In vitro detection of cytotoxic T and NK cells in peripheral blood of patients with various drug-induced skin diseases

BACKGROUND: Cytotoxic cells are involved in most forms of drug-induced skin diseases. Till now, no in vitro test addressed this aspect of drug-allergic responses. Our report evaluates whether drug-induced cytotoxic cells can be detected in peripheral blood of nonacute patients with different forms of drug hypersensitivity, and also whether in vitro detection of these cells could be helpful in drug-allergy diagnosis. METHODS: GranzymeB enzyme-linked immunosorbent spot-forming (ELISPOT) and cell surface expression of the degranulation marker CD107a were evaluated on peripheral blood mononuclear cells from 12 drug-allergic patients in remission state and 16 drug-exposed healthy controls. RESULTS: In 10/12 allergic patients culprit but not irrelevant drug elicited granzymeB release after 48-72 h stimulation. It was clearly positive in patients with high proliferative response to the drug, measured in lymphocyte transformation tests. In patients, who showed moderate or low proliferation and low drug-response in granzymeB ELISPOT, overnight preincubation with interleukin (IL)-7/IL-15 enhanced drug-specific granzymeB release and allowed to clearly identify the offending agent. CD107a staining was positive on CD4+/CD3+, CD8+/CD3+ T cells as well as CD56+/CD3- natural killer cells. None of the drug-exposed healthy donors reacted to the tested drugs and allergic patients reacted only to the offending, but not to tolerated drugs. CONCLUSION: GranzymeB ELISPOT is a highly specific in vitro method to detect drug-reacting cytotoxic cells in peripheral blood of drug-allergic patients even several years after disease manifestation. Together with IL-7/IL-15 preincubation, it may be helpful in indentifying the offending drug even in some patients with weak proliferative drug-response.

Cardiogoniometric parameters for detection of coronary artery disease at rest as a function of stenosis localization and distribution

Cardiogoniometry (CGM), a spatiotemporal electrocardiologic 5-lead method with automated analysis, may be useful in primary healthcare for detecting coronary artery disease (CAD) at rest. Our aim was to systematically develop a stenosis-specific parameter set for global CAD detection. In 793 consecutively admitted patients with presumed non-acute CAD, CGM data were collected prior to elective coronary angiography and analyzed retrospectively. 658 patients fulfilled the inclusion criteria, 405 had CAD verified by coronary angiography; the 253 patients with normal coronary angiograms served as the non-CAD controls. Study patients--matched for age, BMI, and gender--were angiographically assigned to 8 stenosis-specific CAD categories or to the controls. One CGM parameter possessing significance (P < .05) and the best diagnostic accuracy was matched to one CAD category. The area under the ROC curve was .80 (global CAD versus controls). A set containing 8 stenosis-specific CGM parameters described variability of R vectors and R-T angles, spatial position and potential distribution of R/T vectors, and ST/T segment alterations. Our parameter set systematically combines CAD categories into an algorithm that detects CAD globally. Prospective validation in clinical studies is ongoing.

Detection of Merkel cell polyomavirus in epidermodysplasia-verruciformis-associated skin neoplasms

BACKGROUNd: Epidermodysplasia verruciformis (EV) is a rare genodermatosis that is characterized by susceptibility to infection with specific human papillomavirus (HPV) genotypes. Among polyomaviruses, the novel Merkel cell polyomavirus (MCPyV) has been found in different epithelial skin neoplasias.

On a Microcomputer Implementation of an Intrusion-detection Algorithm

The main objective of this paper is to discuss various aspects of implementing a specific intrusion-detection scheme on a micro-computer system using fixed-point arithmetic. The proposed scheme is suitable for detecting intruder stimuli which are in the form of transient signals. It consists of two stages: an adaptive digital predictor and an adaptive threshold detection algorithm. Experimental results involving data acquired via field experiments are also included.

