Search for charginos, neutralinos, and gravitinos at LEP

The hep-ex data base was decided not to be an appropriate place to make DELPHI notes public. Sorry for the inconvenience.Comment: the paper should not have been made publi

Characterization of the Hamamatsu R11265-103-M64 multi-anode photomultiplier tube

The aim of this paper is to fully characterize the new multi-anode photomultiplier tube R11265-103-M64, produced by Hamamatsu. Its high effective active area (77%), its pixel size, the low dark signal rate and the capability to detect single photon signals make this tube suitable for an application in high energy physics, such as for RICH detectors. Four tubes and two different bias voltage dividers have been tested. The results of a standard characterization of the gain and the anode uniformity, the dark signal rate, the cross-talk and the device behaviour as a function of temperature have been studied. The behaviour of the tube is studied in a longitudinal magnetic field up to 100 Gauss. Shields made of a high permeability material are also investigated. The deterioration of the device performance due to long time operation at intense light exposure is studied. A quantitative analysis of the variation of the gain and the dark signals rate due to the aging is described.Comment: 22 page

The running of the electromagnetic coupling alpha in small-angle Bhabha scattering

A method to determine the running of alpha from a measurement of small-angle Bhabha scattering is proposed and worked out. The method is suited to high statistics experiments at e+e- colliders, which are equipped with luminometers in the appropriate angular region. A new simulation code predicting small-angle Bhabha scattering is also presentedComment: 15 pages, 3 Postscript figure

Identification of recurrent genetic patterns from targeted sequencing panels with advanced data science: a case-study on sporadic and genetic neurodegenerative diseases

open8noThis work is funded by the University of Bologna, the IRCCS Institute of Neurological sciences of Bologna, and by the European Grants H2020 GenoMed4All [AM1] (Grant N. 101017549) and H2020 MSCA-ITN IMforFUTURE (Grant N. 721815).Background Targeted Next Generation Sequencing is a common and powerful approach used in both clinical and research settings. However, at present, a large fraction of the acquired genetic information is not used since pathogenicity cannot be assessed for most variants. Further complicating this scenario is the increasingly frequent description of a poli/oligogenic pattern of inheritance showing the contribution of multiple variants in increasing disease risk. We present an approach in which the entire genetic information provided by target sequencing is transformed into binary data on which we performed statistical, machine learning, and network analyses to extract all valuable information from the entire genetic profile. To test this approach and unbiasedly explore the presence of recurrent genetic patterns, we studied a cohort of 112 patients affected either by genetic Creutzfeldt–Jakob (CJD) disease caused by two mutations in the PRNP gene (p.E200K and p.V210I) with different penetrance or by sporadic Alzheimer disease (sAD). Results Unsupervised methods can identify functionally relevant sources of variation in the data, like haplogroups and polymorphisms that do not follow Hardy–Weinberg equilibrium, such as the NOTCH3 rs11670823 (c.3837 + 21 T > A). Supervised classifiers can recognize clinical phenotypes with high accuracy based on the mutational profile of patients. In addition, we found a similar alteration of allele frequencies compared the European population in sporadic patients and in V210I-CJD, a poorly penetrant PRNP mutation, and sAD, suggesting shared oligogenic patterns in different types of dementia. Pathway enrichment and protein–protein interaction network revealed different altered pathways between the two PRNP mutations. Conclusions We propose this workflow as a possible approach to gain deeper insights into the genetic information derived from target sequencing, to identify recurrent genetic patterns and improve the understanding of complex diseases. This work could also represent a possible starting point of a predictive tool for personalized medicine and advanced diagnostic applications.openTarozzi, M.; Bartoletti-Stella, A.; Dall’Olio, D.; Matteuzzi, T.; Baiardi, S.; Parchi, P.; Castellani, G.; Capellari, S.Tarozzi, M.; Bartoletti-Stella, A.; Dall’Olio, D.; Matteuzzi, T.; Baiardi, S.; Parchi, P.; Castellani, G.; Capellari, S