Probing neutron-hidden neutron transitions with the MURMUR experiment

MURMUR is a new passing-through-walls neutron experiment designed to constrain neutron/hidden neutron transitions allowed in the context of braneworld scenarios or mirror matter models. A nuclear reactor can act as a hidden neutron source, such that neutrons travel through a hidden world or sector. Hidden neutrons can propagate out of the nuclear core and far beyond the biological shielding. However, hidden neutrons can weakly interact with usual matter, making possible for their detection in the context of low-noise measurements. In the present work, the novelty rests on a better background discrimination and the use of a mass of a material - here lead - able to enhance regeneration of hidden neutrons into visible ones to improve detection. The input of this new setup is studied using both modelizations and experiments, thanks to tests currently performed with the experiment at the BR2 research nuclear reactor (SCK$\cdot$CEN, Mol, Belgium). A new limit on the neutron swapping probability p has been derived thanks to the measurements taken during the BR2 Cycle 02/2019A: $p < 4.0 \ \times 10^{-10}$ at 95% CL. This constraint is better than the bound from the previous passing-through-wall neutron experiment made at ILL in 2015, despite BR2 is less efficient to generate hidden neutrons by a factor 7.4, thus raising the interest of such experiment using regenerating materials.Comment: 15 pages, 8 figures, final version, accepted for publication in European Physical Journal

Benefit-Harm Analysis for Informed Decision Making on Participating in Colorectal Cancer Screening: A Modeling Study

OBJECTIVES To facilitate informed decision making on participating in colorectal cancer (CRC) screening, we assessed the benefit-harm balance of CRC screening for a wide range of subgroups over different time horizons. METHODS The study combined incidence proportions of benefits and harms of (not) participating in CRC screening estimated by the Adenoma and Serrated pathway to CAncer microsimulation model, a preference eliciting survey, and benefit-harm balance modeling combining all outcomes to determine the net health benefit of CRC screening over 10, 20, and 30 years. Probability of net health benefit was estimated for 210 different subgroups based on age, sex, previous participation in CRC screening, and lifestyle. RESULTS CRC screening was net beneficial in 183 of 210 subgroups over 30 years (median probability [MP] of 0.79, interquartile range [IQR] of 0.69-0.85) across subgroups. Net health benefit was greater for men (MP 0.82; IQR 0.69-0.89) than women (MP 0.76; IQR 0.67-0.83) and for those without history of participation in previous screenings (MP 0.84; IQR 0.80-0.89) compared with those with (MP 0.69; IQR 0.59-0.75). Net health benefit decreased with increasing age, from MP of 0.84 (IQR 0.80-0.86) at age 55 to 0.61 (IQR 0.56-0.71) at age 75. Shorter time horizons led to lower benefit, with MP of 0.70 (IQR 0.62-0.80) over 20 years and 0.54 (IQR 0.48-0.67) over 10 years. CONCLUSIONS Our benefit-harm analysis provides information about net health benefit of screening participation, based on important characteristics and preferences of individuals, which could assist screening invitees in making informed decisions on screening participation

SoLid : Search for Oscillations with Lithium-6 Detector at the SCK-CEN BR2 reactor

Sterile neutrinos have been considered as a possible explanation for the recent reactor and Gallium anomalies arising from reanalysis of reactor flux and calibration data of previous neutrino experiments. A way to test this hypothesis is to look for distortions of the anti-neutrino energy caused by oscillation from active to sterile neutrino at close stand-off (similar to 6-8m) of a compact reactor core. Due to the low rate of anti-neutrino interactions the main challenge in such measurement is to control the high level of gamma rays and neutron background. The SoLid experiment is a proposal to search for active-to-sterile anti-neutrino oscillation at very short baseline of the SCK center dot CEN BR2 research reactor. This experiment uses a novel approach to detect anti-neutrino with a highly segmented detector based on Lithium-6. With the combination of high granularity, high neutron-gamma discrimination using 6LiF:ZnS(Ag) and precise localization of the Inverse Beta Decay products, a better experimental sensitivity can be achieved compared to other state-of-the-art technology. This compact system requires minimum passive shielding allowing for very close stand off to the reactor. The experimental set up of the SoLid experiment and the BR2 reactor will be presented. The new principle of neutrino detection and the detector design with expected performance will be described. The expected sensitivity to new oscillations of the SoLid detector as well as the first measurements made with the 8 kg prototype detector deployed at the BR2 reactor in 2013-2014 will be reported

Mixed-Model Noise Removal in 3D MRI via Rotation-and-Scale Invariant Non-Local Means

