University of Turin

About: University of Turin is a education organization based out in Turin, Piemonte, Italy. It is known for research contribution in the topics: Population & Cancer. The organization has 29607 authors who have published 77952 publications receiving 2480900 citations. The organization is also known as: Universita degli Studi di Torino & Università degli Studi di Torino.

Severely increased risk of amyotrophic lateral sclerosis among Italian professional football players

Abstract: Summary The cause of amyotrophic lateral sclerosis (ALS) is still unknown. A possible relationship between ALS and sport participation has been supposed, but never definitely demonstrated. We studied a cohort of 7325 male professional football players engaged by a football team from the Italian First or Second Division in the period 1970‐2001. ALS cases were identified using different concurrent sources. Standardized morbidity ratios (SMRs) were calculated. During the 137 078 person-years of followup, five ALS cases were identified (mean age of onset, 43.4 years). Three cases had a bulbar onset, significantly more than expected (P = 0.003). Since the number of expected cases was 0.77, the overall SMR was 6.5 [95% confidence interval (CI), 2.1‐15.1]. The SMR was significantly increased for an ALS onset before 49 years, but not for older subjects. A significant increase of the SMR was found in the periods 1980‐1989 and 1990‐ 2001, whereas no ALS case was found in the 1970‐1979 period. A dose‐response relationship between the duration of professional football activity and the risk of ALS was found (>5 years, 15.2, 95% CI, 3.1‐44.4; <5 years, 3.5, 95% CI, 0.4‐12.7). Our findings seem to indicate that playing professional football is a strong risk factor for ALS.

Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV

Abstract: Many measurements and searches for physics beyond the standard model at the LHC rely on the efficient identification of heavy-flavour jets, i.e. jets originating from bottom or charm quarks. In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented. Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. For jets with transverse momenta in the range expected in simulated events, these new developments result in an efficiency of 68% for the correct identification of a b jet for a probability of 1% of misidentifying a light-flavour jet. The improvement in relative efficiency at this misidentification probability is about 15%, compared to previous CMS algorithms. In addition, for the first time algorithms have been developed to identify jets containing two b hadrons in Lorentz-boosted event topologies, as well as to tag c jets. The large data sample recorded in 2016 at a centre-of-mass energy of 13 TeV has also allowed the development of new methods to measure the efficiency and misidentification probability of heavy-flavour jet identification algorithms. The b jet identification efficiency is measured with a precision of a few per cent at moderate jet transverse momenta (between 30 and 300 GeV) and about 5% at the highest jet transverse momenta (between 500 and 1000 GeV).

Development of biocontrol products for postharvest diseases of fruit: The importance of elucidating the mechanisms of action of yeast antagonists

Abstract: s Background Impressive progress was made in the last decade in development, registration and commercialization of biocontrol products based on yeast to manage postharvest pathogens of fruit. To successfully inhibit the pathogen infection and development, several possible mechanisms operate in a tritrophic host-pathogen-antagonist interaction system. Scope and Approach The current reviews focuses on the recent knowledge on the mechanisms by which yeast biocontrol agents (BCAs) interact with pathogens and fruit tissues. The main mechanisms of action explored include antibiosis, mycoparasitism, production of lytic enzymes, induced resistance, competition for limiting nutrients and space, and the role of oxidative stress. Omics techniques can provide a powerful tool to study complex fruit host-pathogen-antagonist-native microflora interactions. Key Findings and Conclusions Various aspects relevant to mechanisms of action of yeast antagonists have been discussed, including unique environment of surface wounds, iron competition, biofilm formation, cell wall degrading enzymes, and involvement of oxidative stress. Outstanding advancement in molecular and omics technologies revolutionized the research about the physiological status of BCAs and the global effect of the application of BCAs on the transcriptome and/or proteome of fruit. Microbial communities on plant surfaces could impact disease control through their interactions with host plants, pathogens, and BCAs, in a quadritrophic interaction system, hence microbiome research opens new research opportunities. The complex modes of action make antagonistic performance and efficacy more dependent on production, formulation, packing, application, and storage. A deep understanding of the mode of action is essential to develop appropriate formulation and methods of application.