Harnessing radiotherapy-induced NK-cell activity by combining DNA damage-response inhibition and immune checkpoint blockade.

BackgroundDespite therapeutic gains from immune checkpoint inhibitors (ICI) in many tumor types, new strategies are needed to extend treatment benefits, especially in patients failing to mount effective antitumor T-cell responses. Radiation and drug therapies can profoundly affect the tumor immune microenvironment. Here, we aimed to identify immunotherapies to increase the antitumor response conferred by combined ataxia telangiectasia and Rad3-related kinase inhibition and radiotherapy.MethodsUsing the human papillomavirus (HPV)-negative murine oral squamous cell carcinoma model, MOC2, we assessed the nature of the antitumor response following ataxia telangiectasia and Rad3-related inhibitor (ATRi)/radiotherapy (RT) by performing RNA sequencing and detailed flow cytometry analyses in tumors. The benefit of immunotherapies based on T cell immunoreceptor with Ig and ITIM domains (TIGIT) and Programmed cell death protein 1 (PD-1) immune checkpoint blockade following ATRi/RT treatment was assessed in the MOC2 model and confirmed in another HPV-negative murine oral squamous cell carcinoma model called SCC7. Finally, immune profiling was performed by flow cytometry on blood samples in patients with head and neck squamous cell carcinoma enrolled in the PATRIOT clinical trial of combined ATRi/RT.ResultsATRi enhances radiotherapy-induced inflammation in the tumor microenvironment, with natural killer (NK) cells playing a central role in maximizing treatment efficacy. We demonstrated that antitumor activity of NK cells can be further boosted with ICI targeting TIGIT and PD-1. Analyses of clinical samples from patients receiving ATRi (ceralasertib) confirm the translational potential of our preclinical studies.ConclusionThis work delineates a previously unrecognized role for NK cells in the antitumor immune response to radiotherapy that can be augmented by small-molecule DNA damage-response inhibitors and immune checkpoint blockade

Multi-center MRI prediction models: Predicting sex and illness course in first episode psychosis patients.

Structural Magnetic Resonance Imaging (MRI) studies have attempted to use brain measures obtained at the first-episode of psychosis to predict subsequent outcome, with inconsistent results. Thus, there is a real need to validate the utility of brain measures in the prediction of outcome using large datasets, from independent samples, obtained with different protocols and from different MRI scanners. This study had three main aims: 1) to investigate whether structural MRI data from multiple centers can be combined to create a machine-learning model able to predict a strong biological variable like sex; 2) to replicate our previous finding that an MRI scan obtained at first episode significantly predicts subsequent illness course in other independent datasets; and finally, 3) to test whether these datasets can be combined to generate multicenter models with better accuracy in the prediction of illness course. The multi-center sample included brain structural MRI scans from 256 males and 133 females patients with first episode psychosis, acquired in five centers: University Medical Center Utrecht (The Netherlands) (n=67); Institute of Psychiatry, Psychology and Neuroscience, London (United Kingdom) (n=97); University of São Paulo (Brazil) (n=64); University of Cantabria, Santander (Spain) (n=107); and University of Melbourne (Australia) (n=54). All images were acquired on 1.5-Tesla scanners and all centers provided information on illness course during a follow-up period ranging 3 to 7years. We only included in the analyses of outcome prediction patients for whom illness course was categorized as either "continuous" (n=94) or "remitting" (n=118). Using structural brain scans from all centers, sex was predicted with significant accuracy (89%; p<0.001). In the single- or multi-center models, illness course could not be predicted with significant accuracy. However, when reducing heterogeneity by restricting the analyses to male patients only, classification accuracy improved in some samples. This study provides proof of concept that combining multi-center MRI data to create a well performing classification model is possible. However, to create complex multi-center models that perform accurately, each center should contribute a sample either large or homogeneous enough to first allow accurate classification within the single-center

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector.

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies

A systematic review of correlates of sedentary behaviour in adults aged 18–65 years: a socio-ecological approach

Background: Recent research shows that sedentary behaviour is associated with adverse cardio-metabolic consequences even among those considered sufficiently physically active. In order to successfully develop interventions to address this unhealthy behaviour, factors that influence sedentariness need to be identified and fully understood. The aim of this review is to identify individual, social, environmental, and policy-related determinants or correlates of sedentary behaviours among adults aged 18-65 years. Methods: PubMed, Embase, CINAHL, PsycINFO and Web of Science were searched for articles published between January 2000 and September 2015. The search strategy was based on four key elements and their synonyms: (a) sedentary behaviour (b) correlates (c) types of sedentary behaviours (d) types of correlates. Articles were included if information relating to sedentary behaviour in adults (18-65 years) was reported. Studies on samples selected by disease were excluded. The full protocol is available from PROSPERO (PROSPERO 2014:CRD42014009823). Results: 74 original studies were identified out of 4041: 71 observational, two qualitative and one experimental study. Sedentary behaviour was primarily measured as self-reported screen leisure time and total sitting time. In 15 studies, objectively measured total sedentary time was reported: accelerometry (n = 14) and heart rate (n = 1). Individual level factors such as age, physical activity levels, body mass index, socio-economic status and mood were all significantly correlated with sedentariness. A trend towards increased amounts of leisure screen time was identified in those married or cohabiting while having children resulted in less total sitting time. Several environmental correlates were identified including proximity of green space, neighbourhood walkability and safety and weather. Conclusions: Results provide further evidence relating to several already recognised individual level factors and preliminary evidence relating to social and environmental factors that should be further investigated. Most studies relied upon cross-sectional design limiting causal inference and the heterogeneity of the sedentary measures prevented direct comparison of findings. Future research necessitates longitudinal study designs, exploration of policy-related factors, further exploration of environmental factors, analysis of inter-relationships between identified factors and better classification of sedentary behaviour domains

