Analgesia postoperatoria: l' epidurale e le altre tecniche

Background: il dolore è un’ esperienza negativa sia sensoriale che emotiva che compromette la normale vita quotidiana della persona. Spesso il dolore acuto è causa di traumi o interventi chirurgici. Il dolore postoperatorio mette il soggetto in uno stato d’impotenza e di sudditanza fisica e mentale inoltre può essere temuto più dello stesso intervento e dell’anestesia. Il dolore acuto, se non trattato, diventa cronico con numerose complicanze a carico dell’organismo. Dalla letteratura si evince come, nonostante il gran numero di studi negli ultimi decenni, il problema è ancora sottostimato e dipende da molteplici fattori. L’obiettivo della ricerca consiste nel cercare in letteratura tra le tecniche analgesiche se esista un gold standard, mettendone in luce pregi e difetti, e confrontarlo con altre tecniche equiparabili. Metodi : lo studio si basa sulla ricerca nelle banche dati, in particolare in PubMed, di tecniche e metodiche analgesiche, che mettano in comparazione il gold standard, nella fattispecie l’analgesia epidurale, con altre tecniche altrettanto valide, mettendo in luce dati su mortalità, morbilità e soddisfazione del paziente. Risultati: dalla ricerca si evince come la tecnica epidurale nel corso degli ultimi decenni si sia attestata come gold standard nel trattamento analgesico post operatorio. Ciò nonostante, altre tecniche regionali si stanno affermando come buoni sostituti come ad esempio la filtrazione continua della ferita, il blocco paravertebrale toracico e l’analgesia controllata dal paziente. Conclusioni: la ricerca ha analizzato prevalentemente i tassi di mortalità e morbilità nel confronto di due tecniche alla volta. Queste non hanno previsto sempre le stesse modalità di inserimento cateteri; inoltre diversi farmaci usati e popolazione target non sempre uguale. Appare comunque evidente la bontà analgesica di altre tecniche, diverse dall’epidurale.ope

Imaging of temporomandibular joint: Approach by direct volume rendering

Materials and Methods: We have studied the temporom-andibular joint anatomy, directly on the living, from 3D images obtained by medical imaging Computed Tomography and Nuclear Magnetic Resonance acquisition, and subsequent re-engineering techniques 3D Surface Rendering and Volume Rendering. Data were analysed with the goal of being able to isolate, identify and distinguish the anatomical structures of the joint, and get the largest possible number of information utilizing software for post-processing work.Results: It was possible to reproduce anatomy of the skeletal structures, as well as through acquisitions of Magnetic Resonance Imaging; it was also possible to visualize the vascular, muscular, ligamentous and tendinous components of the articular complex, and also the capsule and the fibrous cartilaginous disc. We managed the Surface Rendering and Volume Rendering, not only to obtain three-dimensional images for colour and for resolution comparable to the usual anatomical preparations, but also a considerable number of anatomical, minuter details, zooming, rotating and cutting the same images with linking, graduating the colour, transparency and opacity from time to time.Conclusion: These results are encouraging to stimulate further studies in other anatomical districts.Background: The purpose of this study was to conduct a morphological analysis of the temporomandibular joint, a highly specialized synovial joint that permits movement and function of the mandible

Overexpression of melanocortin 2 receptor accessory protein 2 (MRAP2) in adult paraventricular MC4R neurons regulates energy intake and expenditure

The Medical Research Council UK (MRC/Academy of Medical Sciences Clinician Scientist Fellowship Grant G0802796 (to LFC) and NIH grants R01 DK105571, DK097566 and DK107293 (to SD)

A Learning-based Nonlinear Model Predictive Controller for a Real Go-Kart based on Black-box Dynamics Modeling through Gaussian Processes

Lately, Nonlinear Model Predictive Control (NMPC)has been successfully applied to (semi-) autonomous driving problems and has proven to be a very promising technique. However, accurate control models for real vehicles could require costly and time-demanding specific measurements. To address this problem, the exploitation of system data to complement or derive the prediction model of the NMPC has been explored, employing learning dynamics approaches within Learning-based NMPC (LbNMPC). Its application to the automotive field has focused on discrete grey-box modeling, in which a nominal dynamics model is enhanced by the data-driven component. In this manuscript, we present an LbNMPC controller for a real go-kart based on a continuous black-box model of the accelerations obtained by Gaussian Processes. We show the effectiveness of the proposed approach by testing the controller on a real go-kart vehicle, highlighting the approximation steps required to get an exploitable GP model on a real-time application.Comment: Accepted in IEEE Transaction on Control System Technology as Full Paper for SI: State-of-the-art Applications of Model Predictive Control. 12 pages, 20 figure

