T. Richards

Microarray Data Classified by Artificial Neural Networks

Systems biology has enjoyed explosive growth in both the number of people participating in this area of research and the number of publications on the topic. The field of systems biology encompasses the in silico analysis of high-throughput data as provided by DNA or protein microarrays. Along with the increasing availability of microarray data, attention is focused on methods of analyzing the expression rates. One important type of analysis is the classification task, for example, distinguishing different types of cell functions or tumors. Recently, interest has been awakened toward artificial neural networks (ANN), which have many appealing characteristics such as an exceptional degree of accuracy. Nonlinear relationships or independence from certain assumptions regarding the data distribution are also considered. The current work reviews advantages as well as disadvantages of neural networks in the context of microarray analysis. Comparisons are drawn to alternative methods. Selected solutions are discussed, and finally algorithms for the effective combination of multiple ANNs are presented. The development of approaches to use ANN-processed microarray data applicable to run cell and tissue simulations may be slated for future investigation.

Text mining, a race against time? An attempt to quantify possible variations in text corpora of medical publications throughout the years

BACKGROUND The continuous growth of medical sciences literature indicates the need for automated text analysis. Scientific writing which is neither unitary, transcending social situation nor defined by a timeless idea is subject to constant change as it develops in response to evolving knowledge, aims at different goals, and embodies different assumptions about nature and communication. The objective of this study was to evaluate whether publication dates should be considered when performing text mining. METHODS A search of PUBMED for combined references to chemokine identifiers and particular cancer related terms was conducted to detect changes over the past 36 years. Text analyses were performed using freeware available from the World Wide Web. TOEFL Scores of territories hosting institutional affiliations as well as various readability indices were investigated. Further assessment was conducted using Principal Component Analysis. Laboratory examination was performed to evaluate the quality of attempts to extract content from the examined linguistic features. RESULTS The PUBMED search yielded a total of 14,420 abstracts (3,190,219 words). The range of findings in laboratory experimentation were coherent with the variability of the results described in the analyzed body of literature. Increased concurrence of chemokine identifiers together with cancer related terms was found at the abstract and sentence level, whereas complexity of sentences remained fairly stable. CONCLUSIONS The findings of the present study indicate that concurrent references to chemokines and cancer increased over time whereas text complexity remained stable.

MicroRNA target prediction: theory and practice.

Abstract The present study is one of the few that includes tissue samples in the evaluation of target prediction algorithms designed to detect microRNA (miRNA) sequences that might interact with particular messenger RNA (mRNA) sequences. Twelve different target prediction tools were used to find miRNA sequences that might interact with CCL20 gene expression. Different algorithms predicted controversial miRNA sequences for CCL20 regulation due to a different weighting of parameters. Hsa-miR-21 and hsa-miR-145 suggested by four or more programs were chosen for further investigation. Possible real interaction of these miRNA sequences with CCL20 gene expression was monitored using luciferase assays and expression analyses of tissue samples of colorectal adenocarcinoma by either qRT-PCR or ELISA. Folding status of seed-binding sites in complete mRNA and 3′UTR of CCL20 was predicted. Prediction of miRNA expression was attempted based on CCL20 expression data. Eight of the target prediction tools forecasted a role for hsa-miR-21 and four mentioned hsa-miR-145 in CCL20 gene regulation. Laboratory experimentation showed that CCL20 may serve as a target of hsa-miR-21 but not hsa-miR-145. Expression of the molecules resulted in no clear assertion. Folding of seed-binding sites was predicted to be relatively constant for the complete mRNA and 3′UTR. Predicting miRNA expression based on target gene expression was impossible. This might be attributable to the fact that effects of miRNA activity may oscillate between gene product repression and activation. Additional systematic studies are needed to address this issue.

