Hidden Markov Models With Set-Valued Parameters

Hidden Markov models (HMMs) are widely used probabilistic models of sequential data. As with other probabilistic models, they require the specification of local conditional probability distributions, whose assessment can be too difficult and error-prone, especially when data are scarce or costly to acquire. The imprecise HMM (iHMM) generalizes HMMs by allowing the quantification to be done by sets of, instead of single, probability distributions. iHMMs have the ability to suspend judgment when there is not enough statistical evidence, and can serve as a sensitivity analysis tool for standard non-stationary HMMs. In this paper, we consider iHMMs under the strong independence interpretation, for which we develop efficient inference algorithms to address standard HMM usage such as the computation of likelihoods and most probable explanations, as well as performing filtering and predictive inference. Experiments with real data show that iHMMs produce more reliable inferences without compromising the computational efficiency.

Using a Discrete Hidden Markov Model Kernel for lip-based biometric identification

In this paper, a novel and effective lip-based biometric identification approach with the Discrete Hidden Markov Model Kernel (DHMMK) is developed. Lips are described by shape features (both geometrical and sequential) on two different grid layouts: rectangular and polar. These features are then specifically modeled by a DHMMK, and learnt by a support vector machine classifier. Our experiments are carried out in a ten-fold cross validation fashion on three different datasets, GPDS-ULPGC Face Dataset, PIE Face Dataset and RaFD Face Dataset. Results show that our approach has achieved an average classification accuracy of 99.8%, 97.13%, and 98.10%, using only two training images per class, on these three datasets, respectively. Our comparative studies further show that the DHMMK achieved a 53% improvement against the baseline HMM approach. The comparative ROC curves also confirm the efficacy of the proposed lip contour based biometrics learned by DHMMK. We also show that the performance of linear and RBF SVM is comparable under the frame work of DHMMK.

Human odontoblasts express functional TRPV2 channels

Background: The transient receptor potential (TRP) ion channels play a critical role in sensory physiology, where they act as transducers of thermal, mechanical and chemical stimuli. We have previously shown the functional expression of several TRP channels by human odontoblast-like cells and proposed their significance in odontoblast sensory perception. Functional expression of the mechano-sensitiveTRPV2 channel by human odontoblasts would further support a role for TRP channels in odontoblast physiology. Objective: The objective of the current study was to determine the functional expression of TRPV2 by human odontoblasts. Methods: Human dental pulp cells were cultured in the presence of 2 mM β-glycerophoshate to induce an odontoblast phenotype. TRPV2 gene expression was determined by qPCR employing custom designed FAM TRPV2 specific primers and probes (Roche, UK) and the Light Cycler 480 Probes Master (Roche). TRPV2 protein expression was determined following SDS-PAGE and Western blotting of cell lysate preparations. Functional expression of TRPV2 was investigated by Ca2+ microfluorimetry. Results: qPCR data indicated robust expression of TRPV2 in odontoblast-like cells. Western blotting revealed a discrete immunoreactive protein band indicating expression of TRPV2 in cell lysates. In functional assays, the chemical agonist of TRPV2, cannabidiol, was shown to elicit [Ca2+]i transients, that were reduced to baseline in the presence of the TRPV2 antagonist Tranilast, suggesting channel functionality in odontoblast-like cells. Conclusion: These results provide the first evidence for the functional expression of TRPV2 in human odontoblast-like cells, providing further support for the role of TRP channels in odontoblast physiology.

Protease activated receptor 2 expression and functionality in caries

Introduction: Protease activated receptors (PARs) are G-protein-coupled transmembrane receptors that are expressed on many cell types and implicated in various inflammatory processes in vivo. The induction of PAR2 as a result of the inflammatory response associated with dental caries remains to be determined. Objectives: The aim was to localise the expression of PAR2 in human dental pulp from carious teeth and to confirm receptor functionality using an in vitro assay. Methods: Dental pulp sections from decalcified carious teeth were examined by immunocytochemsitry. Membrane preparations from cultured pulp fibroblasts were subject to SDS-PAGE and immunoblotting to confirm fibroblast-associated immunoreactivity. The functionality of PAR2 on dental pulp fibroblasts was studied using calcium imaging in the presence of several potential activators including a PAR2 agonist (PAR2-AP), trypsin and pulpal enzymes from a carious tooth. Results: Immunocytochemistry revealed intense PAR2 immunoreactivity on pulpal fibroblasts subjacent to carious lesions but not in surrounding regions of the dental pulp. Pulp specimens from a dental injury model showed no expression of PAR2, suggesting its expression was related to cellular changes associated with ongoing caries. The localisation of PAR2 staining to pulpal fibroblasts in carious teeth was confirmed by Western blotting which revealed PAR2 immunoreactive bands in membrane fractions prepared from pulp fibroblasts. In functional studies, challenge of cultured pupal fibroblasts with PAR2-AP, trypsin and an extract of proteolytic enzymes from a carious dental pulp, showed specific activation of PAR2. Conclusions: This work demonstrates that PAR2 is functional and inducible in human dental pulp fibroblasts in response to caries and that endogenous pulpal enzymes can activate PAR2.

Diabetes Distress: Understanding the Hidden Struggles of Living with Diabetes and Exploring Intervention Strategies

Diabetes Distress is a rational emotional response to the threat of a life-changing illness. Distinct from depression, it is rooted in the demands of diabetes management and is a product of psychological adjustment. Diabetes distress has been found to be significantly associated with HbA1c and self-care, which demonstrates its clinical use in treatment outcomes. Interpersonal factors such as perceived support and protectiveness of partners significantly contribute to elevated distress, suggesting that these are valued areas of focus for interventions. Pioneering large-scale research, DAWN2, gives voices to the families of those with diabetes and reaffirms the need to consider psychosocial factors in routine diabetes care. Structured diabetes education programmes are the most widely used in helping individuals cope with diabetes, but they fail to consider the psychological or interpersonal aspects of diabetes management. Psycho-educational approaches are found to be effective in reducing diabetes distress while also improving HbA1c. Certain limitations in the current literature are discussed, along with future directions. Of utmost importance is the need for health practitioners, irrespective of background, to demonstrate an understanding of diabetes distress and actively engage in discussion with individuals struggling to cope with diabetes; to normalize this and integrate it into routine diabetes practice.