Mining for Class-Specific Motifs in Protein Sequence Classification

Background: In protein sequence classification, identification of the sequence motifs or n-grams that can precisely discriminate between classes is a more interesting scientific question than the classification itself. A number of classification methods aim at accurate classification but fail to explain which sequence features indeed contribute to the accuracy. We hypothesize that sequences in lower denominations (n-grams) can be used to explore the sequence landscape and to identify class-specific motifs that discriminate between classes during classification. Discriminative n-grams are short peptide sequences that are highly frequent in one class but are either minimally present or absent in other classes. In this study, we present a new substitution-based scoring function for identifying discriminative n-grams that are highly specific to a class. Results: We present a scoring function based on discriminative n-grams that can effectively discriminate between classes. The scoring function, initially, harvests the entire set of 4- to 8-grams from the protein sequences of different classes in the dataset. Similar n-grams of the same size are combined to form new n-grams, where the similarity is defined by positive amino acid substitution scores in the BLOSUM62 matrix. Substitution has resulted in a large increase in the number of discriminatory n-grams harvested. Due to the unbalanced nature of the dataset, the frequencies of the n-grams are normalized using a dampening factor, which gives more weightage to the n-grams that appear in fewer classes and vice-versa. After the n-grams are normalized, the scoring function identifies discriminative 4- to 8-grams for each class that are frequent enough to be above a selection threshold. By mapping these discriminative n-grams back to the protein sequences, we obtained contiguous n-grams that represent short class-specific motifs in protein sequences. Our method fared well compared to an existing motif finding method known as Wordspy. We have validated our enriched set of class-specific motifs against the functionally important motifs obtained from the NLSdb, Prosite and ELM databases. We demonstrate that this method is very generic; thus can be widely applied to detect class-specific motifs in many protein sequence classification tasks. Conclusion: The proposed scoring function and methodology is able to identify class-specific motifs using discriminative n-grams derived from the protein sequences. The implementation of amino acid substitution scores for similarity detection, and the dampening factor to normalize the unbalanced datasets have significant effect on the performance of the scoring function. Our multipronged validation tests demonstrate that this method can detect class-specific motifs from a wide variety of protein sequence classes with a potential application to detecting proteome-specific motifs of different organisms.

Detection of gelatinolytic activity in developing basement membranes of the mouse embryo head by combining sensitive in situ zymography with immunolabeling

Genetic evidence indicates that the major gelatinases MMP-2 and MMP-9 are involved in mammalian craniofacial development. Since these matrix metalloproteinases are secreted as proenzymes that require activation, their tissue distribution does not necessarily reflect the sites of enzymatic activity. Information regarding the spatial and temporal expression of gelatinolytic activity in the head of the mammalian embryo is sparse. Sensitive in situ zymography with dye-quenched gelatin (DQ-gelatin) has been introduced recently; gelatinolytic activity results in a local increase in fluorescence. Using frontal sections of wild-type mouse embryo heads from embryonic day 14.5-15.5, we optimized and validated a simple double-labeling in situ technique for combining DQ-gelatin zymography with immunofluorescence staining. MMP inhibitors were tested to confirm the specificity of the reaction in situ, and results were compared to standard SDS-gel zymography of tissue extracts. Double-labeling was used to show the spatial relationship in situ between gelatinolytic activity and immunostaining for gelatinases MMP-2 and MMP-9, collagenase 3 (MMP-13) and MT1-MMP (MMP-14), a major activator of pro-gelatinases. Strong gelatinolytic activity, which partially overlapped with MMP proteins, was confirmed for Meckel's cartilage and developing mandibular bone. In addition, we combined in situ zymography with immunostaining for extracellular matrix proteins that are potential gelatinase substrates. Interestingly, gelatinolytic activity colocalized precisely with laminin-positive basement membranes at specific sites around growing epithelia in the developing mouse head, such as the ducts of salivary glands or the epithelial fold between tongue and lower jaw region. Thus, this sensitive method allows to associate, with high spatial resolution, gelatinolytic activity with epithelial morphogenesis in the embryo.

Direct detection of Mycoplasma bovis in milk and tissue samples by real-time PCR

Bovine mastitis caused by Mycoplasma bovis is of great economic importance to the beef and dairy industry. Here we describe a new specific real-time PCR assay targeting the uvrC gene that was developed to directly detect M. bovis from milk and tissue samples without laborious DNA purification.