Mathematische Modellierung in der Systembiologie

ZusammenfassungMithilfe eines neu entwickelten mathematischen Modells zur Ausbildung eines Kollagenfasergeflechts sollen Aussagen zur möglichen Bedeutung von Chemotaxis und Haptotaxis für die Histomorphologie einer desmoplastischen Stromareaktion (DSR) getroffen werden. Hierfür werden Fibroblasten als bewegliche diskrete Objekte aufgefasst, die durch ihre Position und Geschwindigkeit in Abhängigkeit von der Zeit charakterisiert sind. Die Migrationspfade werden als Trajektorien stochastischer Prozesse modelliert. Die Implementierung chemotaktischer Effekte setzt die Kenntnis der Konzentrationsverteilung des entsprechenden chemischen Stoffes im Gewebe voraus. Die Beschreibung der Attraktantenverteilung erfolgt mittels einer geeigneten Diffusionsgleichung, die nach Vorgabe von entsprechenden Anfangs- und Randdaten numerisch gelöst wird. Das Einschließen der Haptotaxis erfordert die Modellierung der extrazellulären Matrix (ECM). Die Faserverteilung wird als Vektorfeld modelliert, welches sowohl Informationen über die Dichte als auch die Faserrichtung beinhaltet. Neu produzierte Fasern werden über gewöhnliche Differentialgleichungen mit dem Wanderungsverhalten der fibroblastären Zellen gekoppelt. Geeignete Visualisierungstechniken erlauben einen direkten Vergleich der Simulationsergebnisse mit den Ergebnissen realer Histomorphologie. Erste Vergleiche der computergenerierten Daten mit den realen Pendants zeigen bereits gute Übereinstimmungen und qualifizieren das mathematische Modell als potenziell geeignete Methode zur Beschreibung und Vorhersage des Verlaufs einer DSR. Somit kann die Systembiologie an der Verbesserung der biomedizinischen Forschung entscheidend mitwirken.AbstractA mathematical model of collagen fiber mesh formation was created to evaluate the possible role of chemotaxis and haptotaxis in the histomorphology of a desmoplastic stromal reaction (DSR). Fibroblasts were mathematicaly interpreted as mobile discrete objects, characterized by their velocity and position, both dependent on time. This resulted in cell migration paths, commonly termed “trajectories” which are modulated as stochastic process. The implementation of chemotactic effects requires knowledge of the concentration and distribution of the appropriate chemical substance in the scenario. A simplistic model assumption allows the calculation of a numerical solution of the resulting diffusion equation. Adding haptotaxis necessitates the simulation of the extracellular matrix (ECM). The fiber distribution is modeled as a vector field which contains information on both, fiber density and direction. The production of new fibers is based on ordinary differential equations coupled with the migratory behavior of the cells. Filters help smooth the trajectories. Appropriate visualization allows a direct comparison of the simulation results with histomorphology. Matches between computed data and their real counterparts indicate that the development of mathematical models is appropriate to describe and forecast the course of DSR. This makes systems biology a stepping stone to improving biomedical research.

Mathematical modelling in systems biology. Simulation of the desmoplastic stromal reaction as an example

ZusammenfassungMithilfe eines neu entwickelten mathematischen Modells zur Ausbildung eines Kollagenfasergeflechts sollen Aussagen zur möglichen Bedeutung von Chemotaxis und Haptotaxis für die Histomorphologie einer desmoplastischen Stromareaktion (DSR) getroffen werden. Hierfür werden Fibroblasten als bewegliche diskrete Objekte aufgefasst, die durch ihre Position und Geschwindigkeit in Abhängigkeit von der Zeit charakterisiert sind. Die Migrationspfade werden als Trajektorien stochastischer Prozesse modelliert. Die Implementierung chemotaktischer Effekte setzt die Kenntnis der Konzentrationsverteilung des entsprechenden chemischen Stoffes im Gewebe voraus. Die Beschreibung der Attraktantenverteilung erfolgt mittels einer geeigneten Diffusionsgleichung, die nach Vorgabe von entsprechenden Anfangs- und Randdaten numerisch gelöst wird. Das Einschließen der Haptotaxis erfordert die Modellierung der extrazellulären Matrix (ECM). Die Faserverteilung wird als Vektorfeld modelliert, welches sowohl Informationen über die Dichte als auch die Faserrichtung beinhaltet. Neu produzierte Fasern werden über gewöhnliche Differentialgleichungen mit dem Wanderungsverhalten der fibroblastären Zellen gekoppelt. Geeignete Visualisierungstechniken erlauben einen direkten Vergleich der Simulationsergebnisse mit den Ergebnissen realer Histomorphologie. Erste Vergleiche der computergenerierten Daten mit den realen Pendants zeigen bereits gute Übereinstimmungen und qualifizieren das mathematische Modell als potenziell geeignete Methode zur Beschreibung und Vorhersage des Verlaufs einer DSR. Somit kann die Systembiologie an der Verbesserung der biomedizinischen Forschung entscheidend mitwirken.AbstractA mathematical model of collagen fiber mesh formation was created to evaluate the possible role of chemotaxis and haptotaxis in the histomorphology of a desmoplastic stromal reaction (DSR). Fibroblasts were mathematicaly interpreted as mobile discrete objects, characterized by their velocity and position, both dependent on time. This resulted in cell migration paths, commonly termed “trajectories” which are modulated as stochastic process. The implementation of chemotactic effects requires knowledge of the concentration and distribution of the appropriate chemical substance in the scenario. A simplistic model assumption allows the calculation of a numerical solution of the resulting diffusion equation. Adding haptotaxis necessitates the simulation of the extracellular matrix (ECM). The fiber distribution is modeled as a vector field which contains information on both, fiber density and direction. The production of new fibers is based on ordinary differential equations coupled with the migratory behavior of the cells. Filters help smooth the trajectories. Appropriate visualization allows a direct comparison of the simulation results with histomorphology. Matches between computed data and their real counterparts indicate that the development of mathematical models is appropriate to describe and forecast the course of DSR. This makes systems biology a stepping stone to improving biomedical research.

