bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Energy Absorption Capacity of Equine Support Bandages
Authors: Vanderby R. , Neirby D. , Nordheim E. V. , Libbey C. J. , Crawford W. H. 
Published: March 2018

SummarySupport bandages are placed on the distal limbs of horses to provide protection to the flexor tendons and suspensory ligaments during athletic activity. In this study, an equine cadaver leg model was used to measure the energy absorption capacity and the rate of energy absorption capacity loss of support bandages. Five different configurations of bandages were applied to the limb at two degrees of applications tension. In all configurations and at both tensions, bandaged legs absorbed significantly more energy than non-bandaged legs. Significant differences existed between bandage configurations in their ability to absorb energy. In addition, the effect of application tension on the energy absorption capacity of a bandage was found to be highly significant. The ability of a bandage to absorb energy declined over a 45 cycle trial. However, significant differences between bandage configurations in this respect were not found unless the bandage material was applied at full stretch tension. When the bandages were constructed with higher application tensions the rate of lost energy absorption capacity of the bandages was increased. The importance of bandage configuration and application tension for clinical use is discussed.An equine cadaver leg model was used to measure the energy absorption capacity and the rate of energy absorption capacity loss of support bandages.
In Vitro Strain Patterns of the Intact Equine Metacarpus and Metatarsus Following Plate Luting
Authors: Cordey J. R. , Nunamaker D. M. , Tate M. L. , McIff T. , Perren S. M. , Turner A. S. 
Published: March 2018

SummaryWith internal fixation of fractures using a plate and screws, the stability of the fixation is achieved mainly by the force generated by either lag screws or plate screws. The plate protects the bone from overload. The important mechanism in the function of plate fixation is the friction between the undersurface of the plate and the bone surface. It has become evident that plate luting, i. e. interposition of a bone cement layer between the plate and the bone, will alter the transmission of expected forces due to improved contact between the plate and the bone. The purpose of this project was to evaluate the load/strain relationships that occurred following plate luting and to understand why this procedure improved the mechanical behaviour of plate fixation in equine bone. We measured the strain patterns that occurred in unplated, plated and luted equine third metacarpal and metatarsal bones under simulated physiological conditions. Plate application resulted in reduced strain under the plate and increased strain at the opposite cortex. Following plate luting, this effect was more pronounced. Hysteresis between the loading-unloading cycle was less pronounced in the luted plates. This indicated that plate luting increased the effect of strain protection.Plate luting was shown to reduce the strain under the plate and to increase it in the transcortex, effectively increasing the effect of strain protection.
A Sequential Method for Discovering Probabilistic Motifs in Proteins
Authors: Fotiadis D. I. , Likas A. , Blekas K. 
Published: March 2018

Summary

Objectives:
This paper proposes a greedy algorithm for learning a mixture of motifs model through likelihood maximization, in order to discover common substrings, known as motifs, from a given collection of related biosequences.

Methods:
The approach sequentially adds a new motif component to a mixture model by performing a combined scheme of global and local search for appropriately initializing the component parameters. A hierarchical clustering scheme is also applied initially which leads to the identification of candidate motif models and speeds up the global searching procedure.

Results:
The performance of the proposed algorithm has been studied in both artificial and real biological datasets. In comparison with the well-known MEME approach, the algorithm is advantageous since it identifies motifs with significant conservation and produces larger protein fingerprints.

Conclusion:
The proposed greedy algorithm constitutes a promising approach for discovering multiple probabilistic motifs in biological sequences. By using an effective incremental mixture modeling strategy, our technique manages to successfully overcome the limitation of the MEME scheme which erases motif occurrences each time a new motif is discovered.
Decreased Fractal Correlation in Diurnal Physical Activity in Chronic Fatigue Syndrome
Authors: Ohashi K. , Bleijenberg G. , Werf S. , Prins J. , Amaral L. A. N. , Natelson B. H. , Yamamoto Y. 
Published: March 2018

Summary

Objectives:
Our objectives were to study the temporal correlation of physical activity time series in patients with chronic fatigue syndrome (CFS) during normal daily life and to examine if it could identify the altered physical activity in these patients.

Methods:
Fractal scaling exponents of diurnal and nocturnal physical activity time series in 10 CFS patients and 6 healthy control subjects (CON) were calculated by the detrended fluctuation analysis (DFA) and the wavelet transform modulus maxima (WTMM) method. We hypo-thesized that, due to their illness- and/or fatigue-induced resting episodes, altered physical activity patterns in CFS patients might be observed at the interruption of activity bursts. Thus, we further developed a new method, the wavelet transform negative modulus maxima (WTNMM) method, which could evaluate the temporal correlation at the interruption of activities. We compared the fractal scaling exponents for CFS and CON by each method.

