Dichlorvos exposure impedes extraction and amplification of DNA from insects in museum collections

Background: The insecticides dichlorvos, paradichlorobenzene and naphthalene have been commonly used to eradicate pest insects from natural history collections. However, it is not known how these chemicals affect the DNA of the specimens in the collections. We thus tested the effect of dichlorvos, paradichlorobenzene and naphthalene on DNA of insects (Musca domestica) by extracting and amplifying DNA from specimens exposed to insecticides in two different concentrations over increasing time intervals. Results: The results clearly show that dichlorvos impedes both extraction and amplification of mitochondrial and nuclear DNA after relatively short time, whereas paradichlorobenzene and naphthalene do not. Conclusion: Collections treated with paradichlorobenzene and naphthalene, are better preserved concerning DNA, than those treated with dichlorvos. Non toxic pest control methods should, however, be preferred due to physical damage of specimens and putative health risks by chemicals.

Identification of cause of impairment in spiral drawings, using non-stationary feature extraction approach

Parkinson’s disease is a clinical syndrome manifesting with slowness and instability. As it is a progressive disease with varying symptoms, repeated assessments are necessary to determine the outcome of treatment changes in the patient. In the recent past, a computer-based method was developed to rate impairment in spiral drawings. The downside of this method is that it cannot separate the bradykinetic and dyskinetic spiral drawings. This work intends to construct the computer method which can overcome this weakness by using the Hilbert-Huang Transform (HHT) of tangential velocity. The work is done under supervised learning, so a target class is used which is acquired from a neurologist using a web interface. After reducing the dimension of HHT features by using PCA, classification is performed. C4.5 classifier is used to perform the classification. Results of the classification are close to random guessing which shows that the computer method is unsuccessful in assessing the cause of drawing impairment in spirals when evaluated against human ratings. One promising reason is that there is no difference between the two classes of spiral drawings. Displaying patients self ratings along with the spirals in the web application is another possible reason for this, as the neurologist may have relied too much on this in his own ratings.