Flow Cytofluorimetric Analysis of Anti-LRP4 (LDL Receptor-Related Protein 4) Autoantibodies in Italian Patients with Myasthenia Gravis

Myasthenia gravis (MG) is an autoimmune disease in which 90% of patients have autoantibodies against the muscle nicotinic acetylcholine receptor (AChR), while autoantibodies to muscle-specific tyrosine kinase (MuSK) have been detected in half (5%) of the remaining 10%. Recently, the low-density lipoprotein receptor-related protein 4 (LRP4), identified as the agrin receptor, has been recognized as a third autoimmune target in a significant portion of the double sero-negative (dSN) myasthenic individuals, with variable frequency depending on different methods and origin countries of the tested population. There is also convincing experimental evidence that anti-LRP4 autoantibodies may cause MG

Associating mutations causing cystinuria with disease severity with the aim of providing precision medicine

Background Cystinuria is an inherited disease that results in the formation of cystine stones in the kidney, which can have serious health complications. Two genes (SLC7A9 and SLC3A1) that form an amino acid transporter are known to be responsible for the disease. Variants that cause the disease disrupt amino acid transport across the cell membrane, leading to the build-up of relatively insoluble cystine, resulting in formation of stones. Assessing the effects of each mutation is critical in order to provide tailored treatment options for patients. We used various computational methods to assess the effects of cystinuria associated mutations, utilising information on protein function, evolutionary conservation and natural population variation of the two genes. We also analysed the ability of some methods to predict the phenotypes of individuals with cystinuria, based on their genotypes, and compared this to clinical data. Results Using a literature search, we collated a set of 94 SLC3A1 and 58 SLC7A9 point mutations known to be associated with cystinuria. There are differences in sequence location, evolutionary conservation, allele frequency, and predicted effect on protein function between these mutations and other genetic variants of the same genes that occur in a large population. Structural analysis considered how these mutations might lead to cystinuria. For SLC7A9, many mutations swap hydrophobic amino acids for charged amino acids or vice versa, while others affect known functional sites. For SLC3A1, functional information is currently insufficient to make confident predictions but mutations often result in the loss of hydrogen bonds and largely appear to affect protein stability. Finally, we showed that computational predictions of mutation severity were significantly correlated with the disease phenotypes of patients from a clinical study, despite different methods disagreeing for some of their predictions. Conclusions The results of this study are promising and highlight the areas of research which must now be pursued to better understand how mutations in SLC3A1 and SLC7A9 cause cystinuria. The application of our approach to a larger data set is essential, but we have shown that computational methods could play an important role in designing more effective personalised treatment options for patients with cystinuria

Associating mutations causing cystinuria with disease severity with the aim of providing precision medicine

Background Cystinuria is an inherited disease that results in the formation of cystine stones in the kidney, which can have serious health complications. Two genes (SLC7A9 and SLC3A1) that form an amino acid transporter are known to be responsible for the disease. Variants that cause the disease disrupt amino acid transport across the cell membrane, leading to the build-up of relatively insoluble cystine, resulting in formation of stones. Assessing the effects of each mutation is critical in order to provide tailored treatment options for patients. We used various computational methods to assess the effects of cystinuria associated mutations, utilising information on protein function, evolutionary conservation and natural population variation of the two genes. We also analysed the ability of some methods to predict the phenotypes of individuals with cystinuria, based on their genotypes, and compared this to clinical data. Results Using a literature search, we collated a set of 94 SLC3A1 and 58 SLC7A9 point mutations known to be associated with cystinuria. There are differences in sequence location, evolutionary conservation, allele frequency, and predicted effect on protein function between these mutations and other genetic variants of the same genes that occur in a large population. Structural analysis considered how these mutations might lead to cystinuria. For SLC7A9, many mutations swap hydrophobic amino acids for charged amino acids or vice versa, while others affect known functional sites. For SLC3A1, functional information is currently insufficient to make confident predictions but mutations often result in the loss of hydrogen bonds and largely appear to affect protein stability. Finally, we showed that computational predictions of mutation severity were significantly correlated with the disease phenotypes of patients from a clinical study, despite different methods disagreeing for some of their predictions. Conclusions The results of this study are promising and highlight the areas of research which must now be pursued to better understand how mutations in SLC3A1 and SLC7A9 cause cystinuria. The application of our approach to a larger data set is essential, but we have shown that computational methods could play an important role in designing more effective personalised treatment options for patients with cystinuria

CIBERER : Spanish national network for research on rare diseases: A highly productive collaborative initiative

