Breast density classification with deep convolutional neural networks

Breast density classification is an essential part of breast cancer screening. Although a lot of prior work considered this problem as a task for learning algorithms, to our knowledge, all of them used small and not clinically realistic data both for training and evaluation of their models. In this work, we explore the limits of this task with a data set coming from over 200,000 breast cancer screening exams. We use this data to train and evaluate a strong convolutional neural network classifier. In a reader study, we find that our model can perform this task comparably to a human expert

DataSHIELD: resolving a conflict in contemporary bioscience—performing a pooled analysis of individual-level data without sharing the data

Background Contemporary bioscience sometimes demands vast sample sizes and there is often then no choice but to synthesize data across several studies and to undertake an appropriate pooled analysis. This same need is also faced in health-services and socio-economic research. When a pooled analysis is required, analytic efficiency and flexibility are often best served by combining the individual-level data from all sources and analysing them as a single large data set. But ethico-legal constraints, including the wording of consent forms and privacy legislation, often prohibit or discourage the sharing of individual-level data, particularly across national or other jurisdictional boundaries. This leads to a fundamental conflict in competing public goods: individual-level analysis is desirable from a scientific perspective, but is prevented by ethico-legal considerations that are entirely valid

ICOSL+ plasmacytoid dendritic cells as inducer of graft-versus-host disease, responsive to a dual ICOS/CD28 antagonist

Acute graft-versus-host disease (aGVHD) remains a major complication of allogeneic hematopoietic cell transplantation (HCT). CD146 and CCR5 are proteins that mark activated T helper 17 (Th17) cells. The Th17 cell phenotype is promoted by the interaction of the receptor ICOS on T cells with ICOS ligand (ICOSL) on dendritic cells (DCs). We performed multiparametric flow cytometry in a cohort of 156 HCT recipients and conducted experiments with aGVHD murine models to understand the role of ICOSL+ DCs. We observed an increased frequency of ICOSL+ plasmacytoid DCs, correlating with CD146+CCR5+ T cell frequencies, in the 64 HCT recipients with gastrointestinal aGVHD. In murine models, donor bone marrow cells from ICOSL-deficient mice compared to those from wild-type mice reduced aGVHD-related mortality. Reduced aGVHD resulted from lower intestinal infiltration of pDCs and pathogenic Th17 cells. We transplanted activated human ICOSL+ pDCs along with human peripheral blood mononuclear cells into immunocompromised mice and observed infiltration of intestinal CD146+CCR5+ T cells. We found that prophylactic administration of a dual human ICOS/CD28 antagonist (ALPN-101) prevented aGVHD in this model better than did the clinically approved belatacept (CTLA-4-Fc), which binds CD80 (B7-1) and CD86 (B7-2) and interferes with the CD28 T cell costimulatory pathway. When started at onset of aGVHD signs, ALPN-101 treatment alleviated symptoms of ongoing aGVHD and improved survival while preserving antitumoral cytotoxicity. Our data identified ICOSL+-pDCs as an aGVHD biomarker and suggest that coinhibition of the ICOSL/ICOS and B7/CD28 axes with one biologic drug may represent a therapeutic opportunity to prevent or treat aGVHD

Realizing the promise of population biobanks: a new model for translation

The promise of science lies in expectations of its benefits to societies and is matched by expectations of the realisation of the significant public investment in that science. In this paper, we undertake a methodological analysis of the science of biobanking and a sociological analysis of translational research in relation to biobanking. Part of global and local endeavours to translate raw biomedical evidence into practice, biobanks aim to provide a platform for generating new scientific knowledge to inform development of new policies, systems and interventions to enhance the public’s health. Effectively translating scientific knowledge into routine practice, however, involves more than good science. Although biobanks undoubtedly provide a fundamental resource for both clinical and public health practice, their potentiating ontology—that their outputs are perpetually a promise of scientific knowledge generation—renders translation rather less straightforward than drug discovery and treatment implementation. Biobanking science, therefore, provides a perfect counterpoint against which to test the bounds of translational research. We argue that translational research is a contextual and cumulative process: one that is necessarily dynamic and interactive and involves multiple actors. We propose a new multidimensional model of translational research which enables us to imagine a new paradigm: one that takes us from bench to bedside to backyard and beyond, that is, attentive to the social and political context of translational science, and is cognisant of all the players in that process be they researchers, health professionals, policy makers, industry representatives, members of the public or research participants, amongst others

Losartan to reduce inflammation and fibrosis endpoints in HIV disease

Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved. BACKGROUND: Persistent inflammation and incomplete immune recovery among persons with HIV (PHIV) are associated with increased disease risk. We hypothesized that the angiotensin receptor blocker (ARB) losartan would reduce inflammation by mitigating nuclear factor (NF)κB responses and promote T-cell recovery via inhibition of transforming growth factor-beta (TGFβ)-mediated fibrosis. METHODS: Losartan (100 mg) versus placebo over 12 months was investigated in a randomized (1 : 1) placebo-controlled trial, among PHIV age at least 50 years, receiving antiretroviral therapy (ART), with HIV RNA less than 200 copies/ml and CD4+ cell count 600 cells/μl or less. Inflammation, fibrosis and myocardial biomarkers were measured in blood using ELISA, electrochemiluminescence and immunoturbidimetric methods, and T-cell and monocyte phenotypes were assessed with flow cytometry among a subset of participants. Changes over follow-up in (log-2 transformed) biomarkers and cell phenotypes (untransformed) were compared between losartan and placebo arms using linear mixed models. RESULTS: Among 108 PHIV (n = 52 to losartan; n = 56 to placebo), 97% had a month 12 visit. Median age was 57 years and baseline CD4+ cell count was 408 cells/μl. Losartan treatment was not associated with an improvement in interleukin-6 levels, or other blood measures of inflammation, immune activation, fibrosis activity or myocardial function. CD4+ and CD8+ T cells also did not differ by treatment group. Losartan reduced SBP and DBP by 6 and 5 mmHg, respectively. CONCLUSION: Among older PHIV with viral suppression, losartan did not improve blood measures of inflammation nor T-cell immune recovery. Losartan treatment is unlikely to reduce inflammation associated comorbidities to a clinically meaningful degree, beyond the benefits from lowering blood pressure. CLINICALTRIALSGOV: NCT02049307

Short Communication: A Pilot Study of the Effects of Losartan Versus Placebo on Pneumoproteins in HIV: A Secondary Analysis of a Randomized Double Blind Study

HIV is an independent risk factor for lung disease, including chronic obstructive pulmonary disease (COPD) and emphysema. Angiotensin receptor blockers may be beneficial in COPD and emphysema through pathways that have been implicated in HIV-related lung disease. We performed a randomized comparison of the effects of losartan versus placebo on the plasma concentrations of the pneumoproteins, surfactant protein D (SPD) and club cell secretory protein (CCSP), in people living with HIV (PLWH). A total of 108 PLWH were included (52 assigned to losartan and 56 assigned to placebo). We found no difference in the change from baseline in log concentrations of CCSP or SPD over 1 year of follow-up. For SPD, we found a strong interaction by CD4+ counts, where those with CD4+ counts \u3e350 cells/mm treated with losartan had more reduction (improvement) in SPD concentration than those treated with placebo ( value for interaction \u3c.001). In conclusion, we did not find a beneficial effect of losartan on pneumoprotein concentrations in PLWH, but PLWH with higher CD4+ counts may have improvement in SPD when treated with losartan