Use of fuzzy edge single-photon emission computed tomography analysis in definite Alzheimer's disease - a retrospective study

<p>Abstract</p> <p>Background</p> <p>Definite Alzheimer's disease (AD) requires neuropathological confirmation. Single-photon emission computed tomography (SPECT) may enhance diagnostic accuracy, but due to restricted sensitivity and specificity, the role of SPECT is largely limited with regard to this purpose.</p> <p>Methods</p> <p>We propose a new method of SPECT data analysis. The method is based on a combination of parietal lobe selection (as regions-of-interest (ROI)), 3D fuzzy edge detection, and 3D watershed transformation. We applied the algorithm to three-dimensional SPECT images of human brains and compared the number of watershed regions inside the ROI between AD patients and controls. The Student's two-sample t-test was used for testing domain number equity in both groups.</p> <p>Results</p> <p>AD patients had a significantly reduced number of watershed regions compared to controls (<it>p </it>< 0.01). A sensitivity of 94.1% and specificity of 80% was obtained with a threshold value of 57.11 for the watershed domain number. The narrowing of the SPECT analysis to parietal regions leads to a substantial increase in both sensitivity and specificity.</p> <p>Conclusions</p> <p>Our non-invasive, relatively low-cost, and easy method can contribute to a more precise diagnosis of AD.</p

Satellite DNA in Paphiopedilum subgenus Parvisepalum as revealed by high-throughput sequencing and fluorescent in situ hybridization

Background: Satellite DNA is a rapidly diverging, largely repetitive DNA component of many eukaryotic genomes. Here we analyse the evolutionary dynamics of a satellite DNA repeat in the genomes of a group of Asian subtropical lady slipper orchids (Paphiopedilum subgenus Parvisepalum and representative species in the other subgenera/sections across the genus). A new satellite repeat in Paphiopedilum subgenus Parvisepalum, SatA, was identified and characterized using the RepeatExplorer pipeline in HiSeq Illumina reads from P. armeniacum (2n = 26). Reconstructed monomers were used to design a satellite-specific fluorescent in situ hybridization (FISH) probe. The data were also analysed within a phylogenetic framework built using the internal transcribed spacer (ITS) sequences of 45S nuclear ribosomal DNA. Results: SatA comprises c. 14.5% of the P. armeniacum genome and is specific to subgenus Parvisepalum. It is composed of four primary monomers that range from 230 to 359 bp and contains multiple inverted repeat regions with hairpin loop motifs. A new karyotype of P. vietnamense (2n = 28) is presented and shows that the chromosome number in subgenus Parvisepalum is not conserved at 2n = 26, as previously reported. The physical locations of SatA sequences were visualised on the chromosomes of all seven Paphiopedilum species of subgenus Parvisepalum (2n = 26–28), together with the 5S and 45S rDNA loci using FISH. The SatA repeats were predominantly localisedin the centromeric, peri-centromeric and sub-telocentric chromosome regions, but the exact distribution pattern was species-specific. Conclusions: We conclude that the newly discovered, highly abundant and rapidly evolving satellite sequence SatA is specific to Paphiopedilum subgenus Parvisepalum. SatA and rDNA chromosomal distributions are characteristic of species, and comparisons between species reveal that the distribution patterns generate a strong phylogenetic signal. We also conclude that the ancestral chromosome number of subgenus Parvisepalum and indeed of all Paphiopedilum could be either 2n = 26 or 28, if P. vietnamense is sister to all species in the subgenus as suggested by the ITS data

Reliability of Transcriptional Cycles and the Yeast Cell-Cycle Oscillator

A recently published transcriptional oscillator associated with the yeast cell cycle provides clues and raises questions about the mechanisms underlying autonomous cyclic processes in cells. Unlike other biological and synthetic oscillatory networks in the literature, this one does not seem to rely on a constitutive signal or positive auto-regulation, but rather to operate through stable transmission of a pulse on a slow positive feedback loop that determines its period. We construct a continuous-time Boolean model of this network, which permits the modeling of noise through small fluctuations in the timing of events, and show that it can sustain stable oscillations. Analysis of simpler network models shows how a few building blocks can be arranged to provide stability against fluctuations. Our findings suggest that the transcriptional oscillator in yeast belongs to a new class of biological oscillators

Possible Associations of NTRK2 Polymorphisms with Antidepressant Treatment Outcome: Findings from an Extended Tag SNP Approach

Background: Data from clinical studies and results from animal models suggest an involvement of the neurotrophin system in the pathology of depression and antidepressant treatment response. Genetic variations within the genes coding for the brain-derived neurotrophic factor (BDNF) and its key receptor Trkb (NTRK2) may therefore influence the response to antidepressant treatment. Methods: We performed a single and multi-marker association study with antidepressant treatment outcome in 398 depressed Caucasian inpatients participating in the Munich Antidepressant Response Signature (MARS) project. Two Caucasian replication samples (N = 249 and N = 247) were investigated, resulting in a total number of 894 patients. 18 tagging SNPs in the BDNF gene region and 64 tagging SNPs in the NTRK2 gene region were genotyped in the discovery sample; 16 nominally associated SNPs were tested in two replication samples. Results: In the discovery analysis, 7 BDNF SNPs and 9 NTRK2 SNPs were nominally associated with treatment response. Three NTRK2 SNPs (rs10868223, rs1659412 and rs11140778) also showed associations in at least one replication sample and in the combined sample with the same direction of effects ($P_{corr}$ = .018, $P_{corr}$ = .015 and $P_{corr}$ = .004, respectively). We observed an across-gene BDNF-NTRK2 SNP interaction for rs4923468 and rs1387926. No robust interaction of associated SNPs was found in an analysis of BDNF serum protein levels as a predictor for treatment outcome in a subset of 93 patients. Conclusions/Limitations: Although not all associations in the discovery analysis could be unambiguously replicated, the findings of the present study identified single nucleotide variations in the BDNF and NTRK2 genes that might be involved in antidepressant treatment outcome and that have not been previously reported in this context. These new variants need further validation in future association studies