Aeromonas and Pseudomonas: antibiotic and heavy metal resistance species from Iskenderun Bay, Turkey (northeast Mediterranean Sea)

We studied the susceptibility patterns to 15 different antibiotics and six heavy metals in Aeromonas spp. and Pseudomonas spp. isolated from Iskenderun Bay, Turkey (northeast Mediterranean Sea). A high percentage of Aeromonas isolates showed resistance to cefazolin (66.6%) and trimethoprim–sulphamethoxazole (66.6%). Amongst the Pseudomonas isolates, there was a high incidence of resistance to nitrofurantoin (86.2%), cefazolin (84.8%) and cefuroxime (71.7%). Most isolates showed tolerance to different concentrations of heavy metals, and minimal inhibition concentrations ranged from 25 to >3,200 μg/ml. The Aeromonas spp. and Pseudomonas spp. showed high resistance to copper of 98.3% and 75.4%, respectively, and low resistance to lead of 1.7% and 7.2%, respectively. Our results show that antibiotic and heavy metal resistant Aeromonas spp. and Pseudomonas spp. were widespread in Iskenderun Bay in 2007 and 2008. The increasing presence of antibiotic and heavy metal resistant Aeromonas spp. and Pseudomonas spp. may become a potential human health hazard.     

Effect of diosmin on lipid peoxidation and organ damage against subacute deltamethrin exposure in rats

Environmental Science and Pollution Research - The aim of this study was to investigate the protective efficacy of diosmin against subacute deltamethrin exposure. For this purpose, 40 male Wistar...     

Prenatal prediction of childhood-onset spinal muscular atrophy (SMA) in Turkish families

Childhood-onset spinal muscular atrophy (SMA) is one of the most common neurodegenerative genetic disorders. SMN1 is the SMA-determining gene deleted or mutated in the majority of SMA cases. There is no effective cure or treatment for this disease yet. Thus, the availability of prenatal testing is important. Here we report prenatal prediction for 68 fetuses in 63 Turkish SMA families using direct deletion analysis of the SMN1 gene by restriction digestion. The genotype of the index case was known in 40 families (Group A) but unknown in the remaining 23 families (Group B). A total of ten fetuses were predicted to be affected. Eight of these fetuses were derived from Group A and two of these fetuses were from Group B families. Two fetuses from the same family in Group A had the SMNhyb1 gene in addition to homozygous deletion of the NAIP gene. One fetus from Group A was homozygously deleted for only exon 8 of the SMN2 gene, and further analysis showed the presence of both the SMN1 and SMNhyb1 genes but not the SMN2 gene. In addition, one carrier with a homozygous deletion of only exon 8 of the SMN1 gene was detected to have a SMNhyb2 gene, which was also found in the fetus. To our knowledge, these are the first prenatal cases with SMNhyb genes. Follow-up studies demonstrated that the prenatal predictions and the phenotype of the fetuses correlated well in 33 type I pregnancies demonstrating that a careful molecular analysis of the SMN genes is very useful in predicting the phenotype of the fetus in families at risk for SMA. Copyright © 2002 John Wiley & Sons, Ltd.     

Evaluation of effect of different membership functions on risk assessment

This study aims to define the relationship between risk degrees and risk indexes on different functional structures with the assumption that risk degrees may not always present a linear relationship with the risk indexes. In this way, risk indexes suitable for expert evaluation of working conditions and computed using three different membership functions are determined. Among the membership functions used, one is preferred as linear and the others are preferred as non-linear. Additionally, a new fuzzy risk assessment (RA) algorithm is developed using these three membership functions. With this new fuzzy RA algorithm, a more flexible and precise process becomes available, while information loss during the determination of the risk index of danger sources is prevented. As a result, non-linear increasing membership function is selected as most suitable for the expression of the relationship between risk degrees and risk indexes.