Altres ajuts: Instituto de Salud Carlos III (ISCIII); Ministerio de Ciencia e Innovación.CIBER (Center for Biomedical Network Research; Centro de Investigación Biomédica En Red) is a public national consortium created in 2006 under the umbrella of the Spanish National Institute of Health Carlos III (ISCIII). This innovative research structure comprises 11 different specific areas dedicated to the main public health priorities in the National Health System. CIBERER, the thematic area of CIBER focused on rare diseases (RDs) currently consists of 75 research groups belonging to universities, research centers, and hospitals of the entire country. CIBERER's mission is to be a center prioritizing and favoring collaboration and cooperation between biomedical and clinical research groups, with special emphasis on the aspects of genetic, molecular, biochemical, and cellular research of RDs. This research is the basis for providing new tools for the diagnosis and therapy of low-prevalence diseases, in line with the International Rare Diseases Research Consortium (IRDiRC) objectives, thus favoring translational research between the scientific environment of the laboratory and the clinical setting of health centers. In this article, we intend to review CIBERER's 15-year journey and summarize the main results obtained in terms of internationalization, scientific production, contributions toward the discovery of new therapies and novel genes associated to diseases, cooperation with patients' associations and many other topics related to RD research

Open source in field geology: a QGIS-mate Android compass

BeeDip is a digital geological compass developed by students and researchers of Urbino University under open source license (GPL) dedicated to the open source QGIS software. The app can be installed in any Android smartphone. Previous apps are able to measure different kind of geological data, but all of them keep a “closed” code (Weng and Grigsby, 2012; Lee et al., 2013). The connection with QGIS is guaranteed by an homonymous plug-in (Phyton developed) which enable the export/import of data and maps from and to the GIS project. The used file format is Geopackage (OGC, 2017), under open source MIT license. This allows to import in the app any georeferenced and tiled geotiff map file, enabling the off-line and custom map visualisation with appropriate symbols and labels. Also the data transfer from the app to QGIS has been facilitated. The digital compass can record surface and line measurements, adding other complementary data/metadata and organising them by projects. Tests and comparisons have been performed to assess the validity of this system in the lab and in the field concluding that the data acquisition is fast and simple, but devices can be calibrated and the accuracy depends mainly on built-in sensors (Novalowa and Pavlis, 2017). The app and the plug-in are open to any contribution of developers and users

A smartphone application for a citizen science project on seafood sustainable consumption

New Information and Communication Technologies (ICT) are playing a key role in Citizen Science outbreak, allowing a wider public participation. The increasingly availability of smartphone can be exploited as a tool for easy and quickly data collection. The idea of the realisation of a smartphone App arises inside a Citizen Science project on sustainable consumption of seafood, “Il pesce giusto”. In fact, the overexploitation, the employment of destructive fishing practices and unsustainable techniques, as well as the widespread illegal fishing, have led to a loss of marine biodiversity and a food resources decline. A monitoring of marine resources consumption is now necessary. Our aim has been to design an App that allows to monitor the sustainability of consumers’ purchases through different criteria: size, origin, production and seasonality of the fish species. This tool can be practically utilised by citizen and can provide us information of the sustainability of marine resources sold in the markets

Distribution of mosquito species in areas with high and low incidence of classic Kaposi's sarcoma and seroprevalence for HHV-8

The 'promoter-arthropod' hypothesis, which postulates that exposure to the bites of certain species of haematophagous arthropods is an environmental risk cofactor linked to human herpes virus 8 (HHV-8) and Kaposi's sarcoma, was investigated in the Po River valley, northern Italy. The presence and density of adult female mosquitoes (Diptera: Culicidae) was determined by CDC light trap catches in two adjacent districts, at variance with respect to Kaposi's sarcoma incidence and HHV-8 seroprevalence. A total of 3910 specimens belonging to I I species was collected in 34 rural sites (six municipalities) representative of the two districts. Five of these species are considered to be possible 'promoters' because of the irritation their bites cause humans: Aedes vexans (Meigen) and Ae. caspius (Pallas) (87% of sampled promoters), Culex modestus Ficalbi, Culiseta annulata (Schrank) and Coquillettidia richiardii (Ficalbi). Six are probable 'non-promoters': Cx. pipiens s.l., Cx. martinii Medschid, Anopheles claviger (Meigen), An. maculipennis s.l., An. plumbeus Stephens and Uranotaenia unguiculata Edwards. The density of promoters by site was correlated with the incidence rates of Kaposi's sarcoma at the district level (Pearson's r = 0.33, P = 0.06) and at the municipal level (r = 0.50, P < 0.01). Similar correlations emerged for non-promoters (r = 0.48, P < 0.01 and r = 0.42, P = 0.01, respectively). The density of promoters was higher than that of non-promoters in sites with livestock (odds ratio, OR = 2.8, 95% CI 2.2-3.6) and in municipalities with Kaposi's sarcoma cases (OR = 2.5, 95% CI 1.7-3.5). The study provides additional evidence of the association between the density of some mosquito species and Kaposi's sarcoma