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Meng X, Pang X, Yang J, Zhang X, Dong H. Recent Advances in Electrochemiluminescence Biosensors for MicroRNA Detection. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024; 20:e2307701. [PMID: 38152970 DOI: 10.1002/smll.202307701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 12/06/2023] [Indexed: 12/29/2023]
Abstract
Electrochemiluminescence (ECL) as an analytical technology with a perfect combination of electrochemistry and spectroscopy has received considerable attention in bioanalysis due to its high sensitivity and broad dynamic range. Given the selectivity of bio-recognition elements and the high sensitivity of the ECL analysis technique, ECL biosensors are powerful platforms for the sensitive detection of biomarkers, achieving the accurate prognosis and diagnosis of diseases. MicroRNAs (miRNAs) are crucial biomarkers involved in a variety of physiological and pathological processes, whose aberrant expression is often related to serious diseases, especially cancers. ECL biosensors can fulfill the highly sensitive and selective requirements for accurate miRNA detection, prompting this review. The ECL mechanisms are initially introduced and subsequently categorize the ECL biosensors for miRNA detection in terms of the quenching agents. Furthermore, the work highlights the signal amplification strategies for enhancing ECL signal to improve the sensitivity of miRNA detection and finally concludes by looking at the challenges and opportunities in ECL biosensors for miRNA detection.
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Affiliation(s)
- Xiangdan Meng
- Beijing Key Laboratory for Bioengineering and Sensing Technology Research Centre for Bioengineering and Sensing Technology School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing, 10083, P. R. China
| | - Xuejiao Pang
- Beijing Key Laboratory for Bioengineering and Sensing Technology Research Centre for Bioengineering and Sensing Technology School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing, 10083, P. R. China
| | - Junyan Yang
- School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing, 100083, P. R. China
| | - Xueji Zhang
- Beijing Key Laboratory for Bioengineering and Sensing Technology Research Centre for Bioengineering and Sensing Technology School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing, 10083, P. R. China
- Marshall Laboratory of Biomedical Engineering, Precision Medicine and Health Research Institute, Shenzhen Key Laboratory for Nano-Biosensing Technology, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Guangdong, 518060, P. R. China
| | - Haifeng Dong
- Beijing Key Laboratory for Bioengineering and Sensing Technology Research Centre for Bioengineering and Sensing Technology School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing, 10083, P. R. China
- Marshall Laboratory of Biomedical Engineering, Precision Medicine and Health Research Institute, Shenzhen Key Laboratory for Nano-Biosensing Technology, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Guangdong, 518060, P. R. China
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Post-operative kinetics of C-reactive protein to distinguish between bacterial infection and systemic inflammation in infants after cardiopulmonary bypass surgery: the early and the late period. Cardiol Young 2022; 32:904-911. [PMID: 34365991 DOI: 10.1017/s1047951121003231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
OBJECTIVES Differentiation between post-operative inflammation and bacterial infection remains an important issue in infants following congenital heart surgery. We primarily assessed kinetics and predictive value of C-reactive protein for bacterial infection in the early (days 0-4) and late (days 5-28) period after cardiopulmonary bypass surgery. Secondary objectives were frequency, type, and timing of post-operative infection related to the risk adjustment for congenital heart surgery score. METHODS This 3-year single-centre retrospective cohort study in a paediatric cardiac ICU analysed 191 infants accounting for 235 episodes of CPBP surgery. Primary outcome was kinetics of CRP in the first 28 days after CPBP surgery in infected and non-infected patients. RESULTS We observed 22 infectious episodes in the early and 34 in the late post-operative period. CRP kinetics in the early post-operative period did not accurately differentiate between infected and non-infected patients. In the late post-operative period, infected infants displayed significantly higher CRP values with a median of 7.91 (1.64-22.02) and 6.92 mg/dl (1.92-19.65) on days 2 and 3 compared to 4.02 (1.99-15.9) and 3.72 mg/dl (1.08-9.72) in the non-infection group. Combining CRP on days 2 and 3 after suspicion of infection revealed a cut-off of 9.47 mg/L with an acceptable predictive accuracy of 76%. CONCLUSIONS In neonates and infants, CRP kinetics is not useful to predict infection in the first 72 hours after CPBP surgery due to the inflammatory response. However, in the late post-operative period, CRP is a valuable adjunctive diagnostic test in conjunction with clinical presentation and microbiological diagnostics.
