Conceptual study and manufacturing of a configurable and weld-free lattice base for automatic food machines

The study is aimed at developing a modular lattice base for automatic food machines, starting with a solution already patented by some of the authors. In this case, welded carpentry modules were interlocked with a system of profiles and metal inserts, also in welded carpentry, and the union was stabilized by structural adhesive bonding. Since welding involves long processing times and thermal distortions to be restored later, the driver of this study is to limit the use of welding as much as possible while increasing the modularity of the construction. For this purpose, various solution concepts have been generated where a common feature is the presence of rods of the same geometry and section to be joined together in configurable structural nodes. The concepts are qualitatively evaluated in light of the requirements, and the selected concept is digitally and physically prototyped. The prototype has been in service from over 5 years without showing any problems whatsoever

Designing a Cockpit for Image Quality Evaluation

Image Quality (IQ) as assessed by humans is a concept hard to be defined, since it relies on many different features, including both low level and high level visual characteristics. Image luminance, contrast, color distribution, smoothness, presence of noise or of geometric distortions are some examples of low level cues usually contributing to image quality. Aesthetic canons and trends, displacement of the objects in the scene, significance and message of the imaged visual content are instances of the high level (i.e. semantic) concepts that may be involved in image quality assessment. Despite subjective evaluation of IQ being very popular in many applications (e.g. image restoration, colorization and noise removal), it may be scarcely reliable due to subjectivity issues and biases. Therefore, an objective evaluation, i.e. an image quality assessment based on visual features extracted from the image and mathematically modelled, is highly desirable, since it guarantees the repeatability of the results and it enables the automation of image quality measurements. Here the crucial point lies in the detection of visual elements salient for IQ. Many objective, numerical measures have been proposed in the literature. They differ from one another in the features considered to be relevant to IQ, and in the presence of a reference image, an image of \u201cperfect\u201d quality with which to compare the image to be evaluated. Objective measures are thus broadly classified as full-reference, reduced-reference or no-reference, according to the availability of reference information. Due to the complexity of the IQ assessment process, a single measure may be not robust and accurate enough to capture and numerically summarize all the aspects concurring to IQ. Therefore, we propose to employ multiple objective IQ measures assembled in a cockpit of objective IQ measures. This cockpit should be designed to offer not only an extensive analysis and overview of features relevant to IQ, but also as a tool to automate the selection of machine vision algorithms devoted to image enhancement. In this work we describe a preliminary version of a cockpit, and we employ it to assess a set of images of the same scene acquired under different conditions, with different devices or even processed by computer algorithms

Automatic quantification of histochemical images of cancerous tissue samples: a method based on a computational model of human color vision

Protein Ki 67 is present in replicating nuclei It is therefore used as a marker of tumor aggressiveness Its quantification is important for diagnostic and prognostic evaluations For pKi 67 quantification, the Ki 67 index is estimated by clinicians Ki 67 index the percentage of marked tumor nuclei with respect to all tumour nuclei BUT histochemical images have high dimension and high resolution Human counting procedures are labourious, time consuming, error prone, affected by high inter and intra variability. Clinicians need automatic counting procedures to aid their work. sections (marked for pKi 67 of cancerous tissue They show high color/luminance variability, problems due to the biological procedures applied for tissue staining (tissue cuts, tissue folds, unwanted and unspecific colorations) and image acquisition acquisition ( noise). The aim: develop an automatic system estimating the Ki67 index: the percentage of replicating cells (brownish) with respect to all cells (brownish+bluish). Problem solved with stress + simple thresholding+ supervised learner. Expert users manually select three training sample sets: 1) marked nuclei; 2) not marked nuclei; 3) background tissue. The color of each training pixel p is coded as Color(p)=[R(p),B(p),H(p)] and a bayesian tree is trained (R,B from RGB color space, H from HSV c olo r space). Training sets allow computing the median area of marked nuclei (medAOn), and the median area of not marked nuclei (medAOff). Two index estimations (IE1 and IE2) Correlation(IE1,E30) > Correlation(IE1,E15) Correlation(IE2,E30) > Correlation(IE2,E15) E15 = estimates of expert with 15 years of experience E30 = estimates of expert with 15 years of experience (bayesian)

68Ga-DOTATOC PET/CT-Based Radiomic Analysis and PRRT Outcome: A Preliminary Evaluation Based on an Exploratory Radiomic Analysis on Two Patients

Aim: This work aims to evaluate whether the radiomic features extracted by 68Ga-DOTATOC-PET/CT of two patients are associated with the response to peptide receptor radionuclide therapy (PRRT) in patients affected by neuroendocrine tumor (NET). Methods: This is a pilot report in two NET patients who experienced a discordant response to PRRT (responder vs. non-responder) according to RECIST1.1. The patients presented with liver metastasis from the rectum and pancreas G3-NET, respectively. Whole-body total-lesion somatostatin receptor-expression (TLSREwb-50) and somatostatin receptor-expressing tumor volume (SRETV wb-50) were obtained in pre- and post-PRRT PET/CT. Radiomic analysis was performed, extracting 38 radiomic features (RFs) from the patients' lesions. The Mann–Whitney test was used to compare RFs in the responder patient vs. the non-responder patient. Pearson correlation and principal component analysis (PCA) were used to evaluate the correlation and independence of the different RFs. Results: TLSREwb-50 and SRETVwb-50 modifications correlate with RECIST1.1 response. A total of 28 RFs extracted on pre-therapy PET/CT showed significant differences between the two patients in the Mann–Whitney test (p < 0.05). A total of seven second-order features, with poor correlation with SUVmax and PET volume, were identified by the Pearson correlation matrix. Finally, the first two PCA principal components explain 83.8% of total variance. Conclusion: TLSREwb-50 and SRETVwb-50 are parameters that might be used to predict and to assess the PET response to PRRT. RFs might have a role in defining inter-patient heterogeneity and in the prediction of therapy response. It is important to implement future studies with larger and more homogeneous patient populations to confirm the efficacy of these biomarkers

