Demenzverdacht, aber normale neuropsychologische Screening-Untersuchung - wie weiter?

Die Demenz betrifft viele, belastet Angehörige und führt zu hohen Kosten, weshalb die Schweiz eine Sensibilisierungskampagne lancierte, um u.a. die Früherkennung der Demenz zu fördern. Dank der Früherkennung erleben Patienten und Angehörige Vorteile, wie weniger Notfallzuweisungen oder spätere Heimeintritte. Die Früherkennung ist aber schwierig, wenn Patienten zwar Gedächtnisprobleme beklagen, die Screening-Tests aber normal ausfallen. Möglicherweise helfen Geruchstests und weitere klinische Zeichen bei der Entscheidung, welche Patienten weiter abgeklärt werden. Die Zeit für funktionelle Bildgebungen und Biomarker ist noch nicht reif. Zentral bleibt bei kognitiven Beschwerden und normalem Screening das Gespräch mit Patient und Angehörigen, um nächste Schritte gemeinsam zu beschliessen. Der Hausarzt nimmt dabei eine zentrale, koordinierende und beratende Funktion ein, um Menschen mit Gedächtnisstörungen kompetent und effizient zu betreuen.

[Microbiological point of care tests]

It is well known that the early initiation of a specific antiinfective therapy is crucial to reduce the mortality in severe infection. Procedures culturing pathogens are the diagnostic gold standard in such diseases. However, these methods yield results earliest between 24 to 48 hours. Therefore, severe infections such as sepsis need to be treated with an empirical antimicrobial therapy, which is ineffective in an unknown fraction of these patients. Today's microbiological point of care tests are pathogen specific and therefore not appropriate for an infection with a variety of possible pathogens. Molecular nucleic acid diagnostics such as polymerase chain reaction (PCR) allow the identification of pathogens and resistances. These methods are used routinely to speed up the analysis of positive blood cultures. The newest PCR based system allows the identification of the 25 most frequent sepsis pathogens by PCR in parallel without previous culture in less than 6 hours. Thereby, these systems might shorten the time of possibly insufficient antiinfective therapy. However, these extensive tools are not suitable as point of care diagnostics. Miniaturization and automating of the nucleic acid based method is pending, as well as an increase of detectable pathogens and resistance genes by these methods. It is assumed that molecular PCR techniques will have an increasing impact on microbiological diagnostics in the future.

Streptococcus spp. and related bacteria: Their identification and their pathogenic potential for chronic mastitis - A molecular approach

Streptococcus spp. and related bacteria form a large group of organisms which are associated with bovine intramammary Infections (IMI). Some of them are the well-known mastitis pathogens Streptococcus uberis and Streptococcus agalactiae. In addition, there are a considerable number of these gram-positive, catalase-negative cocci (PNC) with unclear mastitic pathogenicity such as Aerococcus viridans which make the conventional diagnostics of PNC difficult. One diagnostic, API 20 Strep (API, Biomerieux) is recommended which, as a phenotypic assay, involves a series of miniaturized biochemical tests. Recently, preference is given to genotypic identification methods. In particular, sequencing of the 16S rRNA gene allows highly reproducible and accurate identification of bacteria and permits discovery of novel, clinically relevant bacteria. As a consequence, the aim of the present study was to compare identification of IMI-associated PNC by the API method as well as by sequencing of their 16S rRNA gene (16S). Furthermore, the correlation of these bacteria to bovine chronic mastitis and their phylogeny was investigated. 102 PNC isolated from single quarter milk samples were identified by API and 16S sequencing. Considering Streptococcus uberis, Streptococcus dysgalactiae subsp. dysgalactiae and Streptococcus agalactiae, both methods generated fully concordant results. In contrast, a very high disconcordance was observed for most of the other PNC, in particular Enterococcus spp., Aerococcus viridans and the viridans streptococci were shown as apathogenic. Lactococcus garvieae was found to be an opportunistic pathogen causing IMI during late lactation. In addition, PNC isolated from milk were frequently observed together with other bacteria, in particular with Staphylococcus spp. In these cases, the levels of somatic cell counts (SCC) were determined by the specific PNC present in the sample. Considering PNC phylogeny based on 16S sequencing, 3 major clusters were observed. They included all the common mastitis pathogens (cluster I), the Lactococcus spp., Enterococcus spp. and Aerococcus spp. (cluster II) and all the viridans streptococci (cluster III).

Time course based artifact identification for independent components of resting-state FMRI

In functional magnetic resonance imaging (fMRI) coherent oscillations of the blood oxygen level-dependent (BOLD) signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting-state networks (RSN). Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA) and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting-state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82, and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting-state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting-state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

Phenotypic and genotypic identification of streptococci and related bacteria isolated from bovine intramammary infections.

