Medizin
Refine
Document Type
- Article (2)
Language
- English (2)
Has Fulltext
- yes (2)
Is part of the Bibliography
- no (2)
Keywords
- Phylogenetic analysis (2) (remove)
Institute
The bluebottle blow fly Calliphora vicina is a common species distributed throughout Europe that can play an important role as forensic evidence in crime investigations. Developmental rates of C. vicina from distinct populations from Germany and England were compared under different temperature regimes to explore the use of growth data from different geographical regions for local case work. Wing morphometrics and molecular analysis between these populations were also studied as indicators for biological differences. One colony each of German and English C. vicina were cultured at the Institute of Legal Medicine in Frankfurt, Germany. Three different temperature regimes were applied, two constant (16°C & 25°C) and one variable (17–26°C, room temperature = RT). At seven time points (600, 850, 1200, 1450, 1800, 2050, and 2400 accumulated degree hours), larval lengths were measured; additionally, the durations of the post feeding stage and intrapuparial metamorphosis were recorded. For the morphometric and molecular study, 184 females and 133 males from each C. vicina population (Germany n = 3, England n = 4) were sampled. Right wings were measured based on 19 landmarks and analyzed using canonical variates analysis and discriminant function analysis. DNA was isolated from three legs per specimen (n = 61) using 5% chelex. A 784 bp long fragment of the mitochondrial cytochrome b gene was sequenced; sequences were aligned and phylogenetically analyzed. Similar larval growth rates of C. vicina were found from different geographic populations at different temperatures during the major part of development. Nevertheless, because minor differences were found a wider range of temperatures and sampling more time points should be analyzed to obtain more information relevant for forensic case work. Wing shape variation showed a difference between the German and English populations (P<0.0001). However, separation between the seven German and English populations at the smaller geographic scale remained ambiguous. Molecular phylogenetic analysis by maximum likelihood method could not unambiguously separate the different geographic populations at a national (Germany vs England) or local level.
Replacement therapy in severe hemophilia A leads to factor VIII (FVIII) inhibitors in 30% of patients. Factor VIII gene (F8) mutation type, a family history of inhibitors, ethnicity and intensity of treatment are established risk factors, and were included in two published prediction tools based on regression models. Recently investigated immune regulatory genes could also play a part in immunogenicity. Our objective is to identify bio-clinical and genetic markers for FVIII inhibitor development, taking into account potential genetic high order interactions. The study population consisted of 593 and 79 patients with hemophilia A from centers in Bonn and Frankfurt respectively. Data was collected in the European ABIRISK tranSMART database. A subset of 125 severely affected patients from Bonn with reliable information on first treatment was selected as eligible for risk stratification using a hybrid tree-based regression model (GPLTR). In the eligible subset, 58 (46%) patients developed FVIII inhibitors. Among them, 49 (84%) were “high risk” F8 mutation type. 19 (33%) had a family history of inhibitors. The GPLTR model, taking into account F8 mutation risk, family history of inhibitors and product type, distinguishes two groups of patients: a high-risk group for immunogenicity, including patients with positive HLA-DRB1*15 and genotype G/A and A/A for IL-10 rs1800896, and a low-risk group of patients with negative HLA-DRB1*15 / HLA-DQB1*02 and T/T or G/T for CD86 rs2681401. We show associations between genetic factors and the occurrence of FVIII inhibitor development in severe hemophilia A patients taking into account for high-order interactions using a generalized partially linear tree-based approach.