High Validation Rate Research Articles

Application of serum protein profiling in diagnosis, prognosis and evaluation of curative effect of pancreatic adenocarcinoma

To establish decision tree and logistic regression classification models for diagnosing pancreatic adenocarcinoma (PaCa) and for screening serum biomarkers related to evaluation of different stages and curative effects. Serum samples obtained from subjects with pancreatic adenocarcinoma (n = 58) and normal pancreas (n = 51) were applied to strong anion exchange chromatography (SAX2) chips for protein profiling by SELDI-TOF-MS to screen multiple serum biomarkers. Biomarker Wizard software and several statistical methods including algorithm of decision tree, logistic regression and ROC curves were used to construct the decision tree or logistic regression classification models. Average of 61 mass peaks were detected at the molecular range of 2000-30,000, ten decision trees with the highest cross validation rate were chosen to construct the classification models, which can differentiate PaCa from normal pancreas with a sensitivity of 83.3% and a specificity of 100%. Logistic regression was used to achieve the AUC (0.976 +/- 0.011, P < 0.001) with a sensitivity of 77.6% - 91.4% and a specificity of 92.2% - 100%. Six mass peaks were combined by logistic regression to achieve the AUC 0.897 +/- 0.054, 0.978 +/- 0.021 and 0.792 +/- 0.107 (P < 0.05) in the three groups (patients at stage I and II, stage II and III, stage III and IV). One mass peak (M/Z 4,016) was screened (P < 0.05) significantly between the preoperative and postoperative PaCa samples and the intensity decreased weeks after operation. Decision tree and logistic regression classification models of the mass peaks screened by SELDI-TOF-MS serum profiling can be used to differentiate pancreatic adenocarcinoma from normal pancreas, and is superior to CA 199. The detected mass peaks are helpful for the evaluation of curative effect and prognosis of pancreatic adenocarcinoma.

Exon Array Analysis using re-defined probe sets results in reliable identification of alternatively spliced genes in non-small cell lung cancer

BackgroundTreatment of non-small cell lung cancer with novel targeted therapies is a major unmet clinical need. Alternative splicing is a mechanism which generates diverse protein products and is of functional relevance in cancer.ResultsIn this study, a genome-wide analysis of the alteration of splicing patterns between lung cancer and normal lung tissue was performed. We generated an exon array data set derived from matched pairs of lung cancer and normal lung tissue including both the adenocarcinoma and the squamous cell carcinoma subtypes. An enhanced workflow was developed to reliably detect differential splicing in an exon array data set. In total, 330 genes were found to be differentially spliced in non-small cell lung cancer compared to normal lung tissue. Microarray findings were validated with independent laboratory methods for CLSTN1, FN1, KIAA1217, MYO18A, NCOR2, NUMB, SLK, SYNE2, TPM1, (in total, 10 events) and ADD3, which was analysed in depth. We achieved a high validation rate of 69%. Evidence was found that the activity of FOX2, the splicing factor shown to cause cancer-specific splicing patterns in breast and ovarian cancer, is not altered at the transcript level in several cancer types including lung cancer.ConclusionsThis study demonstrates how alternatively spliced genes can reliably be identified in a cancer data set. Our findings underline that key processes of cancer progression in NSCLC are affected by alternative splicing, which can be exploited in the search for novel targeted therapies.

Randomized Controlled Trial of the Prevent— Teach—Reinforce (PTR) Tertiary Intervention for Students With Problem Behaviors

Although there is literature supporting the effectiveness of tertiary behavioral supports, the majority of the studies have been conducted with single-subject designs. The Prevent—Teach—Reinforce (PTR) model is a standardized model of a school-based tertiary intervention. This study reports initial results from a randomized controlled trial to compare whether the PTR model, as implemented by typical school personnel, is more effective than interventions typically used (i.e., services as usual). To date, 245 students in Grades K-8 have been enrolled in the study, and preliminary results show that students who received the PTR intervention had significantly higher social skills and academic engaged time and significantly lower problem behavior when compared with students who received services as usual. Teachers gave high social validity ratings to the intervention. Implications for widescale school adoption are discussed.

