Validation of real-time methylation-specific PCR to determine O6-methylguanine-DNA methyltransferase gene promoter methylation in glioma.

Epigenetic silencing of the DNA repair protein O(6)-methylguanine-DNA methyltransferase (MGMT) by promoter methylation predicts successful alkylating agent therapy, such as with temozolomide, in glioblastoma patients. Stratified therapy assignment of patients in prospective clinical trials according to tumor MGMT status requires a standardized diagnostic test, suitable for high-throughput analysis of small amounts of formalin-fixed, paraffin-embedded tumor tissue. A direct, real-time methylation-specific PCR (MSP) assay was developed to determine methylation status of the MGMT gene promoter. Assay specificity was obtained by selective amplification of methylated DNA sequences of sodium bisulfite-modified DNA. The copy number of the methylated MGMT promoter, normalized to the beta-actin gene, provides a quantitative test result. We analyzed 134 clinical glioma samples, comparing the new test with the previously validated nested gel-based MSP assay, which yields a binary readout. A cut-off value for the MGMT methylation status was suggested by fitting a bimodal normal mixture model to the real-time results, supporting the hypothesis that there are two distinct populations within the test samples. Comparison of the tests showed high concordance of the results (82/91 [90%]; Cohen's kappa = 0.80; 95% confidence interval, 0.82-0.95). The direct, real-time MSP assay was highly reproducible (Pearson correlation 0.996) and showed valid test results for 93% (125/134) of samples compared with 75% (94/125) for the nested, gel-based MSP assay. This high-throughput test provides an important pharmacogenomic tool for individualized management of alkylating agent chemotherapy.

Lack of association between beta-herpesvirus infection and bronchiolitis obliterans syndrome in lung transplant recipients in the era of antiviral prophylaxis.

BACKGROUND: Cytomegalovirus (CMV), human herpesvirus-6 and -7 (HHV-6 and -7) are beta-herpesviruses that commonly reactivate and have been proposed to trigger acute rejection and chronic allograft injury. We assessed the contribution of these viruses in the development of bronchiolitis obliterans syndrome (BOS) after lung transplantation. METHODS: Quantitative real-time polymerase chain reaction of bronchoalveolar lavage samples were performed for CMV, HHV-6 and -7 in a prospective cohort of lung transplant recipients. A time-dependent Cox regression analysis was used to correlate the risk of BOS and acute rejection in patients with and without beta-herpesviruses infection. RESULTS: Ninety-three patients were included in the study over a period of 3 years. A total of 581 samples from bronchoalveolar lavage were obtained. Sixty-one patients (65.6%) had at least one positive result for one of the beta-herpesviruses: 48 patients (51.6%) for CMV and 19 patients (20.4%) for both HHV-6 and -7. Median peak viral load was 3419 copies/mL for CMV, 258 copies/mL for HHV-6, and 665 copies/mL for HHV-7. Acute rejection (>or=grade 2) occurred in 46.2% and BOS (>or=stage 1) in 19.4% of the patients. In the Cox regression model the relative risk of acute rejection or BOS was not increased in patients with any beta-herpesviruses reactivation. Acute rejection was the only independently associated risk factor for BOS. CONCLUSIONS: In lung transplant recipients receiving prolonged antiviral prophylaxis, reactivation of beta-herpesviruses within the allograft was common. However, despite high viral loads in many patients, virus replication was not associated with the development of rejection or BOS.

Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.

Optimization of Snow Drifting Mitigation and Control Methods for Iowa Conditions Part II, TR-626, 2015

