qPCR-based mitochondrial DNA quantification: Influence of template DNA fragmentation on accuracy

Real-time PCR (qPCR) is the method of choice for quantification of mitochondrial DNA (mtDNA) by relative comparison of a nuclear to a mitochondrial locus. Quantitative abnormal mtDNA content is indicative of mitochondrial disorders and mostly confines in a tissue-specific manner. Thus handling of degradation-prone bioptic material is inevitable. We established a serial qPCR assay based on increasing amplicon size to measure degradation status of any DNA sample. Using this approach we can exclude erroneous mtDNA quantification due to degraded samples (e.g. long post-exicision time, autolytic processus, freeze-thaw cycles) and ensure abnormal DNA content measurements (e.g. depletion) in non-degraded patient material. By preparation of degraded DNA under controlled conditions using sonification and DNaseI digestion we show that erroneous quantification is due to the different preservation qualities of the nuclear and the mitochondrial genome. This disparate degradation of the two genomes results in over- or underestimation of mtDNA copy number in degraded samples. Moreover, as analysis of defined archival tissue would allow to precise the molecular pathomechanism of mitochondrial disorders presenting with abnormal mtDNA content, we compared fresh frozen (FF) with formalin-fixed paraffin-embedded (FFPE) skeletal muscle tissue of the same sample. By extrapolation of measured decay constants for nuclear DNA (λnDNA) and mtDNA (λmtDNA) we present an approach to possibly correct measurements in degraded samples in the future. To our knowledge this is the first time different degradation impact of the two genomes is demonstrated and which evaluates systematically the impact of DNA degradation on quantification of mtDNA copy number.

Intraoperative template-molded bone flap reconstruction for patient-specific cranioplasty

Cranioplasty is a common neurosurgical procedure. Free-hand molding of polymethyl methacrylate (PMMA) cement into complex three-dimensional shapes is often time-consuming and may result in disappointing cosmetic outcomes. Computer-assisted patient-specific implants address these disadvantages but are associated with long production times and high costs. In this study, we evaluated the clinical, radiological, and cosmetic outcomes of a time-saving and inexpensive intraoperative method to mold custom-made implants for immediate single-stage or delayed cranioplasty. Data were collected from patients in whom cranioplasty became necessary after removal of bone flaps affected by intracranial infection, tumor invasion, or trauma. A PMMA replica was cast between a negative form of the patient's own bone flap and the original bone flap with exactly the same shape, thickness, and dimensions. Clinical and radiological follow-up was performed 2 months post-surgery. Patient satisfaction (Odom criteria) and cosmesis (visual analogue scale for cosmesis) were evaluated 1 to 3 years after cranioplasty. Twenty-seven patients underwent intraoperative template-molded patient-specific cranioplasty with PMMA. The indications for cranioplasty included bone flap infection (56%, n = 15), calvarian tumor resection (37%, n = 10), and defect after trauma (7%, n = 2). The mean duration of the molding procedure was 19 ± 7 min. Excellent radiological implant alignment was achieved in 94% of the cases. All (n = 23) but one patient rated the cosmetic outcome (mean 1.4 years after cranioplasty) as excellent (70%, n = 16) or good (26%, n = 6). Intraoperative cast-molded reconstructive cranioplasty is a feasible, accurate, fast, and cost-efficient technique that results in excellent cosmetic outcomes, even with large and complex skull defects.

A 3-center comparison of 1-year mortality outcomes between transcatheter aortic valve implantation and surgical aortic valve replacement on the basis of propensity score matching among intermediate-risk surgical patients

This study sought to compare all-cause mortality in patients at intermediate surgical risk undergoing transcatheter aortic valve implantation (TAVI) or surgical aortic valve replacement (SAVR).

From EEG dependency multichannel matching pursuit to sparse topographic EEG decomposition

In this work, we present a multichannel EEG decomposition model based on an adaptive topographic time-frequency approximation technique. It is an extension of the Matching Pursuit algorithm and called dependency multichannel matching pursuit (DMMP). It takes the physiologically explainable and statistically observable topographic dependencies between the channels into account, namely the spatial smoothness of neighboring electrodes that is implied by the electric leadfield. DMMP decomposes a multichannel signal as a weighted sum of atoms from a given dictionary where the single channels are represented from exactly the same subset of a complete dictionary. The decomposition is illustrated on topographical EEG data during different physiological conditions using a complete Gabor dictionary. Further the extension of the single-channel time-frequency distribution to a multichannel time-frequency distribution is given. This can be used for the visualization of the decomposition structure of multichannel EEG. A clustering procedure applied to the topographies, the vectors of the corresponding contribution of an atom to the signal in each channel produced by DMMP, leads to an extremely sparse topographic decomposition of the EEG.