Computational identification and functional validation of regulatory motifs in cartilage-expressed genes.

Chondrocyte gene regulation is important for the generation and maintenance of cartilage tissues. Several regulatory factors have been identified that play a role in chondrogenesis, including the positive transacting factors of the SOX family such as SOX9, SOX5, and SOX6, as well as negative transacting factors such as C/EBP and delta EF1. However, a complete understanding of the intricate regulatory network that governs the tissue-specific expression of cartilage genes is not yet available. We have taken a computational approach to identify cis-regulatory, transcription factor (TF) binding motifs in a set of cartilage characteristic genes to better define the transcriptional regulatory networks that regulate chondrogenesis. Our computational methods have identified several TFs, whose binding profiles are available in the TRANSFAC database, as important to chondrogenesis. In addition, a cartilage-specific SOX-binding profile was constructed and used to identify both known, and novel, functional paired SOX-binding motifs in chondrocyte genes. Using DNA pattern-recognition algorithms, we have also identified cis-regulatory elements for unknown TFs. We have validated our computational predictions through mutational analyses in cell transfection experiments. One novel regulatory motif, N1, found at high frequency in the COL2A1 promoter, was found to bind to chondrocyte nuclear proteins. Mutational analyses suggest that this motif binds a repressive factor that regulates basal levels of the COL2A1 promoter.

Effect sizes and standardization in neighbourhood models of forest stands: potential biases and misinterpretations

Effects of conspecific neighbours on survival and growth of trees have been found to be related to species abundance. Both positive and negative relationships may explain observed abundance patterns. Surprisingly, it is rarely tested whether such relationships could be biased or even spurious due to transforming neighbourhood variables or influences of spatial aggregation, distance decay of neighbour effects and standardization of effect sizes. To investigate potential biases, communities of 20 identical species were simulated with log-series abundances but without species-specific interactions. No relationship of conspecific neighbour effects on survival or growth with species abundance was expected. Survival and growth of individuals was simulated in random and aggregated spatial patterns using no, linear, or squared distance decay of neighbour effects. Regression coefficients of statistical neighbourhood models were unbiased and unrelated to species abundance. However, variation in the number of conspecific neighbours was positively or negatively related to species abundance depending on transformations of neighbourhood variables, spatial pattern and distance decay. Consequently, effect sizes and standardized regression coefficients, often used in model fitting across large numbers of species, were also positively or negatively related to species abundance depending on transformation of neighbourhood variables, spatial pattern and distance decay. Tests using randomized tree positions and identities provide the best benchmarks by which to critically evaluate relationships of effect sizes or standardized regression coefficients with tree species abundance. This will better guard against potential misinterpretations.

Sensitivity and fragmentation calibration of the ROSINA double focusing mass spectrometer

The goal of this work has been to calibrate sensitivities and fragmentation pattern of various molecules as well as further characterize the lab model of the ROSINA Double Focusing Mass Spectrometer (DFMS) on board ESA’s Rosetta spacecraft bound to comet 67P/Churyumov-Gerasimenko. The detailed calibration and characterization of the instrument is key to understand and interpret the results in the coma of the comet. A static calibration was performed for the following species: Ne, Ar, Kr, Xe, H2O, N2, CO2, CH4, C2H6, C3H8, C4H10, and C2H4. The purpose of the calibration was to obtain sensitivities for all detectors and emissions, the fragmentation behavior of the ion source and to show the capabilities to measure isotopic ratios at the comet. The calibration included the recording of different correction factors to evaluate the data, including a detailed investigation of the detector gain. The quality of the calibration that could be tested for different gas mixtures including the calibration of the density inside the ion source when calibration gas from the gas calibration unit is introduced. In conclusion the calibration shows that DFMS meets the design requirements and that DFMS will be able to measure the D/H at the comet and help shed more light on the puzzle about the origin of water on Earth.

Transcriptional and translational regulators of gene expression in germ cell development