BACKGROUND Streptococcus spp. and other Gram-positive, catalase-negative cocci (PNC) form a large group of microorganisms which can be found in the milk of cows with intramammary infection. The most frequently observed PNC mastitis pathogens (major pathogens) are Streptococcus uberis, Strep. dysgalactiae, and Strep. agalactiae. The remaining PNC include a few minor pathogens and a large nonpathogenic group. Improved methods are needed for the accurate identification and differentiation of PNC. A total of 151 PNC were collected from cows with intramammary infection and conclusively identified by 16S rRNA sequencing as reference method. Nine phenotypic microbiological tests (alpha-hemolysis, CAMP reaction, esculin hydrolysis, growth on kanamycin esculin azide agar and on sodium chloride agar, inulin fermentation, hippurate hydrolysis, leucine aminopeptidase and pyrrolidonyl peptidase activity), multiplex PCR for the three major pathogens (target genes for Strep. uberis, Strep. dysgalactiae and Strep. agalactiae: pauA, 16S rRNA, and sklA3, respectively), and mass spectroscopy using the matrix-assisted laser desorption ionization-time of flight (MALDI-TOF MS) were evaluated for the diagnosis and discrimination of the three clinically most relevant PNC. RESULTS The probability that a strain of Strep. uberis, Strep. dysgalactiae and Strep. agalactiae was correctly identified by combining the results of the 9 phenotypic tests was 92%, 90%, and 100%, respectively. Applying the multiplex PCR, all strains of the three major pathogens were correctly identified and no false positive results occurred. Correct identification was observed for all strains of Strep. uberis and Strep. agalactiae using MALDI-TOF MS. In the case of Strep. dysgalactiae, some variability was observed at the subspecies level, but all strains were allocated to one single cluster. CONCLUSIONS The results of the present study show that reliable identification of the clinically most relevant PNC (Strep. uberis, Strep. agalactiae and Strep. dysgalactiae) can be obtained by use of a combination of colony morphology, hemolysis type and catalase reaction, and a multiplex PCR with specific primers restricted to these 3 pathogens. The MALDI-TOF MS is a fast method that shows promising results, although identification of Strep. dysgalactiae at the subspecies level is not yet satisfactory.

Identification of animal Pasteurellaceae by MALDI-TOF mass spectrometry

Species of the family Pasteurellaceae play an important role as primary or opportunistic, predominantly respiratory, pathogens in domestic and wild animals. Some of them cause severe disease with high economic losses in commercial animal husbandry. Hence, rapid and accurate differentiation of Pasteurellaceae is important and signifies a particular challenge to diagnostic laboratories. Identification and differentiation of Pasteurellaceae is mostly done using phenotypic tests or genetic identification based on sequence similarity of housekeeping genes, such as the rrs gene encoding the 16S ribosomal RNA (16S rRNA). Both approaches are time consuming, laborious, and costly, therefore often delaying the final diagnosis of disease or epidemics. Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry represents an alternative rapid and reliable method for the differentiation of most members of the family Pasteurellaceae. It is able to differentiate within a few minutes the currently known 18 genera and most of the over 60 species and subspecies of Pasteurellaceae including many members encountered in veterinary diagnostic laboratories. A few closely related species and subspecies that cannot be discriminated by MALDI-TOF are easily identified further by complementary simple tests, such as hemolysis done simultaneously or routinely during pathogen isolation.

Generation of a recombinant Gag virus-like-particle panel for the evaluation of p24 antigen detection by diagnostic HIV tests.

BACKGROUND Detection of HIV-1 p24 antigen permits early identification of primary HIV infection and timely intervention to limit further spread of the infection. Principally, HIV screening should equally detect all viral variants, but reagents for a standardised test evaluation are limited. Therefore, we aimed to create an inexhaustible panel of diverse HIV-1 p24 antigens. METHODS We generated a panel of 43 recombinantly expressed virus-like particles (VLPs), containing the structural Gag proteins of HIV-1 subtypes A-H and circulating recombinant forms (CRF) CRF01_AE, CRF02_AG, CRF12_BF, CRF20_BG and group O. Eleven 4th generation antigen/antibody tests and five antigen-only tests were evaluated for their ability to detect VLPs diluted in human plasma to p24 concentrations equivalent to 50, 10 and 2 IU/ml of the WHO p24 standard. Three tests were also evaluated for their ability to detect p24 after heat-denaturation for immune-complex disruption, a pre-requisite for ultrasensitive p24 detection. RESULTS Our VLP panel exhibited an average intra-clade p24 diversity of 6.7%. Among the 4th generation tests, the Abbott Architect and Siemens Enzygnost Integral 4 had the highest sensitivity of 97.7% and 93%, respectively. Alere Determine Combo and BioRad Access were least sensitive with 10.1% and 40.3%, respectively. Antigen-only tests were slightly more sensitive than combination tests. Almost all tests detected the WHO HIV-1 p24 standard at a concentration of 2 IU/ml, but their ability to detect this input for different subtypes varied greatly. Heat-treatment lowered overall detectability of HIV-1 p24 in two of the three tests, but only few VLPs had a more than 3-fold loss in p24 detection. CONCLUSIONS The HIV-1 Gag subtype panel has a broad diversity and proved useful for a standardised evaluation of the detection limit and breadth of subtype detection of p24 antigen-detecting tests. Several tests exhibited problems, particularly with non-B subtypes.