Results 71 to 80 of about 11,147,694 (408)
Fracture, aging, and disease in bone [PDF]
Journal of Materials Research, 2006 From a public health perspective, developing a detailed mechanistic understanding of the well-known increase with age in fracture risk of human bone is essential. This also represents a challenge from materials science and fracture mechanics viewpoints.
Ager, Joel, Balooch, G., Ritchie, R. O.
openaire +4 more sources
Role of galectin-3 in bone cell differentiation, bone pathophysiology and vascular osteogenesis [PDF]
, 2017 Galectin-3 is expressed in various tissues, including the bone, where it is considered a marker of chondrogenic and osteogenic cell lineages. Galectin-3 protein was found to be increased in the differentiated chondrocytes of the metaphyseal plate ...
Fantauzzi, Claudia Blasetti +3 more
core +2 more sources
FEBS Letters, EarlyView.B cells sense external mechanical forces and convert them into biochemical signals through mechanotransduction. Understanding how malignant B cells respond to physical stimuli represents a groundbreaking area of research. This review examines the key mechano‐related molecules and pathways in B lymphocytes, highlights the most relevant techniques to ...
Marta Sampietro +2 more
wiley +1 more source
Correlation Analysis Between Ultrasonic Epiphysis Cartilage Thickness and Bone Age
Xiehe Yixue ZazhiObjectivePreliminary exploration of using ultrasound to quantitatively evaluate the development of epiphyseal cartilage and analyze its correlation with bone age, based on the ultrasound findings of the long bone joint end.MethodsA study was conducted on
ZHAO Zeqing +9 more
doaj +1 more source
Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
Applied Sciences, 2022 Age prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age ...
Kamil Janczyk +4 more
doaj +1 more source
Pediatric Bone Age Assessment Using Deep Convolutional Neural Networks [PDF]
bioRxiv, 2017 Skeletal bone age assessment is a common clinical practice to diagnose endocrine and metabolic disorders in child development. In this paper, we describe a fully automated deep learning approach to the problem of bone age assessment using data from the ...
V. Iglovikov +3 more
semanticscholar +1 more source
Pediatric Bone Age Assessment Using Deep Convolutional Neural Networks
, 2018 Skeletal bone age assessment is a common clinical practice to diagnose endocrine and metabolic disorders in child development. In this paper, we describe a fully automated deep learning approach to the problem of bone age assessment using data from ...
A Rakhlin +7 more
core +1 more source
Effects of water-based exercise on bone health of middle-aged and older adults:A systematic review and meta-analysis [PDF]
, 2017 Background: Age-related bone loss is a major health concern. Only exercises associated with high-impact and mechanical loading have been linked to a positive effect on bone turnover; however, these types of exercises may not always be appropriate for ...
Climstein, Mike +3 more
core +1 more source
FEBS Letters, EarlyView.Exposure to common noxious agents (1), including allergens, pollutants, and micro‐nanoplastics, can cause epithelial barrier damage (2) in our body's protective linings. This may trigger an immune response to our microbiome (3). The epithelial barrier theory explains how this process can lead to chronic noncommunicable diseases (4) affecting organs ...
Can Zeyneloglu +17 more
wiley +1 more source
Frontiers in Endocrinology, 2023 IntroductionAutomated bone age assessment has recently become increasingly popular. The aim of this study was to assess the agreement between automated and manual evaluation of bone age using the method according to Tanner-Whitehouse (TW3) and Greulich ...
Klara Maratova +7 more
doaj +1 more source