Mixed noise is a major issue influencing quantitative analysis in different forms of magnetic resonance image (MRI), such as T1 and diffusion image like DWI and DTI. Using different filters sequentially to remove mixed noise will severely deteriorate such medical images. We present a novel algorithm called rotation-and-scale invariant nonlocal means filter (RSNLM) to simultaneously remove mixed noise from different kinds of three-dimensional (3D) MRI images. First, we design a new similarity weights, including rank-ordered absolute difference (ROAD), coming from a trilateral filter (TriF) that is obtained to detect the mixed and high-level noise. Then, we present a shape view to consider the MRI data as a 3D operator, with which the similarity between the patches is calculated with the rigid transformation. The translation, rotation and scale have no influence on the similarity. Finally, the adaptive parameter estimation method of ROAD is illustrated, and the effective proof that validates the proposed algorithm is presented. Experiments using synthetic data with impulse noise, Rician noise, and the real MRI data confirm that the proposed method yields superior performance compared with current state-of-the-art methods

Postnatal Growth after Intrauterine Growth Restriction Alters Central Leptin Signal and Energy Homeostasis

Intrauterine growth restriction (IUGR) is closely linked with metabolic diseases, appetite disorders and obesity at adulthood. Leptin, a major adipokine secreted by adipose tissue, circulates in direct proportion to body fat stores, enters the brain and regulates food intake and energy expenditure. Deficient leptin neuronal signalling favours weight gain by affecting central homeostatic circuitry. The aim of this study was to determine if leptin resistance was programmed by perinatal nutritional environment and to decipher potential cellular mechanisms underneath

The X-ray spectrum of NGC 7213 and the Seyfert--LINER connection

We present an XMM-Newton observation of the Seyfert-LINER galaxy NGC 7213. The RGS soft X-ray spectrum is well fitted with a power law plus soft X-ray collisionally ionised thermal plasma (kT = 0.18 +0.03/-0.01 keV). We confirm the presence of Fe I, XXV and XXVI K-alpha emission in the EPIC spectrum and set tighter constraints on their equivalent widths of 82 +10/-13, 24 +9/-11 and 24 +10/-13 eV respectively. We compare the observed properties together with the inferred mass accretion rate of NGC 7213, to those of other Seyfert and LINER galaxies. We find that NGC 7213 has intermediate X-ray spectral properties lying between those of the weak AGN found in the LINER M81 and higher luminosity Seyfert galaxies. There appears to be a continuous sequence of X-ray properties from the Galactic Centre through LINER galaxies to Seyferts, likely determined by the amount of material available for accretion in the central regions.Comment: 8 pages, 3 figures. Accepted for MNRA

Circulating tumor DNA guided adjuvant chemotherapy in stage II colon cancer (MEDOCC-CrEATE):study protocol for a trial within a cohort study

BACKGROUND: Accurate detection of patients with minimal residual disease (MRD) after surgery for stage II colon cancer (CC) remains an urgent unmet clinical need to improve selection of patients who might benefit form adjuvant chemotherapy (ACT). Presence of circulating tumor DNA (ctDNA) is indicative for MRD and has high predictive value for recurrent disease. The MEDOCC-CrEATE trial investigates how many stage II CC patients with detectable ctDNA after surgery will accept ACT and whether ACT reduces the risk of recurrence in these patients. METHODS/DESIGN: MEDOCC-CrEATE follows the 'trial within cohorts' (TwiCs) design. Patients with colorectal cancer (CRC) are included in the Prospective Dutch ColoRectal Cancer cohort (PLCRC) and give informed consent for collection of clinical data, tissue and blood samples, and consent for future randomization. MEDOCC-CrEATE is a subcohort within PLCRC consisting of 1320 stage II CC patients without indication for ACT according to current guidelines, who are randomized 1:1 into an experimental and a control arm. In the experimental arm, post-surgery blood samples and tissue are analyzed for tissue-informed detection of plasma ctDNA, using the PGDx elio™ platform. Patients with detectable ctDNA will be offered ACT consisting of 8 cycles of capecitabine plus oxaliplatin while patients without detectable ctDNA and patients in the control group will standard follow-up according to guideline. The primary endpoint is the proportion of patients receiving ACT when ctDNA is detectable after resection. The main secondary outcome is 2-year recurrence rate (RR), but also includes 5-year RR, disease free survival, overall survival, time to recurrence, quality of life and cost-effectiveness. Data will be analyzed by intention to treat. DISCUSSION: The MEDOCC-CrEATE trial will provide insight into the willingness of stage II CC patients to be treated with ACT guided by ctDNA biomarker testing and whether ACT will prevent recurrences in a high-risk population. Use of the TwiCs design provides the opportunity to randomize patients before ctDNA measurement, avoiding ethical dilemmas of ctDNA status disclosure in the control group. TRIAL REGISTRATION: Netherlands Trial Register: NL6281/NTR6455 . Registered 18 May 2017, https://www.trialregister.nl/trial/6281

Multitarget Stool DNA Test Performance in an Average-Risk Colorectal Cancer Screening Population

