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Aims Slide digitalization has brought pathology to a new era, including powerful image analysis possibilities. However, while being a powerful prognostic tool, immunostaining automated analysis on digital images is still not implemented worldwide in routine clinical practice. Methods and results Digitalized biopsy sections from two independent cohorts of patients, immunostained for membrane or nuclear markers, were quantified with two automated methods. The first was based on stained cell counting through tissue segmentation, while the second relied upon stained area proportion within tissue sections. Different steps of image preparation, such as automated tissue detection, folds exclusion and scanning magnification, were also assessed and validated. Quantification of either stained cells or the stained area was found to be correlated highly for all tested markers. Both methods were also correlated with visual scoring performed by a pathologist. For an equivalent reliability, quantification of the stained area is, however, faster and easier to fine-tune and is therefore more compatible with time constraints for prognosis. Conclusions This work provides an incentive for the implementation of automated immunostaining analysis with a stained area method in routine laboratory practice.

Rapid and specific detection of extended-spectrum β-lactamase-producing (ESBL) bacteria is crucial both for timely antibiotic therapy when treating infected patients as well as for appropriate infection control measures aimed at curbing the spread of ESBL-producing isolates. Whereas a variety of phenotypic methods are currently available for ESBL detection, they remain time consuming and sometimes difficult to interpret while being also affected by a lack of sensitivity and specificity. Considering the longer turnaround time (TAT) of susceptibility testing and culture results, DNA-based ESBL identification would be a valuable surrogate for phenotypic-based methods. Putative ESBL-positive Enterobacteriaceae isolates (n = 330) from clinical specimen were prospectively collected in Bulgaria, Romania and Democratic Republic of Congo and tested in this study. All isolates were assessed for ESBL-production by the E-test method and those giving undetermined ESBL status were re-tested using the combination disk test. A genotypic assay successively combining qPCR detection of blaCTX-M, blaTEM and blaSHV genes with a multiplex pyrosequencing of blaTEM and blaSHV genes was developed in order to detect the most common ESBL-associated TEM and SHV single nucleotides polymorphisms, irrespective of their plasmid and/or chromosomal location. This assay was applied on all Enterobacteriaceae isolates (n = 330). Phenotypic and genotypic results matched in 324/330 (98.2%). Accordingly, real-time PCR combined with multiplex pyrosequencing appears to be a reliable and easy-to-perform assay with high-throughput identification and fast TAT (~5 h).

Background Single Nucleotide Polymorphisms (SNPs) identified in Genome Wide Association Studies (GWAS) have generally moderate association with related complex diseases. Accordingly, Multilocus Genetic Risk Scores (MGRSs) have been computed in previous studies in order to assess the cumulative association of multiple SNPs. When several SNPs have to be genotyped for each patient, using successive uniplex pyrosequencing reactions increases analytical reagent expenses and Turnaround Time (TAT). While a set of several pyrosequencing primers could theoretically be used to analyze multiplex amplicons, this would generate overlapping primer-specific pyro-signals that are visually uninterpretable. Methods In the current study, two multiplex assays were developed consisting of a quadruplex (n=4) and a quintuplex (n=5) polymerase chain reaction (PCR) each followed by multiplex pyrosequencing analysis. The aim was to reliably but rapidly genotype a set of prostate cancer-related SNPs (n=9). The nucleotide dispensation order was selected using SENATOR software. Multiplex pyro-signals were analyzed using the new AdvISER-MH-PYRO software based on a sparse representation of the signal. Using uniplex assays as gold standard, the concordance between multiplex and uniplex assays was assessed on DNA extracted from patient blood samples (n = 10). Results All genotypes (n=90) generated with the quadruplex and the quintuplex pyroquencing assays were perfectly (100 %) concordant with uniplex pyrosequencing. Using multiplex genotyping approach for analyzing a set of 90 patients allowed reducing TAT by approximately 75 % (i.e., from 2025 to 470 min) while reducing reagent consumption and cost by approximately 70 % (i.e., from ∼229 US$ /patient to ∼64 US$ /patient). Conclusions This combination of quadruplex and quintuplex pyrosequencing and PCR assays enabled to reduce the amount of DNA required for multi-SNP analysis, and to lower the global TAT and costs of SNP genotyping while providing results as reliable as uniplex analysis. Using this combined multiplex approach also substantially reduced the production of waste material. These genotyping assays appear therefore to be biologically, economically and ecologically highly relevant, being worth to be integrated in genetic-based predictive strategies for better selecting patients at risk for prostate cancer. In addition, the same approach could now equally be transposed to other clinical/research applications relying on the computation of MGRS based on multi-SNP genotyping.

