Dataset Information

Quality assessment in light microscopy for routine use through simple tools and robust metrics.

ABSTRACT: Although there is a need to demonstrate reproducibility in light microscopy acquisitions, the lack of standardized guidelines monitoring microscope health status over time has so far impaired the widespread use of quality control (QC) measurements. As scientists from 10 imaging core facilities who encounter various types of projects, we provide affordable hardware and open source software tools, rigorous protocols, and define reference values to assess QC metrics for the most common fluorescence light microscopy modalities. Seven protocols specify metrics on the microscope resolution, field illumination flatness, chromatic aberrations, illumination power stability, stage drift, positioning repeatability, and spatial-temporal noise of camera sensors. We designed the MetroloJ_QC ImageJ/Fiji Java plugin to incorporate the metrics and automate analysis. Measurements allow us to propose an extensive characterization of the QC procedures that can be used by any seasoned microscope user, from research biologists with a specialized interest in fluorescence light microscopy through to core facility staff, to ensure reproducible and quantifiable microscopy results.

SUBMITTER: Faklaris O

PROVIDER: S-EPMC9526251 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Quality assessment in light microscopy for routine use through simple tools and robust metrics.

Faklaris Orestis O Bancel-Vallée Leslie L Dauphin Aurélien A Monterroso Baptiste B Frère Perrine P Geny David D Manoliu Tudor T de Rossi Sylvain S Cordelières Fabrice P FP Schapman Damien D Nitschke Roland R Cau Julien J Guilbert Thomas T

The Journal of cell biology 20220929 11

Although there is a need to demonstrate reproducibility in light microscopy acquisitions, the lack of standardized guidelines monitoring microscope health status over time has so far impaired the widespread use of quality control (QC) measurements. As scientists from 10 imaging core facilities who encounter various types of projects, we provide affordable hardware and open source software tools, rigorous protocols, and define reference values to assess QC metrics for the most common fluorescence ...[more]

PMID: 36173380

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Project description:BackgroundThe increasing global demand for health care, driven by demographic shifts, the rise of personalized medicine, and technological innovations necessitate novel approaches to health care delivery. Digital remote assessment tools have emerged as a promising solution, enabling hybrid care models that combine traditional and remote patient management. These tools support the quadruple aim of health care by enhancing the monitoring and evaluation of patient-reported data, thereby improving patient care, boosting operational efficiency, reducing costs, and improving the experience of patients and clinicians. This review seeks to understand how remote assessment tools are used for routine consultation substitution in adult tertiary care centers.ObjectiveThis scoping review aims to evaluate the implementation and health outcomes of digital remote assessment tools used for routine consultation substitutions in adult tertiary care centers. The objectives include assessing the extent of use, types, and effectiveness of these tools in substituting conventional outpatient care.MethodsA comprehensive scoping review was conducted, adhering to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. The review focused on studies that used internet-dependent remote assessment technologies for patient data transfer in tertiary care settings. A detailed search strategy was used across multiple databases, with studies selected based on predefined inclusion and exclusion criteria. Data extraction and analysis were performed by independent reviewers, with a focus on the functionalities of the tools and their alignment with the Quadruple Aim of Healthcare.ResultsThe review included 12 studies, highlighting a growing interest in remote assessment technologies across diverse clinical settings. The interventions varied in length, from 4 weeks to 12 months, and demonstrated a range of functionalities, including symptom monitoring and postsurgical follow-ups. The use of these tools was associated with improved clinical outcomes, such as timely intervention for clinical deterioration and enhanced clinical protocol adherence. Additionally, a small number of studies identified potential cost savings in terms of reduced unplanned health care contacts and optimized clinical resource use. Patient and clinician experiences were generally positive, with high adherence to remote assessments and an appreciation for the personalized and timely care facilitated by these technologies. Barriers included high initial setup costs for digital technologies, leading to an inflated cost per patient in small sample studies.ConclusionsDigital remote assessment tools offer significant potential to enhance health care delivery by improving health outcomes, reducing costs, and enriching patient and clinician experiences. Their flexibility and adaptability make them suitable for various clinical contexts, supporting the personalization of care and operational efficiency. While digital remote assessment tools offer significant potential, careful consideration of implementation strategies, equity, cost, and clinician and patient experiences is crucial for successful clinical integration.

Project description:BackgroundChromatographic peakpicking continues to represent a significant bottleneck in automated LC-MS workflows. Uncontrolled false discovery rates and the lack of manually-calibrated quality metrics require researchers to visually evaluate individual peaks, requiring large amounts of time and breaking replicability. This problem is exacerbated in noisy environmental datasets and for novel separation methods such as hydrophilic interaction columns in metabolomics, creating a demand for a simple, intuitive, and robust metric of peak quality.ResultsHere, we manually labeled four HILIC oceanographic particulate metabolite datasets to assess the performance of individual peak quality metrics. We used these datasets to construct a predictive model calibrated to the likelihood that visual inspection by an MS expert would include a given mass feature in the downstream analysis. We implemented two novel peak quality metrics, a custom signal-to-noise metric and a test of similarity to a bell curve, both calculated from the raw data in the extracted ion chromatogram, and found that these outperformed existing measurements of peak quality. A simple logistic regression model built on two metrics reduced the fraction of false positives in the analysis from 70-80% down to 1-5% and showed minimal overfitting when applied to novel datasets. We then explored the implications of this quality thresholding on the conclusions obtained by the downstream analysis and found that while only 10% of the variance in the dataset could be explained by depth in the default output from the peakpicker, approximately 40% of the variance was explained when restricted to high-quality peaks alone.ConclusionsWe conclude that the poor performance of peakpicking algorithms significantly reduces the power of both univariate and multivariate statistical analyses to detect environmental differences. We demonstrate that simple models built on intuitive metrics and derived from the raw data are more robust and can outperform more complex models when applied to new data. Finally, we show that in properly curated datasets, depth is a major driver of variability in the marine microbial metabolome and identify several interesting metabolite trends for future investigation.

Dataset Information

Quality assessment in light microscopy for routine use through simple tools and robust metrics.

Publications

Quality assessment in light microscopy for routine use through simple tools and robust metrics.

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