Europe was officially declared free from malaria in 1975; nevertheless, this disease remains a potential problem related to the presence of former vectors, belonging to the Anopheles maculipennis complex. Autochthonous-introduced malaria cases, recently reported in European countries, together with the predicted climatic and environmental changes, have increased the concern of health authorities over the possible resurgence of this disease in the Mediterranean Basin. In Italy, to study the distribution and bionomics of indigenous anopheline populations and to assess environmental parameters that could influence their dynamics, an entomological study was carried out in 2005-2006 in an at-risk study area. This model area is represented by the geographical region named the Maremma, a Tyrrhenian costal plain in Central Italy, where malaria was hyperendemic up to the 1950s. Fortnightly, entomological surveys (April-October) were carried out in four selected sites with different ecological features. Morphological and molecular characterization, blood meal identification, and parity rate assessment of the anophelines were performed. In total, 8274 mosquitoes were collected, 7691 of which were anophelines. Six Anopheles species were recorded, the most abundant of which were Anopheles labranchiae and An. maculipennis s.s. An. labranchiae is predominant in the coastal plain, where it is present in scattered foci. However, this species exhibits a wider than expected range: in fact it has been recorded, for the first time, inland where An. maculipennis s.s. is the most abundant species. Both species fed on a wide range of animal hosts, also showing a marked aggressiveness on humans, when available. Our findings demonstrated the high receptivity of the Maremma area, where the former malaria vector, An. labranchiae, occurs at different densities related to the kind of environment, climatic parameters, and anthropic activities.
In recent years, human DNA sampling and collection has accelerated without the development of enforceable rules protecting the human rights of donors. The need for regulation of biobanking is especially acute in Iceland, whose parliament has granted a for-profit corporation, deCODE Genetics, an exclusive license to create a centralized database of health records for studies on human genetic variation. Until recently, how deCODE Genetics would get genetic material for its genotypic-phenotypic database remained unclear. However, in May 2000, the Icelandic Parliament passed the Icelandic Biobanks Act, the world's earliest attempt to construct binding rules for the use of biobanks in scientific research. Unfortunately, Iceland has lost an opportunity for bringing clear and ethically sound standards to the use of human biological samples in deCODE's database and in other projects: the Biobanks Act has extended a notion of "presumed consent" from the use of medical records to the use of patients' biological samples; worse, the act has made it possible--perhaps likely--that a donor's wish to withdraw his/her sample will be ignored. Inadequacies in the Act's legislative process help account for these deficiencies in the protection of donor autonomy.
A major moral problem in relation to the deCODE genetics database project in Iceland is that the heavy emphasis placed on technical security of healthcare information has precluded discussion about the issue of consent for participation in the database. On the other hand, critics who have emphasised the issue of consent have most often demanded that informed consent for participation in research be obtained. While I think that individual consent is of major significance, I argue that this demand for informed consent is neither suitable nor desirable in this case. I distinguish between three aspects of the database and show that different types of consent are appropriate for each. In particular, I describe the idea of a written authorisation based on general information about the database as an alternative to informed consent and presumed consent in database research.
[COMPARATIVE ANALYSIS OF THE MLVA25- AND MLVA7-TYPING ACCORDING TO THEIR ABILITY TO ASCERTAIN FOCAL AFFILIATION OF YERSINIA PESTIS STRAINS BY THE EXAMPLE OF ISOLATES FROM THE CENTRAL-CAUCASIAN HIGHLAND NATURAL PLAGUE FOCUS].
Comparative analysis of the MLVA25- and MLVA7-typing ability to evaluate focal belonging of Y. pestis strains by the example of bv. medievalis isolates from the Central-Caucasian highland natural plague focus was carried out. The MLVA25-types of-82 isolates from this area were determined and included into the database containing information on 949 Y. pestis strains from other natural foci of Russia and other countries. Categorical-UPGMA dendrograms were created on the bases of the data concerning all 25 VNTR loci or only seven of them, which were recommended by the experts of the Russian Research Anti-Plague Institute "Microbe" for differentiation of the Y. pestis strains according to their affiliation to specific foci. The obtained data indicated greater possibility of diagnostic mistakes in the case of the MLVA7-typing and supported expediency of division of the Central-Caucasian highland natural plague focus into two sub-foci.
The histologic grade (HG) of breast cancer is an established prognostic factor. The grade is usually reported on a scale ranging from 1 to 3, where grade 3 tumours are the most aggressive. However, grade 2 is associated with an intermediate risk of recurrence, and carries limited information for clinical decision-making. Patients classified as grade 2 are at risk of both under- and over-treatment.
RNA-sequencing analysis was conducted in a cohort of 275 women diagnosed with invasive breast cancer. Multivariate prediction models were developed to classify tumours into high and low transcriptomic grade (TG) based on gene- and isoform-level expression data from RNA-sequencing. HG2 tumours were reclassified according to the prediction model and a recurrence-free survival analysis was performed by the multivariate Cox proportional hazards regression model to assess to what extent the TG model could be used to stratify patients. The prediction model was validated in N=487 breast cancer cases from the The Cancer Genome Atlas (TCGA) data set. Differentially expressed genes and isoforms associated with HGs were analysed using linear models.
The classification of grade 1 and grade 3 tumours based on RNA-sequencing data achieved high accuracy (area under the receiver operating characteristic curve = 0.97). The association between recurrence-free survival rate and HGs was confirmed in the study population (hazard ratio of grade 3 versus 1 was 2.62 with 95 % confidence interval = 1.04-6.61). The TG model enabled us to reclassify grade 2 tumours as high TG and low TG gene or isoform grade. The risk of recurrence in the high TG group of grade 2 tumours was higher than in low TG group (hazard ratio = 2.43, 95 % confidence interval = 1.13-5.20). We found 8200 genes and 13,809 isoforms that were differentially expressed between HG1 and HG3 breast cancer tumours.
Gene- and isoform-level expression data from RNA-sequencing could be utilised to differentiate HG1 and HG3 tumours with high accuracy. We identified a large number of novel genes and isoforms associated with HG. Grade 2 tumours could be reclassified as high and low TG, which has the potential to reduce over- and under-treatment if implemented clinically.
Cites: Bioinformatics. 2015 Jan 15;31(2):166-925260700