Lauwerys BR, Hernández-Lobato D, Gramme P, Ducreux J, Dessy A, Focant I, et al. (2015) Heterogeneity of Synovial Molecular Patterns in Patients with Arthritis. PLoS ONE 10(4): e0122104. doi:10.1371/journal.pone.0122104, Objectives: Early diagnosis of rheumatoid arthritis (RA) is an unmet medical need in the field of rheumatology. Previously, we performed high-density transcriptomic studies on synovial biopsies from patients with arthritis, and found that synovial gene expression profiles were significantly different according to the underlying disorder. Here, we wanted to further explore the consistency of the gene expression signals in synovial biopsies of patients with arthritis, using low-density platforms. Methods: Low-density assays (cDNA microarray and microfluidics qPCR) were designed, based on the results of the high-density microarray data. Knee synovial biopsies were obtained from patients with RA, spondyloarthropathies (SA) or osteoarthritis (OA) (n = 39), and also from patients with initial undifferentiated arthritis (UA) (n = 49). Results: According to high-density microarray data, several molecular pathways are differentially expressed in patients with RA, SA and OA: T and B cell activation, chromatin remodelling, RAS GTPase activation and extracellular matrix regulation. Strikingly, disease activity (DAS28-CRP) has a significant influence on gene expression patterns in RA samples. Using the low-density assays, samples from patients with OA are easily discriminated from RA and SA samples. However, overlapping molecular patterns are found, in particular between RA and SA biopsies. Therefore, prediction of the clinical diagnosis based on gene expression data results in a diagnostic accuracy of 56.8%, which is increased up to 98.6%by the addition of specific clinical symptoms in the prediction algorithm. Similar observations are made in initial UA samples, in which overlapping molecular patterns also impact the accuracy of the diagnostic algorithm. When clinical symptoms are added, the diagnostic accuracy is strongly improved. Conclusions: Gene expression signatures are overall different in patients with OA, RA and SA, but overlapping molecular signatures are found in patients with these conditions. Therefore, an accurate diagnosis in patients with UA requires a combination of gene expression and clinical data., This work was supported by grants from the Région Wallonne (BioWin), and the Fondation Saint-Luc (Cliniques Universitaires Saint-Luc, Brussels, Belgium). JD is funded by a unrestricted UCB grant (« Chaire UCB sur les rhumatismes inflammatoires et systémiques »). BRL is a part-time research fellow (« Clinicien-chercheur ») of the Fonds National de la Recherche Scientifique (Communauté française de Belgique). DNAlytics provided support in the form of salaries for authors PG and TH, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.

Cryobanking and transplantation of ovarian tissue is a promising approach to restore fertility in cancer patients. However, ischemic stress following avascular ovarian cortex grafting is known to induce stromal tissue fibrosis and alterations in follicular development. The aim of the study was to analyze the impact of freeze-thawing and grafting procedures on gene expression in human ovarian tissue. Frozen-thawed ovarian tissue from 14 patients was xenografted for 7 days to nude mice and one ungrafted fragment was used as a control. Immediately after recovery, grafts were processed for RNA extraction and histological analysis. Their expression profile was screened by whole-genome oligonucleotide array (n = 4) and validated by reverse-transcriptase polymerase chain analysis (n = 10). After data filtering, the Limma package was used to build a linear regression model for each gene and to compute its fold change between tissues on Days 0 and 7. After adjusting the P-value by the Sidak method, 84 of the transcripts were significantly altered after 7 days of grafting, including matrix metalloproteinase-9 and -14 and angiogenic factors such as placental growth factor and C-X-C chemokine receptor type 4 (CXCR4). Major biological processes were related to tissue remodeling, including secretory processes, cellular adhesion and response to chemical and hormonal stimuli. Angiopoietin signaling, the interleukin-8 pathway and peroxisome proliferator-activated receptor activation were shown to be differentially regulated. On Day 7, overexpression was confirmed by PCR for interleukin-8, transforming growth factor-beta 1, matrix metalloproteinase-14 and CXCR4, compared with ungrafted controls. In conclusion, new as well as known genes involved in tissue restructuring and angiogenesis were identified and found to play a key role during the first days after human ovarian tissue transplantation. This will facilitate the development of strategies to optimize grafting techniques.

