Brain trauma and autophagy: What flies and mice can teach us about conserved responses

Drosophila models have been successfully used to identify many genetic components that affect neurodegenerative disorders. Recently, there has been a growing interest in identifying innate and environmental factors that influence the individual outcomes following traumatic brain injury (TBI). This includes both severe TBI and more subtle, mild TBI (mTBI), which is common in people playing contact sports. Autophagy, as a clearance pathway, exerts protective effects in multiple neurological disease models. In a recent publication, we highlighted the development of a novel repetitive mTBI system using Drosophila, which recapitulates several phenotypes associated with trauma in mammalian models. In particular, flies subjected to mTBI exhibit an acute impairment of the macroautophagy/autophagy pathway that is restored 1 wk following traumatic injury exposure. These phenotypes closely resemble temporary autophagy defects observed in a mouse TBI model. Through these studies, we also identified methods to directly assess autophagic responses in the fly nervous system and laid the groundwork for future studies designed to identify genetic, epigenetic and environmental factors that have an impact on TBI outcomes.     

Biodesulfurization of dibenzothiophene by Gordonia sp. AHV-01 and optimization by using of response surface design procedure

A novel desulfurizing bacterium has been isolated from oil-contaminated soils in Khuzestan. The ability for dibenzothiophene desulfurization and its biochemical pathway were investigated. The bacterium was identified as Gordonia sp. AHV-01 (Genbank Accession No HQ607780) by 16S rRNA gene sequencing. HPLC results and Gibb's assay were shown that dibenzothiophene desulfurized via 4S-pathway Maximum growth (0.426 g dry cells/L) and produced 2-hydroxybiphenyl (63.1 microM) were observed at 120 h of cultivation. By using of response surface design procedure the optimization of pH, temperature and rotary shaker round on the desulfurization reaction of isolate AHV-01 were performed. The optimum conditions were determined at pH of 7.0, temperature of 30 degrees C and rotary shaker round of 180 rpm. At these conditions, the dibenzothiophene desulfurization activity was increased and maximum 2-hydroxybiphenyl production was detected 70.29 microM at 96 h. According to these results, Isolate AHV-01 was capable to desulfurize dibenzothiophene via 4S-pathway and likely it can be useful to reduce organic sulfur contents of crude oil.     

Growth, seed development and genetic analysis in wild type and Def mutant of Pisum sativum L

Background

Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI), but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests) were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression) in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test.

Results

Press' Q test showed that all classifiers performed better than chance alone (p < 0.05). Support Vector Machines showed the larger overall classification accuracy (Median (Me) = 0.76) an area under the ROC (Me = 0.90). However this method showed high specificity (Me = 1.0) but low sensitivity (Me = 0.3). Random Forest ranked second in overall accuracy (Me = 0.73) with high area under the ROC (Me = 0.73) specificity (Me = 0.73) and sensitivity (Me = 0.64). Linear Discriminant Analysis also showed acceptable overall accuracy (Me = 0.66), with acceptable area under the ROC (Me = 0.72) specificity (Me = 0.66) and sensitivity (Me = 0.64). The remaining classifiers showed overall classification accuracy above a median value of 0.63, but for most sensitivity was around or even lower than a median value of 0.5.

Conclusions

When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing.     

The expression of Terpenoid Indole Alkaloid (TIAs) pathway genes in Catharanthus roseus in response to salicylic acid treatment

Molecular Biology Reports - Vinblastine and vincristine are two important anti-cancer drugs that are synthesized by the Terpenoid Indole Alkaloids (TIAs) pathway in periwinkle (Catharanthus...     

Characterization and structural analysis of wild type and a non-abscission mutant at the development funiculus (Def) locus in Pisum sativum L

Background  

In pea seeds (Pisum sativum L.), the Def locus defines an abscission event where the seed separates from the funicle through the intervening hilum region at maturity. A spontaneous mutation at this locus results in the seed failing to abscise from the funicle as occurs in wild type peas. In this work, structural differences between wild type peas that developed a distinct abscission zone (AZ) between the funicle and the seed coat and non-abscission def mutant were characterized.     

Biodesulfurization of dibenzothiophene by <Emphasis Type="Italic">Gordonia</Emphasis> sp. AHV-01 and optimization by using of response surface design procedure

A novel desulfurizing bacterium has been isolated from oil-contaminated soils in Khuzestan. The ability for dibenzothiophene desulfurization and its biochemical pathway were investigated. The bacterium was identified as Gordonia sp. AHV-01 (Genbank Accession no. HQ607780) by 16S rRNA gene sequencing. HPLC results and Gibb’s assay were shown that dibenzothiophene desulfurized via 4S-pathway. Maximum growth (0.426 g dry cells/L) and produced 2-hydroxybiphenyl (63.1 μM) were observed at 120 h of cultivation. By using of response surface design procedure the optimization of pH, temperature and rotary shaker round on the desulfurization reaction of isolate AHV-01 were performed. The optimum conditions were determined at pH of 7.0, temperature of 30°C and rotary shaker round of 180 rpm. At these conditions, the dibenzothiophene desulfurization activity was increased and maximum 2-hydroxybiphenyl production was detected 70.29 μM at 96 h. According to these results, isolate AHV-01 was capable to desulfurize dibenzothiophene via 4S-pathway and likely it can be useful to reduce organic sulfur contents of crude oil.