Endoscopic resection of a large colonic leiomyosarcoma

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Rapid malignant progression of an intraparenchymal choroid plexus papillomas

Background: Choroid plexus tumors (CPTs) are rare neoplasms accounting for only 0.3-0.6% of all brain tumors in adults and 2-5% in children. The World Health Organization (WHO) classification describes three histological grades: grade I is choroid plexus papilloma (CPP), grade II is atypical papilloma, and grade III is the malignant form of carcinoma. In adults, CPTs rarely have a supratentorial localization. Case Description: Here we report a very rare case of an intraparenchymal parietal CPP with a rapid histological transition from grade I to grade III WHO in a 67-year-old man, in <7 months. Conclusion: Because of the rarity of these oncotypes, descriptions of each new case are useful, mostly to consider this diagnostic entity in extraventricular brain tumors of adults, despite an unusual location

Peripheral facial palsy following ventriculoperitoneal shunt. The lesson we have learned

The most frequent complications after shunt surgery are infective and obstructive. Other types are less common, and eventually occur due to technical errors during brain ventricular puncture, opening the intraperitoneal cavity or the tunnelling of the catheter between the two points. Although rare, there are well-reported complications related to the poor positioning of the distal catheter, with perforation of organs and tissues. We report a very rare case of a male patient with normal pressure hydrocephalus submitted to ventriculoperitoneal shunt. During tunnelling of the shunt stylet, a peripheral facial palsy due to injury to the extra cranial segment of the facial nerve occurred. To the best of our knowledge this is the second case described in Literature. The patient and the surgeon should be aware of this very rare but possible complication in shunt surgery being careful to the course of the facial nerve in the mastoid region

The effect of maxillary protraction, with or without rapid palatal expansion, on airway dimensions: A systematic review and meta-analysis

Aim The use of maxillary protraction appliances (MPAs) and Facemask (FM), with or without a rapid maxillary expansion (RME), have become a routine orthopaedic treatment procedure for the treatment of Class III in growing individuals; several authors have suggested that maxillary protraction could have a positive impact on airway dimensions. The purpose of this systematic review and meta- analysis was to assess the efficacy of maxillary protraction appliances (MPAs), with or without a rapid maxillary expansion (RME), on airway dimensions in children in mixed or early permanent dentition. Methods An electronic search was performed on PubMed, Medline, Scopus, The Cochrane Library, EMBASE and the System for Information on Grey Literature in Europe until November 30th, 2019. The Newcastle-Ottawa (NOS) scale was used to assess the studies’ quality. Review Manager 5.3 (provided by the Cochrane Collaboration) was used to synthesize the effects on airway dimensions. Results After full text assessment, 8 studies were included in the qualitative and quantitative synthesis. NOS scores ranged 6 to 9 indicating high quality. The effects of two therapeutic protocols were compared, treatment with MPAs only (113 subjects treated - 65 controls) and the treatment with MPAs + RME (137 subjects treated-87 controls). The MPAs only treatment group displayed a significantly increase in nasopharyngeal airway dimension at PNS-AD1 (random: mean difference, 1.39 mm, 95% CI, 0.32 mm, 2.47 mm, p= 0.01) and at PNS-AD2 (random: mean difference, 1.70 mm, 95% CI, 1.14 mm, 2.26 mm, p= 0.00001). No statistically significant changes were found post treatment in MPAs + RME treatment groups at PNS-AD1 (P= 0.15), PNS-AD2 (P= 0.17), McNamara’s upper pharynx (MPAs + RME P= 0.05, MPAs P= 0.99) and McNamara lower pharynx (MPAs + RME P= 0.25, MPAs P= 0.40). Conclusion MPAs only treatment can increase the pharyngeal thickness after treatment both at PNS-A1 and PNS-AD2. MPA+ RME had no effect on sagittal widths compared with controls, but the effect on the transverse dimension could not be assessed

Non-invasive, transdermal, path-selective and specific glucose monitoring via a graphene-based platform

Currently, there is no available needle-free approach for diabetics to monitor glucose levels in the interstitial fluid. Here, we report a path-selective, non-invasive, transdermal glucose monitoring system based on a miniaturized pixel array platform (realized either by graphene-based thin-film technology, or screen-printing). The system samples glucose from the interstitial fluid via electroosmotic extraction through individual, privileged, follicular pathways in the skin, accessible via the pixels of the array. A proof of principle using mammalian skin ex vivo is demonstrated for specific and ‘quantized’ glucose extraction/detection via follicular pathways, and across the hypo- to hyper-glycaemic range in humans. Furthermore, the quantification of follicular and non-follicular glucose extraction fluxes is clearly shown. In vivo continuous monitoring of interstitial fluid-borne glucose with the pixel array was able to track blood sugar in healthy human subjects. This approach paves the way to clinically relevant glucose detection in diabetics without the need for invasive, finger-stick blood sampling

A Multilinear Sampling Algorithm to Estimate Shapley Values

Shapley values are great analytical tools in game theory to measure the importance of a player in a game. Due to their axiomatic and desirable properties such as efficiency, they have become popular for feature importance analysis in data science and machine learning. However, the time complexity to compute Shapley values based on the original formula is exponential, and as the number of features increases, this becomes infeasible. Castro et al. [1] developed a sampling algorithm, to estimate Shapley values. In this work, we propose a new sampling method based on a multilinear extension technique as applied in game theory. The aim is to provide a more efficient (sampling) method for estimating Shapley values. Our method is applicable to any machine learning model, in particular for either multiclass classifications or regression problems. We apply the method to estimate Shapley values for multilayer perceptrons (MLPs) and through experimentation on two datasets, we demonstrate that our method provides more accurate estimations of the Shapley values by reducing the variance of the sampling statistics

Laboratori. Scuola e Università: Sezione di "Dionysus ex Machina. Rivista online di studi sul teatro antico" 7

La sezione raccoglie documenti dal mondo della scuola e dell'università, in un'ottica di confronto tra approcci differenti al teatro antico: propone quindi interventi di taglio diverso, dedicati alla riflessione sui filoni della ricerca, alla presentazione di metodologie e tradizioni scientifiche e didattiche, come di esperienze laboratoriali e progetti di messa in scena

Variational-LSTM autoencoder to forecast the spread of coronavirus across the globe.

Modelling the spread of coronavirus globally while learning trends at global and country levels remains crucial for tackling the pandemic. We introduce a novel variational-LSTM Autoencoder model to predict the spread of coronavirus for each country across the globe. This deep Spatio-temporal model does not only rely on historical data of the virus spread but also includes factors related to urban characteristics represented in locational and demographic data (such as population density, urban population, and fertility rate), an index that represents the governmental measures and response amid toward mitigating the outbreak (includes 13 measures such as: 1) school closing, 2) workplace closing, 3) cancelling public events, 4) close public transport, 5) public information campaigns, 6) restrictions on internal movements, 7) international travel controls, 8) fiscal measures, 9) monetary measures, 10) emergency investment in health care, 11) investment in vaccines, 12) virus testing framework, and 13) contact tracing). In addition, the introduced method learns to generate a graph to adjust the spatial dependences among different countries while forecasting the spread. We trained two models for short and long-term forecasts. The first one is trained to output one step in future with three previous timestamps of all features across the globe, whereas the second model is trained to output 10 steps in future. Overall, the trained models show high validation for forecasting the spread for each country for short and long-term forecasts, which makes the introduce method a useful tool to assist decision and policymaking for the different corners of the globe