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31.
Denise Lee Marcella D. Walker Hsin Yi Chen John A. Chabot James A. Lee Jennifer H. Kuo 《Surgery》2019,165(1):107-113
Background
Bone mineral density (BMD) has been found to improve after parathyroidectomy (PTX) in patients with primary hyperparathyroidism. There are few data on the effect of PTX on BMD in normocalcemic and normohormonal primary hyperparathyroidism.Methods
A retrospective analysis of 92 primary hyperparathyroidism patients who underwent PTX between 2004 and 2012 with pre- and post-PTX dual-energy x-ray absorptiometry was performed. Within-person changes in BMD pre- and post-PTX were analyzed using log linear mixed models, stratified by biochemical status.Results
Bone mineral density increased post-PTX in the whole cohort at the lumbar spine (+2.5%), femoral neck (+2.1%), and total hip (+1.9%) and decreased at the one-third radius (–0.9%). On comparison of BMD changes by profile, BMD increased in those with the typical profile at the lumbar spine (3.2%), femoral neck (2.9%), and total hip (2.9%) but declined at the one-third radius (–1.5%). In contrast, BMD improved only at the femoral neck (4.3%) in the normohormonal group and did not change at any site in the normocalcemic group. The typical group had a greater increase in BMD over time at the femoral neck and total hip compared with normocalcemic patients.Conclusion
Our results indicate that the skeletal benefit of PTX was attenuated in normocalcemic and normohormonal patients, suggesting that skeletal changes after PTX may depend on biochemical profile. 相似文献32.
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Jennifer Novak Yujie Cui Paul Frankel Mina S. Sedrak Scott Glaser Richard Li Sabin Motwani Brian Kavanagh Arya Amini 《Practical radiation oncology》2021,11(3):e263-e266
PurposeTwitter is an increasingly popular social media platform within the health care community. The objective of this analysis is to characterize the profile of radiation oncology–related tweets and Twitter users over the past 6 years.Methods and MaterialsUsing the web-based social media analytics platform Symplur Signals, we filtered tweets containing at least 1 of the following hashtags or key words: #radonc, #radiationoncology, "rad onc," or "radiation oncology." We evaluated radiation oncology–related Twitter activity between October 2014 and March 2020 for tweet frequency, tweet content, and individuals or groups posting tweets. We identified the most influential Twitter users contributing to radiation oncology–related tweets.ResultsFrom 2014 to 2020, the quarterly volume of radiation oncology–related tweets increased from 5027 to 29,763. Physicians contributed the largest growth in tweet volume. Academic radiation oncologists comprise 60% of the most influential Twitter accounts responsible for radiation oncology–related content. The number of radiation-oncology resident physicians on Twitter increased from 25 to 328 over the past 6 years, and 20% of radiation-oncology residency programs have a Twitter account. Seventy-one percent of radiation oncology–related tweets generated direct communication via mentions, and 59% of tweets contain links to external sources, including scientific articles.ConclusionsThe number of physicians contributing radiation oncology–related Twitter content has increased significantly in recent years. Academic radiation oncologists are the primary influencers of radiation oncology–related Twitter activity. Twitter is used by radiation oncologists to both professionally network and discuss findings related to the field. There remains the opportunity for radiation oncologists to broaden their audience on Twitter to encompass a more diverse community, including patients. 相似文献
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Jennifer C. Sasaki Ashley Allemang Steven M. Bryce Laura Custer Kerry L. Dearfield Yasmin Dietz Azeddine Elhajouji Patricia A. Escobar Albert J. Fornace Jr Roland Froetschl Sheila Galloway Ulrike Hemmann Giel Hendriks Heng-Hong Li Mirjam Luijten Gladys Ouedraogo Lauren Peel Stefan Pfuhler Daniel J. Roberts Véronique Thybaud Jan van Benthem Carole L. Yauk Maik Schuler 《Environmental and molecular mutagenesis》2020,61(1):114-134
In May 2017, the Health and Environmental Sciences Institute's Genetic Toxicology Technical Committee hosted a workshop to discuss whether mode of action (MOA) investigation is enhanced through the application of the adverse outcome pathway (AOP) framework. As AOPs are a relatively new approach in genetic toxicology, this report describes how AOPs could be harnessed to advance MOA analysis of genotoxicity pathways using five example case studies. Each of these genetic toxicology AOPs proposed for further development includes the relevant molecular initiating events, key events, and adverse outcomes (AOs), identification and/or further development of the appropriate assays to link an agent to these events, and discussion regarding the biological plausibility of the proposed AOP. A key difference between these proposed genetic toxicology AOPs versus traditional AOPs is that the AO is a genetic toxicology endpoint of potential significance in risk characterization, in contrast to an adverse state of an organism or a population. The first two detailed case studies describe provisional AOPs for aurora kinase inhibition and tubulin binding, leading to the common AO of aneuploidy. The remaining three case studies highlight provisional AOPs that lead to chromosome breakage or mutation via indirect DNA interaction (inhibition of topoisomerase II, production of cellular reactive oxygen species, and inhibition of DNA synthesis). These case studies serve as starting points for genotoxicity AOPs that could ultimately be published and utilized by the broader toxicology community and illustrate the practical considerations and evidence required to formalize such AOPs so that they may be applied to genetic toxicity evaluation schemes. Environ. Mol. Mutagen. 61:114–134, 2020. © 2019 Wiley Periodicals, Inc. 相似文献
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Konrad Matyja Anna Małachowska-Jutsz Anna K. Mazur Kazimierz Grabas 《Ecotoxicology (London, England)》2016,25(5):924-939
Dehydrogenase activity is frequently used to assess the general condition of microorganisms in soil and activated sludge. Many studies have investigated the inhibition of dehydrogenase activity by various compounds, including heavy metal ions. However, the time after which the measurements are carried out is often chosen arbitrarily. Thus, it can be difficult to estimate how the toxic effects of compounds vary during the reaction and when the maximum of the effect would be reached. Hence, the aim of this study was to create simple and useful mathematical model describing changes in dehydrogenase activity during exposure to substances that inactivate enzymes. Our model is based on the Lagergrens pseudo-first-order equation, the rate of chemical reactions, enzyme activity, and inactivation and was created to describe short-term changes in dehydrogenase activity. The main assumption of our model is that toxic substances cause irreversible inactivation of enzyme units. The model is able to predict the maximum direct toxic effect (MDTE) and the time to reach this maximum (TMDTE). In order to validate our model, we present two examples: inactivation of dehydrogenase in microorganisms in soil and activated sludge. The model was applied successfully for cadmium and copper ions. Our results indicate that the predicted MDTE and TMDTE are more appropriate than EC50 and IC50 for toxicity assessments, except for long exposure times. 相似文献
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