To compare the relapse-free survival (RFS) in Vietnamese (n=141) and white (n=94) children living in Vietnam and Belgium, respectively, and treated in their own country for acute lymphoblastic leukemia according to the same FRALLE 2000 protocol.RFS was significantly worse in Vietnamese children (hazards ratio=4.48; 95% confidence interval [CI], 2.16-9.3; P0.01). The 5-year RFS was 83.8% (95% CI, 76.3%-92.0%) and 47.8% (95% CI, 35.6%-64.2%) for white and Vietnamese children, respectively. In the latter group, relapses occurred in bone marrow and cerebrospinal fluid at a much earlier stage. The outcome was compared at first relapse only because of different treatments afterward, according to the country. Both series were similar for sex, age at diagnosis, initial white blood cell count, cytogenetic abnormalities, and corticosensitivity at day 8. Higher frequency of L2-acute lymphoblastic leukemia (P0.001) but lower frequency of T-acute lymphoblastic leukemia (P=0.004) were observed in Vietnamese children.Several factors may contribute to the poor RFS in Vietnamese children, which include the time interval before the first intrathecal therapy and differences in the management of drug-related toxicity. However, additional contribution of socioeconomic factors and/or variations in pharmacogenetic polymorphisms in Vietnamese patients cannot currently be ruled out.

Acute lymphoblastic leukemia (ALL) is the most common of all paediatric cancers. Aside from predisposing to ALL, polymorphisms could also be associated with poor outcome. Indeed, genetic variations involved in drug metabolism could, at least partially, be responsible for heterogeneous responses to standardized leukemia treatments, hence requiring more personalized therapy. The aims of this study were to (a) to determine the prevalence of seven common genetic polymorphisms including those that affect the folate and/or thiopurine metabolic pathways, i.e. cyclin D1 (CCND1-G870A), γ-glutamyl hydrolase (GGH-C452T), methylenetetrahydrofolate reductase (MTHFR-C677T and MTHFR-A1298C), thymidylate synthase promoter (TYMS-TSER), thiopurine methyltransferase (TPMT*3A and TPMT*3C) and inosine triphosphate pyrophosphatase (ITPA-C94A), in Caucasian (n = 94, age20) and Vietnamese (n = 141, age16 years) childhood ALL and (b) to assess the impact of a multilocus genetic risk score (MGRS) on relapse-free survival (RFS) using a Cox proportional-hazards regression model.The prevalence of MTHFR-677TT genotype was significantly higher in Caucasians (P = 0.008), in contrast to the prevalence of TYMS-TSER*3R/3R and ITPA-94AA/AC genotypes which were significantly higher in Vietnamese (P0.001 and P = 0.02, respectively). Compared with children with a low MGRS (≤ 3), those with a high MGRS (≥ 4) were 2.06 (95% CI = 1.01, 4.22; P = 0.04) times more likely to relapse. Adding MGRS into a multivariate Cox regression model with race/ethnicity and four clinical variables improved the predictive accuracy of the model (AUC from 0.682 to 0.709 at 24 months).Including MGRS into a clinical model improved the predictive accuracy of short and medium term prognosis, hence confirming the association between well determined pharmacogenotypes and outcome of paediatric ALL. Whether variants on other genes associated with folate metabolism can substantially improve the predictive value of current MGRS is not known but deserves further evaluation.

Separating CBRN mixed samples that contain both chemical and biological warfare agents (CB mixed sample) in liquid and solid matrices remains a very challenging issue. Parameters were set up to assess the performance of a simple filtration-based method first optimized on separate C- and B-agents, and then assessed on a model of CB mixed sample. In this model, MS2 bacteriophage, Autographa californica nuclear polyhedrosis baculovirus (AcNPV), Bacillus atrophaeus and Bacillus subtilis spores were used as biological agent simulants whereas ethyl methylphosphonic acid (EMPA) and pinacolyl methylphophonic acid (PMPA) were used as VX and soman (GD) nerve agent surrogates, respectively. Nanoseparation centrifugal devices with various pore size cut-off (30 kD up to 0.45 µm) and three RNA extraction methods (Invisorb, EZ1 and Nuclisens) were compared. RNA (MS2) and DNA (AcNPV) quantification was carried out by means of specific and sensitive quantitative real-time PCRs (qPCR). Liquid chromatography coupled to time-of-flight mass spectrometry (LC/TOFMS) methods was used for quantifying EMPA and PMPA. Culture methods and qPCR demonstrated that membranes with a 30 kD cut-off retain more than 99.99% of biological agents (MS2, AcNPV, Bacillus Atrophaeus and Bacillus subtilis spores) tested separately. A rapid and reliable separation of CB mixed sample models (MS2/PEG-400 and MS2/EMPA/PMPA) contained in simple liquid or complex matrices such as sand and soil was also successfully achieved on a 30 kD filter with more than 99.99% retention of MS2 on the filter membrane, and up to 99% of PEG-400, EMPA and PMPA recovery in the filtrate. The whole separation process turnaround-time (TAT) was less than 10 minutes. The filtration method appears to be rapid, versatile and extremely efficient. The separation method developed in this work constitutes therefore a useful model for further evaluating and comparing additional separation alternative procedures for a safe handling and preparation of CB mixed samples.

Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with higher risk of prostate cancer (PCa). This study aimed to evaluate whether published SNPs improve the performance of a clinical risk-calculator in predicting prostate biopsy result.Three hundred forty-six patients with a previous prostate biopsy (191 positive, 155 negative) were enrolled. After literature search, nine SNPs were selected for their statistically significant association with increased PCa risk. Allelic odds ratios were computed and a new logistic regression model was built integrating the clinical risk score (i.e., prior biopsy results, PSA level, prostate volume, transrectal ultrasound, and digital rectal examination) and a multilocus genetic risk score (MGRS). Areas under the receiver operating characteristic (ROC) curves (AUC) of the clinical score alone versus the integrated clinic-genetic model were compared. The added value of the MGRS was assessed using the Integrated Discrimination Improvement (IDI) and Net Reclassification Improvement (NRI) statistics.Predictive performance of the integrated clinico-genetic model (AUC = 0.781) was slightly higher than predictive performance of the clinical score alone (AUC = 0.770). The prediction of PCa was significantly improved with an IDI of 0.015 (P-value = 0.035) and a continuous NRI of 0.403 (P-value 0.001).The predictive performance of the clinical model was only slightly improved by adding MGRS questioning the real clinical added value with regards to the cost of genetic testing and performance of current inexpensive clinical risk-calculators.

The motor clinical hallmarks of Parkinson's disease (PD) are usually quantified by physicians using validated clinimetric scales such as the Unified Parkinson's Disease Rating Scale (MDS-UPDRS). However, clinical ratings are prone to subjectivity and inter-rater variability. The PD medical community is therefore looking for a simple, inexpensive, and objective rating method. As a first step towards this goal, a triaxial accelerometer-based system was used in a sample of 36 PD patients and 10 age-matched controls as they performed the MDS-UPDRS finger tapping (FT) task. First, raw signals were epoched to isolate the successive single FT movements. Next, eighteen FT task movement features were extracted, depicting MDS-UPDRS features and accelerometer specific features. An ordinal logistic regression model and a greedy backward algorithm were used to identify the most relevant features in the prediction of MDS-UPDRS FT scores, given by 3 specialists in movement disorders (SMDs). The Goodman-Kruskal Gamma index obtained (0.961), depicting the predictive performance of the model, is similar to those obtained between the individual scores given by the SMD (0.870 to 0.970). The automatic prediction of MDS-UPDRS scores using the proposed system may be valuable in clinical trials designed to evaluate and modify motor disability in PD patients.

Contains fulltext : 116540.pdf (Publisher’s version ) (Open Access) BACKGROUND: Angiotensin-converting enzyme (ACE) (EC 4.15.1) metabolizes many biologically active peptides and plays a key role in blood pressure regulation and vascular remodeling. Elevated ACE levels are associated with different cardiovascular and respiratory diseases. METHODS AND RESULTS: Two Belgian families with a 8-16-fold increase in blood ACE level were incidentally identified. A novel heterozygous splice site mutation of intron 25 - IVS25+1G>A (c.3691+1G>A) - cosegregating with elevated plasma ACE was identified in both pedigrees. Messenger RNA analysis revealed that the mutation led to the retention of intron 25 and Premature Termination Codon generation. Subjects harboring the mutation were mostly normotensive, had no left ventricular hypertrophy or cardiovascular disease. The levels of renin-angiotensin-aldosterone system components in the mutated cases and wild-type controls were similar, both at baseline and after 50 mg captopril. Compared with non-affected members, quantification of ACE surface expression and shedding using flow cytometry assay of dendritic cells derived from peripheral blood monocytes of affected members, demonstrated a 50% decrease and 3-fold increase, respectively. Together with a dramatic increase in circulating ACE levels, these findings argue in favor of deletion of transmembrane anchor, leading to direct secretion of ACE out of cells. CONCLUSIONS: We describe a novel mutation of the ACE gene associated with a major familial elevation of circulating ACE, without evidence of activation of the renin-angiotensin system, target organ damage or cardiovascular complications. These data are consistent with the hypothesis that membrane-bound ACE, rather than circulating ACE, is responsible for Angiotensin II generation and its cardiovascular consequences. 12 p.