Blowing and drifting of snow is a major concern for transportation efficiency and road safety in regions where their development is common. One common way to mitigate snow drift on roadways is to install plastic snow fences. Correct design of snow fences is critical for road safety and maintaining the roads open during winter in the US Midwest and other states affected by large snow events during the winter season and to maintain costs related to accumulation of snow on the roads and repair of roads to minimum levels. Of critical importance for road safety is the protection against snow drifting in regions with narrow rights of way, where standard fences cannot be deployed at the recommended distance from the road. Designing snow fences requires sound engineering judgment and a thorough evaluation of the potential for snow blowing and drifting at the construction site. The evaluation includes site-specific design parameters typically obtained with semi-empirical relations characterizing the local transport conditions. Among the critical parameters involved in fence design and assessment of their post-construction efficiency is the quantification of the snow accumulation at fence sites. The present study proposes a joint experimental and numerical approach to monitor snow deposits around snow fences, quantitatively estimate snow deposits in the field, asses the efficiency and improve the design of snow fences. Snow deposit profiles were mapped using GPS based real-time kinematic surveys (RTK) conducted at the monitored field site during and after snow storms. The monitored site allowed testing different snow fence designs under close to identical conditions over four winter seasons. The study also discusses the detailed monitoring system and analysis of weather forecast and meteorological conditions at the monitored sites. A main goal of the present study was to assess the performance of lightweight plastic snow fences with a lower porosity than the typical 50% porosity used in standard designs of such fences. The field data collected during the first winter was used to identify the best design for snow fences with a porosity of 50%. Flow fields obtained from numerical simulations showed that the fence design that worked the best during the first winter induced the formation of an elongated area of small velocity magnitude close to the ground. This information was used to identify other candidates for optimum design of fences with a lower porosity. Two of the designs with a fence porosity of 30% that were found to perform well based on results of numerical simulations were tested in the field during the second winter along with the best performing design for fences with a porosity of 50%. Field data showed that the length of the snow deposit away from the fence was reduced by about 30% for the two proposed lower-porosity (30%) fence designs compared to the best design identified for fences with a porosity of 50%. Moreover, one of the lower-porosity designs tested in the field showed no significant snow deposition within the bottom gap region beneath the fence. Thus, a major outcome of this study is to recommend using plastic snow fences with a porosity of 30%. It is expected that this lower-porosity design will continue to work well for even more severe snow events or for successive snow events occurring during the same winter. The approach advocated in the present study allowed making general recommendations for optimizing the design of lower-porosity plastic snow fences. This approach can be extended to improve the design of other types of snow fences. Some preliminary work for living snow fences is also discussed. Another major contribution of this study is to propose, develop protocols and test a novel technique based on close range photogrammetry (CRP) to quantify the snow deposits trapped snow fences. As image data can be acquired continuously, the time evolution of the volume of snow retained by a snow fence during a storm or during a whole winter season can, in principle, be obtained. Moreover, CRP is a non-intrusive method that eliminates the need to perform man-made measurements during the storms, which are difficult and sometimes dangerous to perform. Presently, there is lots of empiricism in the design of snow fences due to lack of data on fence storage capacity on how snow deposits change with the fence design and snow storm characteristics and in the estimation of the main parameters used by the state DOTs to design snow fences at a given site. The availability of such information from CRP measurements should provide critical data for the evaluation of the performance of a certain snow fence design that is tested by the IDOT. As part of the present study, the novel CRP method is tested at several sites. The present study also discusses some attempts and preliminary work to determine the snow relocation coefficient which is one of the main variables that has to be estimated by IDOT engineers when using the standard snow fence design software (Snow Drift Profiler, Tabler, 2006). Our analysis showed that standard empirical formulas did not produce reasonable values when applied at the Iowa test sites monitored as part of the present study and that simple methods to estimate this variable are not reliable. The present study makes recommendations for the development of a new methodology based on Large Scale Particle Image Velocimetry that can directly measure the snow drift fluxes and the amount of snow relocated by the fence.

Intraneuronal angiotensinergic system in rat and human dorsal root ganglia.

To elucidate the local formation of angiotensin II (Ang II) in the neurons of sensory dorsal root ganglia (DRG), we studied the expression of angiotensinogen (Ang-N)-, renin-, angiotensin converting enzyme (ACE)- and cathepsin D-mRNA, and the presence of protein renin, Ang II, Substance P and calcitonin gene-related peptide (CGRP) in the rat and human thoracic DRG. Quantitative real time PCR (qRT-PCR) studies revealed that rat DRG expressed substantial amounts of Ang-N- and ACE mRNA, while renin mRNA as well as the protein renin were untraceable. Cathepsin D-mRNA and cathepsin D-protein were detected in the rat DRG indicating the possibility of existence of pathways alternative to renin for Ang I formation. Angiotensin peptides were successfully detected with high performance liquid chromatography and radioimmunoassay in human DRG extracts. In situ hybridization in rat DRG confirmed additionally expression of Ang-N mRNA in the cytoplasm of numerous neurons. Intracellular Ang II staining could be shown in number of neurons and their processes in both the rat and human DRG. Interestingly we observed neuronal processes with angiotensinergic synapses en passant, colocalized with synaptophysin, within the DRG. In the DRG, we also identified by qRT-PCR, expression of Ang II receptor AT(1A) and AT(2)-mRNA while AT(1B)-mRNA was not traceable. In some neurons Substance P and CGRP were found colocalized with Ang II. The intracellular localization and colocalization of Ang II with Substance P and CGRP in the DRG neurons may indicate a participation and function of Ang II in the regulation of nociception. In conclusion, these results suggest that Ang II may be produced locally in the neurons of rat and human DRG and act as a neurotransmitter.

