Inhibition of the dorsolateral cortex reveals specific mechanisms behind emotional control.

Reappraisal is a complex emotional control strategy based on cognitive change. To complete the reappraisal task, one is required to deeply elaborate on the affective stimulus to create its new interpretation. The involvement of the prefrontal cortex in this process was examined in the study, where inhibition of the left or right dorsolateral area was carried out using transcranial magnetic stimulation. In a between-subject design, we used an alternative control condition for the reappraisal task. It was intended to better account for overall task activity compared to typical passive conditions. Late positive potential was affected after inhibition of the prefrontal area, suggesting hindered emotional control. This effect was specific to the reappraisal task, which possibly reflects the disturbance of attention allocation to emotional stimuli. We could also observe an increased transfer of information from the visual area during the control task that was based on the elaboration of emotional stimuli but did not involve cognitive change. Our results support the additive impact of several factors on the overall efficiency of emotional control.

Development of an SPRi Test for the Quantitative Detection of Cadherin 12 in Human Plasma and Peritoneal Fluid.

A new method for the determination of cadherin 12 (CDH12)-an adhesive protein that has a significant impact on the development, growth, and movement of cancer cells-was developed and validated. The method is based on a biosensor using surface plasmon resonance imaging (SPRi) detection. A quartz crystal microbalance was used to analyze the characteristics of the formation of successive layers of the biosensor, from the linker monolayer to the final capture of CDH12 from solution. The association equilibrium constant (KA = 1.66 × 1011 dm3 mol-1) and the dissociation equilibrium constant (KD = 7.52 × 10-12 mol dm-3) of the anti-CDH12 antibody-CDH12 protein complex were determined. The determined analytical parameters, namely the values determining the accuracy, precision, and repeatability of the method, do not exceed the permissible 20% deviations specified by the aforementioned institutions. The proposed method is also selective with respect to possible potential interferents, occurring in up to 100-fold excess concentration relative to the CDH12 concentration. The determined Limit of Quantification (LOQ = 4.92 pg mL-1) indicates the possibility of performing quantitative analysis in human plasma or peritoneal fluid without the need to concentrate the samples; however, particular attention should be paid to their storage conditions, as the analyte does not exhibit high stability. The Passing-Bablok regression model revealed good agreement between the reference method and the SPRi biosensor, with ρSpearman values of 0.961 and 0.925.

Plasma and Peritoneal Fluid Fibronectin and Collagen IV Levels as Potential Biomarkers of Endometriosis.

Laparoscopy as a diagnostic tool for patients with suspected endometriosis is associated with several potentially life-threatening complications. Therefore, it is imperative to identify reliable, non-invasive biomarkers of the disease. The aim of this study was to analyse the concentrations of fibronectin and type IV collagen in peritoneal fluid and plasma to assess their role as potential biomarkers in the diagnosis of endometriosis. Fibronectin and collagen IV protein levels were assessed by surface plasmon resonance imaging (SPRi) biosensors with the usage of monoclonal antibodies. All patients enrolled in the study were referred for laparoscopy for the diagnosis of infertility or chronic pelvic pain (n = 84). The study group included patients with endometriosis confirmed during surgery (n = 49). The concentration of fibronectin in the plasma (329.3 ± 98.5 mg/L) and peritoneal fluid (26.8 ± 11.1 µg/L) in women with endometriosis was significantly higher than in the control group (251.2 ± 84.0 mg/L, 7.0 ± 5.9 µg/L). Fibronectin levels were independent of endometriosis stage (p = 0.874, p = 0.469). No significant differences were observed in collagen IV levels (p = 0.385, p = 0.465). The presence of elevated levels of fibronectin may indicate abnormalities in cell-ECM signalling during the course of endometriosis, and may be a potential biomarker for early detection.

Two Biosensors for the Determination of VEGF-R2 in Plasma by Array SPRi.