Distinct reactivities of interleukin-4-specific antibodies with recombinant and native canine interleukin-4 in various assays

Interleukin 4 (IL-4) plays a central role in immune responses to parasites and allergens. IL-4 drives the differentiation of naive T cells into Th2 cells and regulates immunoglobulin class switching to IgE.Little is known about the role of IL-4 in canine allergies and parasite infections. Most of the information derives from measurement of IL-4 mRNA expression in dog tissues, but detection of IL-4 protein has been difficult so far, probably due to low sensitivity of available methods. Antibodies (Ab) specific for canine IL-4 are available from various sources, but these Ab have been produced against recombinant Escherichia coli-expressed canine IL-4 and there is only limited information on their reactivities with native canine IL-4. Therefore, in the present study, we tested six available canine IL-4-specific Ab for their reactivities with recombinant canine IL-4 expressed in E. coli (rec.IL-4) or in mammalian cells (mam.IL-4), and with supernatants from stimulated canine peripheral blood mononuclear cells (PBMCs) using several detection methods, including Western blotting, ELISA, cytokine bead assay, and intracellular IL-4 staining. Additionally, we tested a bovine IL-4-specific antibody that has been previously shown to cross-react with canine IL-4. All tested Ab except anti-bovine IL-4 reacted with rec.IL-4, and most of them reacted with mam.IL-4. However, only the cytokine bead assay was sensitive enough to allow the detection of IL-4 in supernatants of canine PBMCs.

Rapid and highly specific screening for NPM1 mutations in acute myeloid leukemia

NPM1 mutations, the most frequent molecular alterations in acute myeloid leukemia (AML), have become important for risk stratification and treatment decisions for patients with normal karyotype AML. Rapid screening for NPM1 mutations should be available shortly after diagnosis. Several methods for detecting NPM1 mutations have been described, most of which are technically challenging and require additional laboratory equipment. We developed and validated an assay that allows specific, rapid, and simple screening for NPM1 mutations. FAST PCR spanning exons 8 to 12 of the NPM1 gene was performed on 284 diagnostic AML samples. PCR products were visualized on a 2 % agarose E-gel and verified by direct sequencing. The FAST PCR screening method showed a specificity and sensitivity of 100 %, i.e., all mutated cases were detected, and none of negative cases carried mutations. The limit of detection was at 5-10 % of mutant alleles. We conclude that the FAST PCR assay is a highly specific, rapid (less than 2 h), and sensitive screening method for the detection of NPM1 mutations. Moreover, this method is inexpensive and can easily be integrated in the routine molecular diagnostic work-up of established risk factors in AML using standard laboratory equipment.

The time window for generation of dendritic spikes by coincidence of action potentials and EPSPs is layer specific in somatosensory cortex

The precise timing of events in the brain has consequences for intracellular processes, synaptic plasticity, integration and network behaviour. Pyramidal neurons, the most widespread excitatory neuron of the neocortex have multiple spike initiation zones, which interact via dendritic and somatic spikes actively propagating in all directions within the dendritic tree. For these neurons, therefore, both the location and timing of synaptic inputs are critical. The time window for which the backpropagating action potential can influence dendritic spike generation has been extensively studied in layer 5 neocortical pyramidal neurons of rat somatosensory cortex. Here, we re-examine this coincidence detection window for pyramidal cell types across the rat somatosensory cortex in layers 2/3, 5 and 6. We find that the time-window for optimal interaction is widest and shifted in layer 5 pyramidal neurons relative to cells in layers 6 and 2/3. Inputs arriving at the same time and locations will therefore differentially affect spike-timing dependent processes in the different classes of pyramidal neurons.

Association between sentinel lymph node excision with or without preoperative SPECT/CT and metastatic node detection and disease-free survival in melanoma

Malignant melanoma has become an increasing interdisciplinary public health challenge worldwide. Sentinel lymph node excision (SLNE) is considered the most sensitive and specific staging test for the detection of micrometastatic melanoma in regional lymph nodes.

