Effect of levodopa on interleukin-15 and RANTES circulating levels in patients affected by Parkinson's disease.

Parkinson's disease (PD) is an extra-pyramidal neurodegenerative disorder, in which alterations of the immune system are involved. Interleukin (IL)-15 stimulates cellular immune response and induces growth and differentiation of various immune cells. RANTES, promoting leukocyte infiltration to sites of inflammation, mediates the trafficking and homing of immune cells. To clarify the potential effect of levodopa on the immunological network of PD, we analyzed IL-15 and RANTES serum levels in PD patients, treated or not with levodopa, and in healthy donors. Levodopa-treated patients showed significantly higher IL-15 and RANTES circulating levels with respect to healthy controls and higher, although not significantly, levels with respect to untreated patients. So, we hypothesize that the immunological alterations found in PD may be linked, at least in part, to levodopa therapy

Firewall management with FireWall synthesizer

Firewalls are notoriously hard to configure and maintain. Policies are written in low-level, system-specific languages where rules are inspected and enforced along non-trivial control flow paths. Moreover, firewalls are tightly related to Network Address Translation (NAT) since filters need to be specified taking into account the possible translations of packet addresses, further complicating the task of network administrators. To simplify this job, we propose FIRE WALL SYNTHESIZER (FWS), a tool that decompiles real firewall configurations from different systems into an abstract specification. This representation highlights the meaning of a configuration, i.e., the allowed connections with possible address translations. We show the usage of FWS in analyzing and maintaining a configuration on a simple (yet realistic) scenario and we discuss how the tool scales on real-world policies

Storiografia filosofica e storiografia religiosa. Due punti di vista a confronto. Scritti in onore di Luciano Malusa

Il volume raccoglie una trentina di contributi sul tema della storiografia filosofica nel suo rapporto con la storiografia religiosa

Epidermal growth factor receptor expression identifies functionally and molecularly distinct tumor-initiating cells in human glioblastoma multiforme and is required for gliomagenesis

Epidermal growth factor receptor (EGFR) is a known diagnostic and, although controversial, prognostic marker of human glioblastoma multiforme (GBM). However, its functional role and biological significance in GBM remain elusive. Here, we show that multiple GBM cell subpopulations could be purified from the specimens of patients with GBM and from cancer stem cell (CSC) lines based on the expression of EGFR and of other putative CSC markers. All these subpopulations are molecularly and functionally distinct, are tumorigenic, and need to express EGFR to promote experimental tumorigenesis. Among them, EGFR-expressing tumor-initiating cells (TIC) display the most malignant functional and molecular phenotype. Accordingly, modulation of EGFR expression by gain-of-function and loss-of-function strategies in GBM CSC lines enhances and reduces their tumorigenic ability, respectively, suggesting that EGFR plays a fundamental role in gliomagenesis. These findings open up the possibility of new therapeutically relevant scenarios, as the presence of functionally heterogeneous EGFR(pos) and EGFR(neg) TIC subpopulations within the same tumor might affect clinical response to treatment

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

133. Antiqui philosophi. Storia e filosofia in Bonaventura

Il saggio analizza l'approccio storico-filosofico bonaventuriano, con particolare attenzione al suo Commento alle Sentenze e alle Collationes in Hexaemeron

Il Dante "bonaventuriano" di Ernesto Jallonghi

Si tratta della prima parte di un saggio che analizza la fortuna della interpretazione della "Commedia" e, pi\uf9 in generale, dell'opera dantesca come dipendenti dall'influsso del pensiero bonaventurian