Contexte La telesurveillance medicale a domicile (TSM) represente une alternative pour ameliorer le pronostic des patients atteints d’insuffisance cardiaque (IC). Cependant, l’efficacite clinique de la TSM, basee sur les variations de poids corporel demeure controversee. Nous avons voulu identifier les caracteristiques dans l’evolution des parametres telesurveilles qui sont predictifs de la decompensation cardiaque, en considerant le statut clinique des patients. Methodes Des patients ambulatoires souffrant d’IC ont complete quotidiennement pendant six mois a l’aveugle, des mesures de poids, de pression arterielle et de pouls, enregistrees sous forme de signal. Le critere cardiaque composite (CCC) etait la survenue d’un deces, d’une hospitalisation ou d’une visite urgente. Des statistiques ont ete calculees sur des fenetres de temps de 3, 5 et 7 jours, et soumises a une regression logistique dans un sous-ensemble de donnees (entrainement) pour construire un score signal dont la precision a ete testee dans un autre sous-ensemble de donnees (test). Un score clinique a ete calcule sur la base du score « Meta-Analysis Global Group in Chronic Heart Failure » (MAGGIC). Ces deux scores ont ete combines avec une regression logistique. Le pouvoir diagnostique des scores a ete evalue avec des courbes ROC. Resultats Au total, 146 patients ont complete l’etude et 96 CCC ont ete enregistres. Le score signal integrait l’ecart-type du poids sur 3 jours, la pente du poids sur 3 et sur 7 jours. Il etait predictif du CCC (donnees d’entrainement : AUC = 0,761, p p p p Conclusion La technologie TSM visant a predire les complications de l’IC devrait integrer le statut clinique des patients.

Allograft inflammation and fibrosis among maintenance pediatric liver transplant recipients – genetic predisposition and antibodies, connecting the missing links. Varma S1, Latinne D2, Komuta M3, Ambroise J4, Smets F1, Baldin P3,Reding R5 , Stephenne X1, and Sokal EM1 Universite Catholique de Louvain, Cliniques Universitaires St Luc, 1Service de Gastroenterologie et Hepatologie Pediatrique, 3Service de Anatomopathologie 4 Centre for Applied Molecular Technologies (CTMA), Institut de Recherche Experimentale et Clinique (IREC), 5 Paediatric Surgery and Transplantation Unit, Brussels, Belgium Aim: To determine impact of HLA allo-antibodies, non-HLA auto-antibodies and HLA-DRB1 genotype amongst stable, long term pediatric liver transplantation (LT) recipients; on allograft health. Background: Role of HLA allo-antibodies and non-HLA auto-antibodies in late allograft fibrosis and inflammation is unclear in pediatric LT, though inferior long-term outcomes with class II donor specific HLA antibodies (Class-II DSA) post LT are suggested. HLA DRB1*03 or 04 genotype predisposes to auto-immune hepatitis (AIH), prototype of antibody related hepatic inflammation. Patients: Stable LT recipients transplanted in 2006-2012 and with >2 protocol biopsies were included. Autoimmune hepatitis, hepatitis B or C infection as indication of LT; ABOi graft, biliary or vascular complications post LT, re-transplantation were exclusion criteria. Methods Data were collected at 1-month pre-LT and simultaneous to last protocol biopsy. HLA, ANA, SMA, LKM antibodies, HLA-DRB1 genotype of recipients and histological aspects of biopsy, were collected. Histological parameters including rejection, bile duct proliferation, lobular inflammation, and portal tract infiltration were assessed while fibrosis was evaluated using Metavir and liver allograft fibrosis scoring (LAFSc). Results 15 of 89 included children had class-II DSA post LT. Class-II DSA was associated with allograft fibrosis using Metavir and LAFSc–score (p