Challenges in the early detection of psychosis in children and adolescents

The early detection and treatment of persons at-risk for psychosis is currently regarded a promising strategy in fighting the devastating consequences of psychotic disorders. The two current at-risk approaches, i.e., the "ultra high risk" and the "basic symptom" criteria, were mainly developed on adult samples. Initial evidence suggests, however, that they cannot simply be applied to children and adolescents. For ultra high risk criteria, there is indication of some attenuated psychotic symptoms being potentially non-specific in adolescents and of brief limited intermittent symptoms being difficult to clinically classify in children when observable behavioral correlates are missing. For basic symptoms, too, only preliminary indication of their usefulness in children and adolescents exists. Since developmental peculiarities in the assessment of basic symptoms should be considered, a child and youth version of the Schizophrenia Proneness Instrument (SPI-CY) was developed. In conclusion, research on the clinical-prognostic validity of the at-risk criteria and their potential adoption to the special needs of children and adolescents is needed. If a Prodromal Risk Syndrome for Psychosis or Attenuated Psychotic Symptoms Syndrome will be included into DSM-V, it has to be highlighted that its suitability for children and adolescents is only insufficiently known.

Break detection of annual Swiss temperature series

[1] Instrumental temperature series are often affected by artificial breaks (“break points”) due to (e.g.,) changes in station location, land-use, or instrumentation. The Swiss climate observation network offers a high number and density of stations, many long and relatively complete daily to sub-daily temperature series, and well-documented station histories (i.e., metadata). However, for many climate observation networks outside of Switzerland, detailed station histories are missing, incomplete, or inaccessible. To correct these records, the use of reliable statistical break detection methods is necessary. Here, we apply three statistical break detection methods to high-quality Swiss temperature series and use the available metadata to assess the methods. Due to the complex terrain in Switzerland, we are able to assess these methods under specific local conditions such as the Foehn or crest situations. We find that the temperature series of all stations are affected by artificial breaks (average = 1 break point / 48 years) with discrepancies in the abilities of the methods to detect breaks. However, by combining the three statistical methods, almost all of the detected break points are confirmed by metadata. In most cases, these break points are ascribed to a combination of factors in the station history.

Detection of exon deletions within an entire gene (CFTR) by relative quantification on the LightCycler

BACKGROUND: Cystic fibrosis (CF) is associated with at least 1 pathogen point sequence variant on each CFTR allele. Some symptomatic patients, however, have only 1 detectable pathogen sequence variant and carry, on the other allele, a large deletion that is not detected by conventional screening methods. METHODS: For relative quantitative real-time PCR detection of large deletions in the CFTR gene, we designed DNA-specific primers for each exon of the gene and primers for a reference gene (beta2-microglobulin). For PCR we used a LightCycler system (Roche) and calculated the gene-dosage ratio of CFTR to beta2-microglobulin. We tested the method by screening all 27 exons in 3 healthy individuals and 2 patients with only 1 pathogen sequence variant. We then performed specific deletion screenings in 10 CF patients with known large deletions and a blinded analysis in which we screened 24 individuals for large deletions by testing 8 of 27 exons. RESULTS: None of the ratios for control samples were false positive (for deletions or duplications); moreover, for all samples from patients with known large deletions, the calculated ratios for deleted exons were close to 0.5. In addition, the results from the blinded analysis demonstrated that our method can also be used for the screening of single individuals. CONCLUSIONS: The LightCycler assay allows reliable and rapid screening for large deletions in the CFTR gene and detects the copy number of all 27 exons.

A Data-Analytic Strategy for Protein-Biomarker Discovery: Profiling of High-Dimensional Proteomic Data for Cancer Detection

With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of "signature" protein profiles specific to each pathologic state (e.g., normal vs. cancer) or differential profiles between experimental conditions (e.g., treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data analytic strategy for discovering protein biomarkers based on such high-dimensional mass-spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data analytic strategy takes properties of the SELDI mass-spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After these pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary predictors and construct a summary classifier. We empirically evaluate sensitivity and specificity of the resulting summary classifiers with a test dataset that is independent from the training dataset used to construct the summary classifiers. The proposed method performed nearly perfectly in distinguishing cancer and benign hyperplasia from normal. In the classification of cancer vs. benign hyperplasia, however, an appreciable proportion of the benign specimens were classified incorrectly as cancer. We discuss practical issues associated with our proposed approach to the analysis of SELDI output and its application in cancer biomarker discovery.