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Islim AI, Millward CP, Piper RJ, Fountain DM, Mehta S, Kolamunnage-Dona R, Ali U, Koszdin SD, Georgious T, Mills SJ, Brodbelt AR, Mathew RK, Santarius T, Jenkinson MD. External validation and recalibration of an incidental meningioma prognostic model - IMPACT: protocol for an international multicentre retrospective cohort study. BMJ Open 2022; 12:e052705. [PMID: 35042706 PMCID: PMC8768908 DOI: 10.1136/bmjopen-2021-052705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
INTRODUCTION Due to the increased use of CT and MRI, the prevalence of incidental findings on brain scans is increasing. Meningioma, the most common primary brain tumour, is a frequently encountered incidental finding, with an estimated prevalence of 3/1000. The management of incidental meningioma varies widely with active clinical-radiological monitoring being the most accepted method by clinicians. Duration of monitoring and time intervals for assessment, however, are not well defined. To this end, we have recently developed a statistical model of progression risk based on single-centre retrospective data. The model Incidental Meningioma: Prognostic Analysis Using Patient Comorbidity and MRI Tests (IMPACT) employs baseline clinical and imaging features to categorise the patient with an incidental meningioma into one of three risk groups: low, medium and high risk with a proposed active monitoring strategy based on the risk and temporal trajectory of progression, accounting for actuarial life expectancy. The primary aim of this study is to assess the external validity of this model. METHODS AND ANALYSIS IMPACT is a retrospective multicentre study which will aim to include 1500 patients with an incidental intracranial meningioma, powered to detect a 10% progression risk. Adult patients ≥16 years diagnosed with an incidental meningioma between 1 January 2009 and 31 December 2010 will be included. Clinical and radiological data will be collected longitudinally until the patient reaches one of the study endpoints: intervention (surgery, stereotactic radiosurgery or fractionated radiotherapy), mortality or last date of follow-up. Data will be uploaded to an online Research Electronic Data Capture database with no unique identifiers. External validity of IMPACT will be tested using established statistical methods. ETHICS AND DISSEMINATION Local institutional approval at each participating centre will be required. Results of the study will be reported through peer-reviewed articles and conferences and disseminated to participating centres, patients and the public using social media.
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Affiliation(s)
- Abdurrahman I Islim
- Institute of Systems, Molecular & Integrative Biology, University of Liverpool, Liverpool, UK
- Department of Neurosurgery, The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Christopher P Millward
- Institute of Systems, Molecular & Integrative Biology, University of Liverpool, Liverpool, UK
- Department of Neurosurgery, The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Rory J Piper
- Department of Neurosurgery, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Daniel M Fountain
- Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Salford, UK
| | - Shaveta Mehta
- Institute of Systems, Molecular & Integrative Biology, University of Liverpool, Liverpool, UK
- Department of Clinical Oncology, The Clatterbridge Cancer Centre NHS Foundation Trust, Wirral, UK
| | - Ruwanthi Kolamunnage-Dona
- Department of Health Data Science, Institute of Population Health, University of Liverpool, Liverpool, UK
| | - Usama Ali
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | | | - Samantha J Mills
- Department of Neuroradiology, The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Andrew R Brodbelt
- Institute of Systems, Molecular & Integrative Biology, University of Liverpool, Liverpool, UK
- Department of Neurosurgery, The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Ryan K Mathew
- Leeds Institute of Medical Research at St James's, University of Leeds School of Medicine, Leeds, UK
- Department of Neurosurgery, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Thomas Santarius
- Department of Neurosurgery, Addenbrooke's Hospital, Cambridge, UK
- Division of Neurosurgery, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Michael D Jenkinson
- Institute of Systems, Molecular & Integrative Biology, University of Liverpool, Liverpool, UK
- Department of Neurosurgery, The Walton Centre NHS Foundation Trust, Liverpool, UK
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Kolamunnage-Dona R, Berhane S, Potts H, Williams EH, Tanner J, Janowitz T, Hoare M, Johnson P. Sorafenib is associated with a reduced rate of tumour growth and liver function deterioration in HCV-induced hepatocellular carcinoma. J Hepatol 2021; 75:879-887. [PMID: 34052255 PMCID: PMC9158473 DOI: 10.1016/j.jhep.2021.05.015] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 04/29/2021] [Accepted: 05/06/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND & AIMS Sorafenib has been the standard of care for patients with advanced hepatocellular carcinoma and although immunotherapeutic approaches are now challenging this position, it retains an advantage in HCV-seropositive patients. We aimed to quantify the rate of tumour progression in patients receiving sorafenib and relate this figure to survival, both overall, and according to viral status. METHODS Using serial data from an international clinical trial we applied a joint model to combine survival and progression over time in order to estimate the rate of tumour growth as assessed by tumour burden and serum alpha-fetoprotein, and the impact of treatment on liver function. RESULTS High tumour burden at baseline was associated with an increased risk of death. In patients still alive at the end of the study, the progression in relation to tumour burden was very low compared to those who died within the study. Overall, the change in mean tumour burden was 0.12 mm per day or an absolute growth rate of 3.6 mm/month. Median doubling time was 665 days. For those who progressed above 0.12 mm per day or the 12% rate, median survival was 234 days compared to 384 days if the rate was below 12%. Tumour growth rate and serum alpha-fetoprotein rise were significantly lower in those who were HCV seropositive as was the rate of decline in liver function. These results were replicated in 2 independent patient groups. CONCLUSION Our analysis suggests that sorafenib treatment is associated with improved survival in patients with advanced hepatocellular carcinoma mainly by decreasing the rate of tumour growth and liver function deterioration among patients with HCV infection. LAY SUMMARY Among patients receiving sorafenib for advanced hepatocellular carcinoma the rate of tumour growth (as assessed by changes in tumour size and the biomarker alpha-fetoprotein) and the deterioration of liver function is less in those who have the hepatitis C virus, than in those who do not.
