Synthetic calcium pyrophosphate dihydrate crystals and, to a lesser extent, synthetic hydroxyapatite crystals increased the amount of interleukin-1/mononuclear cell factor released by human blood monocytes, as measured by collagenase and prostaglandin E2 production by rabbit chondrocytes, human dermal fibroblasts, and adherent rheumatoid synovial cells. The same crystals also directly induced collagenase and prostaglandin E2 secretion by rabbit chondrocytes, and potentiated the action of interleukin-1/mononuclear cell factor on chondrocytes. These mechanisms may be important in the pathogenesis of the destructive arthropathies associated with these crystals.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1002/art.1780301208 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Investigation of Calcium Phosphate-Based Biopolymer Composite Scaffolds for Bone Tissue Engineering.
Int J Mol Sci
December 2024
Institute of Technical Physics and Materials Science, HUN-REN Centre for Energy Research, Konkoly-Thege str. 29-33, H-1121 Budapest, Hungary.
We present a novel method for preparing bioactive and biomineralized calcium phosphate (mCP)-loaded biopolymer composite scaffolds with a porous structure. Two types of polymers were investigated as matrices: one natural, cellulose acetate (CA), and one synthetic, polycaprolactone (PCL). Biomineralized calcium phosphate particles were synthesized via wet chemical precipitation, followed by the addition of organic biominerals, such as magnesium gluconate and zinc gluconate, to enhance the bioactivity of the pure CP phase.
View Article and Find Full Text PDFNeuronal connection dysfunction is a convergent cause of cognitive deficits in mental disorders. Cognitive processes are finely regulated at the synaptic level by membrane proteins, some of which are shed and detectable in patients' cerebrospinal fluid (CSF). However, whether these soluble synaptic proteins can harnessed as innovative pro-cognitive factors to treat brain disorders remains unclear.
View Article and Find Full Text PDFAn Overview on Bioactive Glasses for Bone Regeneration and Repair: Preparation, Reinforcement, and Applications.
Tissue Eng Part B Rev
January 2025
Materials Science and Engineering, School of Materials and Chemistry, University of Shanghai for Science & Technology, Shanghai, China.
Synthetic bone transplantation has emerged in recent years as a highly promising strategy to address the major clinical challenge of bone tissue defects. In this field, bioactive glasses (BGs) have been widely recognized as a viable alternative to traditional bone substitutes due to their unique advantages, including favorable biocompatibility, pronounced bioactivity, excellent biodegradability, and superior osseointegration properties. This article begins with a comprehensive overview of the development and success of BGs in bone tissue engineering, and then focuses on their composite reinforcement systems with biodegradable metals, calcium-phosphorus (Ca-P)-based bioceramics, and biodegradable medical polymers, respectively.
View Article and Find Full Text PDFSelective extraction of lithium over alkali and alkaline earth ions by synergistic solvent extraction.
Green Chem
December 2024
KU Leuven, Department of Chemistry Celestijnenlaan 200F P.O. box 2404 B-3001 Leuven Belgium
Direct lithium extraction (DLE) from natural surface and geothermal brines is very challenging due to the low ratio of lithium to other metals, and the lack of suitable materials that bind lithium with sufficiently high selectivity. In this paper, a synergistic solvent extraction system is described that comprises a liquid ion exchanger (saponified bis(2-ethylhexyl)dithiophosphoric acid) and a lithium-selective ligand (2,9-dibutyl-1,10-phenanthroline) in an aliphatic diluent. The extraction mechanism was investigated and was confirmed to involve the binding of lithium to the selective ligand, while the liquid ion exchanger facilitates the transfer of metal ions from the aqueous to the organic phase.
View Article and Find Full Text PDFPredicting the likelihood of readmission in patients with ischemic stroke: An explainable machine learning approach using common data model data.
Int J Med Inform
December 2024
Department of Health Policy and Management, School of Medicine, Kangwon National University, 510 School of Medicine Building #1 (N414), 1, Kangwondaehak-gil, Chuncheon-si, Gangwon-do 24341, Republic of Korea; Department of Preventive Medicine, Kangwon National University Hospital, 156 Baengnyeong-ro, Chuncheon-si, Gangwon-do 24289, Republic of Korea; Team of Public Medical Policy Development, Gangwon State Research Institute for People's Health, 880 Baksa-ro, Seo-myeon, Chuncheon-si, Gangwon-do 24461, Republic of Korea. Electronic address:
Background: Ischemic stroke affects 15 million people worldwide, causing five million deaths annually. Despite declining mortality rates, stroke incidence and readmission risks remain high, highlighting the need for preventing readmission to improve the quality of life of survivors. This study developed a machine-learning model to predict 90-day stroke readmission using electronic medical records converted to the common data model (CDM) from the Regional Accountable Care Hospital in Gangwon state in South Korea.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!