Excessive collagen turnover products are released during colorectal cancer progression and elevated in serum from metastatic colorectal cancer patients

During cancer progression, the homeostasis of the extracellular matrix becomes imbalanced with an excessive collagen remodeling by matrix metalloproteinases. As a consequence, small protein fragments of degraded collagens are released into the circulation. We have investigated the potential of protein fragments of collagen type I, III and IV as novel biomarkers for colorectal cancer. Specific fragments of degraded type I, III and IV collagen (C1M, C3M, C4M) and type III collagen formation (Pro-C3) were assessed in serum from colorectal cancer patients, subjects with adenomas and matched healthy controls using well-characterized and validated ELISAs. Serum levels of the biomarkers were significantly elevated in colorectal cancer patients compared to subjects with adenomas (C1M, Pro-C3, C3M) and controls (C1M, Pro-C3). When patients were stratified according to their tumour stage, all four biomarkers were able to differentiate stage IV metastatic patients from all other stages. Combination of all markers with age and gender in a logistic regression model discriminated between metastatic and non-metastatic patients with an AUROC of 0.80. The data suggest that the levels of these collagen remodeling biomarkers may be a measure of tumour activity and invasiveness and may provide new clinical tools for monitoring of patients with advanced stage colorectal cancer

Intrinsic quadrupole moment of the nucleon

We address the question of the intrinsic quadrupole moment Q_0 of the nucleon in various models. All models give a positive intrinsic quadrupole moment for the proton. This corresponds to a prolate deformation. We also calculate the intrinsic quadrupole moment of the Delta(1232). All our models lead to a negative intrinsic quadrupole moment of the Delta corresponding to an oblate deformation.Comment: 17 pages, 5 figure

Neural network approximated Bayesian inference of edge electron density profiles at JET

A neural network (NN) has been trained on the inference of the edge electron density profiles from measurements of the JET lithium beam emission spectroscopy (Li-BES) diagnostic. The novelty of the approach resides in the fact that the network has been trained to be a fast surrogate model of an existing Bayesian model of the diagnostic implemented within the Minerva framework. Previous work showed the very first application of this method to an x-ray imaging diagnostic at the W7-X experiment, and it was argued that the method was general enough that it may be applied to different physics systems. Here, we try to show that the claim made there is valid. What makes the approach general and versatile is the common definition of different models within the same framework. The network is tested on data measured during several different pulses and the predictions compared to the results obtained with the full model Bayesian inference. The NN analysis only requires tens of microseconds on a GPU compared to the tens of minutes long full inference. Finally, in relation to what was presented in the previous work, we demonstrate an improvement in the method of calculation of the network uncertainties, achieved by using a state-of-the-art deep learning technique based on a variational inference interpretation of the network training. The advantage of this calculation resides in the fact that it relies on fewer assumptions, and no extra computation time is required besides the conventional network evaluation time. This allows estimating the uncertainties also in real time applications.Comunidad Europea de la Energía Atómica. EURATOM - 2014-2018 y 2019-2020 - 63305

Genetic and environmental influence on thyroid gland volume and thickness of thyroid isthmus: a twin study.

Objectives Decreased thyroid volume has been related to increased prevalence of thyroid cancer.Subjects and methods One hundred and fourteen Hungarian adult twin pairs (69 monozygotic, 45 dizygotic) with or without known thyroid disorders underwent thyroid ultrasound. Thickness of the thyroid isthmus was measured at the thickest portion of the gland in the midline using electronic calipers at the time of scanning. Volume of the thyroid lobe was computed according to the following formula: thyroid height*width*depth*correction factor (0.63).Results Age-, sex-, body mass index- and smoking-adjusted heritability of the thickness of thyroid isthmus was 50% (95% confidence interval [CI], 35 to 66%). Neither left nor right thyroid volume showed additive genetic effects, but shared environments were 68% (95% CI, 48 to 80%) and 79% (95% CI, 72 to 87%), respectively. Magnitudes of monozygotic and dizygotic co-twin correlations were not substantially impacted by the correction of covariates of body mass index and smoking. Unshared environmental effects showed a moderate influence on dependent parameters (24-50%).Conclusions Our analysis support that familial factors are important for thyroid measures in a general twin population. A larger sample size is needed to show whether this is because of common environmental (e.g. intrauterine effects, regional nutrition habits, iodine supply) or genetic effects