Germ cell development is a highly coordinated process driven, in part, by regulatory mechanisms that control gene expression. Not only transcription, but also translation, is under regulatory control to direct proper germ cell development. In this dissertation, I have focused on two regulators of germ cell development. One is the homeobox protein RHOX10, which has the potential to be both a transcriptional and translational regulator in mouse male germ cell development. The other is the RNA-binding protein, Hermes, which functions as a translational regulator in Xenopus laevis female germ cell development. ^ Rhox10 is a member of reproductive homeobox gene X-(linked (Rhox) gene cluster, of which expression is developmentally regulated in developing mouse testes. To identify the cell types and developmental stages in which Rhox10 might function, I characterized its temporal and spatial expression pattern in mouse embryonic, neonatal, and adult tissues. Among other things, this analysis revealed that both the level and the subcellular localization of RHOX10 are regulated during germ cell development. To understand the role of Rhox10 in germ cell development, I generated transgenic mice expressing an artificial microRNA (miRNA) targeting Rhox10. While this artificial miRNA robustly downregulated RHOX10 protein expression in vitro, it did not significantly reduce RHOX10 expression in vivo. So I next elected to knockdown RHOX10 levels in spermatogonial stem cells (SSCs), which I found highly express both Rhox10 mRNA and RHOX10 protein. Using a recently developed in vitro culture system for SSCs combined with a short-hairpin RNA (shRNA) approach, I strongly depleted RHOX10 expression in SSCs. These RHOX10-depleted cells exhibited a defect in the ability to form stem cell clusters in vitro. Expression profiling analysis revealed many genes regulated by Rhox10, including many meiotic genes, which could be downstream of Rhox10 in a molecular pathway that controls SSC differentiation. ^ RNA recognition motif (RRM) containing protein, Hermes is localized in germ plasm, where dormant mRNAs are also located, of Xenopus oocytes, which implicates its role in translational regulator. To understand the function of Hermes in oocyte meiosis, I used a morpholino oligonucleotide (MO) based knockdown approach. Microinjection of Hermes MO into fully grown oocytes, which are arrested in meiotic prophase, caused acceleration of oocytes reentry into meiosis (i.e., maturation) upon progesterone induction. Using a candidate approach, I identified at least three targets of Hermes: Ringo/Spy, Xcat2, and Mos. Ringo/Spy and Mos are known to have functions in oocyte maturation, while Ringo/Spy, Xcat2 mRNA are localized in the germ plasm of oocytes, which drives germ cell specification after fertilization. This led me to propose that Hermes functions in both oocyte maturation and germ cell development through its ability to regulate 3 crucial target mRNAs. ^

New methods for quantification and analysis of quantitative real-time polymerase chain reaction data

Quantitative real-time polymerase chain reaction (qPCR) is a sensitive gene quantitation method that has been widely used in the biological and biomedical fields. The currently used methods for PCR data analysis, including the threshold cycle (CT) method, linear and non-linear model fitting methods, all require subtracting background fluorescence. However, the removal of background fluorescence is usually inaccurate, and therefore can distort results. Here, we propose a new method, the taking-difference linear regression method, to overcome this limitation. Briefly, for each two consecutive PCR cycles, we subtracted the fluorescence in the former cycle from that in the later cycle, transforming the n cycle raw data into n-1 cycle data. Then linear regression was applied to the natural logarithm of the transformed data. Finally, amplification efficiencies and the initial DNA molecular numbers were calculated for each PCR run. To evaluate this new method, we compared it in terms of accuracy and precision with the original linear regression method with three background corrections, being the mean of cycles 1-3, the mean of cycles 3-7, and the minimum. Three criteria, including threshold identification, max R2, and max slope, were employed to search for target data points. Considering that PCR data are time series data, we also applied linear mixed models. Collectively, when the threshold identification criterion was applied and when the linear mixed model was adopted, the taking-difference linear regression method was superior as it gave an accurate estimation of initial DNA amount and a reasonable estimation of PCR amplification efficiencies. When the criteria of max R2 and max slope were used, the original linear regression method gave an accurate estimation of initial DNA amount. Overall, the taking-difference linear regression method avoids the error in subtracting an unknown background and thus it is theoretically more accurate and reliable. This method is easy to perform and the taking-difference strategy can be extended to all current methods for qPCR data analysis.^

Unconstrained and Contactless Hand Geometry Biometrics

This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely Support Vector Machines (SVM) and k-Nearest Neighbour (k-NN). Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices

Development of a hand-gesture recognition system for human-computer interaction

The aim of this Master Thesis is the analysis, design and development of a robust and reliable Human-Computer Interaction interface, based on visual hand-gesture recognition. The implementation of the required functions is oriented to the simulation of a classical hardware interaction device: the mouse, by recognizing a specific hand-gesture vocabulary in color video sequences. For this purpose, a prototype of a hand-gesture recognition system has been designed and implemented, which is composed of three stages: detection, tracking and recognition. This system is based on machine learning methods and pattern recognition techniques, which have been integrated together with other image processing approaches to get a high recognition accuracy and a low computational cost. Regarding pattern recongition techniques, several algorithms and strategies have been designed and implemented, which are applicable to color images and video sequences. The design of these algorithms has the purpose of extracting spatial and spatio-temporal features from static and dynamic hand gestures, in order to identify them in a robust and reliable way. Finally, a visual database containing the necessary vocabulary of gestures for interacting with the computer has been created.

