Background & Aims
Radiocontrast agents are required for radiographic procedures, but these agents can injure tissues by unknown mechanisms. We investigated whether exposure of pancreatic tissues to radiocontrast agents during endoscopic retrograde cholangiopancreatography (ERCP) causes pancreatic inflammation, and studied the effects of these agents on human cell lines and in mice.
Methods
We exposed mouse and human acinar cells to the radiocontrast agent iohexol (Omnipaque) and measured intracellular release of Ca2+, calcineurin activation (using a luciferase reporter), activation of nuclear factor-κB (NF-κB, using a luciferase reporter), and cell necrosis (via propidium iodide uptake). We infused the radiocontrast agent into the pancreatic ducts of wild type mice (C57BL/6) to create a mouse model of post-ERCP pancreatitis; some mice were given intraperitoneal injections of the calcineurin inhibitor FK506 before and after infusion of the radiocontrast agent. CnAβ−/− mice were also used. This experiment was also performed in mice given infusions of AAV6-NF-κB-luciferase, to assess activation of this transcription factor in vivo.
Results
Incubation of mouse and human acinar cells, but not HEK293 or COS7 cells, with iohexol led to a peak and then plateau in Ca2+ signaling, along with activation of the transcription factors NF-κB and NFAT. Suppressing Ca2+ signaling or calcineurin with BAPTA, cyclosporine A, or FK506 prevented activation of NF-κB and acinar cell injury. Calcineurin Aβ-deficient mice were protected against induction of pancreatic inflammation by iohexol. The calcineurin inhibitor FK506 prevented contrast-induced activation of NF-κB in pancreata of mice; this was observed by live imaging of mice given infusions of AAV6- NF-kB-luciferase.
Conclusions
Radiocontrast agents cause pancreatic inflammation in mice, via activation of NF-κB, Ca2+ signaling, and calcineurin. Calcineurin inhibitors might be developed to prevent post-ERCP pancreatitis in patients.
Background: NF-B is an important signaling molecule in the development of acute pancreatitis. Results: Adeno-associated virus-NF-B-luciferase-infused mice showed a 77-and 140-fold increase in pancreas-specific NF-B bioluminescence following caerulein and caerulein ϩ LPS pancreatitis, respectively. Conclusion: NF-B activation can be examined in a live, dynamic fashion during pancreatic inflammation. Significance: This technique offers a valuable tool to study real-time activation of NF-B in vivo.
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This study demonstrates how Machine Learning techniques and Big Data Analytics can be used in the insurance sector. Due to various web technologies, mobile devices, and sensor devices, the amount of data in the insurance sector is currently growing daily. Large amounts of data are known as big data as a result. Volume, Velocity, and volume are three characteristics of big data. Machine Learning plays a significant role in converting data into information. Because Machine Learning has the ability to learn from the input data and is a fundamental part of data analytics tools, it learns from data to provide new insights, predictions, and decisions from vast amounts of data. In the insurance sector, machine learning has a wide range of uses, such as customer segmentation, fraud detection, customer retention, claim processing, and claim review. As a result of this study, machine learning creates various prediction models for the insurance industry such as AdaBoost, Naïve Bay, K-Nearest Neighbor, and Decision Tree. As a result, Machine Learning is currently seen as a fundamental game changer for insurance businesses. The potential use of machine learning in insurance businesses will be further investigated by integrating big data tools.
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