Vascular endothelial growth factor receptor 2 (VEGF-R2) is a marker of angiogenesis and metastasis of cancer. Two biosensors for the determination of VEGF-R2 in plasma have been developed. One of them is based on a pure gold chip, and the other on a silver/gold bimetallic chip; both have the receptor, monoclonal rabbit antibody specific for human VEGF-R2, attached to the chip via a cysteamine linker. The biosensor with the gold chip exhibits linearity of the analytical signal between 0.03 and 2 ng/mL, a precision of 1.4% and recovery between 99% and 102%. The biosensor with the bimetallic chip exhibits linearity between 0.03 and 1 ng/mL, a precision of 2.2% and recovery between 99% and 103%. Both biosensors tolerate a 1:100 excess of VEGF, VEGF-R1 and VEGF-R3. Both biosensors were validated by parallel determination of VEGF-R2 in 27 different plasma samples using the ELISA immunosensor assay, with very good agreement of the results. Thermodynamic parameters of the interaction of VEGF-R2 with the antibody were determined by QCM (Quartz Crystal Microbalance) and SPRi (Surface Plasmon Resonance imaging) measurements.

Clinical characteristics of pruritus in patients with bullous pemphigoid: a preliminary questionnaire-based study.

INTRODUCTION: Bullous pemphigoid (BP) is the most common autoimmune blistering disease. Although pruritus is a leading symptom in BP, its specific characteristics have not been explored. AIM: To determine the itch characteristics in newly diagnosed BP patients by using the Questionnaire of Descriptive Assessment of Pruritus and visual analogue scale (VAS) and to correlate itch with disease severity. MATERIAL AND METHODS: The study included 32 patients with BP (mean age: 75.4 ±12.2 years; 20 women, 12 men), who filled in the questionnaire. Bullous Pemphigoid Disease Area Index (BPDAI) was assessed. RESULTS: In 78.1% of BP patients pruritus occurred at least once daily. Pruritus was most frequent in the evening and at night and frequently persisted for more than 10 min in more than a half of patients (long itch episodes). Aggravating factors were sweating (50.0%), heat (59.4%) and stress (46.9%), but the major relieving factor was cold (34.4%). Itch intensity in BP was assessed as moderate (mean VAS score: 5.8 points) and did not correlate with disease severity (BPDAI). BP patients declared difficulties caused by pruritus: falling asleep (53.1%) and awakening at night (50%). CONCLUSIONS: This study provided detailed characteristics in BP patients confirming that pruritus is classified as an important troublesome symptom. Therefore there is a need to search for therapeutic solutions.

SeQuiLa: an elastic, fast and scalable SQL-oriented solution for processing and querying genomic intervals.

SUMMARY: Efficient processing of large-scale genomic datasets has recently become possible due to the application of 'big data' technologies in bioinformatics pipelines. We present SeQuiLa-a distributed, ANSI SQL-compliant solution for speedy querying and processing of genomic intervals that is available as an Apache Spark package. Proposed range join strategy is significantly (∼22×) faster than the default Apache Spark implementation and outperforms other state-of-the-art tools for genomic intervals processing. AVAILABILITY AND IMPLEMENTATION: The project is available at http://biodatageeks.org/sequila/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genes sharing the protein family domain decrease the performance of classification with RNA-seq genomic signatures.

BACKGROUND: The experience with running various types of classification on the CAMDA neuroblastoma dataset have led us to the conclusion that the results are not always obvious and may differ depending on type of analysis and selection of genes used for classification. This paper aims in pointing out several factors that may influence the downstream machine learning analysis. In particular those factors are: type of the primary analysis, type of the classifier and increased correlation between the genes sharing a protein domain. They influence the analysis directly, but also interplay between them may be important. We have compiled the gene-domain database and used it for analysis to see the differences between the genes that share a domain versus the rest of the genes in the datasets. RESULTS: The major findings are: pairs of genes that share a domain have an increased Spearman's correlation coefficients of counts; genes sharing a domain are expected to have a lower predictive power due to increased correlation. For most of the cases it can be seen with the higher number of misclassified samples; classifiers performance may vary depending on a method, still in most cases using genes sharing a domain in the training set results in a higher misclassification rate; increased correlation in genes sharing a domain results most often in worse performance of the classifiers regardless of the primary analysis tools used, even if the primary analysis alignment yield varies. CONCLUSIONS: The effect of sharing a domain is likely more a results of real biological co-expression than just sequence similarity and artifacts of mapping and counting. Still, this is more difficult to conclude and needs further research. The effect is interesting itself, but we also point out some practical aspects in which it may influence the RNA sequencing analysis and RNA biomarker use. In particular it means that a gene signature biomarker set build out of RNA-sequencing results should be depleted for genes sharing common domains. It may cause to perform better when applying classification. REVIEWERS: This article was reviewed by Dimitar Vassiliev and Susmita Datta.

