Chromosomal Regions in Prostatic Carcinomas Studied by Comparative Genomic Hybridization, Hierarchical Cluster Analysis and Self-Organizing Feature Maps

Comparative genomic hybridization (CGH) is an established genetic method which enables a genome‐wide survey of chromosomal imbalances. For each chromosome region, one obtains the information whether there is a loss or gain of genetic material, or whether there is no change at that place. Therefore, large amounts of data quickly accumulate which must be put into a logical order. Cluster analysis can be used to assign individual cases (samples) to different clusters of cases, which are similar and where each cluster may be related to a different tumour biology. Another approach consists in a clustering of chromosomal regions by rewriting the original data matrix, where the cases are written as rows and the chromosomal regions as columns, in a transposed form. In this paper we applied hierarchical cluster analysis as well as two implementations of self‐organizing feature maps as classical and neuronal tools for cluster analysis of CGH data from prostatic carcinomas to such transposed data sets. Self‐organizing maps are artificial neural networks with the capability to form clusters on the basis of an unsupervised learning rule. We studied a group of 48 cases of incidental carcinomas, a tumour category which has not been evaluated by CGH before. In addition we studied a group of 50 cases of pT2N0‐tumours and a group of 20 pT3N0‐carcinomas. The results show in all case groups three clusters of chromosomal regions, which are (i) normal or minimally affected by losses and gains, (ii) regions with many losses and few gains and (iii) regions with many gains and few losses. Moreover, for the pT2N0‐ and pT3N0‐groups, it could be shown that the regions 6q, 8p and 13q lay all on the same cluster (associated with losses), and that the regions 9q and 20q belonged to the same cluster (associated with gains). For the incidental cancers such clear correlations could not be demonstrated

Chromosomal regions in prostatic carcinomas studied by comparative genomic hybridization, hierarchical cluster analysis and self-organizing feature maps, Anal

Abstract. Comparative genomic hybridization (CGH) is an established genetic method which enables a genome-wide survey of chromosomal imbalances. For each chromosome region, one obtains the information whether there is a loss or gain of genetic material, or whether there is no change at that place. Therefore, large amounts of data quickly accumulate which must be put into a logical order. Cluster analysis can be used to assign individual cases (samples) to different clusters of cases, which are similar and where each cluster may be related to a different tumour biology. Another approach consists in a clustering of chromosomal regions by rewriting the original data matrix, where the cases are written as rows and the chromosomal regions as columns, in a transposed form. In this paper we applied hierarchical cluster analysis as well as two implementations of self-organizing feature maps as classical and neuronal tools for cluster analysis of CGH data from prostatic carcinomas to such transposed data sets. Self-organizing maps are artificial neural networks with the capability to form clusters on the basis of an unsupervised learning rule. We studied a group of 48 cases of incidental carcinomas, a tumour category which has not been evaluated by CGH before. In addition we studied a group of 50 cases of pT2N0-tumours and a group of 20 pT3N0-carcinomas. The results show in all case groups three clusters of chromosomal regions, which are (i) normal or minimally affected by losses and gains, (ii) regions with many losses and few gains and (iii) regions with many gains and few losses. Moreover, for the pT2N0-and pT3N0-groups, it could be shown that the regions 6q, 8p and 13q lay all on the same cluster (associated with losses), and that the regions 9q and 20q belonged to the same cluster (associated with gains). For the incidental cancers such clear correlations could not be demonstrated

Quantification of cAMP and cGMP analogs in intact cells: pitfalls in enzyme immunoassays for cyclic nucleotides

Immunoassays are routinely used as research tools to measure intracellular cAMP and cGMP concentrations. Ideally, this application requires antibodies with high sensitivity and specificity. The present work evaluates the cross-reactivity of commercially available cyclic nucleotide analogs with two non-radioactive and one radioactive cAMP and cGMP immunoassay. Most of the tested cyclic nucleotide analogs showed low degree competition with the antibodies; however, with Rp-cAMPS, 8-Br-cGMP and 8-pCPT-cGMP, a strong cross-reactivity with the corresponding cAMP and cGMP, respectively, immunoassays was observed. The determined EIA-binding constants enabled the measurement of the intracellular cyclic nucleotide concentrations and revealed a time- and lipophilicity-dependent cell membrane permeability of the compounds in the range of 10–30% of the extracellular applied concentration, thus allowing a more accurate prediction of the intracellular analog levels in a given experiment

Registered replication report: a large multilab cross-cultural conceptual replication of Turri, Buckwalter, & Blouw (2015)

According to the Justified True Belief account of knowledge (JTB), a person can only truly know something if they have a belief that is both justified and true (i.e., knowledge is justified true belief). This account was challenged by Gettier (1963), who argued that JTB does not explain knowledge attributions in certain situations, later called Gettier-type cases, wherein a protagonist is justified in believing something to be true, but their belief was only correct due to luck. Lay people may not attribute knowledge to protagonists with justified but only luckily true beliefs. While some research has found evidence for these so-called Gettier intuitions (e.g., Machery et al., 2017a), Turri et al. (2015) found no evidence that participants attributed knowledge in a counterfeit-object Gettier-type case differently than in a matched case of justified true belief. In a large-scale, cross-cultural conceptual replication of Turri and colleagues’ (2015) Experiment 1 (N = 4,724) using a within-participants design and three vignettes across 19 geopolitical regions, we did find evidence for Gettier intuitions; participants were 1.86 times more likely to attribute knowledge to protagonists in standard cases of justified true belief than to protagonists in Gettier-type cases. These results suggest that Gettier intuitions may be detectable across different scenarios and cultural contexts. However, the size of the Gettier intuition effect did vary by vignette, and the Turri et al. (2015) vignette produced the smallest effect, which was similar in size to that observed in the original study. Differences across vignettes suggest epistemic intuitions may also depend on contextual factors unrelated to the criteria of knowledge, such as the characteristics of the protagonist being evaluated

Classification of Incidental Carcinoma of the Prostate Using Learning Vector Quantization and Support Vector Machines

The subclassification of incidental prostatic carcinoma into the categories T1a and T1b is of major prognostic and therapeutic relevance. In this paper an attempt was made to find out which properties mainly predispose to these two tumor categories, and whether it is possible to predict the category from a battery of clinical and histopathological variables using newer methods of multivariate data analysis. The incidental prostatic carcinomas of the decade 1990–99 diagnosed at our department were reexamined. Besides acquisition of routine clinical and pathological data, the tumours were scored by immunohistochemistry for proliferative activity and p53‐overexpression. Tumour vascularization (angiogenesis) and epithelial texture were investigated by quantitative stereology. Learning vector quantization (LVQ) and support vector machines (SVM) were used for the purpose of prediction of tumour category from a set of 10 input variables (age, Gleason score, preoperative PSA value, immunohistochemical scores for proliferation and p53‐overexpression, 3 stereological parameters of angiogenesis, 2 stereological parameters of epithelial texture). In a stepwise logistic regression analysis with the tumour categories T1a and T1b as dependent variables, only the Gleason score and the volume fraction of epithelial cells proved to be significant as independent predictor variables of the tumour category. Using LVQ and SVM with the information from all 10 input variables, more than 80 of the cases could be correctly predicted as T1a or T1b category with specificity, sensitivity, negative and positive predictive value from 74–92%. Using only the two significant input variables Gleason score and epithelial volume fraction, the accuracy of prediction was not worse. Thus, descriptive and quantitative texture parameters of tumour cells are of major importance for the extent of propagation in the prostate gland in incidental prostatic adenocarcinomas. Classical statistical tools and neuronal approaches led to consistent conclusions