Error detection and error memory in spatial navigation as reflected by electrodermal activity

The study investigated spatial navigation by means of electrodermal activity (EDA). Two groups of healthy subjects (group 1, age <38; group 2, age ≥38) were recorded during navigation through two 3-D virtual mazes differing in difficulty, that is, Maze Simple (MazeS) and Maze Complex (MazeC). Our results show (1) an effect of difficulty, that is, larger skin conductance responses (SCRs) and slower velocity profiles while navigating through MazeC as compared to MazeS. (2) An effect of age, that is, larger SCRs and faster velocity profiles in younger subjects (group 1) compared to older subjects (group 2). (3) An effect of maze region, that is, SCRs increased when subjects entered dead ends with group 1 (young group) decreasing in velocity, whereas group 2 (old group) increased in velocity. (4) And an error memory effect, that is, subjects who remembered an error at a given decision point (crossroads preceding dead ends in MazeC) from previous trials, and then if they did not repeat that error, elicited decreased SCRs as compared to subjects who did not remember and subsequently repeated an error. The latter aspect is the most impactful as it shows that EDA is able to reflect error detection and memory during spatial navigation. Our data designate EDA as suitable monitoring tool for identification and differentiation of the affective correlates underlying spatial navigation, which has recently attracted researchers' attention due to its increased use in 3-D virtual environment

Identification of common horsetail (<i>Equisetum arvense</i> L.; Equisetaceae) using Thin Layer Chromatography versus DNA barcoding

The global herbal products market has grown in recent years, making regulation of these products paramount for public healthcare. For instance, the common horsetail (Equisetum arvense L.) is used in numerous herbal products, but it can be adulterated with closely related species, especially E. palustre L. that can produce toxic alkaloids. As morphology-based identification is often difficult or impossible, the identification of processed material can be aided by molecular techniques. In this study, we explore two molecular identification techniques as methods of testing the purity of these products: a Thin Layer Chromatography approach (TLC-test) included in the European Pharmacopoeia and a DNA barcoding approach, used in recent years to identify material in herbal products. We test the potential of these methods for distinguishing and identifying these species using material from herbarium collections and commercial herbal products. We find that both methods can discriminate between the two species and positively identify E. arvense. The TLC-test is more cost- and time-efficient, but DNA barcoding is more powerful in determining the identity of adulterant species. Our study shows that, although DNA barcoding presents certain advantages, other established laboratory methods can perform as well or even better in confirming species’ identity in herbal products

MHC I Stabilizing Potential of Computer-Designed Octapeptides

Experimental results are presented for 180 in silico designed octapeptide sequences and their stabilizing effects on the major histocompatibility class I molecule H-2Kb. Peptide sequence design was accomplished by a combination of an ant colony optimization algorithm with artificial neural network classifiers. Experimental tests yielded nine H-2Kb stabilizing and 171 nonstabilizing peptides. 28 among the nonstabilizing octapeptides contain canonical motif residues known to be favorable for MHC I stabilization. For characterization of the area covered by stabilizing and non-stabilizing octapeptides in sequence space, we visualized the distribution of 100,603 octapeptides using a self-organizing map. The experimental results present evidence that the canonical sequence motives of the SYFPEITHI database on their own are insufficient for predicting MHC I protein stabilization

iTReX: Interactive exploration of mono- and combination therapy dose response profiling data

High throughput screening methods, measuring the sensitivity and resistance of tumor cells to drug treatments have been rapidly evolving. Not only do these screens allow correlating response profiles to tumor genomic features for developing novel predictors of treatment response, but they can also add evidence for therapy decision making in precision oncology. Recent analysis methods developed for either assessing single agents or combination drug efficacies enable quantification of dose-response curves with restricted symmetric fit settings. Here, we introduce iTReX, a user-friendly and interactive Shiny/R application, for both the analysis of mono- and combination therapy responses. The application features an extended version of the drug sensitivity score (DSS) based on the integral of an advanced five-parameter dose-response curve model and a differential DSS for combination therapy profiling. Additionally, iTReX includes modules that visualize drug target interaction networks and support the detection of matches between top therapy hits and the sample omics features to enable the identification of druggable targets and biomarkers. iTReX enables the analysis of various quantitative drug or therapy response readouts (e.g. luminescence, fluorescence microscopy) and multiple treatment strategies (drug treatments, radiation). Using iTReX we validate a cost-effective drug combination screening approach and reveal the application’s ability to identify potential sample-specific biomarkers based on drug target interaction networks. The iTReX web application is accessible at (https://itrex.kitz-heidelberg.de).Peer reviewe

MEDB-41. Identifying a subgroup of patients with early childhood sonic hedgehog-activated medulloblastoma with unfavorable prognosis after treatment with radiation-sparing regimens including intraventricular methotrexate [Abstract]

