The Effects of Differing Teaching Concepts on Pupils’ Attention and Disruptive Behaviour

Lehrer leiden in zunehmendem Maße unter Disziplinstörungen. Die Ursachen sehen sie beinahe ausschließlich in außerschulischen Faktoren. Die vorliegende Untersuchung geht der Frage nach, ob nicht die Art der Unterrichtsgestaltung selbst in einem engen Zusammenhang steht mit der Intensität der Aufmerksamkeit so wie dem Ausmaß des Störverhaltens der Schüler und damit auch mit der Belastung des Lehrers durch die Vergabe von Sanktionen. Es zeigen sich in der Tat große Unterschiede im Verhalten ein und derselben Klasse (2. Schülerjahrgang), wenn zwei Lehrer mit verschiedenem Lehrkonzept unterrichten. (DIPF/Orig.)Teachers tend to suffer increasingly from discipline problems. The causes are seen almost exclusively in external factors. The present study asks whether it is not the type of teaching-method itself that is closely related to the degree of attention and the extent of disruptive behaviour, and consequently also to the strain on the teacher through the issuing of sanctions. Great differences in the behaviour of one and the same dass (second year, seven year olds) do indeed appear when two teachers employ different methods

RGG: A general GUI Framework for R scripts

<p>Abstract</p> <p>Background</p> <p>R is the leading open source statistics software with a vast number of biostatistical and bioinformatical analysis packages. To exploit the advantages of R, extensive scripting/programming skills are required.</p> <p>Results</p> <p>We have developed a software tool called R GUI Generator (RGG) which enables the easy generation of Graphical User Interfaces (GUIs) for the programming language R by adding a few Extensible Markup Language (XML) – tags. RGG consists of an XML-based GUI definition language and a Java-based GUI engine. GUIs are generated in runtime from defined GUI tags that are embedded into the R script. User-GUI input is returned to the R code and replaces the XML-tags. RGG files can be developed using any text editor. The current version of RGG is available as a stand-alone software (RGGRunner) and as a plug-in for JGR.</p> <p>Conclusion</p> <p>RGG is a general GUI framework for R that has the potential to introduce R statistics (R packages, built-in functions and scripts) to users with limited programming skills and helps to bridge the gap between R developers and GUI-dependent users. RGG aims to abstract the GUI development from individual GUI toolkits by using an XML-based GUI definition language. Thus RGG can be easily integrated in any software. The RGG project further includes the development of a web-based repository for RGG-GUIs. RGG is an open source project licensed under the Lesser General Public License (LGPL) and can be downloaded freely at <url>http://rgg.r-forge.r-project.org</url></p

Identification of human pathogens isolated from blood using microarray hybridisation and signal pattern recognition

<p>Abstract</p> <p>Background</p> <p>Pathogen identification in clinical routine is based on the cultivation of microbes with subsequent morphological and physiological characterisation lasting at least 24 hours. However, early and accurate identification is a crucial requisite for fast and optimally targeted antimicrobial treatment. Molecular biology based techniques allow fast identification, however discrimination of very closely related species remains still difficult.</p> <p>Results</p> <p>A molecular approach is presented for the rapid identification of pathogens combining PCR amplification with microarray detection. The DNA chip comprises oligonucleotide capture probes for 25 different pathogens including Gram positive cocci, the most frequently encountered genera of <it>Enterobacteriaceae</it>, non-fermenter and clinical relevant <it>Candida </it>species. The observed detection limits varied from 10 cells (e.g. <it>E. coli</it>) to 10⁵cells (<it>S. aureus</it>) per mL artificially spiked blood. Thus the current low sensitivity for some species still represents a barrier for clinical application. Successful discrimination of closely related species was achieved by a signal pattern recognition approach based on the k-nearest-neighbour method. A prototype software providing this statistical evaluation was developed, allowing correct identification in 100 % of the cases at the genus and in 96.7 % at the species level (n = 241).</p> <p>Conclusion</p> <p>The newly developed molecular assay can be carried out within 6 hours in a research laboratory from pathogen isolation to species identification. From our results we conclude that DNA microarrays can be a useful tool for rapid identification of closely related pathogens particularly when the protocols are adapted to the special clinical scenarios.</p

In silico design and performance of peptide microarrays for breast cancer tumour-auto-antibody testing

The simplicity and potential of minimally invasive testing using sera from patients makes auto-antibody based biomarkers a very promising tool for use in cancer diagnostics. Protein microarrays have been used for the identification of such auto-antibody signatures. Because high throughput protein expression and purification is laborious, synthetic peptides might be a good alternative for microarray generation and multiplexed analyses. In this study, we designed 1185 antigenic peptides, deduced from proteins expressed by 642 cDNA expression clones found to be sero-reactive in both breast tumour patients and controls. The sero-reactive proteins and the corresponding peptides were used for the production of protein and peptide microarrays. Serum samples from females with benign and malignant breast tumours and healthy control sera (n=16 per group) were then analysed. Correct classification of the serum samples on peptide microarrays were 78% for discrimination of ‘malignant versus healthy controls’, 72% for ‘benign versus malignant’ and 94% for ‘benign versus controls’. On protein arrays, correct classification for these contrasts was 69%, 59% and 59%, respectively. The over-representation analysis of the classifiers derived from class prediction showed enrichment of genes associated with ribosomes, spliceosomes, endocytosis and the pentose phosphate pathway. Sequence analyses of the peptides with the highest sero-reactivity demonstrated enrichment of the zinc-finger domain. Peptides’ sero-reactivities were found negatively correlated with hydrophobicity and positively correlated with positive charge, high inter-residue protein contact energies and a secondary structure propensity bias. This study hints at the possibility of using in silico designed antigenic peptide microarrays as an alternative to protein microarrays for the improvement of tumour auto-antibody based diagnostics