Histological quantification of apha smooth muscle actin predicts future graft fibrosis in pediatric liver transplant recipients Varma S1, Stephenne X1, Komuta M2, Bouzin.C3, Ambroise J4, Smets F1, Reding R5, and Sokal EM1 Universite Catholique de Louvain, Cliniques Universitaires St Luc, 1Service de Gastroenterologie et Hepatologie Pediatrique and Pediatric Research Unit, 2Service de Anatomopathologie, 3 Imaging Platform (2IP) Institut de Recherche Experimentale et Clinique (IREC) , 4 Centre for Applied Molecular Technologies (CTMA), Institut de Recherche Experimentale et Clinique (IREC) 5 Unites de Chirurgie Pediatrique, Brussels, Belgium Aims: To evaluate significance of alpha smooth muscle actin (ASMA) expression on liver biopsy as predictor of future graft fibrosis in pediatric liver transplant (LT) recipients. Background: Activated hepatic stellate cells express cytoplasmic protein-alpha smooth muscle actin (ASMA) and subsequently secrete collagen leading to liver fibrosis. As activation of stellate cells precedes collagen deposition, we hypothesize that quantification of ASMA can predict the severity of future fibrosis. Patients: Stable pediatric LT recipients transplanted between 2006-20012, with two protocol biopsies less than two years apart and first being at more than 1year post LT. Patients with biliary, vascular complications, autoimmune hepatitis, hepatitis B or C infection, re-transplantation, or those with inadequate biopsy size were excluded. Methods: Metavir and liver allograft fibrosis scoring (LAFSc) used for fibrosis assessment. Automated staining for ASMA followed by digital quantification of ASMA positive area percentage was done. Fibrosis on initial biopsy specimen was labelled “current fibrosis” and on next biopsy labelled “prospective fibrosis”. The change between “current” and “prospective” fibrosis score was “prospective change in fibrosis”. Bile duct proliferation, lobular inflammation and portal tract infiltration was also evaluated. Results: 32 biopsy specimens, from 18 patients stained for ASMA and 56 evaluated for fibrosis. Significant association between the ASMA positive area percentage on initial biopsy and “prospective change in fibrosis” was seen; using Metavir (p-value = 0.02), LAFSc cumulative (p-value = 0.02) and LAFSc-portal (p-value=0.01) scores. AUROC analysis suggested ASMA positive area percentage > 1.05 to predict increased fibrosis on the next biopsy (60.0 % sensitivity, 90.0 % specificity). Conclusion: ASMA quantification on biopsy in liver transplant recipients predicts the future course of fibrosis, specifically portal fibrosis.

MOTIVATION: Assessment of gene expression on spotted microarrays is based on measurement of fluorescence intensity emitted by hybridized spots. Unfortunately, quantifying fluorescence intensity from hybridized spots does not always correctly reflect gene expression level. Low gene expression levels produce low fluorescence intensities which tend to be confounded with the local background while high gene expression levels produce high fluorescence intensities which rapidly reach the saturation level. Most algorithms that combine data acquired at different voltages of the photomultiplier tube (PMT) assume that a change in scanner setting transforms the intensity measurements by a multiplicative constant. METHODS AND RESULTS: In this paper we introduce a new model of spot foreground intensity which integrates a PMT voltage independent scanner optical bias. This new model is used to implement a "Combining Multiple Scan using a Two-way ANOVA" (CMS2A) method, which is based on a maximum likelihood estimation of the scanner optical bias. After having computed scanner bias, coefficients of the two-way ANOVA model are used for correcting the saturated spots intensities obtained at high PMT voltage by using their counterpart values at lower PMT voltages. The method was compared to state-of-the-art multiple scan algorithms, using data generated from the MAQC study. CMS2A produced fold-changes that were highly correlated with qPCR fold-changes. As the scanner optical bias is accurately estimated within CMS2A, this method allows also avoiding fold-change compression biases whatever the value of this optical bias.

A B-cell epitope is a part of an antigen that is recognized by a specific antibody or B-cell receptor. Detecting the immunogenic region of the antigen is useful in numerous immunodetection and immunotherapeutics applications. The aim of this paper is to find relevant properties to discriminate the location of potential epitopes from the rest of the protein surface. The most relevant properties, identified using two evaluation approaches, are the geometric properties, followed by the conservation score and some chemical properties, such as the proportion of glycine. The selected properties are used in a patch-based epitope localization method including a Single-Layer Perceptron for regression. The output of this Single-Layer Perceptron is used to construct a probability map on the antigen surface. The predictive performances of the method are assessed by computing the AUC using cross validation on two benchmark data sets and by computing the AUC and the precision for a third independent test set.

