Np abstract available.
Cardiovascular Diseases*

Bone remodeling requires a large amount of energy, and is regulated by various hormones. Leptin, produced by adipocytes, is a well-known regulator of energy balance and is also involved in controlling bone mass through interaction with the central nervous system. Serotonin, downstream of leptin, is also emerging as a candidate for controlling energy balance and bone metabolism. Currently, bone is also considered to be an endocrine regulator of energy metabolism. Osteocalcin, secreted from osteoblasts, is known to be a key regulator of glucose and fat metabolism. In this review, we describe a novel concept that asserts that there exists a biological link between bone and energy metabolism, and we summarize what is currently known about the relationship between bone and energy metabolism.
Adipocytes ; Bone Remodeling ; Central Nervous System ; Energy Metabolism* ; Glucose ; Leptin ; Metabolism ; Neurotransmitter Agents ; Osteoblasts ; Osteocalcin ; Serotonin

No abstract available.
Osteoporosis

No abstract available.
Animals ; Bone Density ; Cathepsin K ; Cathepsins ; Models, Animal ; Osteoporosis

Background: Height loss is a simple clinical measure associated with increased fracture risk. However, limited data exists on the association between height loss and fracture risk in postmenopausal Korean women. It is unknown whether this association varies with age. Methods: Data on height loss over a 6-year period were collected from a community-based longitudinal follow-up cohort (Ansung cohort of the Korean Genome and Epidemiology Study). Incident fractures were defined based on self-reported fractures after excluding those due to severe trauma or toes/fingers. The association between incident fractures and height loss was investigated using a Cox proportional hazards model. Results: During a median follow-up of 10 years after the second visit, 259/1,806 participants (median age, 64 years) experienced incident fractures. Overall, a 1 standard deviation (SD) decrease in height (1.6 cm/median 5.8 years) was associated with 9% increased risk of fracture (hazard ratio [HR], 1.09; P=0.037), which lost statistical significance after adjustment for covariates. When stratified into age groups (50–59, 60–69, 70 years or older), a 1 SD decrease in height remained a robust predictor of fracture in the 50 to 59 years age group after adjusting for covariates (adjusted hazard ratio [aHR], 1.52; P=0.003), whereas height loss was not an independent predictor of fracture in the 60 to 69 (aHR, 1.06; P=0.333) or the 70 years or older age groups (aHR, 1.05; P=0.700; P for interaction <0.05, for all). Conclusion Height loss during the previous 6 years was associated with an increased 10-year fracture risk in postmenopausal women in their 50s.

Hyperparathyroidism is a frequent complication of chronic kidney disease (CKD) as a result of prolonged hyperphosphatemia and hypocalcemia. Brown tumor is a rare bony complication of hyperparathyroidism as a result of increased osteoclastic activity and fibroblastic proliferation. Frequent sites of brown tumor are known as ribs, clavicles, mandible, and pelvic bone, but maxilla is very rare site. Twenty seven-year-old woman with stage V CKD on hemodialysis presented with maxillary mass which had gradually increased in size for 3 years. It was painless, but tooth derangement occurred. Initial laboratory findings revealed hypercalcemia (11.0 mg/dL), hyperphosphatemia (6.9 mg/dL), high creatinine (7.5 mg/dL), and high serum PTH (1729.9 pg/mL). The bone mineral density was significantly low (lumbar spine Z-score:
Bone Density ; Calcium ; Clavicle ; Creatinine ; Female ; Femur Neck ; Fibroblasts ; Follow-Up Studies ; Forearm ; Humans ; Hypercalcemia ; Hyperparathyroidism ; Hyperparathyroidism, Secondary ; Hyperphosphatemia ; Hypocalcemia ; Kidney Failure, Chronic ; Kidney Transplantation ; Mandible ; Maxilla ; Osteoclasts ; Parathyroid Glands ; Parathyroidectomy ; Pelvic Bones ; Reference Values ; Renal Dialysis ; Renal Insufficiency, Chronic ; Ribs ; Spine ; Tooth ; Transplants

Bisphosphonates are the most widely used medications for treating high bone turnover osteoporosis, Paget's disease of bone, multiple myeloma and metastatic carcinomas, etc. However, a destructive complication of bisphosphonate-related osteonecrosis of the jaw (BRONJ) can occur. The treatments of BRONJ are challenging and the currently recommended managements for BRONJ are still controversial. Our case demonstrated that teriparatide can be a treatment of choice for intractable BRONJ, which had not been cured for 2 years even with the proper surgical treatment and withdrawal of bisphosphonates.
Bisphosphonate-Associated Osteonecrosis of the Jaw ; Diphosphonates ; Multiple Myeloma ; Osteitis Deformans ; Osteoporosis ; Teriparatide

Large, randomized, controlled trials have demonstrated the efficacy of bisphosphonates (BP) in terms of improving bone mineral density (BMD) and reducing fracture risk. Consequently, bisphosphonates are used widely in the treatment of osteoporosis. Recently, however, several safety issues regarding the long-term use of BP, especially BP-related osteonecrosis of the jaws and atypical fractures, have been noted and have emerged as a limitation of their clinical use. Although the absolute risk is very small, the risks could increase with the long-term use of BP. The anti-fracture efficacy of BP is not sustained after treatment for 5-10 years. Therefore, recommendations suggest that a drug holiday be considered after 5 years of treatment for patients at low risk of fracture. However, as the individual fracture risk varies, the treatment duration should be based on individual clinical risk factors and bone metabolism status. Moreover, recommendations regarding monitoring after discontinuing and reinitiating BP await further studies.
Bone Density ; Diphosphonates ; Holidays ; Humans ; Jaw ; Metabolism ; Osteonecrosis ; Osteoporosis ; Risk Factors

Machine learning (ML) applications have received extensive attention in endocrinology research during the last decade. This review summarizes the basic concepts of ML and certain research topics in endocrinology and metabolism where ML principles have been actively deployed. Relevant studies are discussed to provide an overview of the methodology, main findings, and limitations of ML, with the goal of stimulating insights into future research directions. Clear, testable study hypotheses stem from unmet clinical needs, and the management of data quality (beyond a focus on quantity alone), open collaboration between clinical experts and ML engineers, the development of interpretable high-performance ML models beyond the black-box nature of some algorithms, and a creative environment are the core prerequisites for the foreseeable changes expected to be brought about by ML and artificial intelligence in the field of endocrinology and metabolism, with actual improvements in clinical practice beyond hype. Of note, endocrinologists will continue to play a central role in these developments as domain experts who can properly generate, refine, analyze, and interpret data with a combination of clinical expertise and scientific rigor.

Recently, machine learning (ML) applications have received attention in diabetes and metabolism research. This review briefly provides the basic concepts of ML and specific topics in diabetes research.Exemplary studies are reviewed to provide an overview of the methodology, main findings, limitations, and future research directions for ML-based studies. Well-defined, testable study hypotheses that stem from unmet clinical needs are always the first prerequisite for successful deployment of an MLbased approach to clinical scene. The management of data quality with enough quantity and active collaboration with ML engineers can enhance the ML development process. The interpretable highperformance ML models beyond the black-box nature of some ML principles can be one of the future goals expected by ML and artificial intelligence in the diabetes research and clinical practice settings that is beyond hype. Most importantly, endocrinologists should play a central role as domain experts who have clinical expertise and scientific rigor, for properly generating, refining, analyzing, and interpreting data by successfully integrating ML models into clinical research.