Introduction: Flow cytometry markers have been proposed as useful predictors for the occurrence of posttraumatic inflammatory complications. However, currently the need for a dedicated laboratory and the labour-intensive analytical procedures make these markers less suitable for clinical practice. We tested an approach to overcome these limitations.
Material And Methods: Neutrophils of healthy donors were incubated with antibodies commonly used in trauma research: CD11b (MAC-1), L-selectin (CD62L), FcγRIII (CD16), and FcγRII (CD32) in active form (MoPhab A27). Flow cytometric analysis was performed both on a FACSCalibur, a standard flow cytometer, and on a Cell-Dyn Sapphire, a routine haematology analyser.
Results: There was a high level of agreement between the two types of analysers, with 41% for FcγRIII, 80% for L-selectin, 98% for CD11b, and even a 100% agreement for active FcγRII. Moreover, analysis on the routine haematology analyser was possible in less than a quarter of the time in comparison to the flow cytometer.
Conclusion: Analysis of neutrophil phenotype on the Cell-Dyn Sapphire leads to the same conclusion compared to a standard flow cytometer. The markedly reduced time necessary for analysis and reduced labour intensity constitutes a step forward in implementation of this type of analysis in clinical diagnostics in trauma research.
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http://dx.doi.org/10.1155/2012/509513 | DOI Listing |
Trop Med Health
January 2025
LaoLuxLab/Vaccine Preventable Diseases Laboratory, Institut Pasteur du Laos, Vientiane, Laos.
Background: Individuals with latent tuberculosis infection (LTBI) have a high risk of active infection, morbidity and mortality. Healthcare workers are a group who have increased risk of infection and onward transmission to their patients and other susceptible individuals; however, LTBI is often undiagnosed, and individuals are asymptomatic. Interferon gamma release assays (IGRA) can detect evidence of TB infection in otherwise asymptomatic individuals and are a good indication of LTBI.
View Article and Find Full Text PDFSurg Today
January 2025
Division of Surgery, Istituto Auxologico Italiano IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico), Milan, Italy.
Purposes: We analyzed the acute-phase response in unilateral thyroidectomy by comparing the transoral endoscopic thyroidectomy vestibular approach (TOEVA) with the minimally invasive video-assisted thyroidectomy (MIVAT).
Methods: Patients were randomly assigned to undergo either TOEVA or MIVAT, after we obtained their written informed consent to participate in this study. Blood count, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), interleukin-1β (IL-1β), IL-6 and tumor necrosis factor (TNF-) were measured before surgery and then 4, 24, and 48 h after surgery.
J Neurointerv Surg
January 2025
Institute of Neurointervention, Paracelsus Medical University, Salzburg, Austria.
Background And Purpose: This study evaluates the early clinical performance of the new Artisse Intrasaccular Device (Artisse ISD), a self-expandable intrasaccular flow diverter, for treating wide-necked aneurysms (WNAs). We report initial safety and efficacy outcomes in the first cohort of patients treated with this novel device.
Methods: Prospective clinical and radiological data were collected for all patients treated with the Artisse ISD at three Austrian neurovascular centers from July 2023 to August 2024.
Clin Chem Lab Med
January 2025
Canadian Microbiology Proficiency Testing Program (CMPT), Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, Canada.
Providers of external quality assessment (EQA) programs evaluate data or information obtained and reported by participant laboratories using their routine procedures to examine properties or measurands in samples provided for this purpose. EQA samples must offer participants an equal chance to obtain accurate results, while being designed to provide results in clinically relevant ranges. It is the responsibility of the EQA provider to meet the necessary requirements for homogeneity, stability and some other properties of the EQA items in order to offer participants a fair, reliable and technically interesting EQA experience.
View Article and Find Full Text PDFLung Cancer
December 2024
Università Vita-Salute San Raffaele, Milan, Italy; Department of Medical Oncology, IRCCS Ospedale San Raffaele, Milan, Italy.
Background: Artificial intelligence (AI) models are emerging as promising tools to identify predictive features among data coming from health records. Their application in clinical routine is still challenging, due to technical limits and to explainability issues in this specific setting. Response to standard first-line immunotherapy (ICI) in metastatic Non-Small-Cell Lung Cancer (NSCLC) is an interesting population for machine learning (ML), since up to 30% of patients do not benefit.
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