Virtual tissue. Quaoaring

Virtual tissue can be generated by employing various methods. First steps en route to virtual tissue may encompass the generation of virtual cells. One such approach termed Quaoaring was applied to produce artificial erythrocytes and these were both discocyte and echinocyte in shape. The results were subsequently compared with data gleaned from scanning electron microscopy and atomic force microscopy. Quaoaring has, however, proved to be unsuccessful in creating convincing objects, particularly those which should be echinocytic in appearance.ZusammenfassungEs gibt mannigfaltige Wege, virtuelles Gewebe herzustellen. Erste Schritte dorthin können über die Herstellung virtueller Zellen führen. Eine „Quaoaring“ genannte Methode wurde genutzt, um artifizielle Erythrozyten sowohl der Diskozyten- als auch der Echinozytenform zu erzeugen. Die Ergebnisse wurden mit Daten aus der Rasterelektronenmikroskopie und der „Atomic-Force-Mikroskopie“ verglichen. Quaoaring konnte hierbei insbesondere bei Objekten, die eine Echinozytenform haben sollten, nicht überzeugen.AbstractVirtual tissue can be generated by employing various methods. First steps en route to virtual tissue may encompass the generation of virtual cells. One such approach termed Quaoaring was applied to produce artificial erythrocytes and these were both discocyte and echinocyte in shape. The results were subsequently compared with data gleaned from scanning electron microscopy and atomic force microscopy. Quaoaring has, however, proved to be unsuccessful in creating convincing objects, particularly those which should be echinocytic in appearance.

Perspectives of patients about bioabsorbable internal fixation for maxillofacial fractures.

Purpose: Resorbable/bioabsorbable internal fixation provides effective treatment for maxillofacial fractures and avoids the need for metal hardware removal. We evaluated the initial knowledge, attitudes, subjective demand, and treatment satisfaction of patients concerning bioabsorbable osteofixation for maxillofacial trauma. Materials and Methods: From May 2007 to October 2009, there were 71 patients (63 males and 8 females; mean age: 35 ± 15 years) included in this prospective study. The patients completed preoperative and postoperative (4–6 weeks and 1 year) questionnaires. Results: After receiving information, 70 patients (99%) preferred resorbable/bioabsorbable bone fixation, usually because they preferred to avoid a second operation to remove metal hardware (67 patients [94%]). The higher cost of resorbable/bioabsorbable bone fixation was believed and justified by 41 patients (58%) and not justified by 30 patients (42%). No adverse events were reported by 27 of 34 patients (79%) at 4–6 weeks and by 14 of 21 patients (67%) at 1 year after surgery. Most patients were very satisfied with the outcome of surgery. Conclusion: Patients who have maxillofacial trauma have a high frequency of preference and high satisfaction with resorbable/bioabsorbable than metal osteofixation. Literature review showed increased activity in research and publication worldwide about resorbable bone fixation, suggesting that there may be increased patient demand for resorbable bone fixation in the future.

Signaltheoretische Analyse histologischer Daten im Ortsfrequenzraum

In the present study, a semi-automatic segmentation and classification algorithm is proposed for the analysis of histological and cytological images. In view of the fact that histological and cytological images usually exhibit poor contrast and blurred outlines, classical segmentation algorithms often fail to detect relevant structures. A new algorithm for texture segmentation based on signal processing methods in combination with machine learning techniques was therefore developed.ZusammenfassungDiese Arbeit beschreibt einen neuen Algorithmus zur (semi)automatischen Segmentierung histologischer und zytologischer Präparate. Bedingt durch den Umstand, dass derartige Präparate teilweise nur wenige kontrastreiche Areale und kaum scharfe Konturen aufweisen, sind klassische Segmentierungsverfahren wenig Erfolg versprechend, die relevanten Strukturen zu detektieren. Daher wird angestrebt, die gesuchten Strukturen anhand ihrer Texturierung auf Basis der Wavelet-Transformation zu identifizieren. Die ermittelten Merkmale dienen als Basis für eine nachgeschaltete Klassifikation mittels maschineller Lernverfahren.AbstractIn the present study, a semi-automatic segmentation and classification algorithm is proposed for the analysis of histological and cytological images. In view of the fact that histological and cytological images usually exhibit poor contrast and blurred outlines, classical segmentation algorithms often fail to detect relevant structures. A new algorithm for texture segmentation based on signal processing methods in combination with machine learning techniques was therefore developed.

