A comparison of amino acid distance measures using procrustes analysis.

Four methods to convert an amino acid similarity matrix into a metric distance matrix were compared using procrustes analysis. Procrustes analysis is a rotational fit technique, which assesses the degree of fit between two configurations after optimal matching of the two matrices under translation, rotation and scaling. The analysis shows that not all conversion methods are equivalent, but that the results of two methods are more similar than the others.     

Posttraumatische Syringomyelie

Background

Posttraumatic syringomyelia (PTS) can occur as a rare complication after traumatic spinal cord injury (tSCI) and in cases of delayed diagnosis could lead to disastrous deterioration of both motor and sensory neurological functions.

Objective

To determine influencing factors causing PTS after tSCI.

Material and methods

In a monocentric retrospective two-arm study all patients who were readmitted as inpatients due to increasing neurological impairment caused by PTS (n?=?107) in the period between 1 October 1997 and 31 December 2012 were compared with a randomised group of tSCI patients without PTS (n?=?1590) over the same time period.

Results

Included in the study were 107 patients with an average age of 30.25 years (86 male and 21 female). The most frequent clinical symptoms were changes in sensitivity, pain perception and muscle strength. Within the PTS group, patients older than 30 years had a shorter interval between the onset of SCI and the diagnosis of PTS (p?<?0.001). Both the study and control groups showed a significant age difference at the time of the accident (p?<?0.001). In addition, the number of completely paraplegic (American Spinal Injury Association impairment scale AIS type A) patients was significantly higher within the PTS group (p?<?0.001) and they also had remission to pedestrians significantly less frequently (p?<?0.001). In addition, in a group comparison significantly different neurological levels of paralysis (p?<?0.001) were observed at the time of discharge. Further results showed that younger patients with complete SCI lesions had a higher risk of developing PTS.

Conclusion

The PTS is a rare but severe complication of tSCI, frequently followed by increasing impairment of sensibility, motor function and the autonomic nervous system. As the prognosis of the disease is highly influenced by the time point of the diagnosis, in suspected cases immediate presentation at a specialized center for paraplegic patients is necessary.

     

Uncoupling protein 2 deficiency of non-cancerous tissues inhibits the progression of pancreatic cancer in mice

Background: Pancreatic ductal adenocarcinoma(PDAC) is a disease of the elderly mostly because its development from preneoplastic lesions depends on the accumulation of gene mutations and epigenetic alterations over time. How aging of non-cancerous tissues of the host affects tumor progression, however, remains largely unknown. Methods: We took advantage of a model of accelerated aging, uncoupling protein 2-deficient( Ucp2 knockout, Ucp2 KO) mice, to investigate the growth of orthotopically trans...     

Ursachenzusammenhang zwischen langjähriger Querschnittlähmung und malignen Harnblasentumoren

Trauma und Berufskrankheit - Zur Zusammenhangsbeurteilung traumatisch bedingter Querschnittlähmungen und Jahre später auftretender Harnblasenkarzinome gibt es keine aussagefähige...     

Non-parametric classification of protein secondary structures

Proteins were classified into their families using a classification tree method which is based on the coefficient of variations of physico-chemical and geometrical properties of the secondary structures of proteins. The tree method uses as splitting criterion the increase in purity when a node is split into two subnodes and the size of the tree is controlled by a threshold level for the improvement of the apparent misclassification rate (AMR) of the tree after each splitting step. The classification tree method seems effective in reproducing similar structural groupings as the method of dynamic programming. For comparison, we also used another two methods: neural networks and support vector machines. We could show that the presented classification tree method performs better in classifying proteins into their families. The presented algorithm might be suitable for a rapid preliminary classification of proteins into their corresponding families.     

Upregulated epithelial junction expression represents a novel parameter of the epithelial radiation response to fractionated irradiation in oral mucosa

Purpose

During head and neck cancer treatment, the radiation response of the oral mucosa represents a frequent early side effect. Besides radiation-induced inhibition of proliferation, various other cellular responses occur. The radiation response of adherens and tight junction proteins was so far mostly investigated with large single-dose irradiation protocols, in vivo and in vitro. Therefore, the current study was initiated to investigate the impact of daily fractionated irradiation on the expression of adherens and tight junction proteins in vivo.

Materials and methods

Fractionation with 5?×?3?Gy/week (days 0–4, 7–11) was given to the snouts of mice. Groups of 5 animals per day were euthanized every second day between day 0 (unirradiated controls) and day 14, and their tongues subjected to histological processing. Adherens junction marker (β-catenin and E?cadherin) and tight junction marker (claudin-1 and occludin) expression was analysed in the oral mucosa of unirradiated controls and during two weeks of fractionated irradiation.

Results

Adherens as well as tight junction marker proteins were rapidly and consistently upregulated in both the germinal as well as the functional layer of the oral mucosa. This represents a previously unknown parameter of the epithelial radiation response to clinically relevant fractionation protocols.

Conclusion

Fractionated irradiation significantly enhanced the expression of all proteins investigated. This study revealed a new parameter of the epithelial radiation response to fractionated irradiation.

     

Forest classification trees and forest support vector machines algorithms: Demonstration using microarray data

Classification into multiple classes when the measured variables are outnumbered is a major methodological challenge in -omics studies. Two algorithms that overcome the dimensionality problem are presented: the forest classification tree (FCT) and the forest support vector machines (FSVM). In FCT, a set of variables is randomly chosen and a classification tree (CT) is grown using a forward classification algorithm. The process is repeated and a forest of CTs is derived. Finally, the most frequent variables from the trees with the smallest apparent misclassification rate (AMR) are used to construct a productive tree. In FSVM, the CTs are replaced by SVMs. The methods are demonstrated using prostate gene expression data for classifying tissue samples into four tumor types. For threshold split value 0.001 and utilizing 100 markers the productive CT consisted of 29 terminal nodes and achieved perfect classification (AMR=0). When the threshold value was set to 0.01, a tree with 17 terminal nodes was constructed based on 15 markers (AMR=7%). In FSVM, reducing the fraction of the forest that was used to construct the best classifier from the top 80% to the top 20% reduced the misclassification to 25% (when using 200 markers). The proposed methodologies may be used for identifying important variables in high dimensional data. Furthermore, the FCT allows exploring the data structure and provides a decision rule.