Predictive value of baseline [18f]fdg pet/ct for response to systemic therapy in patients with advanced melanoma

Background/Aim: To evaluate the association between baseline [18F]FDG-PET/CT tumor burden parameters and disease progression rate after first-line target therapy or immunotherapy in advanced melanoma patients. Materials and Methods: Forty four melanoma patients, who underwent [18F]FDG-PET/CT before first-line target therapy (28/44) or immunotherapy (16/44), were retrospectively analyzed. Whole-body and per-district metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were calculated. Therapy response was assessed according to RECIST 1.1 on CT scan at 3 (early) and 12 (late) months. PET parameters were compared using the Mann–Whitney test. Optimal cut-offs for predicting progression were defined using the ROC curve. PFS and OS were studied using Kaplan–Meier analysis. Results: Median (IQR) MTVwb and TLGwb were 13.1 mL and 72.4, respectively. Non-responder patients were 38/44, 26/28 and 12/16 at early evaluation, and 33/44, 21/28 and 12/16 at late evaluation in the whole-cohort, target, and immunotherapy subgroup, respectively. At late evaluation, MTVbone and TLGbone were higher in non-responders compared to responder patients (all p < 0.037) in the whole-cohort and target subgroup and MTVwb and TLGwb (all p < 0.022) in target subgroup. No significant differences were found for the immunotherapy subgroup. No metabolic parameters were able to predict PFS. Controversially, MTVlfn, TLGlfn, MTVsoft + lfn, TLGsoft + lfn, MTVwb and TLGwb were significantly associated (all p < 0.05) with OS in both the whole-cohort and target therapy subgroup. Conclusions: Higher values of whole-body and bone metabolic parameters were correlated with poorer outcome, while higher values of whole-body, lymph node and soft tissue metabolic parameters were correlated with OS

Explaining the Brexit Vote: A Socioeconomic and Psychological Exploration of the Referendum Vote

The proposed book chapter will bring together regional economics and psychological perspectives in relation to Brexit, one year on from Article 50. Extending previous work (Becker, Fetzer, & Novy, 2017; Goodwin and Heath, 2016, Semmens-Wheeler & Hill, 2018) the chapter will exploit regional variations in the Brexit vote to model how well different demographic, socio-economic and other decision-making indicators predict the vote’s outcome by area. Using statistical techniques commonly employed in the literature in both economics and psychology, a focus will be on regional economics, including the role of income/economy vs demography in the vote and psychological perspectives, including the role of empathy and interpersonal reactivity, social dominance orientation, collective self-esteem and modern racial prejudice, among other factors. Drawing on the broader literature, the chapter will consider the potential economic and psychological factors lying behind the results, suggesting possible reasons for regional/demographic variations and areas where further research might be required. An investigation of the literature will discuss developments in these areas to date, as well as provide an overview of research focusing on public perceptions and prospects going forward. This cross-disciplinary chapter will continue to contribute to the growing picture forming around UK’s decision to leave the EU, one year on from Article 50, while providing an insight into the important economic and psychological processes behind Brexit

Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics

In prostate cancer (PCa), the use of new radiopharmaceuticals has improved the accuracy of diagnosis and staging, refined surveillance strategies, and introduced specific and personalized radioreceptor therapies. Nuclear medicine, therefore, holds great promise for improving the quality of life of PCa patients, through managing and processing a vast amount of molecular imaging data and beyond, using a multi-omics approach and improving patients' risk-stratification for tailored medicine. Artificial intelligence (AI) and radiomics may allow clinicians to improve the overall efficiency and accuracy of using these "big data" in both the diagnostic and theragnostic field: from technical aspects (such as semi-automatization of tumor segmentation, image reconstruction, and interpretation) to clinical outcomes, improving a deeper understanding of the molecular environment of PCa, refining personalized treatment strategies, and increasing the ability to predict the outcome. This systematic review aims to describe the current literature on AI and radiomics applied to molecular imaging of prostate cancer

Calcitonin receptor N-glycosylation enhances peptide hormone affinity by controlling receptor dynamics

The class B G protein-coupled receptor (GPCR) calcitonin receptor (CTR) is a drug target for osteoporosis and diabetes. N-glycosylation of asparagine 130 in its extracellular domain (ECD) enhances calcitonin hormone affinity with the proximal GlcNAc residue mediating this effect through an unknown mechanism. Here, we present two crystal structures of salmon calcitonin-bound, GlcNAc-bearing CTR ECD at 1.78 and 2.85 Å resolutions and analyze the mechanism of the glycan effect. The N130 GlcNAc does not contact the hormone. Surprisingly, the structures are nearly identical to a structure of hormone-bound, N-glycan-free ECD, which suggested that the GlcNAc might affect CTR dynamics not observed in the static crystallographic snapshots. Hydrogen-deuterium exchange mass spectrometry and molecular dynamics simulations revealed that glycosylation stabilized a β-sheet adjacent to the N130 GlcNAc and the N-terminal α-helix near the peptide-binding site, while increasing flexibility of the peptide-binding site turret loop. These changes due to N-glycosylation increased the ligand on-rate and decreased its off rate. The glycan effect extended to RAMP-CTR amylin receptor complexes and was also conserved in the related CGRP receptor. These results reveal that N-glycosylation can modulate GPCR function by altering receptor dynamics