Genome-wide discovery of functional transcription factor binding sites by comparative genomics: The case of Stat3

The identification of direct targets of transcription factors is a key problem in the study of gene regulatory networks. However, the use of high throughput experimental methods, such as ChIP-chip and ChIP-sequencing, is limited by their high cost and strong dependence on cellular type and context. We developed a computational method for the genome-wide identification of functional transcription factor binding sites based on positional weight matrices, comparative genomics, and gene expression profiling. The method was applied to Stat3, a transcription factor playing crucial roles in inflammation, immunity and oncogenesis, and able to induce distinct subsets of target genes in different cell types or conditions. A newly generated positional weight matrix enabled us to assign affinity scores of high specificity, as measured by EMSA competition assays. Phylogenetic conservation with 7 vertebrate species was used to select the binding sites most likely to be functional. Validation was carried out on predicted sites within genes identified as differentially expressed in the presence or absence of Stat3 by microarray analysis. Twelve of the fourteen sites tested were bound by Stat3 in vivo, as assessed by Chromatin Immunoprecipitation, allowing us to identify 9 Stat3 transcriptional targets. Given its high validation rate, and the availability of large transcription factor-dependent gene expression datasets obtained under diverse experimental conditions, our approach appears to be a valid alternative to high-throughput experimental assays for the discovery of novel direct targets of transcription factors.

SNP discovery in swine by reduced representation and high throughput pyrosequencing

BackgroundRelatively little information is available for sequence variation in the pig. We previously used a combination of short read (25 base pair) high-throughput sequencing and reduced genomic representation to discover > 60,000 single nucleotide polymorphisms (SNP) in cattle, but the current lack of complete genome sequence limits this approach in swine. Longer-read pyrosequencing-based technologies have the potential to overcome this limitation by providing sufficient flanking sequence information for assay design. Swine SNP were discovered in the present study using a reduced representation of 450 base pair (bp) porcine genomic fragments (approximately 4% of the swine genome) prepared from a pool of 26 animals relevant to current pork production, and a GS-FLX instrument producing 240 bp reads.ResultsApproximately 5 million sequence reads were collected and assembled into contigs having an overall observed depth of 7.65-fold coverage. The approximate minor allele frequency was estimated from the number of observations of the alternate alleles. The average coverage at the SNPs was 12.6-fold. This approach identified 115,572 SNPs in 47,830 contigs. Comparison to partial swine genome draft sequence indicated 49,879 SNP (43%) and 22,045 contigs (46%) mapped to a position on a sequenced pig chromosome and the distribution was essentially random. A sample of 176 putative SNPs was examined and 168 (95.5%) were confirmed to have segregating alleles; the correlation of the observed minor allele frequency (MAF) to that predicted from the sequence data was 0.58.ConclusionThe process was an efficient means to identify a large number of porcine SNP having high validation rate to be used in an ongoing international collaboration to produce a highly parallel genotyping assay for swine. By using a conservative approach, a robust group of SNPs were detected with greater confidence and relatively high MAF that should be suitable for genotyping in a wide variety of commercial populations.

Gene expression patterns within cell lines are predictive of chemosensitivity

BackgroundThe NCI has undertaken a twenty-year project to characterize compound sensitivity patterns in a selected set of sixty tumor derived cell lines. Previous studies have explored the relationship between compound sensitivity patterns to gene expression, protein expression, and DNA copy number for these same cell lines. A strong correlation between the pattern of expression of a biomarker and sensitivity to a compound could suggest a clinically interesting biological relationship between the two.ResultsWe isolated RNA's and measured expression of 40000 genes using cDNA microarrays from the fifty-nine publicly available cell lines. Analysis of this data set in comparison with published gene expression data sets demonstrates a high degree of reproducibility in expression level measurements even using completely independent RNA preparations and array technologies. Using the fifty-nine cell lines for discovery and an additional seven cell lines for which extensive compound sensitivity data were available as a test set, we determined that gene-compound pairs with a correlation coefficient above 0.6 had a false discovery rate of approximately 5%. Large scale features of the gene expression and chemosensitivity data, such as tissue of origin and other physiological factors, did not seem to explain the majority of correlations between gene and compound patterns.ConclusionA comparison of gene expression and compound sensitivity in panels of cell lines was demonstrated to have a relatively high validation and low false discovery rate supporting the use of this approach and datasets for identifying candidate biomarkers and targeted biologically active compounds.

Effects of the Behavior Education Program (BEP) on Office Discipline Referrals of Elementary School Students

The Behavior Education Program (BEP; Crone et al., 2004) is a modified check-in, check-out intervention implemented with students who are at risk for more severe problem behaviors. The purpose of this study was to evaluate the effects of the BEP on problem behavior with 12 elementary school students. Results indicated that the BEP was implemented with high fidelity, led to a decrease in office discipline referrals for the majority of students who received the intervention, and had high social validity ratings. Limitations of the current study are presented, along with suggestions for future research.

