Patient-specific Conditional Joint Models of Shape, Image Features and Clinical Indicators

We propose and demonstrate a joint model of anatomical shapes, image features and clinical indicators for statistical shape modeling and medical image analysis. The key idea is to employ a copula model to separate the joint dependency structure from the marginal distributions of variables of interest. This separation provides flexibility on the assumptions made during the modeling process. The proposed method can handle binary, discrete, ordinal and continuous variables. We demonstrate a simple and efficient way to include binary, discrete and ordinal variables into the modeling. We build Bayesian conditional models based on observed partial clinical indicators, features or shape based on Gaussian processes capturing the dependency structure. We apply the proposed method on a stroke dataset to jointly model the shape of the lateral ventricles, the spatial distribution of the white matter hyperintensity associated with periventricular white matter disease, and clinical indicators. The proposed method yields interpretable joint models for data exploration and patient-specific statistical shape models for medical image analysis.Comment: Supplementary material: https://www.youtube.com/watch?v=gPoHP_iFQI

Energy cost and return for hunting in African wild dogs and Cheetahs

African wild dogs (Lycaon pictus) are reported to hunt with energetically costly long chase distances. We used high-resolution GPS and inertial technology to record 1,119 high-speed chases of all members of a pack of six adult African wild dogs in northern Botswana. Dogs performed multiple short, high-speed, mostly unsuccessful chases to capture prey, while cheetahs (Acinonyx jubatus) undertook even shorter, higher-speed hunts. We used an energy balance model to show that the energy return from group hunting and feeding substantially outweighs the cost of multiple short chases, which indicates that African wild dogs are more energetically robust than previously believed. Comparison with cheetah illustrates the trade-off between sheer athleticism and high individual kill rate characteristic of cheetahs, and the energetic robustness of frequent opportunistic group hunting and feeding by African wild dogs

Investigations on antibody binding to a micro-cantilever coated with a BAM pesticide residue

The attachment of an antibody to an antigen-coated cantilever has been investigated by repeated experiments, using a cantilever-based detection system by Cantion A/S. The stress induced by the binding of a pesticide residue BAM (2,6 dichlorobenzamide) immobilized on a cantilever surface to anti-BAM antibody is measured using the CantiLab4© system from Cantion A/S with four gold-coated cantilevers and piezo resistive readout. The detection mechanism is in principle label-free, but fluorescent-marked antibodies have been used to subsequently verify the binding on the cantilever surface. The bending and increase in mass of each cantilever has also been investigated using a light interferometer and a Doppler Vibrometer. The system has been analyzed during repeated measurements to investigate whether the CantiLab4© system is a suited platform for a pesticide assay system

Novel Information on the Epitope of an Inverse Agonist Monoclonal Antibody Provides Insight into the Structure of the TSH Receptor

The TSH receptor (TSHR) comprises an extracellular leucine-rich domain (LRD) linked by a hinge region to the transmembrane domain (TMD). Insight into the orientation of these components to each other is required for understanding how ligands activate the receptor. We previously identified residue E251 at the LRD-hinge junction as contributing to coupling TSH binding with receptor activation. However, a single residue cannot stabilize the LRD-hinge unit. Therefore, based on the LRD crystal structure we selected for study four other potential LRD-hinge interface charged residues. Alanine substitutions of individual residues K244, E247, K250 and R255 (as well as previously known E251A) did not affect TSH binding or function. However, the cumulative mutation of these residues in varying permutations, primarily K250A and R255A when associated with E251A, partially uncoupled TSH binding and function. These data suggest that these three residues, spatially very close to each other at the LRD base, interact with the hinge region. Unexpectedly and most important, monoclonal antibody CS-17, a TSHR inverse agonist whose epitope straddles the LRD-hinge, was found to interact with residues K244 and E247 at the base of the convex LRD surface. These observations, together with the functional data, exclude residues K244 and E247 from the TSHR LRD-hinge interface. Further, for CS-17 accessibility to K244 and E247, the concave surface of the TSHR LRD must be tilted forwards towards the hinge region and plasma membrane. Overall, these data provide insight into the mechanism by which ligands either activate the TSHR or suppress its constitutive activity

Subcellular localization of type-I thionins in the endosperms of wheat and barley.

Thionins are cysteine-rich polypeptides of about 5,000 Da. Localization at the subcellular level of type I endosperm thionins has been carried out by immunogold labeling, using an antibody that recognizes type I thionin variants. In developing wheat and barley caryopses, sectioned at different times between 13 and 24 days after flowering, this type of thionins was only detected around protein bodies from cells of the starchy endosperm, using light microscopy. Electron microscopy revealed that these proteins were located in electron-dense spheroids in the periphery of protein bodies, at the earlier stages, whereas later the label appeared also as a thin layer around these organelles

The development and application of a new tool to assess the adequacy of the content and timing of antenatal care

