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Recently introduced rapidly mutating Y-chromosomal short tandem repeat (RM Y-STR) loci, displaying a multiple-fold higher mutation rate relative to any other Y-STRs, including those conventionally used in forensic casework, have been demonstrated to improve the resolution of male lineage differentiation and to allow male relative separation usually impossible with standard Y-STRs. However, large and geographically-detailed frequency haplotype databases are required to estimate the statistical weight of RM Y-STR haplotype matches if observed in forensic casework. With this in mind, the Italian Working Group (GEFI) of the International Society for Forensic Genetics launched a collaborative exercise aimed at generating an Italian quality controlled forensic RM Y-STR haplotype database. Overall 1509 male individuals from 13 regional populations covering northern, central and southern areas of the Italian peninsula plus Sicily were collected, including both "rural" and "urban" samples classified according to population density in the sampling area. A subset of individuals was additionally genotyped for Y-STR loci included in the Yfiler and PowerPlex Y23 (PPY23) systems (75% and 62%, respectively), allowing the comparison of RM and conventional Y-STRs. Considering the whole set of 13 RM Y-STRs, 1501 unique haplotypes were observed among the 1509 sampled Italian men with a haplotype diversity of 0.999996, largely superior to Yfiler and PPY23 with 0.999914 and 0.999950, respectively. AMOVA indicated that 99.996% of the haplotype variation was within populations, confirming that genetic-geographic structure is almost undetected by RM Y-STRs. Haplotype sharing among regional Italian populations was not observed at all with the complete set of 13 RM Y-STRs. Haplotype sharing within Italian populations was very rare (0.27% non-unique haplotypes), and lower in urban (0.22%) than rural (0.29%) areas. Additionally, 422 father-son pairs were investigated, and 20.1% of them could be discriminated by the whole set of 13 RM Y-STRs, which was very close to the theoretically expected estimate of 19.5% given the mutation rates of the markers used. Results obtained from a high-coverage Italian haplotype dataset confirm on the regional scale the exceptional ability of RM Y-STRs to resolve male lineages previously observed globally, and attest the unsurpassed value of RM Y-STRs for male-relative differentiation purposes., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

Background: Omalizumab is effective and safe in severe allergic asthma. Few data are available about its impact on lung function and on asthma comorbidities, long-term follow-up of treated patients, adherence, non-responders profile, and optimal treatment duration., Objective: We aimed at evaluating omalizumab-related clinical outcomes and unmet needs in a real-life setting., Methods: We created a collaborative network (NEONet - North East Omalizumab Network) involving 9 Allergy and Respiratory referral centres for severe asthma placed in the North-East of Italy. Patients' data were entered into a common study database shared by all the participating physicians. A preliminary retrospective analysis was performed., Results: Patients come from a common well-defined geographical and environmental district providing a homogeneous population sample. A moderate but statistically significant improvement of the FEV1, and an increasing proportion of exacerbations-free patients were observed since the treatment start. These findings were independent of the baseline severity of bronchial obstruction. A positive impact of omalizumab on rhinitis in patients with both asthma and rhinitis was detected. Moreover the efficacy of omalizumab on asthma seemed not to be affected by the baseline severity of rhinitis., Conclusion: Our retrospective analysis represents a preliminary report from the NEONet activity. It confirmed omalizumab efficacy and provided some new insights about its impact on lung function and on comorbid rhinitis. The network approach, under a prospective view, allows creating a large uniform database, by means of a standardized shared tool for data collecting, and joining a multidisciplinary expertise., (Copyright © 2014 Elsevier Ltd. All rights reserved.)