Results:
Both for CFS and CON, we found the fractal time structures in their diurnal physical activity records for at least up to 35 minutes. No group difference was found in nocturnal activities. The WTNMM method revealed that, in diurnal activities, CFS patients had significantly (p <0.01) smaller fractal scaling exponent (0.87 ± 0.03) compared to controls (1.01 ± 0.03). Such a difference was identified neither by the DFA nor WTMM method.

Conclusions:
CFS patients had more abrupt interruptions of voluntary physical activity during diurnal periods in normal daily life, probed by the decreased correlation in the negative modulus maxima of the wavelet-transformed activity data, possibly due to their exaggerated fatigue.
Fetal Heart Rate Variability due to Vibroacoustic Stimulation: Linear and Nonlinear Contribution
Authors: Signorini M. G. , Arduini D. , Cerutti S. , Magenes G. 
Published: March 2018

Summary

Objectives:
This work aims at characterizing the variation of fetal heart rate (FHR) provoked by vibro-acoustic stimulation (VAS). The FHR signal is analyzed by means of a multiparametric approach consisting of linear and nonlinear indices.

Methods:
The FHR signals of 13 fetuses were collected through a US standard CTG monitor (HP1351A) and were sampled at a frequency of 2 Hz. The VAS was provided after a period of quiet of 10 minutes. The analysis was performed on the quiet period and on two successive time windows of 10 minutes each, after the stimulation. FHR classical parameters (delta, short term variability, long term irregularity, accelerations and decelerations) as well as power spectral density (PSD) and approximate entropy (ApEn) were computed for each period.

Results:
Results confirm that there is a significant change in fetal conditions after the stimulus is applied. This change can be clearly observed either in time domain parameters and in the regularity index (ApEn). Individual data are all consistent with an increase of variability and a decrease of regularity after VAS.

Conclusions:
The obtained results give further strength to the hypothesis that vibratory stimuli tests represent a reliable method for monitoring the neural development of the fetus during pregnancy.
Cortical Potential Imaging of Brain Electrical Activity by Means of Parametric Projection Filter
Authors: Lian J. , He B. , Hori J. 
Published: March 2018

Summary

Objectives:
The objective of this study was to explore suitable spatial filters for inverse estimation of cortical potentials from the scalp electroencephalogram. The effect of incorporating noise covariance into inverse procedures was examined by computer simulations and tested in human experiment.

Methods:
The parametric projection filter, which allows inverse estimation with the presence of information on the noise, was applied to an inhomogeneous three-concentric-sphere model under various noise conditions in order to estimate the cortical potentials from the scalp potentials. The method for determining the optimum regularization parameter, which can be applied for parametric inverse techniques, is also discussed.

Results:
Human visual evoked potential experiment was carried out to examine the performance of the proposed restoration method. The parametric projection filter gave more localized inverse solution of cortical potential distribution than the truncated SVD and Tikhonov regularization.

Conclusion:
The present simulation results suggest that incorporation of information on the noise covariance allows better estimation of cortical potentials, than inverse solutions without knowledge about the noise covariance, when the correlation between the signal and noise is low.
Inclusion of Signal Analysis in a Hybrid Medical Decision Support System
Authors: Cohen M. E. , Meecham W. , Kramer M. , Hudson D. L. 
Published: March 2018

Summary

Objectives:
Signal analysis has played an important role in cardiac diagnosis, both as a separate entity and in conjunction with clinical parameters. Hybrid systems are an effective method for developing higher-order decision models in which biomedical signal data can be incorporated.

Methods:
The hybrid system components include a knowledge-based system that utilizes approximate reasoning techniques, a neural network model based on a potential function approach to supervised learning that uses the general class of Cohen orthogonal functions as potential functions, and a signal analysis component that relies on continuous chaotic modeling to produce a degree of variability in the time series. The hybrid system is illustrated in an application for differentiation among different types of dementia.

Results:
Application of this method to cardiac diagnosis shows that chaotic parameters alone contribute significantly to correct classification while the addition of clinical parameters increases the sensitivity, specificity, and accuracy. Applications to electroencephalogram analysis indicate that the second-order difference plots display significant differences for the different types of EEG waves identifiable by frequency, both in shape and degree of dispersion. Hence the identification of these waves, and the duration of their occurrence, may provide suitable variables for chaotic analysis.

Conclusions:
Results from studies in cardiology demonstrate that using chaotic measures for ECG analysis provide useful information for classification. Sensitivity, specificity, and accuracy are increased if these methods are combined with other clinical parameters in a hybrid system. This approach has been extended to new applications based on EEG analysis combined with other relevant information.
EuCliD® – A Medical Registry
Authors: Amato C. , Carioni C. , Kirchgessner J. , Marcelli D. , Mitteregger A. , Moscardo V. , Orlandini G. , Gatti E. , Steil H. 
Published: March 2018

Summary

Objectives:
The European Clinical Database EuCliD®
* has been developed as a tool for supervising selected quality indicators of about 200 European dialysis centers. Major efforts had to be made to comply with local and European laws regarding data security.

