University of Milano-Bicocca

About: University of Milano-Bicocca is a education organization based out in Milan, Italy. It is known for research contribution in the topics: Population & Blood pressure. The organization has 8972 authors who have published 22322 publications receiving 620484 citations. The organization is also known as: Università degli Studi di Milano-Bicocca & Universita degli Studi di Milano-Bicocca.

Effect of different gonadotrophin priming on IVM of oocytes from women with normal ovaries: a prospective randomized study.

Abstract: This study was designed to determine if the efficiency of in-vitro maturation (IVM) in women with normal ovaries can be improved by gonadotrophin administration. 400 women were randomly allocated in four groups: group A, non-primed cycles; group B, human chorionic gonadotrophin (HCG)-primed cycles; group C, FSH-primed cycles; and group D, FSH- plus HCG-primed cycles. There were significant differences in the IVM rate among the groups. In groups where HCG was used, the overall maturation rate was higher (57.9% in group B and 77.4% in group D; 48.4% in group A and 50.8% in group C) and the percentage of total available metaphase II-stage oocytes was higher (60.4% in group B and 82.1% in group D; 48.4% in group A and 50.8% in group C). The overall clinical pregnancy rate per transfer (CPR) was 18.3% and the implantation rate (IR) was 10.6%. There was a difference in CPR among the groups: group D (29.9%) versus group A (15.3%), P = 0.023; group D versus group B (7.6%), P < 0.0001; group D versus group C (17.3%), P = 0.046. The results of this study are clearly in favour of FSH plus HCG priming. FSH priming and HCG priming alone showed no significant effects on clinical outcome.

Combination of Video Change Detection Algorithms by Genetic Programming

Abstract: Within the field of computer vision, change detection algorithms aim at automatically detecting significant changes occurring in a scene by analyzing the sequence of frames in a video stream. In this paper we investigate how state-of-the-art change detection algorithms can be combined and used to create a more robust algorithm leveraging their individual peculiarities. We exploited genetic programming (GP) to automatically select the best algorithms, combine them in different ways, and perform the most suitable post-processing operations on the outputs of the algorithms. In particular, algorithms’ combination and post-processing operations are achieved with unary, binary and ${n}$ -ary functions embedded into the GP framework. Using different experimental settings for combining existing algorithms we obtained different GP solutions that we termed In Unity There Is Strength . These solutions are then compared against state-of-the-art change detection algorithms on the video sequences and ground truth annotations of the ChangeDetection.net 2014 challenge. Results demonstrate that using GP, our solutions are able to outperform all the considered single state-of-the-art change detection algorithms, as well as other combination strategies. The performance of our algorithm are significantly different from those of the other state-of-the-art algorithms. This fact is supported by the statistical significance analysis conducted with the Friedman test and Wilcoxon rank sum post-hoc tests.

Obestatin inhibits feeding but does not modulate GH and corticosterone secretion in the rat.

Abstract: Obestatin is a recently discovered 23 amino acids peptide derived from the ghrelin gene. As opposed to ghrelin, obestatin was shown to inhibit food intake in mice. The aims of this research were to study the effects of acute obestatin treatment on feeding behavior in the rat and its effects on GH and corticosterone secretion. Our results demonstrate that in young-adult male rats, obestatin effectively blunts the hunger caused by short-term starvation. Obestatin did not modify GH secretion in 10-day-old rats and did not antagonize the GH-releasing effects of hexarelin. Moreover, obestatin administration had no effects on spontaneous corticosterone secretion. In conclusion, these data demonstrate that in young-adult male rats the newly discovered obestatin can inhibit feeding but does not modify GH and corticosterone release in infant rats.

Quantitative versus standard pupillary light reflex for early prognostication in comatose cardiac arrest patients: an international prospective multicenter double-blinded study

Abstract: Purpose: To assess the ability of quantitative pupillometry [using the Neurological Pupil index (NPi)] to predict an unfavorable neurological outcome after cardiac arrest (CA). Methods: We performed a prospective international multicenter study (10 centers) in adult comatose CA patients. Quantitative NPi and standard manual pupillary light reflex (sPLR)—blinded to clinicians and outcome assessors—were recorded in parallel from day 1 to 3 after CA. Primary study endpoint was to compare the value of NPi versus sPLR to predict 3-month Cerebral Performance Category (CPC), dichotomized as favorable (CPC 1–2: full recovery or moderate disability) versus unfavorable outcome (CPC 3–5: severe disability, vegetative state, or death). Results: At any time between day 1 and 3, an NPi ≤ 2 (n = 456 patients) had a 51% (95% CI 49–53) negative predictive value and a 100% positive predictive value [PPV; 0% (0–2) false-positive rate], with a 100% (98–100) specificity and 32% (27–38) sensitivity for the prediction of unfavorable outcome. Compared with NPi, sPLR had significantly lower PPV and significantly lower specificity (p < 0.001 at day 1 and 2; p = 0.06 at day 3). The combination of NPi ≤ 2 with bilaterally absent somatosensory evoked potentials (SSEP; n = 188 patients) provided higher sensitivity [58% (49–67) vs. 48% (39–57) for SSEP alone], with comparable specificity [100% (94–100)]. Conclusions: Quantitative NPi had excellent ability to predict an unfavorable outcome from day 1 after CA, with no false positives, and significantly higher specificity than standard manual pupillary examination. The addition of NPi to SSEP increased sensitivity of outcome prediction, while maintaining 100% specificity.