Dog filariosis in the Lazio region (Central Italy): first report on the presence of Dirofilaria repens

BACKGROUND: Epidemiological investigations were carried out in the Lazio Region to assess the status of canine filariosis and to evaluate the actual risk for veterinary and medical public health. METHODS: Since August 2001 to June 2003, a total of 972 canine blood samples, collected in public kennels and from private owners animals of the 5 Provinces of the Region, were tested. The presence of filarial parasites was evaluated by microscopy and bio-molecular techniques; the species identification was performed by means of the same diagnostic tools. RESULTS: A total of 17/972 (1.75%; 95%CI 1.06%–2.85%) blood samples were parasitized by D. repens,13 out them drawn by dogs resident in the Province of Roma, and 4 in the other provinces. Multivariate analysis was performed in order to evaluate the association between filariosis and risk factors. The origin from coastal territories seems to be a significant risk factor to acquire the infection. CONCLUSION: This is the first report of canine filariosis in the Lazio Region, where D. repens was before reported only in foxes. The risk of human zoonotic infection is stressed, and the absence of other filarial species is discusse

Crowdsourced mapping of unexplored target space of kinase inhibitors

Despite decades of intensive search for compounds that modulate the activity of particular protein targets, a large proportion of the human kinome remains as yet undrugged. Effective approaches are therefore required to map the massive space of unexplored compound-kinase interactions for novel and potent activities. Here, we carry out a crowdsourced benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data. We find the top-performing predictions are based on various models, including kernel learning, gradient boosting and deep learning, and their ensemble leads to a predictive accuracy exceeding that of single-dose kinase activity assays. We design experiments based on the model predictions and identify unexpected activities even for under-studied kinases, thereby accelerating experimental mapping efforts. The open-source prediction algorithms together with the bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking prediction algorithms and for extending the druggable kinome. The IDG-DREAM Challenge carried out crowdsourced benchmarking of predictive algorithms for kinase inhibitor activities on unpublished data. This study provides a resource to compare emerging algorithms and prioritize new kinase activities to accelerate drug discovery and repurposing efforts

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.Peer reviewe

Spiritual belief, social support, physical functioning and depression among older people in Bulgaria and Romania

Objectives: An exploratory investigation is reported into the role of spirituality and religious practice in protecting against depression among older people living in rural villages in Bulgaria and Romania, two neighbouring countries with similar cultural, political and religious histories, but with differing levels of current religiosity. Methods: In both countries, interviews were conducted with samples of 160 persons of 60 years and over in villages of similar socio-economic status. The Hospital Anxiety and Depression-D scale and the Royal Free Interview for Religious and Spiritual Beliefs were used to assess depression and spiritual belief and practice respectively. In addition social support, physical functioning and the presence of chronic diseases were assessed. One year later, follow-up interviews were conducted with 58 of the original sample in Bulgaria, in which additional measures of depression and of spiritual belief and practice were also included. Results: The study demonstrates, as expected, significantly lower levels of spiritual belief in the Bulgarian sample (Bulgarian mean 29.7 (SD = 19.1), Romanian mean 47.6 (SD = 11.2), t = 10.2, p < 0.001), as well as significantly higher levels of depression (Bulgarian mean 12.0 (SD = 4.9), Romanian mean 7.3 (SD = 4.1), t = 9.3, p < 0.001), the latter attributable in large part to higher morbidity and disability rates, but less evidently to differences in strength of belief. However, analyses from both the cross-sectional study and the one-year follow-up of the Bulgarian sample do suggest that spiritual belief and practice may both influence and reflect physical and mental illness. Conclusions: Much of Eastern Europe displays high rates of depression among its older population and provides opportunities for investigation of the role of religious belief and practice in preventing and coping with depression. Further research is encouraged in populations of diverse religiosity