Abstract Background: Current measures of antenatal care use are limited to initiation of care and number of visits. This study aimed to describe the development and application of a tool to assess the adequacy of the content and timing of antenatal care. Methods: The Content and Timing of care in Pregnancy (CTP) tool was developed based on clinical relevance for ongoing antenatal care and recommendations in national and international guidelines. The tool reflects minimal care recommended in every pregnancy, regardless of parity or risk status. CTP measures timing of initiation of care, content of care (number of blood pressure readings, blood tests and ultrasound scans) and whether the interventions were received at an appropriate time. Antenatal care trajectories for 333 pregnant women were then described using a standard tool (the APNCU index), that measures the quantity of care only, and the new CTP tool. Both tools categorise care into 4 categories, from ‘Inadequate’ (both tools) to ‘Adequate plus’ (APNCU) or ‘Appropriate’ (CTP). Participants recorded the timing and content of their antenatal care prospectively using diaries. Analysis included an examination of similarities and differences in categorisation of care episodes between the tools. Results: According to the CTP tool, the care trajectory of 10,2% of the women was classified as inadequate, 8,4% as intermediate, 36% as sufficient and 45,3% as appropriate. The assessment of quality of care differed significantly between the two tools. Seventeen care trajectories classified as ‘Adequate’ or ‘Adequate plus’ by the APNCU were deemed ‘Inadequate’ by the CTP. This suggests that, despite a high number of visits, these women did not receive the minimal recommended content and timing of care. Conclusions: The CTP tool provides a more detailed assessment of the adequacy of antenatal care than the current standard index. However, guidelines for the content of antenatal care vary, and the tool does not at the moment grade over-use of interventions as ‘Inappropriate’. Further work needs to be done to refine the content items prior to larger scale testing of the impact of the new measure

“My Lung Disease Won’t Go Away, it’s There to Stay”: Profiles of Adaptation to Functional Limitations in Workers with Asthma and COPD

Purpose Earlier research has shown that adaptation (i.e., the way in which employees cope with limitations resulting from their disease) is associated with sick leave. Our aim was to investigate signs of adequate or inadequate adaptation in employees with asthma and COPD. Methods A Q-methodological study was carried out among 34 workers with asthma or COPD. Results Four adaptation profiles were distinguished: the eager, the adjusted, the cautious, and the worried workers. The adaptation profiles provide insight into the different ways in which workers with asthma and COPD cope with their illness at work. Conclusions The adaptation profiles serve as a starting point for the design of appropriate (occupational) care. The eager workers experience little difficulties at work; the cautious workers may need assistance in learning how to accept their disease; the worried workers need reassurance, and may need reactivation; the adjusted workers deserve extra attention, and, when necessary, advice on how to live with their asthma or COPD

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

Activity and regulation by growth factors of calmodulin-dependent protein kinase III (elongation factor 2-kinase) in human breast cancer

Calmodulin-dependent protein kinase III (CaM kinase III, elongation factor-2 kinase) is a unique member of the Ca2+/CaM-dependent protein kinase family. Activation of CaM kinase III leads to the selective phosphorylation of elongation factor 2 (eEF-2) and transient inhibition of protein synthesis. Recent cloning and sequencing of CaM kinase III revealed that this enzyme represents a new superfamily of protein kinases. The activity of CaM kinase III is selectively activated in proliferating cells; inhibition of the kinase blocked cells in G0/G1-S and decreased viability. To determine the significance of CaM kinase III in breast cancer, we measured the activity of the kinase in human breast cancer cell lines as well as in fresh surgical specimens. The specific activity of CaM kinase III in human breast cancer cell lines was equal to or greater than that seen in a variety of cell lines with similar rates of proliferation. The specific activity of CaM kinase III was markedly increased in human breast tumour specimens compared with that of normal adjacent breast tissue. The activity of this enzyme was regulated by breast cancer mitogens. In serum-deprived MDA-MB-231 cells, the combination of insulin-like growth factor I (IGF-I) and epidermal growth factor (EGF) stimulated cell proliferation and activated CaM kinase III to activities observed in the presence of 10% serum. Inhibition of enzyme activity blocked cell proliferation induced by growth factors. In MCF-7 cells separated by fluorescence-activated cell sorting, CaM kinase III was increased in S-phase over that of other phases of the cell cycle. In summary, the activity of Ca2+/CaM-dependent protein kinase III is controlled by breast cancer mitogens and appears to be constitutively activated in human breast cancer. These results suggest that CaM kinase III may contribute an important link between growth factor/receptor interactions, protein synthesis and the induction of cellular proliferation in human breast cancer. © 1999 Cancer Research Campaig

Design of Experiments for Screening

The aim of this paper is to review methods of designing screening experiments, ranging from designs originally developed for physical experiments to those especially tailored to experiments on numerical models. The strengths and weaknesses of the various designs for screening variables in numerical models are discussed. First, classes of factorial designs for experiments to estimate main effects and interactions through a linear statistical model are described, specifically regular and nonregular fractional factorial designs, supersaturated designs and systematic fractional replicate designs. Generic issues of aliasing, bias and cancellation of factorial effects are discussed. Second, group screening experiments are considered including factorial group screening and sequential bifurcation. Third, random sampling plans are discussed including Latin hypercube sampling and sampling plans to estimate elementary effects. Fourth, a variety of modelling methods commonly employed with screening designs are briefly described. Finally, a novel study demonstrates six screening methods on two frequently-used exemplars, and their performances are compared