Method:
EuCliD® is a Lotus Notes® based flat-file database currently containing medical data of more than 14,000 dialysis patients from 10 European countries. Another 15,000 patients from 150 centers in 4 South-American countries will be added soon. Data are entered either manually or by means of interfaces to existing local data managing systems. This information is transferred to a central Lotus Notes Server. Data evaluation was performed with statistical tools like SPSS.

Results:
EuCliD® is used as a part of the CQI (Continuous Quality Improvement) management system of Fresenius Medical Care (FMC) dialysis units. Each participating dialysis center receives (currently every half year) benchmarking reports at a regular interval. The benchmark for all quality parameters is the weighted mean of the corresponding data of all centers.

Conclusions:
An obvious impact of data sampling and data evaluation on the quality of the treatments could be observed within the first one and a half years of working with EuCliD®. This also concerns important outcome predictors like Kt/V and hemoglobin concentration as the outcome itself expressed in hospitalization days and survival rates. With the help of EuCliD® the user is able to sample clinical data, identify problems, search for solutions with the aim of improving the dialysis treatment quality and guarantee a high-class treatment quality for all patients.
Content-based Image Retrieval in Medical Applications
Authors: Güld M. O. , Thies C. , Fischer B. , Spitzer K. , Keysers D. , Ney H. , Kohnen M. , Schubert H. , Wein B. B. , Lehmann T. M. 
Published: March 2018

Summary

Objectives:
To develop a general structure for semantic image analysis that is suitable for content-based image retrieval in medical applications and an architecture for its efficient implementation.

Methods:
Stepwise content analysis of medical images results in six layers of information modeling incorporating medical expert knowledge (raw data layer, registered data layer, feature layer, scheme layer, object layer, knowledge layer). A reference database with 10,000 images categorized according to the image modality, orientation, body region, and biological system is used. By means of prototypes in each category, identification of objects and their geometrical or temporal relationships are handled in the object and the knowledge layer, respectively. A distributed system designed with only three core elements is implemented: (i) the central database holds program sources, processing scheme descriptions, images, features, and administrative information about the workstation cluster; (ii) the scheduler balances distributed computing; and (iii) the web server provides graphical user interfaces for data entry and retrieval, which can be easily adapted to a variety of applications for content-based image retrieval in medicine.

Results:
Leaving-one-out experiments were distributed by the scheduler and controlled via corresponding job lists offering transparency regarding the viewpoints of a distributed system and the user. The proposed architecture is suitable for content-based image retrieval in medical applications. It improves current picture archiving and communication systems that still rely on alphanumerical descriptions, which are insufficient for image retrieval of high recall and precision.
Evaluation of Computer-assisted Image Enhancement in Minimal Invasive Endoscopic Surgery
Authors: Vogt F. , Hohenberger W. , Paulus D. , Niemann H. , Schick C. H. , Krüger S. 
Published: March 2018

Summary

Objectives:
This paper focusses on the evaluation of the usage of computer-aided image processing methods for minimal invasive surgery. During video endoscopy of visceral cavities the images are displayed directly on the monitor without further processing. In the course of the operation the former good quality of the images decreases due to typical disturbances like bleeding, smoke or flying particles. These disturbances can be reduced by using image processing methods like color normalization, temporal filtering or equalization.

Methods:
In this double-blinded analysis, 14 surgeons with different levels of experience evaluated 120 image pairs and 5 image sequences, directly comparing original and processed images or movies.

Results:
Color normalization and equalization proved to significantly enhance video endoscopic images. With regard to temporal filtering, an improvement could be seen in the image sequences with filter size 5 being a greater enhancement than filter size 3. Comparing the state of experience and its influence on the results, it occurred that the experienced surgeons preferred the original color while altogether agreeing that the color-normalized images were better.

Conclusions:
The results obtained in the present evaluation show that the image processing methods which were used can significantly improve the quality of video endoscopic images. As a result of this, necessary lavages of the operated area are reduced and a better overview and orientation for the surgeon can be reached.
Light Fields for Minimal Invasive Surgery Using an Endoscope Positioning Robot
Authors: Krüger S. , Schmidt J. , Paulus D. , Niemann H. , Hohenberger W. , Schick C. H. , Vogt F. 
Published: March 2018

Summary

Objectives:
To generate a fast and robust 3-D visualization of the operation site during minimal invasive surgery.

