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Kenawy HM, Marshall SL, Rogot J, Lee AJ, Hung CT, Chahine NO. Blocking toll-like receptor 4 mitigates static loading induced pro-inflammatory expression in intervertebral disc motion segments. J Biomech 2023; 150:111491. [PMID: 36870259 PMCID: PMC10108674 DOI: 10.1016/j.jbiomech.2023.111491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 01/23/2023] [Accepted: 02/08/2023] [Indexed: 02/13/2023]
Abstract
While the anabolic effects of mechanical loading on the intervertebral disc (IVD) have been extensively studied, inflammatory responses to loading have not been as well characterized. Recent studies have highlighted a significant role of innate immune activation, particularly that of toll-like receptors (TLRs), in IVD degeneration. Biological responses of intervertebral disc cells to loading depend on many factors that include magnitude and frequency. The goals of this study were to characterize the inflammatory signaling changes in response to static and dynamic loading of IVD and investigate the contributions of TLR4 signaling in response to mechanical loading. Rat bone-disc-bone motion segments were loaded for 3 hr under a static load (20 % strain, 0 Hz) with or without an additional low-dynamic (4 % dynamic strain, 0.5 Hz) or high-dynamic (8 % dynamic strain, 3 Hz) strain, and results were compared to unloaded controls. Some samples were also loaded with or without TAK-242, an inhibitor of TLR4 signaling. The magnitude of NO release into the loading media (LM) was correlated with the applied frequency and strain magnitudes across different loading groups. Injurious loading profiles, such as static and high-dynamic, significantly increased Tlr4 and Hmgb1 expression while this result was not observed in the more physiologically relevant low-dynamic loading group. TAK-242 co-treatment decreased pro-inflammatory expression in static but not dynamic loaded groups, suggesting that TLR4 plays a direct role in mediating inflammatory responses of IVD to static compression. Overall, the microenvironment induced by dynamic loading diminished the protective effects of the TAK-242, suggesting that TLR4 plays a direct role in mediating inflammatory responses of IVD to static loading injury.
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Affiliation(s)
- Hagar M Kenawy
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Samantha L Marshall
- Department of Orthopedic Surgery, Columbia University Irving Medical Center, New York, NY, USA
| | - James Rogot
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Andy J Lee
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Clark T Hung
- Department of Biomedical Engineering, Columbia University, New York, NY, USA; Department of Orthopedic Surgery, Columbia University Irving Medical Center, New York, NY, USA
| | - Nadeen O Chahine
- Department of Biomedical Engineering, Columbia University, New York, NY, USA; Department of Orthopedic Surgery, Columbia University Irving Medical Center, New York, NY, USA.
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Blumenfeld NR, Bolene MAE, Jaspan M, Ayers AG, Zarrandikoetxea S, Freudman J, Shah N, Tolwani AM, Hu Y, Chern TL, Rogot J, Behnam V, Sekhar A, Liu X, Onalir B, Kasumi R, Sanogo A, Human K, Murakami K, Totapally GS, Fasciano M, Sia SK. Multiplexed reverse-transcriptase quantitative polymerase chain reaction using plasmonic nanoparticles for point-of-care COVID-19 diagnosis. Nat Nanotechnol 2022; 17:984-992. [PMID: 35879456 DOI: 10.1038/s41565-022-01175-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 06/09/2022] [Indexed: 06/15/2023]
Abstract
Quantitative polymerase chain reaction (qPCR) offers the capabilities of real-time monitoring of amplified products, fast detection, and quantitation of infectious units, but poses technical hurdles for point-of-care miniaturization compared with end-point polymerase chain reaction. Here we demonstrate plasmonic thermocycling, in which rapid heating of the solution is achieved via infrared excitation of nanoparticles, successfully performing reverse-transcriptase qPCR (RT-qPCR) in a reaction vessel containing polymerase chain reaction chemistry, fluorescent probes and plasmonic nanoparticles. The method could rapidly detect SARS-CoV-2 RNA from human saliva and nasal specimens with 100% sensitivity and 100% specificity, as well as two distinct SARS-CoV-2 variants. The use of small optical components for both thermocycling and multiplexed fluorescence monitoring renders the instrument amenable to point-of-care use. Overall, this study demonstrates that plasmonic nanoparticles with compact optics can be used to achieve real-time and multiplexed RT-qPCR on clinical specimens, towards the goal of rapid and accurate molecular clinical diagnostics in decentralized settings.
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Affiliation(s)
- Nicole R Blumenfeld
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
- Rover Diagnostics, New York, NY, USA
| | - Michael Anne E Bolene
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
- Rover Diagnostics, New York, NY, USA
| | | | - Abigail G Ayers
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Sabin Zarrandikoetxea
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
- Rover Diagnostics, New York, NY, USA
| | | | - Nikhil Shah
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
- Rover Diagnostics, New York, NY, USA
| | - Angela M Tolwani
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
- Rover Diagnostics, New York, NY, USA
| | - Yuhang Hu
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
- Rover Diagnostics, New York, NY, USA
| | - Terry L Chern
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | | | - Vira Behnam
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Aditya Sekhar
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Xinyi Liu
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
- Rover Diagnostics, New York, NY, USA
| | | | - Robert Kasumi
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Abdoulaye Sanogo
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Kelia Human
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Kasey Murakami
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Goutham S Totapally
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | | | - Samuel K Sia
- Department of Biomedical Engineering, Columbia University, New York, NY, USA.
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