University of Naples Federico II

About: University of Naples Federico II is a education organization based out in Naples, Campania, Italy. It is known for research contribution in the topics: Population & Cancer. The organization has 29291 authors who have published 68803 publications receiving 1920149 citations. The organization is also known as: Università degli Studi di Napoli Federico II & Naples University.

Thrombin functions as an inflammatory mediator through activation of its receptor.

Abstract: A rat model of inflammation was used to investigate the biological effects of thrombin. The thrombin-specific inhibitor Hirulog markedly attentuated the carrageenin-induced edema of the paw of the rat. Injection of thrombin into the paw also produced edema. The effect of thrombin was due to activation of its receptor; a thrombin receptor activating peptide (TRAP) reproduced the effects of thrombin in causing edema. TRAP also increased vascular permeability as demonstrated by extravasation of Evans blue and 125I-labeled serum albumin. The release of bioactive amines played an important role in mediating the TRAP-induced edema; the serotonin/histamine antagonist cryproheptadine and the histamine H2 receptor antagonist cimetidine reduced significantly the edema caused by TRAP. Treatment of rats with the mast cell degranulator 48/80 to deplete these cells of their stores of histamine and serotonin abolished completely the ability of TRAP to produce edema. Histochemical examination confirmed that TRAP treatment led to mast cell degranulation. Thus, it has been possible to demonstrate that thrombin acts as an inflammatory mediator in vivo by activating its receptor, which in turn leads to release of vasoactive amines from mast cells.

Nonlinear Heart Rate Variability features for real-life stress detection. Case study: students under stress due to university examination

Abstract: This study investigates the variations of Heart Rate Variability (HRV) due to a real-life stressor and proposes a classifier based on nonlinear features of HRV for automatic stress detection. 42 students volunteered to participate to the study about HRV and stress. For each student, two recordings were performed: one during an on-going university examination, assumed as a real-life stressor, and one after holidays. Nonlinear analysis of HRV was performed by using Poincare Plot, Approximate Entropy, Correlation dimension, Detrended Fluctuation Analysis, Recurrence Plot. For statistical comparison, we adopted the Wilcoxon Signed Rank test and for development of a classifier we adopted the Linear Discriminant Analysis (LDA). Almost all HRV features measuring heart rate complexity were significantly decreased in the stress session. LDA generated a simple classifier based on the two Poincare Plot parameters and Approximate Entropy, which enables stress detection with a total classification accuracy, a sensitivity and a specificity rate of 90%, 86%, and 95% respectively. The results of the current study suggest that nonlinear HRV analysis using short term ECG recording could be effective in automatically detecting real-life stress condition, such as a university examination.