Deformable templates for tracking and analysis of intravascular ultrasound sequences

Deformable Template models are first applied to track the inner wall of coronary arteries in intravascular ultrasound sequences, mainly in the assistance to angioplasty surgery. A circular template is used for initializing an elliptical deformable model to track wall deformation when inflating a balloon placed at the tip of the catheter. We define a new energy function for driving the behavior of the template and we test its robustness both in real and synthetic images. Finally we introduce a framework for learning and recognizing spatio-temporal geometric constraints based on Principal Component Analysis (eigenconstraints).

VdBH 222: a starburst cluster in the inner Milky Way

Context. It has been suggested that the compact open cluster VdBH 222 is a young massive distant object. Aims. We set out to characterise VdBH 222 using a comprehensive set of multi-wavelength observations. Methods. We obtained multi-band optical (UBVR) and near-infrared (JHKS) photometry of the cluster field, as well as multi-object and long-slit optical spectroscopy for a large sample of stars in the field. We applied classical photometric analysis, as well as more sophisticated methods using the CHORIZOS code, to determine the reddening to the cluster. We then plotted dereddened HR diagrams and determined cluster parameters via isochrone fitting. Results. We have identified a large population of luminous supergiants confirmed as cluster members via radial velocity measurements. We find nine red supergiants (plus one other candidate) and two yellow supergiants. We also identify a large population of OB stars. Ten of them are bright enough to be blue supergiants. The cluster lies behind ≈7.5 mag of extinction for the preferred value of RV = 2.9. Isochrone fitting allows for a narrow range of ages between 12 and 16 Ma. The cluster radial velocity is compatible with distances of ~6 and ~10 kpc. The shorter distance is inconsistent with the age range and Galactic structure. The longer distance implies an age ≈ 12 Ma and a location not far from the position where some Galactic models place the far end of the Galactic bar. Conclusions. VdBH 222 is a young massive cluster with a likely mass >20 000 M⊙. Its population of massive evolved stars is comparable to that of large associations, such as Per OB1. Its location in the inner Galaxy, presumably close to the end of the Galactic bar, adds to the increasing evidence for vigorous star formation in the inner regions of the Milky Way.

A connectionist computational method for face recognition

In this work, a modified version of the elastic bunch graph matching (EBGM) algorithm for face recognition is introduced. First, faces are detected by using a fuzzy skin detector based on the RGB color space. Then, the fiducial points for the facial graph are extracted automatically by adjusting a grid of points to the result of an edge detector. After that, the position of the nodes, their relation with their neighbors and their Gabor jets are calculated in order to obtain the feature vector defining each face. A self-organizing map (SOM) framework is shown afterwards. Thus, the calculation of the winning neuron and the recognition process are performed by using a similarity function that takes into account both the geometric and texture information of the facial graph. The set of experiments carried out for our SOM-EBGM method shows the accuracy of our proposal when compared with other state-of the-art methods.

Using the EM Algorithm to Train Neural Networks: Misconceptions and a New Algorithm for Multiclass Classification

The expectation-maximization (EM) algorithm has been of considerable interest in recent years as the basis for various algorithms in application areas of neural networks such as pattern recognition. However, there exists some misconceptions concerning its application to neural networks. In this paper, we clarify these misconceptions and consider how the EM algorithm can be adopted to train multilayer perceptron (MLP) and mixture of experts (ME) networks in applications to multiclass classification. We identify some situations where the application of the EM algorithm to train MLP networks may be of limited value and discuss some ways of handling the difficulties. For ME networks, it is reported in the literature that networks trained by the EM algorithm using iteratively reweighted least squares (IRLS) algorithm in the inner loop of the M-step, often performed poorly in multiclass classification. However, we found that the convergence of the IRLS algorithm is stable and that the log likelihood is monotonic increasing when a learning rate smaller than one is adopted. Also, we propose the use of an expectation-conditional maximization (ECM) algorithm to train ME networks. Its performance is demonstrated to be superior to the IRLS algorithm on some simulated and real data sets.

A comparison of competing methods for the detection of surgical-site infections in patients undergoing total arthroplasty of the knee, partial and total arthroplasty of hip and femoral or similar vascular bypass

Recent research suggests that the retrospective review of the International Classification of Disease (ICD-9-CM) codes assigned to a patient episode will identify a similar number of healthcare-acquired surgical-site infections as compared with prospective surveillance by infection control practitioners (ICP). We tested this finding by replicating the methods for 380 surgical procedures. The sensitivity and specificity of the ICP undertaking prospective surveillance was 80% and 100%, and the sensitivity and specificity of the review of ICD-10-AM codes was 60% and 98.9%. Based on these results we do not support retrospective review of ICD-10-AM codes in preference prospective surveillance for SSI. (C) 2004 The Hospital Infection Society. Published by Elsevier Ltd. All rights reserved.

