We used the osteogenic sarcoma cell line, UMR-106-01, to determine whether the rise in free cytosolic Ca2+ concentration ([Ca2+]i) and cellular cAMP following PTH stimulation are able to be regulated independently. For this purpose, we compared the effect of a PTH antagonist, stimulation of protein kinase C, augmentation by prostaglandins, and the time course of desensitization of the two cellular responses. Two x 10(-7) M of the PTH antagonist 8,18Nle 34Tyr-bPTH(3-34) amide ([Nle,Tyr]bPTH(3-34)A) was required to inhibit 10(-9) M bPTH(1-34)-stimulated cAMP generation by 50%. 10(-7) M bPTH(1-34) completely overcame the inhibition induced by 10(-6) M [Nle,Tyr]bPTH(3-34)A. Only 7 x 10(-8) M and 2.7 x 10(-7) M [Nle,Tyr]bPTH(3-34)A were required to half maximally inhibit the [Ca2+]i increase evoked by 3 x 10(-8) and 10(-7) M bPTH(1-34), respectively. In addition, dissociation between [Ca2+]i and cAMP signals was observed when modulation by protein kinase C and prostaglandins was tested. Preincubation of the cells with 10 nM TPA for 5 minutes markedly inhibited the PTH-evoked [Ca2+]i increase. Short incubation with PGF2 alpha augmented the PTH-evoked [Ca2+]i increase. Similar pretreatments had no effect on the PTH-stimulated cAMP increase. Finally, preincubation with 1.5 x 10(-9) M bPTH(1-34) for 20 minutes almost completely blocked the effect of 10(-7) M bPTH(1-34) on [Ca2+]i, while preincubation with 5 x 10(-9) M bPTH(1-34) for 4 hours was required to inhibit the effect of 10(-8) M bPTH(1-34) on cAMP production by 50%. The differences in the regulation of the two PTH-stimulated cellular signaling systems, in particular, the response to antagonists and the time course of desensitization, could be at the level of the PTH receptor(s) or at a postreceptor domain.
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http://dx.doi.org/10.1002/jcp.1041520311 | DOI Listing |
J Gen Intern Med
January 2025
Center for Health Optimization and Implementation Research, VA Boston Healthcare System and VA Bedford Healthcare System, Boston and Bedford, MA, USA.
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Anal Chim Acta
March 2025
Artificial Intelligence Research Center, Chang Gung University, Taoyuan, 333323, Taiwan; Department of Artificial Intelligence, College of Intelligent Computing, Chang Gung University, Taoyuan, 333323, Taiwan. Electronic address:
Background: In recent years, employing deep learning methods in the biosensing area has significantly reduced data analysis time and enhanced data interpretation and prediction accuracy. In some SPR fields, research teams have further enhanced detection capabilities using deep learning techniques. However, the application of deep learning to spectroscopic surface plasmon resonance (SPR) biosensors has not been reported.
View Article and Find Full Text PDFEnviron Pollut
January 2025
School of Environment, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China; State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, P. O. Box 2871, Beijing 100085, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China.
Silver-containing nanoparticles (AgCNPs) have attracted increasing concerns because of their potential adverse effects on aquatic ecosystems. However, minimal information is available regarding their concentration, distribution, and speciation in the actual environment. In this work, different species of AgCNPs, including silver nanoparticles (AgNPs), silver chloride (AgCl NPs) and silver sulfide (AgS NPs) in water and sediment samples from Taihu Lake were analyzed by a multistep selective dissolution method combined with single-particle inductively coupled plasma mass spectrometry.
View Article and Find Full Text PDFCad Saude Publica
January 2025
Instituto de Saúde Coletiva, Universidade Federal da Bahia, Salvador, Brasil.
This study aimed to describe the profile and calculate the years of potential life lost (YPLL) due to liver diseases in Brazilian agricultural workers from 2017 to 2022. For this, we analyzed microdata available in the Brazilian Mortality Information System considering the underlying cause of death with codes K70-K77 (International Classsification of Disease, 10th revision - ICD-10) as the outcome of interest. Workers' profile was characterized according to sociodemographic variables and Brazilian regions, forming a comparison group with all other Brazilian workers aged from 18-69 years who died in the same period and from the same underlying cause.
View Article and Find Full Text PDFIntegr Environ Assess Manag
January 2025
Department of Environmental Health Engineering, Faculty of Health, Shiraz University of Medical Sciences, Shiraz, Iran.
This study aimed to evaluate the concentrations of sulfur dioxide (SO2) and nitrogen oxides (NOX) around the Qom (a province in Iran) combined cycle power plant in relation to seasonal variations and fuel type from December 2014 to May 2015. Passive sampling was used in three monitoring sites around the power plant to assess noncarcinogenic health risks associated with exposure to SO2 and NOX. Results showed the higher concentrations of NOX and SO2 in winter than in spring.
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