PURPOSE/METHODS: Clinical and molecular risk factors in 142 patients 3 years] 47% vs 85% [<1 year] vs 84% [1-3 years], p<0.001). No TP53 mutations were detected (n=47). DNA methylation classification identified three subgroups: SHH-1(v12.3) (n=39), SHH-2(v12.3) (n=19), and SHH-3(v12.3) (n=19), with distinct cytogenetic profiles (chromosome 2 gains in SHH-1(v12.3), very few alterations in SHH-2(v12.3), and chromosome 9q losses in SHH-3(v12.3)), age profiles (median age [years] SHH-1(v12.3): 1.7, SHH-2(v12.3): 0.9, SHH-3(v12.3): 3.0, p<0.001), and histological distribution (SHH-2(v12.3): 74% MBEN, SHH-1(v12.3)/SHH-3(v12.3): 77%/79% DMB, p<0.001). PFS was more unfavorable in patients with SHH-3(v12.3)-medulloblastoma (5-year PFS 53% vs 86% [SHH-1(v12.3)] vs 95% [SHH-2(v12.3)], p=0.002), which remained the only risk factor on multivariable Cox regression for PFS. OS was comparable (5-year OS 94% [SHH-3(v12.3)] vs 97% [SHH-1(v12.3)] vs 100% [SHH-2(v12.3)], p=0.6). 8/9 patients with SHH-3(v12.3)-medulloblastoma received radiotherapy at relapse (6 craniospinal, 2 local [1 Gorlin syndrome, 1 BRCA2 germline mutation], 1 no radiotherapy [Gorlin syndrome]). CONCLUSION: We identify patients with an increased risk of relapse when treated with radiation-sparing approaches among children with early childhood SHH-medulloblastoma. If these tumors differ from SHH-3-medulloblastoma typically described in older children remains to be verified. Treatment recommendations need to consider cancer predisposition syndromes

Second-generation molecular subgrouping of medulloblastoma: an international meta-analysis of Group 3 and Group 4 subtypes

In 2012, an international consensus paper reported that medulloblastoma comprises four molecular subgroups (WNT, SHH, Group 3, and Group 4), each associated with distinct genomic features and clinical behavior. Independently, multiple recent reports have defined further intra-subgroup heterogeneity in the form of biologically and clinically relevant subtypes. However, owing to differences in patient cohorts and analytical methods, estimates of subtype number and definition have been inconsistent, especially within Group 3 and Group 4. Herein, we aimed to reconcile the definition of Group 3/Group 4 MB subtypes through the analysis of a series of 1501 medulloblastomas with DNA-methylation profiling data, including 852 with matched transcriptome data. Using multiple complementary bioinformatic approaches, we compared the concordance of subtype calls between published cohorts and analytical methods, including assessments of class-definition confidence and reproducibility. While the lowest complexity solutions continued to support the original consensus subgroups of Group 3 and Group 4, our analysis most strongly supported a definition comprising eight robust Group 3/Group 4 subtypes (types I–VIII). Subtype II was consistently identified across all component studies, while all others were supported by multiple class-definition methods. Regardless of analytical technique, increasing cohort size did not further increase the number of identified Group 3/Group 4 subtypes. Summarizing the molecular and clinico-pathological features of these eight subtypes indicated enrichment of specific driver gene alterations and cytogenetic events amongst subtypes, and identified highly disparate survival outcomes, further supporting their biological and clinical relevance. Collectively, this study provides continued support for consensus Groups 3 and 4 while enabling robust derivation of, and categorical accounting for, the extensive intertumoral heterogeneity within Groups 3 and 4, revealed by recent high-resolution subclassification approaches. Furthermore, these findings provide a basis for application of emerging methods (e.g., proteomics/single-cell approaches) which may additionally inform medulloblastoma subclassification. Outputs from this study will help shape definition of the next generation of medulloblastoma clinical protocols and facilitate the application of enhanced molecularly guided risk stratification to improve outcomes and quality of life for patients and their families

Genome-scale DNA methylation mapping of clinical samples at single-nucleotide resolution

August 1, 2010Bisulfite sequencing measures absolute levels of DNA methylation at single-nucleotide resolution, providing a robust platform for molecular diagnostics. Here, we optimize bisulfite sequencing for genome-scale analysis of clinical samples. Specifically, we outline how restriction digestion targets bisulfite sequencing to hotspots of epigenetic regulation; we show that 30ng of DNA are sufficient for genome-scale analysis; we demonstrate that our protocol works well on formalinfixed, paraffin-embedded (FFPE) samples; and we describe a statistical method for assessing significance of altered DNA methylation patterns.National Institutes of Health (U.S.) (Grant R01HG004401)National Institutes of Health (U.S.) (Grant U54HG03067)National Institutes of Health (U.S.) (Grant U01ES017155

Drug sensitivity profiling of 3D tumor tissue cultures in the pediatric precision oncology program INFORM

The international precision oncology program INFORM enrolls relapsed/refractory pediatric cancer patients for comprehensive molecular analysis. We report a two-year pilot study implementing ex vivo drug sensitivity profiling (DSP) using a library of 75–78 clinically relevant drugs. We included 132 viable tumor samples from 35 pediatric oncology centers in seven countries. DSP was conducted on multicellular fresh tumor tissue spheroid cultures in 384-well plates with an overall mean processing time of three weeks. In 89 cases (67%), sufficient viable tissue was received; 69 (78%) passed internal quality controls. The DSP results matched the identified molecular targets, including BRAF, ALK, MET, and TP53 status. Drug vulnerabilities were identified in 80% of cases lacking actionable (very) high-evidence molecular events, adding value to the molecular data. Striking parallels between clinical courses and the DSP results were observed in selected patients. Overall, DSP in clinical real-time is feasible in international multicenter precision oncology programs