Methods:
Light fields are used to model and visualize the 3-D operation site during minimal invasive surgery. An endoscope positioning robot provides the position and orientation of the endoscope. The a priori unknown transformation from the endoscope plug to the endoscope tip (hand-eye transformation) can either be determined by a three-step algorithm, which includes measuring the endoscope length by hand or by using an automatic hand-eye calibration algorithm. Both methods are described in this paper and their respective computation times and accuracies are compared.

Results:
Light fields were generated during real operations and in the laboratory. The comparison of the two methods to determine the unknown hand-eye transformation was done in the laboratory. The results which are being presented in this paper are: rendered images from the generated light fields, the calculated extrinsic camera parameters and their accuracies with respect to the applied hand-eye calibration method, and computation times.

Conclusion:
Using an endoscope positioning robot and knowing the hand-eye transformation, the fast and robust generation of light fields for minimal invasive surgery is possible.
HELEN, a Modular Framework for Representing and Implementing Clinical Practice Guidelines
Authors: Gausepohl H.-J. , Haak M. , Knaebel S. , Linderkamp O. , Wetter T. , Skonetzki S. 
Published: March 2018

Summary

Objectives:
In order to implement clinical practice guidelines for the Department of Neonatology of the Heidelberg University Medical Center we developed a modular framework consisting of tools for authoring, browsing and executing encoded clinical practice guidelines (CPGs).

Methods:
Based upon a comprehensive analysis of literature, we set up requirements for guideline representation systems. Additionally, we analyzed further aspects such as the critical appraisal and known bridges and barriers for implementing CPGs. Thereafter we went through an evolutionary spiral model to develop a comprehensive ontology. Within this model each cycle focuses on a certain topic of management and implementation of CPGs.

Results:
In order to bring the resulting ontology into practice we developed a framework consisting of a tool for authoring, a server for web-based browsing, and an engine for the execution of certain elements of CPGs. Based upon this framework we encoded and implemented several CPGs in varying medical domains.

Conclusions:
This paper shall present a practical framework for both authors and implementers of CPGs. We have shown the fruitful combination of different knowledge representations such as narrative text and algorithm for implementing CPGs. Finally, we introduced a possible approach for the explicit adaptation of CPGs in order to provide institution-specific recommendations and to support sharing with other medical institutions.
Penalized Binary Regression for Gene Expression Profiling
Authors: Schimek Michae 
Published: March 2018

Summary

Objectives:
A typical bioinformatics task in microarray analysis is the classification of biological samples into two alternative categories. A procedure is needed which, based on the expression levels measured, allows us to compute the probability that a new sample belongs to a certain class.

Methods:
For the purpose of classification the statistical approach of binary regression is considered. High-dimensionality and at the same time small sample sizes make it a challenging task. Standard logit or probit regression fails because of condition problems and poor predictive performance. The concepts of frequentist and of Bayesian penalization for binary regression are introduced. A Bayesian interpretation of the penalized log-likelihood is given. Finally the role of cross-validation for regularization and feature selection is discussed.

Results:
Penalization makes classical binary regression a suitable tool for microarray analysis. We illustrate penalized logit and Bayesian probit regression on a well-known data set and compare the obtained results, also with respect to published results from decision trees.

Conclusions:
The frequentist and the Bayesian penalization concept work equally well on the example data, however some method-specific differences can be made out. Moreover the Bayesian approach yields a quantification (posterior probabilities) of the bias due to the constraining assumptions.
On a Hybrid Method in Dose Finding Studies
Authors: Pinheiro J. C. , Branson M. , Bretz F. 
Published: March 2018

Summary

Objectives:
Combination of multiple testing and modeling techniques in dose-response studies. Use of hypotheses tests to assess the significance of the dose-response signal associated with a given candidate dose-response model. Estimation of target dose(s) following the previous model selection step. Illustration of the method with a real data example.

Methods:
We assume a set of candidate models potentially reflecting the data generating process. The appropriateness of each individual model is evaluated in terms of contrast tests, where each set of contrast weights describes a specific dose-response shape. Optimum contrast weights are computed, which maxi-mize the non-centrality parameters associated with the contrast tests. A reference set of appropriate candidate models is obtained while controlling the familywise error rate. A single model is then selected from this reference set using standard model selection criteria. The final step is devoted to dose finding by applying inverse regression techniques. This is illustrated for estimating the minimum effective dose.

Results:
The method is as powerful as competing standard dose-response tests to detect an overall dose-related trend. In addition, the possibility is given to estimate one or more target doses of interest. The analysis of a real data example confirms the advantages of the proposed hybrid method.

Conclusions:
Combining multiple testing and modeling techniques leads to a powerful tool, which uses the advantages of both approaches: Rigid error control at the significance testing step and flexibility at the dose estimation step. The method can be extended to handle more general linear models including covariates and factorial treatment structures.