A First Order Predicate Logic Formulation of the 3D Reconstruction Problem and its Solution Space

This paper defines the 3D reconstruction problem as the process of reconstructing a 3D scene from numerous 2D visual images of that scene. It is well known that this problem is ill-posed, and numerous constraints and assumptions are used in 3D reconstruction algorithms in order to reduce the solution space. Unfortunately, most constraints only work in a certain range of situations and often constraints are built into the most fundamental methods (e.g. Area Based Matching assumes that all the pixels in the window belong to the same object). This paper presents a novel formulation of the 3D reconstruction problem, using a voxel framework and first order logic equations, which does not contain any additional constraints or assumptions. Solving this formulation for a set of input images gives all the possible solutions for that set, rather than picking a solution that is deemed most likely. Using this formulation, this paper studies the problem of uniqueness in 3D reconstruction and how the solution space changes for different configurations of input images. It is found that it is not possible to guarantee a unique solution, no matter how many images are taken of the scene, their orientation or even how much color variation is in the scene itself. Results of using the formulation to reconstruct a few small voxel spaces are also presented. They show that the number of solutions is extremely large for even very small voxel spaces (5 x 5 voxel space gives 10 to 10(7) solutions). This shows the need for constraints to reduce the solution space to a reasonable size. Finally, it is noted that because of the discrete nature of the formulation, the solution space size can be easily calculated, making the formulation a useful tool to numerically evaluate the usefulness of any constraints that are added.

Pattern analysis on protein properties of Chinese and CIMMYT spring wheat cultivars sown in China and CIMMYT

Improvement of processing quality is a very important objective for Chinese wheat breeding programs. Twenty-five CIMMYT and Chinese spring wheat cultivars were grown at four managed conditions by CIMMYT in Cd. Obregon, Sonora, Mexico and in nine environments in China, over two successive wheat seasons from 2000 to 2002. These trials were used to identify patterns of cultivar, environment and cultivar x environment interactions, and to determine opportunities for indirect selection for protein content and the protein-quality related parameter, SDS sedimentation (SDSS) value. The cultivar Inqalab 91 showed low levels of interaction with environments in the 2000-01 crop cycle for protein content, and expressed intermediate levels for both protein content and SDSS value, across most of the environments in both years. Longmai 26 had consistently high protein content and SDSS value across environments in both years, indicating that it is possible to breed cultivars expressing high yields with good protein properties. Cluster analyses revealed that cultivars grouped differently for protein content and SDSS value. Besides photoperiod, water availability appeared to influence the ranking of cultivars for protein content and SDSS value. Temperature and soil type may underlie the observed interactions for protein content, while temperature may also be a factor associated with interactions for SDSS value. The full irrigation managed environment in Mexico, with the cultivars sown on raised beds two months later than optimum and exposing them to late heat, clustered together with the Chinese environments Huhhot, Yongning, and Hejin in the 2000-01 season for SDSS value. This indicates that there is an opportunity to exploit indirect responses to selection in the CIMMYT management environments for SDSS value with relevance for China's spring wheat regions. However, there seemed little chance for positive indirect selection in CIMMYT's managed environments for China in regard to protein content, as environments clustered distinctly. Pattern analyses permitted a sensible and useful summary for this multi environment experiment, helping in understanding natural relationships and variations in cultivar performance among the various environment groups, and assisting in the structuring of environments.

Screening of obstructive and central apnoea/hypopnoea in children using variability: A preliminary study

Aim: Polysomnography (PSG) is the current standard protocol for sleep disordered breathing (SDB) investigation in children. Presently, there are limited reliable screening tests for both central (CE) and obstructive (OE) respiratory events. This study compared three indices, derived from pulse oximetry and electrocardiogram ( ECG), with the PSG gold standard. These indices were heart rate (HR) variability, arterial blood oxygen de-saturation (SaO(2)) and pulse transit time (PTT). Methods: 15 children (12 male) from routine PSG studies were recruited (aged 3 - 14 years). The characteristics of the three indices were based on known criteria for respiratory events (RPE). Their estimation singly and in combination was evaluated with simultaneous scored PSG recordings. Results: 215 RPE and 215 tidal breathing events were analysed. For OE, the obtained sensitivity was HR (0.703), SaO(2) (0.047), PTT (0.750), considering all three indices (0) and either of the indices (0.828) while specificity was (0.891), (0.938), (0.922), (0.953) and (0.859) respectively. For CE, the sensitivity was HR (0.715), SaO(2) (0.278), PTT (0.662), considering all indices (0.040) and either of the indices (0.868) while specificity was (0.815), (0.954), (0.901), (0.960) and (0.762) accordingly. Conclusions: Preliminary findings herein suggest that the later combination of these non-invasive indices to be a promising screening method of SDB in children.