•Pyometra is associated with insulin resistance and glucose intolerance in bitches.•Reduced tyrosine kinase activity in muscle tissue due to pyometra is similar to observed in diestrus when compared ...with anestrus.•Pyometra and diestrus were associated with higher dissociation constant of the high-affinity insulin receptors.•Bitches in diestrus, but not the ones with pyometra, compensated higher dissociation constants increasing insulin binding capacity.
Diestrus is associated with insulin resistance in bitches and pyometra can further impair insulin sensitivity. This study aimed to compare insulin sensitivity, insulin binding, and tyrosine kinase activity in bitches in anestrus, diestrus, or with pyometra. Patients submitted to elective ovariohysterectomy were divided into anestrus (n = 11) or diestrus (n = 13) according to reproductive history, vaginal cytology, and uterine histology. The group pyometra (n = 8) included bitches diagnosed with the disease based on clinical presentation and abdominal ultrasound findings and further confirmed by uterine histopathology. All patients were submitted to an intravenous glucose tolerance test (IVGTT) before ovariohysterectomy, and rectus abdominis muscle samples were collected during surgery for plasmatic membrane suspension preparation. Muscle-membranes were submitted to cold saturation insulin binding assay for dissociation constant (Kd) and maximum binding capacity (Bmax) determination, as well as exogenous substrate Poly (Glu: Tyr 4:1) phosphorylation assay for basal tyrosine kinase evaluation. Bitches with pyometra showed higher basal insulin (P < 0.001) and higher area under the curve (AUC) for insulin (P = 0.01) and glucose (P < 0.001) response during the IVGTT in comparison with bitches in anestrus or diestrus. Diestrus (P < 0.0001) and pyometra (P = 0.001) were associated with reduced tyrosine kinase activity in comparison with anestrus. No differences were documented in Kd and Bmax results for the low-affinity/high-capacity insulin receptors; however, high-affinity/low-capacity insulin receptors showed higher Kd and Bmax results in bitches in diestrus or with pyometra (P < 0.05) in comparison with anestrus. Despite the pyometra group showed the highest Kd values (P < 0.01), its Bmax results did not differ from the diestrus group (P > 0.05). Diestrus’ higher Kd values and reduced tyrosine kinase activity in muscle tissue were compensated by increased total insulin binding capacity. Absent differences in IVGTT results between diestrus and anestrus bitches corroborate this finding. However, in bitches with pyometra, the highest Kd values were not compensated by increased total insulin binding capacity. This finding was associated with insulin resistance and glucose intolerance in IVGTT results. Moreover, pyometra resolution restored insulin sensitivity and glucose tolerance. These features can play a key role in pyometra-associated CDM, as well as in diabetic remission after pyometra resolution.
In this paper, a new approach to computer supported diagnosis of skin tumors in dermatology is presented. High resolution skin surface profiles are analyzed to recognize malignant melanomas and ...nevocytic nevi (moles), automatically. In the first step, several types of features are extracted by 2D image analysis methods characterizing the structure of skin surface profiles: texture features based on cooccurrence matrices, Fourier features and fractal features. Then, feature selection algorithms are applied to determine suitable feature subsets for the recognition process. Feature selection is described as an optimization problem and several approaches including heuristic strategies, greedy and genetic algorithms are compared. As quality measure for feature subsets, the classification rate of the nearest neighbor classifier computed with the leaving-one-out method is used. Genetic algorithms show the best results. Finally, neural networks with error back-propagation as learning paradigm are trained using the selected feature sets. Different network topologies, learning parameters and pruning algorithms are investigated to optimize the classification performance of the neural classifiers. With the optimized recognition system a classification performance of 97.7% is achieved.
Two 3-D digitised atlases of a female and a male pelvis were generated to support the virtual 3-D planning of hip operations. The anatomical atlases were designed to replace the interactive, ...time-consuming pre-processing steps for the virtual operation planning. Each atlas consists of a labelled reference CT data set and a set of anatomical point landmarks. The paper presents methods for the automatic transfer of these anatomical labels to an individual patient data set. The labelled patient data are used to generate 3-D models of the patient's bone structures. Besides the anatomical labelling, the determination of measures, like angles, distances or sizes of contact areas, is important for the planning of hip operations. Thus, algorithms for the automatic computation of orthopaedic parameters were implemented. A first evaluation of the presented atlas-based segmentation method shows a correct labelling of 98.5% of the bony voxels.
The ultrahigh porosity and varied functionalities of porous metal–organic frameworks make them excellent candidates for applications that range widely from gas storage and separation to catalysis and ...sensing. An interesting feature of some frameworks is the ability to open their pores to a specific guest, enabling highly selective separation. A prerequisite for this is bistability of the host structure, which enables the framework to breathe, that is, to switch between two stability minima in response to its environment. Here we describe a porous framework DUT-8(Ni)—which consists of nickel paddle wheel clusters and carboxylate linkers—that adopts a configurationally degenerate family of disordered states in the presence of specific guests. This disorder originates from the nonlinear linkers arranging the clusters in closed loops of different local symmetries that in turn propagate as complex tilings. Solvent exchange stimulates the formation of distinct disordered frameworks, as demonstrated by high-resolution transmission electron microscopy and diffraction techniques. Guest exchange was shown to stimulate repeatable switching transitions between distinct disorder states.Some flexible metal–organic frameworks are known to exhibit an adaptive behaviour as they convert between two stable forms in response to their environment. Now, a metal–organic framework based on nonlinear linkers has been shown to adopt a much more complex family of degenerate disordered configurations, which can be reversibly interconverted through guest exchange.