INTRODUCTION: We set out to evaluate the performance of a multitarget stool DNA (MT-sDNA) in an average-risk colonoscopy-controlled colorectal cancer (CRC) screening population. MT-sDNA stool test results were evaluated against fecal immunochemical test (FIT) results for the detection of different lesions, including molecularly defined high-risk adenomas and several other tumor characteristics. METHODS: Whole stool samples (n = 1,047) were prospectively collected and subjected to an MT-sDNA test, which tests for KRAS mutations, NDRG4 and BMP3 promoter methylation, and hemoglobin. Results for detecting CRC (n = 7), advanced precancerous lesions (advanced adenoma [AA] and advanced serrated polyps; n = 119), and non-AAs (n = 191) were compared with those of FIT alone (thresholds of 50, 75, and 100 hemoglobin/mL). AAs with high risk of progression were defined by the presence of specific DNA copy number events as measured by low-pass whole genome sequencing. RESULTS: The MT-sDNA test was more sensitive than FIT alone in detecting advanced precancerous lesions (46% (55/119) vs 27% (32/119), respectively, P < 0.001). Specificities among individuals with nonadvanced or negative findings (controls) were 89% (791/888) and 93% (828/888) for MT-sDNA and FIT testing, respectively. A positive MT-sDNA test was associated with multiple lesions (P = 0.005), larger lesions (P = 0.03), and lesions with tubulovillous architecture (P = 0.04). The sensitivity of the MT-sDNA test or FIT in detecting individuals with high-risk AAs (n = 19) from individuals with low-risk AAs (n = 52) was not significantly different. DISCUSSION: In an average-risk screening population, the MT-sDNA test has an increased sensitivity for detecting advanced precancerous lesions compared with FIT alone. AAs with a high risk of progression were not detected with significantly higher sensitivity by MT-sDNA or FIT

Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN)

Aim To develop a decision model for the population-level evaluation of strategies to improve the selection of stage II colon cancer (CC) patients who benefit from adjuvant chemotherapy. Methods A Markov cohort model with a one-month cycle length and a lifelong time horizon was developed. Five health states were included; diagnosis, 90-day mortality, death other causes, recurrence and CC death. Data from the Netherlands Cancer Registry were used to parameterize the model. Transition probabilities were estimated using parametric survival models including relevant clinical and pathological covariates. Subsequently, biomarker status was implemented using external data. Treatment effect was incorporated using pooled trial data. Model development, data sources used, parameter estimation, and internal and external validation are described in detail. To illustrate the use of the model, three example strategies were evaluated in which allocation of treatment was based on (A) 100% adherence to the Dutch guidelines, (B) observed adherence to guideline recommendations and (C) a biomarker-driven strategy. Results Overall, the model showed good internal and external validity. Age, tumor growth, tumor sidedness, evaluated lymph nodes, and biomarker status were included as covariates. For the example strategies, the model predicted 83, 87 and 77 CC deaths after 5 years in a cohort of 1000 patients for strategies A, B and C, respectively. Conclusion This model can be used to evaluate strategies for the allocation of adjuvant chemotherapy in stage II CC patients. In future studies, the model will be used to estimate population-level long-term health gain and cost-effectiveness of biomarker-based selection strategies.Financial support for this study was provided by a grant from ZonMw (Grant number: 848015007). ZonMw had no role in designing the study, interpreting the data, writing the manuscript, and publishing the report

Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN)

Aim: To develop a decision model for the population-level evaluation of strategies to improve the selection of stage II colon cancer (CC) patients who benefit from adjuvant chemotherapy. Methods: A Markov cohort model with a one-month cycle length and a lifelong time horizon was developed. Five health states were included; diagnosis, 90-day mortality, death other causes, recurrence and CC death. Data from the Netherlands Cancer Registry were used to parameterize the model. Transition probabilities were estimated using parametric survival models including relevant clinical and pathological covariates. Subsequently, biomarker status was implemented using external data. Treatment effect was incorporated using pooled trial data. Model development, data sources used, parameter estimation, and internal and external validation are described in detail. To illustrate the use of the model, three example strategies were evaluated in which allocation of treatment was based on (A) 100% adherence to the Dutch guidelines, (B) observed adherence to guideline recommendations and (C) a biomarker-driven strategy. Results: Overall, the model showed good internal and external validity. Age, tumor growth, tumor sidedness, evaluated lymph nodes, and biomarker status were included as covariates. For the example strategies, the model predicted 83, 87 and 77 CC deaths after 5 years in a cohort of 1000 patients for strategies A, B and C, respectively. Conclusion: This model can be used to evaluate strategies for the allocation of adjuvant chemotherapy in stage II CC patients. In future studies, the model will be used to estimate population-level long-term health gain and cost-effectiveness of biomarker-based selection strategies