Biological agents may be characterized (in terms of quantity (or concentration), purity, nature) using optical ways like spectrometry, fluorometry and real-time PCR for example. Most of these techniques are based on absorbance or fluorescence. Indeed, many biological molecules can absorb the light when excited at wavelengths close to blue and ultraviolet (UV). For example, DNA, RNA and proteins feature an absorption peak in the deep UV, more precisely around 260 and 280 nm (Karczemska & Sokolowska, 2001). This work is widely focused on those wavelengths. A biological sample concentration measurement method can be based on UV light absorbance or transmittance, as already known and realized with high-cost and large-size biomedical apparatus. But, often, the difficulties come from the limitation for measuring very small concentrations (close to a few ng/μL or lower) since themeasurement of such small light intensity variations at those low wavelengths requires a precise light source, and very efficient photodetectors. Reducing the dimensions of such a characterization system further requires a small light source, a miniaturized photosensor and a processing system with high precision to reduce the measurement variations. Some light-emitting diodes (LED) performing at those UV wavelengths have recently appeared and may be used to implement the light source. Concerning the optical sensor, while accurate but high-cost photosensors in technologies such as AlGaN and SiC provide high sensitivities in UV lowwavelengths thanks to their semiconductor bandgap (Yotter & Wilson, 2003), the silicon-on-insulator (SOI) layers absorb the photons in that specific range thanks to an appropriate thickness of the silicon. Adding excellent performances of low power consumption, good temperature behavior and high speed (Flandre et al., 1999; 2001), the SOI technology allows the designers for integrating a specific signal processing integrated CMOS circuit to transform the photocurrent into a digital signal for example. This opens the possibility to build a low-cost, complete and portable microsystem, including the light source, the photodetector and a recipient for the sample to characterize. For this chapter, we start with a state-of-the-art describing the current DNA quantification methods with their advantages and disadvantages. Since we will work at low optical wavelengths, we review different ultraviolet light sources that are used in laboratories or in biomedical fields. A description of different photodetectors in various technologies, more especially in SOI, suitable for DNA quantification will then be presented. Afterwards, we 14

Rapid and reliable assessment of Acinetobacter baumannii resistance to quinolones was successfully achieved through pyrosequencing of the gyrA and parC quinolone-resistance determining regions. A strong correlation was found between quinolone resistance and mutations in gyrA codon 83 and/or in the parC gene (codons 80 or 84). Absence of QRDR mutations was associated with susceptibility to quinolones.

Background The structural genomics centers provide hundreds of protein structures of unknown function. Therefore, developing methods enabling the determination of a protein function automatically is imperative. The determination of a protein function can be achieved by studying the network of its physical interactions. In this context, identifying a potential binding site between proteins is of primary interest. In the literature, methods for predicting a potential binding site location generally are based on classification tools. The aim of this paper is to show that regression tools are more efficient than classification tools for patches based binding site predictors. For this purpose, we developed a patches based binding site localization method usable with either regression or classification tools. Results We compared predictive performances of regression tools with performances of machine learning classifiers. Using leave-one-out cross-validation, we showed that regression tools provide better predictions than classification ones. Among regression tools, Multilayer Perceptron ranked highest in the quality of predictions. We compared also the predictive performance of our patches based method using Multilayer Perceptron with the performance of three other methods usable through a web server. Our method performed similarly to the other methods. Conclusion Regression is more efficient than classification when applied to our binding site localization method. When it is possible, using regression instead of classification for other existing binding site predictors will probably improve results. Furthermore, the method presented in this work is flexible because the size of the predicted binding site is adjustable. This adaptability is useful when either false positive or negative rates have to be limited.

Highly sensitive measurement of DNA concentration on portable, easy-to-use, low-cost miniaturized equipments without sample waste is challenging.

