Tularemia in a common marmoset (Callithrix jacchus) diagnosed by 16S rRNA sequencing

We report a case of tularemia in a common marmoset (Callithrix jacchus) diagnosed by determination of the isolate's 16S ribosomal RNA (rRNA) gene sequence. Pathological examination of the animal revealed a multifocal acute necrotizing hepatitis, interstitial nephritis, splenitis, and lymphangitis of the mandibular, retropharyngeal, and cervical and mesenteric lymph nodes. Moreover, multiple foci of acute necrosis were found in the epithelium of the jejunum and the interstitium of the lung. Bacteriological investigations revealed a septicemia. The isolated infectious agent was uncommon, not routinely diagnosed in our laboratory and therefore difficult to identify by conventional tools in a reasonable time and effort. thus, we decided to perform a genetic analysis based on the 16S rRNA gene sequence. Thereby, an infection with Francisella tularensis, the causative agent of tularemia, was unambiguously diagnosed. This shows the great advantage 16S rRNA gene sequencing has as a general identification approach for unusual or rare isolates.

Disease-modifying genes and monogenic disorders: experience in cystic fibrosis

The mechanisms responsible for the determination of phenotypes are still not well understood; however, it has become apparent that modifier genes must play a considerable role in the phenotypic heterogeneity of Mendelian disorders. Significant advances in genetic technologies and molecular medicine allow huge amounts of information to be generated from individual samples within a reasonable time frame. This review focuses on the role of modifier genes using the example of cystic fibrosis, the most common lethal autosomal recessive disorder in the white population, and discusses the advantages and limitations of candidate gene approaches versus genome-wide association studies. Moreover, the implications of modifier gene research for other monogenic disorders, as well as its significance for diagnostic, prognostic, and therapeutic approaches are summarized. Increasing insight into modifying mechanisms opens up new perspectives, dispelling the idea of genetic disorders being caused by one single gene.

Day-to-night time differences in the relationship between cardiorespiratory coordination and heart rate variability

Heart rate variability (HRV) and cardiorespiratory coordination, i.e. the temporal interplay between oscillations of heartbeat and respiration, reflect information related to the cardiovascular and autonomic nervous system. The purpose of this study was to investigate the relationship between spectral measures of HRV and measures of cardiorespiratory coordination. In 127 subjects from a normal population a 24 h Holter ECG was recorded. Average heart rate (HR) and the following HRV parameters were calculated: very low (VLF), low (LF) and high frequency (HF) oscillations and LF/HF. Cardiorespiratory coordination was quantified using average respiratory rate (RespR), the ratio of heart rate and respiratory rate (HRR), the phase coordination ratio (PCR) and the extent of cardiorespiratory coordination (PP). Pearson's correlation coefficient r was used to quantify the relationship between each pair of the variables across all subjects. HR and HRR correlated strongest during daytime (r = 0.89). LF/HF and PP showed a negative correlation to a reasonable degree (r = -0.69). During nighttime sleep these correlations decreased whereas the correlation between HRR and RespR (r = -0.47) as well as between HRR and PCR (r = 0.73) increased substantially. In conclusion, HRR and PCR deliver considerably different information compared to HRV measures whereas PP is partially linked reciprocally to LF/HF.

A study of the time complexity of an Elitist Genetic Algorithm used for associating optical observations of MEO and GEO Space Debris

Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). In this context both the correct associations among the observations, and the orbits of the objects have to be determined. The complexity of the MTT problem is defined by its dimension S. Where S stands for the number of ’fences’ used in the problem, each fence consists of a set of observations that all originate from dierent targets. For a dimension of S ˃ the MTT problem becomes NP-hard. As of now no algorithm exists that can solve an NP-hard problem in an optimal manner within a reasonable (polynomial) computation time. However, there are algorithms that can approximate the solution with a realistic computational e ort. To this end an Elitist Genetic Algorithm is implemented to approximately solve the S ˃ MTT problem in an e cient manner. Its complexity is studied and it is found that an approximate solution can be obtained in a polynomial time. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the correlation and orbit determination problems simultaneously, and is able to e ciently process large data sets with minimal manual intervention.