A hyperactive quantitative trait locus allele of Arabidopsis BRX contributes to natural variation in root growth vigor.

Quantitative trait loci analysis of natural Arabidopsis thaliana accessions is increasingly exploited for gene isolation. However, to date this has mostly revealed deleterious mutations. Among them, a loss-of-function allele identified the root growth regulator BREVIS RADIX (BRX). Here we present evidence that BRX and the paralogous BRX-LIKE (BRXL) genes are under selective constraint in monocotyledons as well as dicotyledons. Unexpectedly, however, whereas none of the Arabidopsis orthologs except AtBRXL1 could complement brx null mutants when expressed constitutively, nearly all monocotyledon BRXLs tested could. Thus, BRXL proteins seem to be more diversified in dicotyledons than in monocotyledons. This functional diversification was correlated with accelerated rates of sequence divergence in the N-terminal regions. Population genetic analyses of 30 haplotypes are suggestive of an adaptive role of AtBRX and AtBRXL1. In two accessions, Lc-0 and Lov-5, seven amino acids are deleted in the variable region between the highly conserved C-terminal, so-called BRX domains. Genotyping of 42 additional accessions also found this deletion in Kz-1, Pu2-7, and Ws-0. In segregating recombinant inbred lines, the Lc-0 allele (AtBRX(Lc-0)) conferred significantly enhanced root growth. Moreover, when constitutively expressed in the same regulatory context, AtBRX(Lc-0) complemented brx mutants more efficiently than an allele without deletion. The same was observed for AtBRXL1, which compared with AtBRX carries a 13 amino acid deletion that encompasses the deletion found in AtBRX(Lc-0). Thus, the AtBRX(Lc-0) allele seems to contribute to natural variation in root growth vigor and provides a rare example of an experimentally confirmed, hyperactive allelic variant.

Differential expression of 240 kDa ConA-binding glycoprotein in vitro and in vivo detected by immunochemical methods.

The expression of the 240 ConA-binding glycoprotein (240 kDa), a marker of synaptic junctions isolated from the rat cerebellum, was studied by immunocytochemical techniques in forebrain and cerebellum from rat and chicken, and in chick dorsal root ganglia. Parallel studies were carried out either on tissue sections or in dissociated cell cultures. In all cases non neuronal cells were not immunostained. The tissue sections of cerebellum from rat and chick exhibited 240 kDa glycoprotein immunoreactivity, especially in the molecular layer, while the forebrain sections from rat and chick did not show any significant immunostaining. In contrast, in dissociated forebrain cell cultures, all neuronal cells expressed 240 kDa glycoprotein immunoreactivity, while glial cells remained totally unlabelled. In tissue sections of dorsal root ganglion (DRG), sensory neurons expressed the 240 kDa only after the embryonic day (E 10). A large number of small neurons in the dorsomedial part of DRG were immunostained with 240 kDa glycoprotein antiserum, whereas only a small number of neurons in the ventrolateral part of the ganglia displayed 240 kDa immunoreactivity. In dissociated DRG cells cultures (mixed or neuron-enriched DRG cell cultures) all the neuronal perikarya but not their processes were stained. These studies indicate that 240 kDa glycoprotein expression is completely modified in cultures of neurons of CNS or PNS since the antigen becomes synthetized in high amount by all cells independent of synapse formation. This demonstrates that the expression of 240 kDa is controlled by the cell environment.

Sieve Analysis of Combined Aggregate Samples by Different Test Methods, MLR-84-05, 1982

This past winter the sieve analysis of combined aggregate was investigated. This study was given No. 26 by the Central Laboratory. The purpose of this work was to try and develop a sieve analysis procedure for combined aggregate which is less time consuming and has the same accuracy as the method described in I.M. 304. In an attempt to use a variety of aggregates for this investigation, a request was made to each District Materials Office to obtain at least 3 different combined aggregate samples in their respective districts. At the same time it was also requested that the field technician test these samples, prior to submitting them to the Central Laboratory. The field technician was instructed to test each sample as described in method I.M. 304 and also by a modified AASHTO T27 method which will be identified in the report as Method A. The modified AASHTO Method A was identical to T27 with the exception that a smaller sample is used for testing. The field technicians submitted the samples, test results and also comments regarding the modified AASHTO procedure. The general comments of the modified AASHTO procedure were: The method was much simpler to follow; however, it took about the same amount of time so there was no real advantage. After reviewing AASHTO T27, T164, I.M. 304 and Report No. FHWA-RD-77-53 another test method was purposed. Report No. FHWA-RD-77-53 is a report prepared by FHWA from data they gathered concerning control practices and shortcut or alternative test methods for aggregate gradation. A second test method was developed which also was very similar to AASHTO T27, The test procedure for this method is attached and is identified as Method B. The following is a summary of test results submitted by the Field Technicians and obtained by the aggregate section of the Central Laboratory.