Observation of a J^PC = 1-+ exotic resonance in diffractive dissociation of 190 GeV/c pi- into pi- pi- pi+

The COMPASS experiment at the CERN SPS has studied the diffractive dissociation of negative pions into the pi- pi- pi+ final state using a 190 GeV/c pion beam hitting a lead target. A partial wave analysis has been performed on a sample of 420000 events taken at values of the squared 4-momentum transfer t' between 0.1 and 1 GeV^2/c^2. The well-known resonances a1(1260), a2(1320), and pi2(1670) are clearly observed. In addition, the data show a significant natural parity exchange production of a resonance with spin-exotic quantum numbers J^PC = 1-+ at 1.66 GeV/c^2 decaying to rho pi. The resonant nature of this wave is evident from the mass-dependent phase differences to the J^PC = 2-+ and 1++ waves. From a mass-dependent fit a resonance mass of 1660 +- 10+0-64 MeV/c^2 and a width of 269+-21+42-64 MeV/c^2 is deduced.Comment: 7 page, 3 figures; version 2 gives some more details, data unchanged; version 3 updated authors, text shortened, data unchange

The Polarised Valence Quark Distribution from semi-inclusive DIS

The semi-inclusive difference asymmetry A^{h^{+}-h^{-}} for hadrons of opposite charge has been measured by the COMPASS experiment at CERN. The data were collected in the years 2002-2004 using a 160 GeV polarised muon beam scattered off a large polarised ^6LiD target and cover the range 0.006 < x < 0.7 and 1 < Q^2 < 100 (GeV/c)^2. In leading order QCD (LO) the asymmetry A_d^{h^{+}-h^{-}} measures the valence quark polarisation and provides an evaluation of the first moment of Delta u_v + Delta d_v which is found to be equal to 0.40 +- 0.07 (stat.) +- 0.05 (syst.) over the measured range of x at Q^2 = 10 (GeV/c)^2. When combined with the first moment of g_1^d previously measured on the same data, this result favours a non-symmetric polarisation of light quarks Delta u-bar = - Delta d-bar at a confidence level of two standard deviations, in contrast to the often assumed symmetric scenario Delta u-bar = Delta d-bar = Delta s-bar = Delta s.Comment: 7 pages, 3 figures, COMPASS, revised: details added, author list update

Racial/Ethnic Differences in Multiple Self-Care Behaviors in Adults with Diabetes

OBJECTIVE: To assess racial/ethnic differences in multiple diabetes self-care behaviors. DESIGN: Cross-sectional study. PARTICIPANTS: 21,459 participants with diabetes in the 2003 Behavioral Risk Factor Surveillance survey. MEASUREMENTS: The study assessed self-care behaviors including physical activity, fruits/vegetables consumption, glucose testing, and foot examination, as well as a composite of the 4 self-care behaviors across racial/ethnic groups. Multiple logistic regression was used to assess the independent association between race/ethnicity, the composite variable, and each self-care behavior controlling for covariates. STATA was used for statistical analysis. RESULTS: Overall, 6% engaged in all 4 self-care behaviors, with a range of 5% in non-insulin users to 8% in insulin users. Blacks were less likely to exercise (OR 0.63, 95% CI 0.51, 0.79), while Hispanics and “others” were not significantly different from whites. Hispanics (OR 0.64, 95% CI 0.49, 0.82) and others (OR 0.69, 95% CI 0.49, 0.96) were less likely to do home glucose testing, while blacks were not significantly different from whites. Blacks (OR 1.42, 95% CI 1.12, 1.80) were more likely to do home foot examinations, while Hispanics and others were not significantly different from whites. Blacks (OR 0.56, 95% CI 0.36, 0.87) were less likely to engage in all 4 behaviors, while Hispanics and others were not significantly different from whites. There were no significant racial/ethnic differences in fruit and vegetable consumption. CONCLUSIONS: Few patients engage in multiple self-care behaviors at recommended levels, and there are significant racial/ethnic differences in physical activity, dietary, and foot care behaviors among adults with diabetes

Role of Sleep Disturbance in Chronic Hepatitis C Infection

Chronic infection with the hepatitis C virus (CHC) is associated with physical and mental symptoms including fatigue and depression that adversely affect quality of life. A related complaint, sleep disturbance, has received little attention in the literature, with the exception of sleep changes noted in cirrhosis and end-stage liver disease. We present an overview of studies indicating sleep problems in patients with CHC, with about 60% to 65% of individuals reporting such complaints. Evidence suggests that impairments in sleep quality exist independent of antiviral therapy with interferon-α and prior to advanced stages of liver disease. Further investigation of sleep disturbance in CHC patients with a mild stage of liver disease may provide important information on disease course as well as allow additional opportunities for patient support