Visual Personal Familiarity in Amnestic Mild Cognitive Impairment

BACKGROUND: Patients with amnestic mild cognitive impairment are at high risk for developing Alzheimer's disease. Besides episodic memory dysfunction they show deficits in accessing contextual knowledge that further specifies a general concept or helps to identify an object or a person. METHODOLOGY/PRINCIPAL FINDINGS: Using functional magnetic resonance imaging, we investigated the neural networks associated with the perception of personal familiar faces and places in patients with amnestic mild cognitive impairment and healthy control subjects. Irrespective of stimulus type, patients compared to control subjects showed lower activity in right prefrontal brain regions when perceiving personally familiar versus unfamiliar faces and places. Both groups did not show different neural activity when perceiving faces or places irrespective of familiarity. CONCLUSIONS/SIGNIFICANCE: Our data highlight changes in a frontal cortical network associated with knowledge-based personal familiarity among patients with amnestic mild cognitive impairment. These changes could contribute to deficits in social cognition and may reduce the patients' ability to transition from basic to complex situations and tasks

Species identification through mitochondrial rRNA genetic analysis

Inter-species and intraspecific variations in mitochondrial DNA (mtDNA) were observed in a bioinformatics analysis of the mitochondrial genomic sequences of 11 animal species. Some highly conserved regions were identified in the mitochondrial 12S and 16S ribosomal RNA (rRNA) genes of these species. To test whether these sequences are universally conserved, primers were designed to target the conserved regions of these two genes and were used to amplify DNA from 21 animal tissues, including two of unknown origin. By sequencing these PCR amplicons and aligning the sequences to a database of non-redundant nucleotide sequences, it was confirmed that these amplicons aligned specifically to mtDNA sequences from the expected species of origin. This molecular technique, when combined with bioinformatics, provides a reliable method for the taxonomic classification of animal tissues