Mathematische Modellierung in der Systembiologie@@@Mathematical modelling in systems biology: Beispiel einer Simulation der desmoplastischen Stromareaktion@@@Simulation of the desmoplastic stromal reaction as an example

ZusammenfassungMithilfe eines neu entwickelten mathematischen Modells zur Ausbildung eines Kollagenfasergeflechts sollen Aussagen zur möglichen Bedeutung von Chemotaxis und Haptotaxis für die Histomorphologie einer desmoplastischen Stromareaktion (DSR) getroffen werden. Hierfür werden Fibroblasten als bewegliche diskrete Objekte aufgefasst, die durch ihre Position und Geschwindigkeit in Abhängigkeit von der Zeit charakterisiert sind. Die Migrationspfade werden als Trajektorien stochastischer Prozesse modelliert. Die Implementierung chemotaktischer Effekte setzt die Kenntnis der Konzentrationsverteilung des entsprechenden chemischen Stoffes im Gewebe voraus. Die Beschreibung der Attraktantenverteilung erfolgt mittels einer geeigneten Diffusionsgleichung, die nach Vorgabe von entsprechenden Anfangs- und Randdaten numerisch gelöst wird. Das Einschließen der Haptotaxis erfordert die Modellierung der extrazellulären Matrix (ECM). Die Faserverteilung wird als Vektorfeld modelliert, welches sowohl Informationen über die Dichte als auch die Faserrichtung beinhaltet. Neu produzierte Fasern werden über gewöhnliche Differentialgleichungen mit dem Wanderungsverhalten der fibroblastären Zellen gekoppelt. Geeignete Visualisierungstechniken erlauben einen direkten Vergleich der Simulationsergebnisse mit den Ergebnissen realer Histomorphologie. Erste Vergleiche der computergenerierten Daten mit den realen Pendants zeigen bereits gute Übereinstimmungen und qualifizieren das mathematische Modell als potenziell geeignete Methode zur Beschreibung und Vorhersage des Verlaufs einer DSR. Somit kann die Systembiologie an der Verbesserung der biomedizinischen Forschung entscheidend mitwirken.AbstractA mathematical model of collagen fiber mesh formation was created to evaluate the possible role of chemotaxis and haptotaxis in the histomorphology of a desmoplastic stromal reaction (DSR). Fibroblasts were mathematicaly interpreted as mobile discrete objects, characterized by their velocity and position, both dependent on time. This resulted in cell migration paths, commonly termed “trajectories” which are modulated as stochastic process. The implementation of chemotactic effects requires knowledge of the concentration and distribution of the appropriate chemical substance in the scenario. A simplistic model assumption allows the calculation of a numerical solution of the resulting diffusion equation. Adding haptotaxis necessitates the simulation of the extracellular matrix (ECM). The fiber distribution is modeled as a vector field which contains information on both, fiber density and direction. The production of new fibers is based on ordinary differential equations coupled with the migratory behavior of the cells. Filters help smooth the trajectories. Appropriate visualization allows a direct comparison of the simulation results with histomorphology. Matches between computed data and their real counterparts indicate that the development of mathematical models is appropriate to describe and forecast the course of DSR. This makes systems biology a stepping stone to improving biomedical research.

Analysis of histological datasets by signal processing methods

In the present study, a semi-automatic segmentation and classification algorithm is proposed for the analysis of histological and cytological images. In view of the fact that histological and cytological images usually exhibit poor contrast and blurred outlines, classical segmentation algorithms often fail to detect relevant structures. A new algorithm for texture segmentation based on signal processing methods in combination with machine learning techniques was therefore developed.ZusammenfassungDiese Arbeit beschreibt einen neuen Algorithmus zur (semi)automatischen Segmentierung histologischer und zytologischer Präparate. Bedingt durch den Umstand, dass derartige Präparate teilweise nur wenige kontrastreiche Areale und kaum scharfe Konturen aufweisen, sind klassische Segmentierungsverfahren wenig Erfolg versprechend, die relevanten Strukturen zu detektieren. Daher wird angestrebt, die gesuchten Strukturen anhand ihrer Texturierung auf Basis der Wavelet-Transformation zu identifizieren. Die ermittelten Merkmale dienen als Basis für eine nachgeschaltete Klassifikation mittels maschineller Lernverfahren.AbstractIn the present study, a semi-automatic segmentation and classification algorithm is proposed for the analysis of histological and cytological images. In view of the fact that histological and cytological images usually exhibit poor contrast and blurred outlines, classical segmentation algorithms often fail to detect relevant structures. A new algorithm for texture segmentation based on signal processing methods in combination with machine learning techniques was therefore developed.