Evaluation of auto-antibody serum biomarkers for breast cancer screening and in silico analysis of sero-reactive proteins

Aberrantly expressed proteins in tumours evoke an immunological response. These immunogenic proteins can serve as potential biomarkers for the early diagnosis of cancers. In this study, we performed a candidate marker screen on macroarrays containing 38,016 human proteins, derived from a human fetal-brain expression library, with the pools of sera from breast cancer patients (1 pool of benign samples, 3 pools of ductal carcinoma and 2 pools of lobular carcinoma) and 1 pool of sera from healthy women. A panel of 642 sero-reactive clones were deduced from these macroarray experiments which include 284 in-frame clones. Over-representation analyses of the sero-reactive in-frame clones enabled the identification of the sets of genes over-expressed in various pathways of the functional categories (KEGG, Transpath, Pfam and GO). Protein microarrays, generated using the His-tag proteins derived from the macroarray experiments, were used to evaluate the sera from breast cancer patients (24 malignant, 16 benign) and 20 control individuals. Using the PAM algorithm we elucidated a panel of 50 clones which enabled the correct classification prediction of 93% of the breast-nodule positive group (benign &amp; malignant) sera from healthy individuals’ sera with 100% sensitivity and 85% specificity. This was followed by over-representation analysis of the significant clones derived from the class prediction

Strategies for validation and testing of DNA methylation biomarkers

DNA methylation is a stable covalent epigenetic modification of primarily CpG dinucleotides that has recently gained considerable attention for its use as a biomarker in different clinical settings, including disease diagnosis, prognosis and therapeutic response prediction. Although the advent of genome-wide DNA methylation profiling in primary disease tissue has provided a manifold resource for biomarker development, only a tiny fraction of DNA methylation-based assays have reached clinical testing. Here, we provide a critical overview of different analytical methods that are suitable for biomarker validation, including general study design considerations, which might help to streamline epigenetic marker development. Furthermore, we highlight some of the recent marker validation studies and established markers that are currently commercially available for assisting in clinical management of different cancers

Transcriptomal analysis of varicella-zoster virus infection using long oligonucleotide-based microarrays

Varicella-zoster virus (VZV) is a human herpes virus that causes varicella as a primary infection and herpes zoster following reactivation of the virus from a latent state in trigeminal and spinal ganglia. In order to study the global pattern of VZV gene transcription, VZV microarrays using 75-base oligomers to 71 VZV open reading frames (ORFs) were designed and validated. The long-oligonucleotide approach maximizes the stringency of detection and polarity of gene expression. To optimize sensitivity, microarrays were hybridized to target RNA and the extent of hybridization measured using resonance light scattering. Microarray data were normalized to a subset of invariant ranked host-encoded positive-control genes and the data subjected to robust formal statistical analysis. The programme of viral gene expression was determined for VZV (Dumas strain)-infected MeWo cells and SVG cells (an immortalized human astrocyte cell line) 72 h post-infection. Marked quantitative and qualitative differences in the viral transcriptome were observed between the two different cell types using the Dumas laboratory-adapted strain. Oligonucleotide-based VZV arrays have considerable promise as a valuable tool in the analysis of viral gene transcription during both lytic and latent infections, and the observed heterogeneity in the global pattern of viral gene transcription may also have diagnostic potentia

MethCancerDB – aberrant DNA methylation in human cancer

Early detection, classification and prognosis of human cancers by analysis of CpG methylation carry huge diagnostic potential. MethCancerDB collects and annotates genes and sequences from the abundance of published methylation studies and interlinks them to all methylation-relevant bioinformatical resources. MethCancerDB starts with 4720 entries from 348 sources and is freely accessible at http://www.methcancerdb.net

Diagnostic significance of CK19, TG, Ki67 and galectin-3 expression for papillary thyroid carcinoma in the northeastern region of China

<p>Abstract</p> <p>Background</p> <p>To evaluate the expression and differential diagnostic significance of CK19, TG, Ki67 and galectin-3 in papillary thyroid carcinoma (PTC) (metastatic and non metastatic), follicular adenoma and nodular goiter in patients from the northeastern part of China.</p> <p>Methods</p> <p>441 PTC specimens and 151 other benign thyroid specimens (97 cases of nodular goiter, 54 cases of nonmalignant follicular adenoma) were collected. Immunohistochemistry for CK19, TG, Ki67 and galectin-3 was performed.</p> <p>Results</p> <p>CK19, TG, Ki67 and galectin-3 expression was 96.37% (425/441), 82.77% (365/441), and 40.59% (179/441), 96.82% (427/441), respectively, for the PTC group and the expression of these markers in the benign thyroid lesions group was 25.83% (39/151), 79.47% (120/151), and 37.09% (56/151), 50.99% (77/151), respectively. The expression of CK19 and galectin-3 in PTC was much higher than that in the nonmalignant group (p < 0.05). However, the expression of TG, Ki67 did not differ among these two groups (p > 0.05). The diagnostic efficiency of CK19 and galectin-3 for PTC was 96.37% (537/592) and 84.63% (501/592). CK19 and galectin-3 expression rate in PTC was higher than that in benign disease cases.</p> <p>Conclusions</p> <p>The diagnostic efficiency of CK19 for PTC was slightly better than galectin-3. The utilization of these markers combined with morphologic evaluation may be helpful in the differential diagnosis of papillary thyroid carcinoma in the northeastern region of China.</p