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Affiliation(s)
| | - Sarah Berhane
- NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, UK; Institute of Applied Health Research, University of Birmingham, UK
| | - Harry Potts
- School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | | | - James Tanner
- Department of Radiology, University of Cambridge, Cambridge, UK
| | - Tobias Janowitz
- CRUK Cambridge Institute, University of Cambridge, Cambridge, UK; Cold Spring Harbor Laboratory, NY, USA; Northwell Health Cancer Institute, NY, USA
| | - Matthew Hoare
- CRUK Cambridge Institute, University of Cambridge, Cambridge, UK; Department of Medicine, University of Cambridge, Cambridge, UK
| | - Philip Johnson
- Department of Molecular and Clinical Cancer Medicine, University of Liverpool, UK.
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Campbell KR, Juarez-Colunga E, Grunwald GK, Cooper J, Davis S, Gralla J. Comparison of a time-varying covariate model and a joint model of time-to-event outcomes in the presence of measurement error and interval censoring: application to kidney transplantation. BMC Med Res Methodol 2019; 19:130. [PMID: 31242848 PMCID: PMC6595621 DOI: 10.1186/s12874-019-0773-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Accepted: 06/09/2019] [Indexed: 12/29/2022] Open
Abstract
Background Tacrolimus (TAC) is an immunosuppressant drug given to kidney transplant recipients post-transplant to prevent antibody formation and kidney rejection. The optimal therapeutic dose for TAC is poorly defined and therapy requires frequent monitoring of drug trough levels. Analyzing the association between TAC levels over time and the development of potentially harmful de novo donor specific antibodies (dnDSA) is complex because TAC levels are subject to measurement error and dnDSA is assessed at discrete times, so it is an interval censored time-to-event outcome. Methods Using data from the University of Colorado Transplant Center, we investigated the association between TAC and dnDSA using a shared random effects (intercept and slope) model with longitudinal and interval censored survival sub-models (JM) and compared it with the more traditional interval censored survival model with a time-varying covariate (TVC). We carried out simulations to compare bias, level and power for the association parameter in the TVC and JM under varying conditions of measurement error and interval censoring. In addition, using Markov Chain Monte Carlo (MCMC) methods allowed us to calculate clinically relevant quantities along with credible intervals (CrI). Results The shared random effects model was a better fit and showed both the average TAC and the slope of TAC were associated with risk of dnDSA. The simulation studies demonstrated that, in the presence of heavy interval censoring and high measurement error, the TVC survival model underestimates the association between the survival and longitudinal measurement and has inflated type I error and considerably less power to detect associations. Conclusions To avoid underestimating associations, shared random effects models should be used in analyses of data with interval censoring and measurement error. Electronic supplementary material The online version of this article (10.1186/s12874-019-0773-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Kristen R Campbell
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, 80045, Colorado, USA
| | - Elizabeth Juarez-Colunga
- Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, 80045, Colorado, USA. .,Adult and Child Consortium for Health Outcomes and Delivery Science, University of Colorado Anschutz Medical Campus, Aurora, 80045, Colorado, USA.
| | - Gary K Grunwald
- Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, 80045, Colorado, USA
| | - James Cooper
- Division of Renal Diseases and Hypertension, University of Colorado Anschutz Medical Campus, Aurora, 80045, Colorado, USA
| | - Scott Davis
- Division of Renal Diseases and Hypertension, University of Colorado Anschutz Medical Campus, Aurora, 80045, Colorado, USA
| | - Jane Gralla
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, 80045, Colorado, USA.,Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, 80045, Colorado, USA
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