple, semi-automated approach to quantify NET-like structures and DNA area. DANA can analyze many fluorescent microscope images at once and provides data on a per cell, per image, and per sample basis. Using fluorescent microscope images of Sytox-stained human neutrophils, DANA quantified a similar frequency of NET-like structures to the frequency determined by two different individuals counting by eye, and in a fraction of the time. As expected, DANA also detected increased DNA area and frequency of NET-like structures in neutrophils from subjects with rheumatoid arthritis as compared to control subjects. Using images of DAPI-stained murine neutrophils, DANA (installed by an individual with no programming background) gave similar frequencies of NET-like structures as the frequency of NETs determined by two individuals counting by eye. Further, DANA quantified more NETs in stimulated murine neutrophils compared to unstimulated, as expected.ConclusionsDANA provides a means to quantify DNA decondensation and the frequency of NET-like structures using a variety of different fluorescent markers in a rapid, reliable, simple, high-throughput, and cost-effective manner making it optimal to assess NETosis in a variety of conditions.Electronic supplementary materialThe online version of this article (10.1186/s12575-018-0072-y) contains supplementary material, which is available to authorized users.

PURPOSE The objective was to examine the relationship between contemporary redlining (mortgage lending bias on the basis of property location) and survival among older women with breast cancer in the United States. METHODS A redlining index using Home Mortgage Disclosure Act data (2007-2013) was linked by census tract with a SEER-Medicare cohort of 27,516 women age 66-90 years with an initial diagnosis of stage I-IV breast cancer in 2007-2009 and follow-up through 2015. Cox proportional hazards models were used to examine the relationship between redlining and both all-cause and breast cancer–specific mortality, accounting for covariates. RESULTS Overall, 34% of non-Hispanic White, 57% of Hispanic, and 79% of non-Hispanic Black individuals lived in redlined tracts. As the redlining index increased, women experienced poorer survival. This effect was strongest for women with no comorbid conditions, who comprised 54% of the sample. For redlining index values of 1 (low), 2 (moderate), and 3 (high), as compared with 0.5 (least), hazard ratios (HRs) (and 95% CIs) for all-cause mortality were HR = 1.10 (1.06 to 1.14), HR = 1.27 (1.17 to 1.38), and HR = 1.39 (1.25 to 1.55), respectively, among women with no comorbidities. A similar pattern was found for breast cancer–specific mortality. CONCLUSION Contemporary redlining is associated with poorer breast cancer survival. The impact of this bias is emphasized by the pronounced effect even among women with health insurance (Medicare) and no comorbid conditions. The magnitude of this neighborhood level effect demands an increased focus on upstream determinants of health to support comprehensive patient care. The housing sector actively reveals structural racism and economic disinvestment and is an actionable policy target to mitigate adverse upstream health determinants for the benefit of patients with cancer.

Background: Breast cancer patients of low socioeconomic status (SES) have worse survival than more affluent women and are also more likely to undergo surgery in low-volume facilities. Since breast cancer patients treated in high-volume facilities have better survival, regionalizing the care of low SES patients toward high-volume facilities might reduce SES disparities in survival. Objective: We leverage a natural experiment in New York state to examine whether a policy precluding payment for breast cancer surgery for New York Medicaid beneficiaries undergoing surgery in low-volume facilities led to reduced SES disparities in mortality. Research Design: A multivariable difference-in-differences regression analysis compared mortality of low SES (dual enrollees, Medicare-Medicaid) breast cancer patients to that of wealthier patients exempt from the policy (Medicare only) for time periods before and after the policy implementation. Subjects: A total of 14,183 Medicare beneficiaries with breast cancer in 2006–2008 or 2014–2015. Measures: All-cause mortality at 3 years after diagnosis and Medicaid status, determined by Medicare administrative data. Results: Both low SES and Medicare-only patients had better 3-year survival after the policy implementation. However, the decline in mortality was larger in magnitude among the low SES women than others, resulting in a 53% smaller SES survival disparity after the policy after adjustment for age, race, and comorbid illness. Conclusion: Regionalization of early breast cancer care away from low-volume centers may improve outcomes and reduce SES disparities in survival.

An impressive comparison of G(r) calculated with PDFgetX2(1) from data of Naphthalen taken at room temperature with a Stoe Stadi P powder diffractometer in Transmission mode equipped with a Ag-tube, a Ge(111)-monochromator for pure Ag-Kα1-radiation (0.5594 Å) as well as the Dectris MYTHEN 1K with1mm chip size and from synchrotron data, beamline X17A, NSLS Brookhaven with a wavelength of 0.1839 Å, yields amazingly similar peak widths for both experiment sites. To observe the temperature dependence of this resolution, the same laboratory setup with an additional Oxford Cryosystems Cobra or a Stoe furnace has been chosen to compare the signal width as a function of T. Low temperature data for these PDF calculation experiments has been taken from LaB6 as a crystalline standard and Naphthalene as well known organic phase. In addition high temperature G(r)-data from Ammonium Nitride will be demonstrated.

e18557 Background: The purpose of this study was to examine the association between measures of housing quality, stability, and access on breast cancer stage at diagnosis among older women living in the United States. Methods: This study included 67,588 women aged 66-90 with data from the SEER-Medicare linked database. The primary outcome was breast cancer stage at diagnosis. Multinomial regression models were performed using a three-category outcome (stage 0, early-stage (I-II), late-stage (III-IV)). The key independent variables were median housing value, percentage living in the same house as the previous year, percentage owner occupied homes, and an index of contemporary mortgage lending bias (redlining). Results: In adjusted models, higher contemporary mortgage lending bias was significantly associated with later-stage diagnosis (RR = 1.10 1.02-1.20; RR = 1.31, 95% CI 1.16-1.49; RR = 1.41, 95% CI 1.24-1.60 for Least to High, respectively). Median housing value was inversely associated with later-stage diagnosis, but to a lesser degree than mortgage lending bias (RR = 0.88, 95%CI 0.80-0.96; RR = 0.77, 95% CI 0.68-0.88 for second and third tertiles, respectively). Owner occupancy and tenure were not significantly associated with late-stage diagnosis in adjusted models. Conclusions: Contemporary mortgage lending bias demonstrated a significant dose-response relationship with later stage at diagnosis of breast cancer in this cohort of elderly women. Policy interventions aimed at reducing the effects of redlining with the goal of decreasing late-stage breast cancer diagnosis to improve prognosis should be considered. Table. Relative risk of late stage breast cancer diagnosis based on measures of housing quality and stability, as well as redlining. Risk is relative to the base outcome, stage 0. Values for the first tertile of housing quality and stability as well as the “least” category for redlining are not shown in this table as they are the base outcome which the other values are compared to. Standard error was adjusted for MSA clustering effects in all models.[Table: see text]