Enhanced-reality video fluorescence: a real-time assessment of intestinal viability.

OBJECTIVE: Our aim was to evaluate a fluorescence-based enhanced-reality system to assess intestinal viability in a laparoscopic mesenteric ischemia model. MATERIALS AND METHODS: A small bowel loop was exposed, and 3 to 4 mesenteric vessels were clipped in 6 pigs. Indocyanine green (ICG) was administered intravenously 15 minutes later. The bowel was illuminated with an incoherent light source laparoscope (D-light-P, KarlStorz). The ICG fluorescence signal was analyzed with Ad Hoc imaging software (VR-RENDER), which provides a digital perfusion cartography that was superimposed to the intraoperative laparoscopic image [augmented reality (AR) synthesis]. Five regions of interest (ROIs) were marked under AR guidance (1, 2a-2b, 3a-3b corresponding to the ischemic, marginal, and vascularized zones, respectively). One hour later, capillary blood samples were obtained by puncturing the bowel serosa at the identified ROIs and lactates were measured using the EDGE analyzer. A surgical biopsy of each intestinal ROI was sent for mitochondrial respiratory rate assessment and for metabolites quantification. RESULTS: Mean capillary lactate levels were 3.98 (SD = 1.91) versus 1.05 (SD = 0.46) versus 0.74 (SD = 0.34) mmol/L at ROI 1 versus 2a-2b (P = 0.0001) versus 3a-3b (P = 0.0001), respectively. Mean maximal mitochondrial respiratory rate was 104.4 (±21.58) pmolO2/second/mg at the ROI 1 versus 191.1 ± 14.48 (2b, P = 0.03) versus 180.4 ± 16.71 (3a, P = 0.02) versus 199.2 ± 25.21 (3b, P = 0.02). Alanine, choline, ethanolamine, glucose, lactate, myoinositol, phosphocholine, sylloinositol, and valine showed statistically significant different concentrations between ischemic and nonischemic segments. CONCLUSIONS: Fluorescence-based AR may effectively detect the boundary between the ischemic and the vascularized zones in this experimental model.

Navigator-gated and real-time motion corrected free-breathing MR Imaging of myocardial late enhancement.

PURPOSE: A new magnetic resonance imaging approach for detection of myocardial late enhancement during free-breathing was developed. METHODS AND RESULTS: For suppression of respiratory motion artifacts, a prospective navigator technology including real-time motion correction and a local navigator restore was implemented. Subject specific inversion times were defined from images with incrementally increased inversion times acquired during a single dynamic scout navigator-gated and real-time motion corrected free-breathing scan. Subsequently, MR-imaging of myocardial late enhancement was performed with navigator-gated and real-time motion corrected adjacent short axis and long axis (two, three and four chamber) views. This alternative approach was investigated in 7 patients with history of myocardial infarction 12 min after i. v. administration of 0.2 mmol/kg body weight gadolinium-DTPA. CONCLUSION: With the presented navigator-gated and real-time motion corrected sequence for MR-imaging of myocardial late enhancement data can be completely acquired during free-breathing. Time constraints of a breath-hold technique are abolished and optimized patient specific inversion time is ensured.

Detection of Leishmania RNA virus in Leishmania parasites.

