Preliminary Design and Numerical Analysis of a Scrap Tires Pyrolysis System

Abstract A plant prototype for whole scrap tires disposal and the consequent syngas production via pyrolysis has been developed. A numerical analysis on the innovative pyrolysis reactor, constituted by an autoclave closing device and an explosion-proof water system has been carried out. The aim of this analysis is to investigate the fluid-dynamics in the pyrolysis chamber and model the syngas production. The simulations, performed in the pre-realization system phase, have allowed to determine: i) the flow field of the fluid within the reactor, so as to optimize the geometry (e.g. size, vacuum system, water tank); ii) the temperature range, in order to determine the correct placement of thermocouples within reactor and prevent overheating that could compromise the safety of the system; iii) the pressure range, necessary to avoid the eventual flooding of the tires themselves. Thanks to these results, the test bench has been built at the CURTI S.p.A laboratory and experimental analysis has been performed. The experimental data are acquired and then elaborated, as shown in the paper

Comparison of Bone Segmentation Software over Different Anatomical Parts

Three-dimensional bone shape reconstruction is a fundamental step for any subject-specific musculo-skeletal model. Typically, medical images are processed to reconstruct bone surfaces via slice-by-slice contour identification. Freeware software packages are available, but commercial ones must be used for the necessary certification in clinics. The commercial software packages also imply expensive hardware and demanding training, but offer valuable tools. The aim of the present work is to report the performance of five commercial software packages (Mimics®, Amira™, D2P™, Simpleware™, and Segment 3D Print™), particularly the time to import and to create the model, the number of triangles of the mesh, and the STL file size. DICOM files of three different computed tomography scans from five different human anatomical areas were utilized for bone shape reconstruction by using each of these packages. The same operator and the same hosting hardware were used for these analyses. The computational time was found to be different between the packages analyzed, probably because of the pre-processing implied in this operation. The longer “time-to-import” observed in one software is likely due to the volume rendering during uploading. A similar number of triangles per megabyte (approximately 20 thousand) was observed for the five commercial packages. The present work showed the good performance of these software packages, with the main features being better than those analyzed previously in freeware packages

Basal cell carcinoma: A comprehensive review

Basal cell carcinoma (BCC) is the most common type of carcinoma worldwide. BCC development is the result of a complex interaction between environmental, phenotypic and genetic factors. However, despite the progress in the field, BCC biology and mechanisms of resistance against systemic treatments have been poorly investigated. The aim of the present review is to provide a revision of BCC histological and molecular features, including microRNA (miRNA) dysregulation, with a specific focus on the molecular basis of BCC systemic therapies. Papers from the last ten years regarding BCC genetic and phenotypic alterations, as well as the mechanism of resistance against hedgehog pathway inhibitors vismodegib and sonidegib were included. The involvement of miRNAs in BCC resistance to systemic therapies is emerging as a new field of knowledge

Classification performance for covid patient prognosis from automatic ai segmentation—a single-center study

Background: COVID assessment can be performed using the recently developed individual risk score (prediction of severe respiratory failure in hospitalized patients with SARS-COV2 infection, PREDI-CO score) based on High Resolution Computed Tomography. In this study, we evaluated the possibility of automatizing this estimation using semi-supervised AI-based Radiomics, leveraging the possibility of performing non-supervised segmentation of ground-glass areas. Methods: We collected 92 from patients treated in the IRCCS Sant’Orsola-Malpighi Policlinic and public databases; each lung was segmented using a pre-trained AI method; ground-glass opacity was identified using a novel, non-supervised approach; radiomic measurements were collected and used to predict clinically relevant scores, with particular focus on mortality and the PREDI-CO score. We compared the prediction obtained through different machine learning approaches. Results: All the methods obtained a well-balanced accuracy (70%) on the PREDI-CO score but did not obtain satisfying results on other clinical characteristics due to unbalance between the classes. Conclusions: Semi-supervised segmentation, implemented using a combination of non-supervised segmentation and feature extraction, seems to be a viable approach for patient stratification and could be leveraged to train more complex models. This would be useful in a high-demand situation similar to the current pandemic to support gold-standard segmentation for AI training

3D Patient-Specific Virtual Models for Presurgical Planning in Patients with Recto-Sigmoid Endometriosis Nodules: A Pilot Study

Background and Objective: In recent years, 3D printing has been used to support surgical planning or to guide intraoperative procedures in various surgical specialties. An improvement in surgical planning for recto-sigmoid endometriosis (RSE) excision might reduce the high complication rate related to this challenging surgery. The aim of this study was to build novel presurgical 3D models of RSE nodules from magnetic resonance imaging (MRI) and compare them with intraoperative findings. Materials and Methods: A single-center, observational, prospective, cohort, pilot study was performed by enrolling consecutive symptomatic women scheduled for minimally invasive surgery for RSE between November 2019 and June 2020 at our institution. Preoperative MRI were used for building 3D models of RSE nodules and surrounding pelvic organs. 3D models were examined during multi-disciplinary preoperative planning, focusing especially on three domains: degree of bowel stenosis, nodule's circumferential extension, and bowel angulation induced by the RSE nodule. After surgery, the surgeon was asked to subjectively evaluate the correlation of the 3D model with the intra-operative findings and to express his evaluation as "no correlation", "low correlation", or "high correlation" referring to the three described domains. Results: seven women were enrolled and 3D anatomical virtual models of RSE nodules and surrounding pelvic organs were generated. In all cases, surgeons reported a subjective "high correlation" with the surgical findings. Conclusion: Presurgical 3D models could be a feasible and useful tool to support surgical planning in women with recto-sigmoidal endometriotic involvement, appearing closely related to intraoperative findings

Non-myogenic mesenchymal cells contribute to muscle degeneration in facioscapulohumeral muscular dystrophy patients

Muscle-resident non-myogenic mesenchymal cells play key roles that drive successful tissue regeneration within the skeletal muscle stem cell niche. These cells have recently emerged as remarkable therapeutic targets for neuromuscular disorders, although to date they have been poorly investigated in facioscapulohumeral muscular dystrophy (FSHD). In this study, we characterised the non-myogenic mesenchymal stromal cell population in FSHD patients’ muscles with signs of disease activity, identified by muscle magnetic resonance imaging (MRI), and compared them with those obtained from apparently normal muscles of FSHD patients and from muscles of healthy, age-matched controls. Our results showed that patient-derived cells displayed a distinctive expression pattern of mesenchymal markers, along with an impaired capacity to differentiate towards mature adipocytes in vitro, compared with control cells. We also demonstrated a significant expansion of non-myogenic mesenchymal cells (identified as CD201- or PDGFRA-expressing cells) in FSHD muscles with signs of disease activity, which correlated with the extent of intramuscular fibrosis. In addition, the accumulation of non-myogenic mesenchymal cells was higher in FSHD muscles that deteriorate more rapidly. Our results prompt a direct association between an accumulation, as well as an altered differentiation, of non-myogenic mesenchymal cells with muscle degeneration in FSHD patients. Elucidating the mechanisms and cellular interactions that are altered in the affected muscles of FSHD patients could be instrumental to clarify disease pathogenesis and identifying reliable novel therapeutic targets