Inhibiting metabotropic glutamate receptor 5 after stroke restores brain function and connectivity

Stroke results in local neural disconnection and brain-wide neuronal network dysfunction leading to neurological deficits. Beyond the hyper-acute phase of ischaemic stroke, there is no clinically-approved pharmacological treatment that alleviates sensorimotor impairments. Functional recovery after stroke involves the formation of new or alternative neuronal circuits including existing neural connections. The type-5 metabotropic glutamate receptor (mGluR5) has been shown to modulate brain plasticity and function and is a therapeutic target in neurological diseases outside of stroke. We investigated whether mGluR5 influences functional recovery and network reorganization rodent models of focal ischaemia. Using multiple behavioural tests, we observed that treatment with negative allosteric modulators (NAMs) of mGluR5 (MTEP, fenobam and AFQ056) for 12 days, starting 2 or 10 days after stroke, restored lost sensorimotor functions, without diminishing infarct size. Recovery was evident within hours after initiation of treatment and progressed over the subsequent 12 days. Recovery was prevented by activation of mGluR5 with the positive allosteric modulator VU0360172 and accelerated in mGluR5 knock-out mice compared with wild-type mice. After stroke, multisensory stimulation by enriched environments enhanced recovery, a result prevented by VU0360172, implying a role of mGluR5 in enriched environment-mediated recovery. Additionally, MTEP treatment in conjunction with enriched environment housing provided an additive recovery enhancement compared to either MTEP or enriched environment alone. Using optical intrinsic signal imaging, we observed brain-wide disruptions in resting-state functional connectivity after stroke that were prevented by mGluR5 inhibition in distinct areas of contralesional sensorimotor and bilateral visual cortices. The levels of mGluR5 protein in mice and in tissue samples of stroke patients were unchanged after stroke. We conclude that neuronal circuitry subserving sensorimotor function after stroke is depressed by a mGluR5-dependent maladaptive plasticity mechanism that can be restored by mGluR5 inhibition. Post-acute stroke treatment with mGluR5 NAMs combined with rehabilitative training may represent a novel post-acute stroke therapy

Preoperative Localization in Colonic Surgery (PLoCoS Study): a multicentric experience on behalf of the Italian Society of Colorectal Surgery (SICCR)

The aim of this prospective multicentric study was to compare the accurate colonic lesion localization ratio between CT and colonoscopy in comparison with surgery. All consecutive patients from 1st January to 31st December 2019 with a histologically confirmed diagnosis of dysplastic adenoma or adenocarcinoma with planned elective, curative colonic resection who underwent both colonoscopy and CT scans were included. Each patient underwent conventional colonoscopy and CT to stage the tumour, and the localization results of each procedure were registered. CT and colonoscopic localization were compared with surgical localization, adopted as the reference. Our analysis included 745 patients from 23 centres. After comparing the accuracy of colonoscopy and CT (for visible lesions) in localizing colonic lesions, no significant differences were found between the two preoperative tools (510/661 vs 499/661 correctly localized lesions, p = 0.518). Furthermore, after analysing only the patients who underwent complete colonoscopy and had a visible lesion on CT, no significant difference was observed between conventional colonoscopy and CT (331/427 vs 340/427, p = 0.505). Considering the intraoperative localization results as a reference, a comparison between colonoscopy and CT showed that colonoscopy significantly failed to correctly locate the lesions localized in the descending colon (17/32 vs 26/32, p = 0.031). We did not identify an advantage in using CT to localize colonic tumours. In this setting, colonoscopy should be considered the reference to properly localize lesions; however, to better identify lesions in the descending colon, CT could be considered a valuable tool to improve the accuracy of lesion localization

Stroke recovery activity-dependent mechanisms

Stroke is the leading cause of disability in developed countries and among the major causes of death worldwide. During a stroke, neurons deprived of their normal metabolic substrates cease to function in seconds and show signs of structural damage after only a few minutes which result in the impairment of sensory and motor function. Loss of function after stroke is due to neuronal death and irreversible ischemic damage in the infarct core but also to cell dysfunction in the areas surrounding the infarct. These areas represent the peri-infarct, a region of reduced blood supply and reversible damage, and the intact remote areas directly connected to the damaged tissue or hub regions of the brain network.Clinical evidence shows that physical and cognitive therapy, as well as social interactions, facilitate the recovery process and promote improvement of lost neurological function after stroke. In the experimental setting, these observations can be mimicked by an enriched environment (EE), which provides an activity-dependent stimulation of the brain. The EE is a housing condition for rodents combining multisensory stimulation and social interactions that improve lost neurological function without affecting the extent of brain damage after experimental stroke.This thesis deals with the concept of EE and mechanisms underlying activity-dependent plasticity in the brain after stroke and their influence on functional recovery. We propose that EE balances mechanisms critical for stroke recovery, such as the detrimental and beneficial components of the post-stroke inflammatory response, and the activation of ECM-degrading processes which ultimately lead to improved brain functional connectivity and behavioral outcome. Finally, this thesis suggests that a general stimulating and positive environment can be the optimal base for specific interventions in neurological rehabilitation

Analisi di sensibilità globale e propagazione dell'incertezza di modelli autoregressivi impiegati nell'ambito del monitoraggio strutturale

LAUREA MAGISTRALENegli ultimi anni, l’approccio data-based è diventato sempre più diffuso nell'ambito del monitoraggio strutturale (SHM), grazie alla sua relativa facilità di implementazione. Infatti, a differenza dell’approccio model-based, non necessita di alcun modello ad elementi finiti della struttura in esame. Nell'ambito dell’approccio data-based i modelli autoregressivi sono tra i più utilizzati. In questo lavoro di tesi è proposta un’indagine numerica dei modelli autoregressivi e della relativa feature, la distanza di Mahalanobis. Lo studio si focalizza sulla propagazione dell’incertezza, attraverso il metodo di Monte Carlo, e sull'analisi alla sensibilità, mediante l’Analisi alla Sensibilità Globale (GSA), considerando diverse tipologie di danneggiamento. L’insieme delle simulazioni numeriche condotte permette, inoltre, di analizzare l’effetto del rumore di misura e l’influenza dell’ordine del modello autoregressivo, sull'efficacia di identificazione del danno. Grazie ai risultati ottenuti attraverso l’analisi numerica di questi modelli, viene sviluppata, all'interno del lavoro di tesi, una innovativa metodologia di applicazione della distanza di Mahalanobis per applicazioni di monitoraggio strutturale, mediante modelli autoregressivi. L'efficacia di questa nuova strategia viene testata sperimentalmente, sfruttando un banco di prova realizzato ad hoc per lo scopo.In latest years, data-based approach have become increasingly common in the field of Structural Health Monitoring (SHM), due to their relative ease of implementation. Indeed, unlike the model-based approach, they do not require any finite element models of the structure taken into consideration. Related to data-based approach, the autoregressive models are the most used. The main purpose of this thesis is to achieve a numerical investigation for the autoregressive models and the related feature, the Mahalanobis distance. It is possible to analyse the propagation of uncertainty, through the Monte Carlo method, using numerical simulation. Moreover, the Global Sensitivity Analysis (GSA), lead the examination of the autoregressive models sensitivity to several types of damage, which may affect the system. The simulations also allow to analyse the effect of the measurement noise and the influence of the autoregressive model order, on the effectiveness of damage detection, for this kind of algorithms. According to the results, obtained through the numerical analysis, in this graduation thesis, an innovative methodology for the application of the Mahalanobis distance is developed, in the field of SHM, using autoregressive models. The effectiveness of this strategy is tested experimentally on a bench test, designed specifically for this purpose