Development of bullous pemphigoid in a patient with psoriasis and metabolic syndrome.

Bullous pemphigoid (BP) is an autoimmune subepidermal blistering disease that most commonly affects adults older than 60 years, whereas psoriasis vulgaris (PV) is a chronic immune-mediated disease that affects both children and adults. Bullous pemphigoid and PV may coexist with each other as well as with various other internal disorders, which may lead to early death. We report the case of a 35-year-old man with a 15-year history of PV and obesity who developed tense blisters with annular arrangement and normal-appearing perilesional skin localized mainly on the trunk, arms, and legs resembling linear IgA bullous dermatosis. This case demonstrated the development of BP in a patient with chronic PV and metabolic syndrome. Although the nature of this unique coincidence is not clear, methotrexate (MTX) seems to be first-line regimen for such cases.

Preferred analysis methods for single genomic regions in RNA sequencing revealed by processing the shape of coverage.

The informational content of RNA sequencing is currently far from being completely explored. Most of the analyses focus on processing tables of counts or finding isoform deconvolution via exon junctions. This article presents a comparison of several techniques that can be used to estimate differential expression of exons or small genomic regions of expression, based on their coverage function shapes. The problem is defined as finding the differentially expressed exons between two samples using local expression profile normalization and statistical measures to spot the differences between two profile shapes. Initial experiments have been done using synthetic data, and real data modified with synthetically created differential patterns. Then, 160 pipelines (5 types of generator × 4 normalizations × 8 difference measures) are compared. As a result, the best analysis pipelines are selected based on linearity of the differential expression estimation and the area under the ROC curve. These platform-independent techniques have been implemented in the Bioconductor package rnaSeqMap. They point out the exons with differential expression or internal splicing, even if the counts of reads may not show this. The areas of application include significant difference searches, splicing identification algorithms and finding suitable regions for QPCR primers.

rnaSeqMap: a Bioconductor package for RNA sequencing data exploration.

BACKGROUND: The throughput of commercially available sequencers has recently significantly increased. It has reached the point where measuring the RNA expression by the depth of coverage has become feasible even for largest genomes. The development of software tools is constantly following the progress of biological hardware. In particular, as RNA sequencing software can be regarded genome browsers, exon junction tools and statistical tools operating on counts of reads in predefined regions. The library rnaSeqMap, freely available via Bioconductor, is an RNA sequencing software which is independent of any biological hardware platform. It is based upon standard Bioconductor infrastructure for sequencing data and includes several novel features focused on deeper understanding of coverage expression profiles and discovery of novel transcription regions. RESULTS: rnaSeqMap is a toolbox for analyses that may be performed with the use of gene annotations or alternatively, in an unsupervised mode, on any genomic region to find novel or non-standard transcripts. The data back-end may be a MySQL database or a set of files in standard BAM format. The processing in R can be run on a machine without any particular hardware requirements, and scales linearly with the number of genomic loci and number of samples analyzed. The main features of rnaSeqMap include coverage operations, discovering irreducible regions of high expression, significance search and splicing analyses with nucleotide granularity. CONCLUSIONS: This software may be used for a range of applications related to RNA sequencing by building customized analysis pipelines. The applicability and precision is expected to increase in parallel with the progress of the genome coverage in sequencers.