Sclerostin and DKK1 Inhibition Preserves and Augments Alveolar Bone Volume and Architecture in Rats with Alveolar Bone Loss.

Alveolar bone is a mechanosensitive tissue that provides structural support for teeth. Alveolar bone loss is common with aging, menopause, tooth loss, and periodontitis and can lead to additional tooth loss, reduced denture fixation, and challenges in placing dental implants. The current studies suggest that sclerostin and DKK1, which are established osteocyte-derived inhibitors of bone formation, contribute to alveolar bone loss associated with estrogen ablation and edentulism in rats. Estrogen-deficient ovariectomized rats showed significant mandibular bone loss that was reversed by systemic administration of sclerostin antibody (SAB) alone and in combination with DKK1 antibody (DAB). Osteocytes in the dentate and edentulous rat maxilla expressed Sost (sclerostin) and Dkk1 (DKK1) mRNA, and molar extraction appeared to acutely increase DKK1 expression. In a chronic rat maxillary molar extraction model, systemic SAB administration augmented the volume and height of atrophic alveolar ridges, effects that were enhanced by coadministering DAB. SAB and SAB+DAB also fully reversed bone loss that developed in the opposing mandible as a result of hypo-occlusion. In both treatment studies, alveolar bone augmentation with SAB or SAB+DAB was accompanied by increased bone mass in the postcranial skeleton. Jaw bone biomechanics showed that intact sclerostin-deficient mice exhibited stronger and denser mandibles as compared with wild-type controls. These studies show that sclerostin inhibition, with and without DKK1 coinhibition, augmented alveolar bone volume and architecture in rats with alveolar bone loss. These noninvasive approaches may have utility for the conservative augmentation of alveolar bone.

Gabapentin-induced pharmacodynamic effects in the spinal nerve ligation model of neuropathic pain.

BACKGROUND: The function of brain networks can be changed in a maladaptive manner in response to chronic neuropathic pain. Analgesics can reduce pain by acting on such networks via direct or indirect (peripheral or spinal) mechanisms. This investigation aimed to map gabapentin's pharmacodynamics (PD) in the rodent brain following induction of neuropathic pain in order to further understand its PD profile. METHODS: Pharmacological magnetic resonance imaging (phMRI) and a novel functional connectivity analysis procedure were performed following vehicle or gabapentin treatment in the rat spinal nerve ligation (SNL) model of neuropathic pain as well as sham animals. RESULTS: phMRI performed in SNL animals revealed robust gabapentin-induced responses throughout the hippocampal formation, yet significant (p < 0.05, corrected for multiple comparisons) responses were also measured in other limbic structures and the sensorimotor system. In comparison, sham animals displayed weaker and less widespread phMRI signal changes subsequent to gabapentin treatment. Next, communities of networks possessing strong functional connectivity were elucidated in vehicle-treated SNL and sham animals. We observed that SNL and sham animals possessed distinct functional connectivity signatures. When measuring how gabapentin altered the behaviour of the discovered networks, a decrease in functional connectivity driven by gabapentin was not only observed, but the magnitude of this PD effect was greater in SNL animals. CONCLUSIONS: Using phMRI and functional connectivity analysis approaches, the PD effects of gabapentin in a preclinical neuropathic pain state were characterized. Furthermore, the current results offer insights on which brain systems gabapentin directly or indirectly acts upon.

Fast maximum-likelihood estimation methods for scintillation cameras and other optical sensors.

Maximum-likelihood estimation methods offer many advantages for processing experimental data to extract information, especially when combined with carefully measured calibration data. There are many tasks relevant to x-ray and gamma-ray detection that can be addressed with a new, fast ML-search algorithm that can be implemented in hardware or software. Example applications include gamma-ray event position, energy, and timing estimation, as well as general applications in optical testing and wave-front sensing.

Real-time Data Acquisition and Maximum-Likelihood Estimation for Gamma Cameras.

We have developed modular gamma-ray cameras for biomedical imaging that acquire data with a raw list-mode acquisition architecture. All observations associated with a gamma-ray event, such as photomultiplier (PMT) signals and time, are assembled into an event packet and added to an ordered list of event entries that comprise the acquired data. In this work we present the design of the data-acquisition system, and discuss algorithms for a specialized computing engine to reside in the data path between the front and back ends of each camera and carry out maximum-likelihood position and energy estimations in real time while data was being acquired..