Nonsynonymous SNPs: validation characteristics, derived allele frequency patterns, and suggestive evidence for natural selection

We experimentally investigated more than 1,200 entries in dbSNP that would change amino-acids (nsSNPs), using various subsets of DNA samples drawn from 18 global populations (approximately 1,000 subjects in total). First, we mined the data for any SNP features that correlated with a high validation rate. Useful predictors of valid SNPs included multiple submissions to dbSNP, having a dbSNP validation statement, and being present in a low number of ESTs. Together, these features improved validation rates by almost 10-fold. Higher-abundance SNPs (e.g., T/C variants) also validated more frequently. Second, we considered derived alleles and noted a considerably (approximately 10%) increased average derived allele frequency (DAF) in Europeans vs. Africans, plus a further increase in some other populations. This was not primarily due to an SNP ascertainment bias, nor to the effects of natural selection. Instead, it can be explained as a drift-based, progressive increase in DAF that occurs over many generations and becomes exaggerated during population bottlenecks. This observation could be used as the basis for novel DAF-based tests for comparing demographic histories. Finally, we considered individual marker patterns and identified 37 SNPs with allele frequency variance or FST values consistent with the effects of population-specific natural selection. Four particularly striking clusters of these markers were apparent, and three of these coincide with genes/regions from among only several dozen such domains previously suggested by others to carry signatures of selection.

Laser Diagnostics of Gun-Type Spray. Clustering and Compound-Cluster Combustion of Liquid Spray.

A concept of is proposed in order to investigate an applicability of group combustion theory to practical spray combustion, in which strong turbulent coherent vortex is formed and influenced spray behavior significantly. This turbulent coherent structure causes inhomogeneous droplet distribution and its population, and causes interphase exchange of properties and combustion under the effects of preferential interactions. In application of group combustion ; theory to practical spray combustion, these points were taken into account and phase Doppler measurement (PDA) data was analyzed : there are multiple clusters, characterized by their size and followabiliy (Stokes effect) ; clusters of different droplet sizes are produced at the same time in the flow field ; the turbulent scale on cluster formation should be considered by the droplet's inter-arrival time statistics. In this research, PDA measurement with high sampling-rates and high validation-rates was carried out by optimizing the PDA set-up parameters. The integral length scale of each size cluster and the inter-arrival time statistics of the droplets can be obtained, based on the instantaneous droplet velocities as well as, but also Stokes' number, cluster size and inter-arrival time. The size-classified group combustion number is evaluated by the experimental data to demonstrate the applicability of group combustion theory. The interaction between the turbulent coherent vortex and small droplets of less than 30μm generates essential clusters of the droplets and its combustion can be characterized by group combustion. The size of these clusters corresponds to the integral scale of the turbulent vortices. The effect of turbulent coherent structure on compound-cluster formation is examined and this effect is successfully evaluated by the Stokes effect.

Measurement of the local group combustion number of droplet clusters in a premixed spray stream

We have succeeled previously in the experimental observation of the group combustion behavior of spray flames by statistically and spectrally processing the light-emission signals from radicals together with the Mie-scattering signal from droplet clusters in a premixed spray flame. It was interesting that even uniformly premixed droplet streams burn in groups due to their eddy motion and preferential flame propagation, hence generating temporal and spatial variation in the scale of droplet clusters. In the present study, time-series signals of the light emission in OH and CH bands, the Mie scattering from droplets. and the size and velocity of droplets with a phase Doppler anemometer (PDA) were monitored simultaneously. The high data rate and high validation rate of PDA measurement accomplished by the optimized design of optics enabled us to distinguish instaneous charateristics of individual droplet clusters in the flame. Thus, we estimated the modified group combustion number Gc for individual droplet cluster using the measured mean separation distance between droplet centers and the total number of droplets for each droplet cluster. Note that Chiu et al. defined their original group combustion number for a quasi-steady laminar combustion of a cloud of equally spaced drops based on the theory of isolated droplet combustion. We examined the transition of group combustion mode of droplet clusters as a function of the distance from the burner port using Gc. It was found that the derived Gc values were concentrated within the range of the original diagram predicted by Chiu et al. The Gc value averaged over all droplet clusters passing a monitoring spot. c, fell within the range of external group combustion mode at the inital stage of combustion and moved to the range of internal group combustion mode as the evaporation and combustion of the cluster proceeded, which was in good accordance with the previous experimental observations.

Counselor trainees' explanations of behavior: attributions to traits, situations, and interaction.

Counselor trainees' views of generic causes of behavior were investigated. Thirty-seven counselor education graduate students were asked to assign validity ratings to seven possible explanations of what determines behavior. Participants were asked to make judgments either in reference to their own behavior or to someone else's behavior. The students assigned high validity ratings to an "interaction" explanation for behavior. Further, consistent with previous research findings that concern attributional processes, when counselor trainees explained their own behavior, they assigned relatively high ratings to external causes; when explaining others' behavior, they assigned relatively high validity ratings to internal causes.