Motivation: Human decisions often proceed in two steps. Initially those most preferred are chosen followed by a subsequent choice of these preferences. Applying one artificial neural network (ANN), a ...classification is limited to the preselection process. The final categorization is only possible by a subsequent ANN that distinguishes the pre-chosen classes. Existing strategies using coupled ANNs are discussed and a new approach particularly suited for multiclass classification problems is introduced (‘Subsequent ANN’, SANN). Results: Evaluating a simulated data base comprising 3 classes, classification results of SANN were obviously superior to those achieved by ANN. To evaluate a real-world data base the microarray benchmark GCM (14 classes) was chosen. The ANN results reached 72%, comparable to previous results. Using SANN, up to 81% of the tumors were correctly classified. Availability: Programs used in this work and numerical results are available upon request.
This paper describes methods for the automatic atlas-based segmentation of bone structures of the hip, the automatic detection of anatomical point landmarks and the computation of orthopedic ...parameters to avoid the interactive, time-consuming pre-processing steps for the virtual planning of hip operations.
Based on the CT data of the Visible Human Data Sets, two three-dimensional atlases of the human pelvis have been built. The atlases consist of labeled CT data sets, 3D surface models of the separated structures and associated anatomical point landmarks. The atlas information is transferred to the patient data by a non-linear gray value-based registration algorithm. A surface-based registration algorithm was developed to detect the anatomical landmarks on the patient's bone structures. Furthermore, a software tool for the automatic computation of orthopedic parameters is presented. Finally, methods for an evaluation of the atlas-based segmentation and the atlas-based landmark detection are explained.
A first evaluation of the presented atlas-based segmentation method shows the correct labeling of 98.5% of the bony voxels. The presented landmark detection algorithm enables the precise and reliable localization of orthopedic landmarks. The accuracy of the landmark detection is below 2.5 mm.
The atlas-based segmentation of bone structures, the atlas-based landmark detection and the automatic computation of orthopedic measures are suitable to essentially reduce the time-consuming user interaction during the pre-processing of the CT data for the virtual three-dimensional planning of hip operations.
To report the use of three dimensional (3D) computed tomographic (CT) imaging, computer simulation and rapid prototype modelling to aid surgical correction of a complex antebrachial deformity in a ...dog.
A six-year-old, 13 kg spayed female Chihuahua crossbreed dog was presented for worsening forelimb gait and exercise intolerance. Both forelimbs had gross angular limb deformity with carpal hyper-flexion, valgus and radial procurvatum. Surgical planning from radiographs was problematic therefore CT data were used to generate 3D reconstructions of the antebrachium. Using imaging software we then quantified the nature of the deformity using a previously unreported method based on the centre of rotation of angulation as a 3D model. Computer simulated closing of the virtual wedge osteotomy was then performed as proof of concept. A stereolithographic model complete with osteotomy axes, was then created in plastic using a rapid prototyping machine. Oscillating saw guides were fabricated in polymethylmethacrylate and cold sterilised. A closing wedge osteotomy with de-rotation was performed and stabilised with a pre-contoured dynamic compression plate. At the three- and six-month follow-up examinations there was improved weight-bearing and cosmetic appearance.
Computer assistance was valuable for locating and quantifying this antebrachial deformity and conceptualising the corrective surgery. The results of our study suggest that rapid prototyping can be used to create models and saw guides to simplify one-stage corrective osteotomies and more accurately treat angular limb deformity.
The introduction of virtual reality techniques in medicine opens up new possibilities for the planning of interventions. The presented software system for virtual operation planning in orthopaedic ...surgery (VIRTOPS) enables the virtual preoperative 3D planning and simulation of pelvis and hip operations. It is used to plan operations of bone tumours with endoprosthetic reconstruction of the hip based on multimodal image information. The operation and the endosprothetic reconstruction of the pelvis are simulated using virtual reality techniques. Stereoscopic visualisation techniques and 3D input devices support the 3D interaction with the virtual 3D models. The main task of the preoperative planning process is the individual design of an anatomically adaptable modular prosthesis. The placement and the design of the endoprosthesis are supported by different functions and visualisation techniques. The resulting 3D images and movies can be used for the documentation of the operation planning procedure, as well as, for the preoperative information of the patient.
Accurately predicting disease progress from a set of predictive variables is an important aspect of clinical work. For binary outcomes, the classical approach is to develop prognostic logistic ...regression (LR) models. Alternatively, machine learning algorithms were proposed with artificial neural networks (ANN) having become popular over the last decades. Although some studies have compared predictive accuracies of LR and ANN models, some concerns regarding their methodological quality have been voiced. Our comparison has the advantage of being based on two large independent data sets allowing for elaborate model development and independent validation.
From the German Stroke Database, a learning data set including 1754 prospectively recruited patients with acute ischemic stroke was used. Utilizing LR and ANN, two prognostic models were developed predicting restitution of functional independence and survival after 100 days. The resulting models were applied to classify 1470 patients with acute ischemic stroke; this test data set was collected independently from the learning data. Error fractions in the test data were determined, and differences in error fractions between the algorithms were calculated with 95% confidence intervals.
For most prognostic models, error fractions in the test data were below 40%. There was no difference between the algorithms except for the model predicting completely versus incompletely restituted or deceased patients (difference in error fractions = 4.01% 2.10-5.96%, p = 0.0001).
The conscientiously applied LR remains the gold standard for prognostic modelling; however, ANN can be an alternative automated "quick and easy" multivariate analysis.
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