Cognitive processess and cognitive reserve in multiple sclerosis

Multiple Sclerosis (MS) is characterized by motor, cognitive, and neuropsychiatric symptoms, which can occur independently. While MS is traditionally considered an inflammatory disease of the white matter, degeneration of gray matter is increasingly recognized as an important contributor to the progressive cognitive decline. A protective factor against the progression of cognitive dysfunction in MS could be the cognitive reserve, defined as resistance to brain dysfunction. Aim of the present study is to evaluate the role of cognitive reserve for different aspects of cognitive dysfunction of patients with MS. We found that patients with MS and lower cognitive reserve have poorer neuropsychological performance and slower information speed processing. These findings support the notion that intellectual reserve may protect some aspects of cognitive function in patients with MS

Explainable Artificial Intelligence in communication networks: A use case for failure identification in microwave networks

Artificial Intelligence (AI) has demonstrated superhuman capabilities in solving a significant number of tasks, leading to widespread industrial adoption. For in-field network-management application, AI-based solutions, however, have often risen skepticism among practitioners as their internal reasoning is not exposed and their decisions cannot be easily explained, preventing humans from trusting and even understanding them. To address this shortcoming, a new area in AI, called Explainable AI (XAI), is attracting the attention of both academic and industrial researchers. XAI is concerned with explaining and interpreting the internal reasoning and the outcome of AI-based models to achieve more trustable and practical deployment. In this work, we investigate the application of XAI for network management, focusing on the problem of automated failure-cause identification in microwave networks. We first introduce the concept of XAI, highlighting its advantages in the context of network management, and we discuss in detail the concept behind Shapley Additive Explanations (SHAP), the XAI framework considered in our analysis. Then, we propose a framework for a XAI-assisted ML-based automated failure-cause identification in microwave networks, spanning model's development and deployment phases. For the development phase, we show how to exploit SHAP for feature selection and how to leverage SHAP to inspect misclassified instances during model's development process, and how to describe model's global behavior based on SHAP's global explanations. For the deployment phase, we propose a framework based on predictions uncertainty to detect possibly wrong predictions that will be inspected through XAI

Embryological considerations on a case of coexistence of persistent left superior vena cava and partially left inferior vena cava

The persistent left superior vena cava (PLSVC) is the most common venous thoracic congenital anomaly. The PLSCV generally drains into the right atrium, which it reaches through a dilated coronary sinus. Its presence is usually unrecognized, until a venous approach is performed. Abnormalities of the inferior vena cava (IVC) are rare (0.2-0.3% of healthy subjects and 0.6-2% of patients with cardiovascular defects). A single left IVC (LIVC) is very rare (11.9% of all the abnormalities) [1]. To the best of our knowledge, the coexistence of PLSCV and LICV has not been previously described. We present a case of a 32-year-old woman on hemodialysis for more than 12 years. An angiography demonstrated both a normal right SVC and a PLSCV and a single IVC with a lower left course, an intermediate circumaortic ring and an upper normal right course. The double SVC can be consequent to the failed development of the anastomosis between the anterior cardinal veins and the patency of the caudal part of the left anterior cardinal vein forming the PLSCV. As to the partially LIVC, its iliac and subrenal parts can be the results of the persistence of the left supracardinal vein. The circumaortic venous ring might indicate that a persistent intersupracardinal anastomosis receiving the left and the right renal veins was maintained around the abdominal aorta [2], while the superior part represents the normal right subcardinal and hepatic derivatives. The existence of anomalies should be considered, as they can have important implications in invasive procedures such as venous catheter placement, and may represent a speculative bridge between clinicians and embryologists

iron metabolism modification during repeated show jumping event in equine athletes

Abstract In athletic horse the evaluation of iron status is of great importance to improve physical performance and health status of animal. The aim of this study was to evaluate the changes of iron indices following show jumping. Ten regularly trained Italian Saddlebred horses aged 7-8 years (mean body weight 467±12 kg) were subjected to three days jumping competition. Blood samples were collected at 5 time points: T0 (the day before competitions), T1 (immediately after exercise at day 1), T2 (immediately after exercise at day 2), T3 (immediately after exercise at day 3) and during the recovery period T4 (24 h after day 3). On each blood sample the values of red blood cell (RBC), hemoglobin concentration (Hb), hematocrit (Hct), serum iron, ferritin, transferrin, total iron-binding capacity (TIBC) and unsaturated iron-binding capacity (UIBC) were assessed. One-way repeated measure analysis of variance (ANOVA) showed a statistical significant effect of exercise (P<0.05) on all studied parameters. The application of Bonferroni's post-hoc comparison showed a statistical significant increase in all studied parameters after exercise. These results provide new information about the changes in iron profile of jumper horse following exercise allowing for better evaluation of the health status and physical performance of this athlete horse