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1.
Cell Physiol Biochem ; 46(4): 1471-1482, 2018.
Article in English | MEDLINE | ID: mdl-29689555

ABSTRACT

BACKGROUND/AIMS: In this study we assessed histomorphometric changes induced by thyroxine (T4) in 3-month-old hyperthyroid male rats and examined whether the potential mechanism of these changes is related to bone changes. METHODS: Rats were classified as either hyperthyroid following administration of 250 µg/kg/day freshly prepared T4 by gavage for 2 months or euthyroid following administration of vehicle alone (n = 8 per group). We measured bone mineral density (BMD), bone biomechanical properties, and bone histomorphometric changes. Levels of serum indicators were also measured, and three right femurs from the two groups were selected for proteomic investigation. RESULTS: Compared with the control rats, hyperthyroid rats showed a reduction in the fifth lumbar vertebral BMD as well as in the entire femoral BMD (p = 0.033 and 0.026, respectively). Histomorphometric analysis of the proximal tibial metaphysis showed that the percentage of the trabecular area, trabecular number, and percentage of the cortical bone area in the hyperthyroid rats significantly decreased compared with those of the control rats. Conversely, bone formation rate (per unit of bone surface and bone volume), percentage of the osteoclast perimeter, trabecular separation, and endosteal mineral apposition rate in the hyperthyroid rats significantly increased compared with the control rats (all p < 0.05). Except for stiffness (p = 0.24), all bone biomechanical properties of the femur showed a significant decreasing trend in the hyperthyroid rats versus the control rats (all p < 0.05). Serum levels of osteocalcin, alkaline phosphatase, terminal telopeptides of type ß collagen, and tartrate-resistant acid phosphatase were higher in the hyperthyroid rats than in the control rats (all p < 0.05). Using isobaric tags for relative and absolute quantification (iTRAQ), the expression levels of 1,310 proteins were found to be significantly different between the hyperthyroid and control rats (711 proteins were upregulated and 599 were downregulated in hyperthyroid rats). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses showed that most of the enzymes in the glycolysis-tricarboxylic acid (TCA) cycle-oxidative phosphorylation signalling pathway were upregulated in hyperthyroid rats, and seven differentially expressed proteins were selected to verify the iTRAQ results using western blotting. CONCLUSION: Energy metabolism via the glycolysis-TCA cycle-oxidative phosphorylation pathway is positively associated with T4-induced bone histomorphometric changes in rats.


Subject(s)
Bone and Bones/pathology , Energy Metabolism/physiology , Hyperthyroidism/pathology , Alkaline Phosphatase/blood , Animals , Bone Density , Bone and Bones/metabolism , Chromatography, High Pressure Liquid , Femur/metabolism , Femur/pathology , Hyperthyroidism/metabolism , Hyperthyroidism/veterinary , Male , Osteocalcin/blood , Rats , Rats, Sprague-Dawley , Spectrometry, Mass, Electrospray Ionization , Tartrate-Resistant Acid Phosphatase/blood , Thyroxine/blood , Triiodothyronine/blood
2.
Pattern Recognit Lett ; 32(15): 2128-2135, 2011 Nov 01.
Article in English | MEDLINE | ID: mdl-22140290

ABSTRACT

Image-based morphometry is an important area of pattern recognition research, with numerous applications in science and technology (including biology and medicine). Fisher Linear Discriminant Analysis (FLDA) techniques are often employed to elucidate and visualize important information that discriminates between two or more populations. We demonstrate that the direct application of FLDA can lead to undesirable errors in characterizing such information and that the reason for such errors is not necessarily the ill conditioning in the resulting generalized eigenvalue problem, as usually assumed. We show that the regularized eigenvalue decomposition often used is related to solving a modified FLDA criterion that includes a least-squares-type representation penalty, and derive the relationship explicitly. We demonstrate the concepts by applying this modified technique to several problems in image-based morphometry, and build discriminant representative models for different data sets.

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