BACKGROUND: Patients suffering from cutaneous leishmaniasis (CL) caused by New World Leishmania (Viannia) species are at high risk of developing mucosal (ML) or disseminated cutaneous leishmaniasis (DCL). After the formation of a primary skin lesion at the site of the bite by a Leishmania-infected sand fly, the infection can disseminate to form secondary lesions. This metastatic phenotype causes significant morbidity and is often associated with a hyper-inflammatory immune response leading to the destruction of nasopharyngeal tissues in ML, and appearance of nodules or numerous ulcerated skin lesions in DCL. Recently, we connected this aggressive phenotype to the presence of Leishmania RNA virus (LRV) in strains of L. guyanensis, showing that LRV is responsible for elevated parasitaemia, destructive hyper-inflammation and an overall exacerbation of the disease. Further studies of this relationship and the distribution of LRVs in other Leishmania strains and species would benefit from improved methods of viral detection and quantitation, especially ones not dependent on prior knowledge of the viral sequence as LRVs show significant evolutionary divergence. METHODOLOGY/PRINCIPAL FINDINGS: This study reports various techniques, among which, the use of an anti-dsRNA monoclonal antibody (J2) stands out for its specific and quantitative recognition of dsRNA in a sequence-independent fashion. Applications of J2 include immunofluorescence, ELISA and dot blot: techniques complementing an arsenal of other detection tools, such as nucleic acid purification and quantitative real-time-PCR. We evaluate each method as well as demonstrate a successful LRV detection by the J2 antibody in several parasite strains, a freshly isolated patient sample and lesion biopsies of infected mice. CONCLUSIONS/SIGNIFICANCE: We propose that refinements of these methods could be transferred to the field for use as a diagnostic tool in detecting the presence of LRV, and potentially assessing the LRV-related risk of complications in cutaneous leishmaniasis.

Cross-country differences in disclosure quality: a study of fair value disclosures by european real estate companies

Companies are under IAS 40 required to report fair values of investment properties on the balance sheet or to disclose them in the notes. The standard requires also that companies have to disclose the methods and significant assumptions applied in determining fair values of investment properties. However, IAS 40 does not include any illustrative examples or other guidance on how to apply the disclosure requirements. We use a sample with publicly traded companies from the real estate sector in the EU. We find that a majority of the companies use income based methods for the measurement of fair values but there are considerable cross-country variations in the level of disclosures about the assumptions used in determining fair values. More specifically, we find that Scandinavian and German origin companies disclose more than French and English origin companies. We also test whether disclosure quality is associated with enforcement quality measured with the “Rule of Law” index according to Kaufmann et al. (2010), and associated with a secrecy- versus transparency-measure based on Gray (1988). We find a positive association between disclosure and earnings quality and a negative association with secrecy.

Human disease and drug pharmacology, complex as real life

In the past decades drug discovery practice has escaped from the complexity of the formerly used phenotypic screening in animals to focus on assessing drug effects on isolated protein targets in the search for drugs that exclusively and potently hit one selected target, thought to be critical for a given disease, while not affecting at all any other target to avoid the occurrence of side-effects. However, reality does not conform to these expectations, and, conversely, this approach has been concurrent with increased attrition figures in late-stage clinical trials, precisely due to lack of efficacy and safety. In this context, a network biology perspective of human disease and treatment has burst into the drug discovery scenario to bring it back to the consideration of the complexity of living organisms and particularly of the (patho)physiological environment where protein targets are (mal)functioning and where drugs have to exert their restoring action. Under this perspective, it has been found that usually there is not one but several disease-causing genes and, therefore, not one but several relevant protein targets to be hit, which do not work on isolation but in a highly interconnected manner, and that most known drugs are inherently promiscuous. In this light, the rationale behind the currently prevailing single-target-based drug discovery approach might even seem a Utopia, while, conversely, the notion that the complexity of human disease must be tackled with complex polypharmacological therapeutic interventions constitutes a difficult-torefuse argument that is spurring the development of multitarget therapies.

Identification of reference genes for expression analysis by real-time quantitative PCR in drought-stressed soybean

The objective of this work was to validate, by quantitative PCR in real time (RT-qPCR), genes to be used as reference in studies of gene expression in soybean in drought-stressed trials. Four genes commonly used in soybean were evaluated: Gmβ-actin, GmGAPDH, GmLectin and GmRNAr18S. Total RNA was extracted from six samples: three from roots in a hydroponic system with different drought intensities (0, 25, 50, 75 and 100 minutes of water stress), and three from leaves of plants grown in sand with different soil moistures (15, 5 and 2.5% gravimetric humidity). The raw cycle threshold (Ct) data were analyzed, and the efficiency of each primer was calculated for an overall analysis of the Ct range among the different samples. The GeNorm application was used to evaluate the best reference gene, according to its stability. The GmGAPDH was the least stable gene, with the highest mean values of expression stability (M), and the most stable genes, with the lowest M values, were the Gmβ-actin and GmRNAr18S, when both root and leaves samples were tested. These genes can be used in RT-qPCR as reference gene for expression analysis.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.