Osteoporose-Update 2021

Jakob, Franz

doi:10.1055/a-1213-2245

Cited by 4 publications

(5 citation statements)

References 14 publications

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“…In foreign literature, we can find the term "silent disease" when the scientists talk about "osteoporosis" [1,8,9]. Elderly and senile ages are critical periods for the development of osteoporosis and its complications -low-energy osteoporotic fractures, the most severe of which is a hip fracture, the occurrence of which leads to prolonged disability and death of the patients [2,[8][9][10]. Additionally, the presence of other osteoporotic fractures, that are vertebral ones, often leads to back pain and reduced work capacity of the patients.…”

Section: Discussionmentioning

confidence: 99%

“…During aging, the risk of various diseases increases in a person, as there are age-related changes in various organs and systems. Bone system aging is characterized by the development of degenerative-dystrophic and metabolic changes that lead to the development of osteoporosis and its complications - low-traumatic fractures, which not only reduce the working capacity of the patients and limit their daily capabilities, but also lead to an increase in mortality rates due to low-traumatic fractures [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

“…Nowadays, the indices of bone mineral density (BMD) and its quality, measured by dual-photon X-ray absorptiometry (DXA), make it possible to assess authentically the bone strength and the risk of osteoporotic fractures. The BMD index determines about 70-75 % of bone strength and, according to the current recommendations of leading world societies (ISCD, IOF), is used for the diagnosis of osteoporosis [1,2].…”

Section: Introductionmentioning

confidence: 99%

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Mathematical model of the bone biological age based on the bone mineral density and quality indicex and Ukrainian FRAX model

Grygorieva

Koshel²,

Pisaruk³

et al. 2022

PJS

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Background. It is well-known that with aging there is a loss of bone mass and its strength, which leads to the development of osteoporosis and its complications. The aim of the study was to create a modern mathematical model for determining the biological age of the bone system, taking into account indices of bone mineral density (BMD) and quality and the FRAX® questionnaire. Materials and methods. 77 women and 44 men aged 30 to 90 years without any significant somatic pathology were included in the study. Patients were divided into 4 age groups: 30–44 years old — young, 45–59 years — mature, 60–74 years — old age and 75–90 years — senile age. We measured the parameters of BMD in the different areas of the skeleton by means of the dual-photon X-ray absorptiometry (DXA, “Prodigy”). The 10-year probability of major osteoporotic and hip fractures was measured using the Ukrainian version of the FRAX®. Statistical analysis was performed in the Statistica 7.0 program (StatSoft Inc., USA). Results. The dependence of the indices of BMD and bone quality, risk of osteoporotic fractures on age and the need for their early determination in young people to predict the risk of osteoporosis and its complications have been proven. The coefficient of determination of the R2 model was 0.62, which indicates that 62 % of the variance of the “Age” can be explained by the predictors included in the model (DXA and FRAX indices); adjusted R2 index was 0.59 (p < 0.001), which indicates high significance of the model. Conclusions. The developed model for estimating the bone biological age has high accuracy and can be used to assess the risk of osteoporosis and its complications in young people for the purpose of predicting the disease.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mathematical model of the bone biological age based on the bone mineral density and quality indicex and Ukrainian FRAX model

Grygorieva

Koshel²,

Pisaruk³

et al. 2022

PJS

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“…The ageing of the musculoskeletal system is characterized by the development of degenerative-dystrophic and metabolic changes, leading to the development of osteoporosis and sarcopenia, which are characterized by generalized loss of bone and muscle tissue. These conditions not only increase the risk of low-energy fractures and falls but also lead to a decrease in the functional activity of the patients, and their disability, and an increase in mortality rates [1,2,3,4,5,6,7].…”

mentioning

confidence: 99%

“…Currently, assessment of bone mineral density (BMD) and quality of bone tissue, measured using dual-energy X-ray absorptiometry (DXA), can provide a reliable estimate of bone strength and the risk of osteoporotic fractures. It has been demonstrated that BMD determines approximately 70-75% of bone strength, and according to recommendations from leading global organizations (ISCD, IOF), it is used to diagnose osteoporosis [1,2].…”

mentioning

confidence: 99%

Method for assessment of the biological age of the musculoskeletal system

Pisaruk

Grygorieva

Koshel

et al. 2023

A&L

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It is well known that degenerative-dystrophic and metabolic changes in the musculoskeletal system progress with age and lead to the development of pathologies, including osteoporosis, sarcopenia etc. With the development of new methods for studying bone and muscle systems, it is important to predict the biological age of the musculoskeletal system to assess the rate of ageing and the possibilities for preventing these diseases and their consequences. The study aimed to develop a mathematical model for the assessment of the biological age of the musculoskeletal system, taking into account indicators of bone mineral density (BMD), trabecular bone score (TBS), parameters of body composition, and some functional tests. 77 women and 44 men aged 30 to 90 years without significant somatic pathology were examined. Measurements of BMD and TBS, as well as indicators of body composition, were performed using dual-energy X-ray absorptiometry (DXA). Statistical processing was performed using the Statistica 7.0 software (StatSoft Inc., USA). The results indicated a significant correlation between age and the BMD and TBS parameters, and body composition indicators. A model for determining the musculoskeletal system’s biological age was built using multiple regression analysis with stepwise inclusion of informative indicators. The model's coefficient of determination (R2) was 0.77, indicating its high significance. The mean absolute error of age calculation after correction for the regression equation error was 5.21 years. The developed model for assessing the musculoskeletal system’s biological age had high accuracy and can be used to assess the risk of osteoporosis, sarcopenia, and complications. ________________________________________________________________________________________Keywords: biological age; musculoskeletal system; osteoporosis; sarcopenia

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Molecular insights into the distinct signaling duration for the peptide-induced PTH1R activation

et al. 2022

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The parathyroid hormone type 1 receptor (PTH1R), a class B1 G protein-coupled receptor, plays critical roles in bone turnover and Ca2+ homeostasis. Teriparatide (PTH) and Abaloparatide (ABL) are terms as long-acting and short-acting peptide, respectively, regarding their marked duration distinctions of the downstream signaling. However, the mechanistic details remain obscure. Here, we report the cryo-electron microscopy structures of PTH– and ABL–bound PTH1R-Gs complexes, adapting similar overall conformations yet with notable differences in the receptor ECD regions and the peptide C-terminal portions. 3D variability analysis and site-directed mutagenesis studies uncovered that PTH–bound PTH1R–Gs complexes display less motions and are more tolerant of mutations in affecting the receptor signaling than ABL–bound complexes. Furthermore, we combined the structural analysis and signaling assays to delineate the molecular basis of the differential signaling durations induced by these peptides. Our study deepens the mechanistic understanding of ligand-mediated prolonged or transient signaling.

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Osteoporose-Update 2021

Cited by 4 publications

References 14 publications

Mathematical model of the bone biological age based on the bone mineral density and quality indicex and Ukrainian FRAX model

Mathematical model of the bone biological age based on the bone mineral density and quality indicex and Ukrainian FRAX model

Method for assessment of the biological age of the musculoskeletal system

Molecular insights into the distinct signaling duration for the peptide-induced PTH1R activation

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