In the Balkan and Taiwan, the relationship between exposure to aristolochic acid and risk of urothelial neoplasms was inferred from the A>T genetic hallmark in TP53 gene from malignant cells. This study aimed to characterize the TP53 mutational spectrum in urothelial cancers consecutive to Aristolochic Acid Nephropathy in Belgium. Serial frozen tumor sections from female patients (n = 5) exposed to aristolochic acid during weight-loss regimen were alternatively used either for p53 immunostaining or laser microdissection. Tissue areas with at least 60% p53-positive nuclei were selected for microdissecting sections according to p53-positive matching areas. All areas appeared to be carcinoma in situ. After DNA extraction, mutations in the TP53 hot spot region (exons 5–8) were identified using nested-PCR and sequencing. False-negative controls consisted in microdissecting fresh-frozen tumor tissues both from a patient with a Li-Fraumeni syndrome who carried a p53 constitutional mutation, and from KRas mutated adenocarcinomas. To rule out false-positive results potentially generated by microdissection and nested-PCR, a phenacetin-associated urothelial carcinoma and normal fresh ureteral tissues (n = 4) were processed with high laser power. No unexpected results being identified, molecular analysis was pursued on malignant tissues, showing at least one mutation in all (six different mutations in two) patients, with 13/16 exonic (nonsense, 2; missense, 11) and 3/16 intronic (one splice site) mutations. They were distributed as transitions (n = 7) or transversions (n = 9), with an equal prevalence of A>T and G>T (3/16 each). While current results are in line with A>T prevalence previously reported in Balkan and Taiwan studies, they also demonstrate that multiple mutations in the TP53 hot spot region and a high frequency of G>T transversion appear as a complementary signature reflecting the toxicity of a cumulative dose of aristolochic acid ingested over a short period of time.

Background Pyrosequencing Allele Quantification (AQ) is a cost-effective DNA sequencing method that can be used for detecting somatic mutations in formalin-fixed paraffin-embedded (FFPE) samples. The method displays a low turnaround time and a high sensitivity. Pyrosequencing suffers however from two main drawbacks including (i) low specificity and (ii) difficult signal interpretation when multiple mutations are reported in a hotspot genomic region. Results Using a constraint-based regression method, the new AdvISER-PYRO-SMQ algorithm was developed in the current study and implemented into an R package. As a proof-of-concept, AdvISER-PYRO-SMQ was used to identify a set of 9 distinct point mutations affecting codon 61 of the NRAS oncogene. In parallel, a pyrosequencing assay using the Qiagen software and its AQ module was used to assess selectively the presence of a single point mutation (NRAS\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$c.182A>G$$\end{document}c.182A>G - Q61R-1) among the set of codon 61 mutations, and to analyze related pyrosequencing signals. AdvISER-PYRO-SMQ produced a lower limit of blank (0 %) than the AQ module of Qiagen software (5.1 %) and similar limit of detection were obtained for both software (5.6 vs 4.8 %). AdvISER-PYRO-SMQ was able to screen for the presence of 9 distinct mutations with a single pyrosequencing reaction whereas the AQ module was limited to screen a single mutation per reaction. Conclusion Using a constraint-based regression method enables to analyze pyrosequencing signal and to detect multiple mutations within a hotspot genomic region with an optimal compromise between sensitivity and specificity. The AdvISER-PYRO-SMQ R package provides a generic tool which can be applied on a wide range of somatic mutations. Its implementation in a Shiny web interactive application (available at https://ucl-irec-ctma.shinyapps.io/Pyrosequencing-NRAS-61/) enables its use in research or clinical routine applications. Electronic supplementary material The online version of this article (doi:10.1186/s13015-016-0086-4) contains supplementary material, which is available to authorized users.

Background The standard approach for preprocessing spotted microarray data is to subtract the local background intensity from the spot foreground intensity, to perform a log2 transformation and to normalize the data with a global median or a lowess normalization. Although well motivated, standard approaches for background correction and for transformation have been widely criticized because they produce high variance at low intensities. Whereas various alternatives to the standard background correction methods and to log2 transformation were proposed, impacts of both successive preprocessing steps were not compared in an objective way. Results In this study, we assessed the impact of eight preprocessing methods combining four background correction methods and two transformations (the log2 and the glog), by using data from the MAQC study. The current results indicate that most preprocessing methods produce fold-change compression at low intensities. Fold-change compression was minimized using the Standard and the Edwards background correction methods coupled with a log2 transformation. The drawback of both methods is a high variance at low intensities which consequently produced poor estimations of the p-values. On the other hand, effective stabilization of the variance as well as better estimations of the p-values were observed after the glog transformation. Conclusion As both fold-change magnitudes and p-values are important in the context of microarray class comparison studies, we therefore recommend to combine the Edwards correction with a hybrid transformation method that uses the log2 transformation to estimate fold-change magnitudes and the glog transformation to estimate p-values.