Metrological framework to support accurate, reliable, and reproducible nucleic acid measurements.
Ontology highlight
ABSTRACT:
SUBMITTER: Milavec M
PROVIDER: S-EPMC8568362 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundAlthough pulmonary artery catheters (PACs) have been the reference standard for calculating cardiac output, echocardiographic estimation of cardiac output (CO) by cardiologists has shown high accuracy compared to PAC measurements. A few studies have assessed the accuracy of echocardiographic estimation of CO in critically ill patients by intensivists with basic training. The aim of this study was to evaluate the accuracy of CO measurements by intensivists with basic training using pulsed-wave Doppler ultrasound vs. PACs in critically ill patients.MethodsCritically ill patients who required hemodynamic monitoring with a PAC were eligible for the study. Three different intensivists with basic critical care echocardiography training obtained three measurements of CO on each patient. The maximum of three separate left-ventricular outflow tract diameter measurements and the mean of three LVOT velocity time integral measurements were used. The inter-observer reliability and correlation of CO measured by PACs vs. critical care echocardiography were assessed.ResultsA total of 20 patients were included. Data were analyzed comparing the measurements of CO by PAC vs. echocardiography. The inter-observer reliability for measuring CO by echocardiography was good based on a coefficient of intraclass correlation of 0.6 (95% CI 0.48-0.86, p < 0.001). Bias and limits of agreement between the two techniques were acceptable (0.64 ± 1.18 L/min, 95% limits of agreement of - 1.73 to 3.01 L/min). In patients with CO < 6.5 L/min, the agreement between CO measured by PAC vs. echocardiography improved (0.13 ± 0.89 L/min; 95% limits of agreement of - 1.64 to 2.22 L/min). The mean percentage of error between the two methods was 17%.ConclusionsCritical care echocardiography performed at the bedside by intensivists with basic critical care echocardiography training is an accurate and reproducible technique to measure cardiac output in critically ill patients.
| S-EPMC6638616 | biostudies-literature
Project description:BACKGROUND:Ultrasonography is a fast and patient-friendly modality to assess cartilage thickness. However, inconsistent results regarding accuracy have been reported. Therefore, we asked what are (1) the accuracy, (2) reproducibility, and (3) reliability of ultrasonographic cartilage thickness measurement using contrast-enhanced micro-CT for validation? METHODS:A series of 50 cartilage-bone plugs were harvested from fresh bovine and porcine joints. Ultrasonic cartilage thickness was determined using an A-mode, 20-MHz hand-held ultrasonic probe with native (1580?m/s) and adjusted speed of sound (1696?m/s). All measurements were performed by two observers at two different occasions. Angle of insonation was controlled by tilting the device and recording minimal thickness. Retrieval of exact location for measurement was facilitated by aligning the circular design of both cartilage-bone plug and ultrasonic device. There was no soft tissue interference between cartilage surface and ultrasonic probe. Ground truth measurement was performed using micro-CT with iodine contrast agent and a voxel size of 16??m. The mean cartilage thickness was 1.383?±?0.402?mm (range, 0.588-2.460?mm). RESULTS:Mean accuracy was 0.074?±?0.061?mm (0.002-0.256?mm) for native and 0.093?±?0.098?mm (0.000-0.401?mm) for adjusted speed of sound. Bland-Altman analysis showed no systematic error. High correlation was found for native and adjusted speed of sound with contrast-enhanced micro-CT (both r?=?0.973; p?<?0.001). A perfect agreement for reproducibility (intraclass correlation coefficient [ICC] 0.992 and 0.994) and reliability (ICC 0.993, 95% confidence interval 0.990-0.995) was found. CONCLUSIONS:Ultrasonic cartilage thickness measurement could be shown to be highly accurate, reliable, and reproducible. The A-mode ultrasonic cartilage thickness measurement is a fast and patient-friendly modality which can detect early joint degeneration and facilitate decision making in joint preserving surgery.
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Project description:Reactions between a gas phase and a solid material are of high importance in the study of alternative ways for energy conversion utilizing otherwise useless carbon dioxide (CO2). The photocatalytic CO2 reduction to hydrocarbon fuels like e.g., methane (CH4) is such a potential candidate process converting solar light into molecular bonds. In this work, the design, construction, and operation of a high-purity gas-solid photoreactor is described. The design aims at eliminating any unwanted carbon-containing impurities and leak points, ensuring the collection of reliable and reproducible data in photocatalytic CO2 reduction measurements. Apart from the hardware design, a detailed experimental procedure including gas analysis is presented, allowing newcomers in the field of gas-solid CO2 reduction to learn the essential basics and valuable tricks. By performing extensive blank measurements (with/without sample and/or light) the true performance of photocatalytic materials can be monitored, leading to the identification of trends and the proposal of possible mechanisms in CO2 photoreduction. The reproducibility of measurements between different versions of the here presented reactor on the ppm level is evidenced.
| S-EPMC10545968 | biostudies-literature
Project description:Protein-RNA and protein-DNA complexes play critical roles in biology. Despite considerable recent advances in protein structure prediction, the prediction of the structures of protein-nucleic acid complexes without homology to known complexes is a largely unsolved problem. Here we extend the RoseTTAFold machine learning protein-structure-prediction approach to additionally predict nucleic acid and protein-nucleic acid complexes. We develop a single trained network, RoseTTAFoldNA, that rapidly produces three-dimensional structure models with confidence estimates for protein-DNA and protein-RNA complexes. Here we show that confident predictions have considerably higher accuracy than current state-of-the-art methods. RoseTTAFoldNA should be broadly useful for modeling the structure of naturally occurring protein-nucleic acid complexes, and for designing sequence-specific RNA and DNA-binding proteins.
| S-EPMC10776382 | biostudies-literature
Project description:Machine learning algorithms hold the promise to effectively automate the analysis of histopathological images that are routinely generated in clinical practice. Any machine learning method used in the clinical diagnostic process has to be extremely accurate and, ideally, provide a measure of uncertainty for its predictions. Such accurate and reliable classifiers need enough labelled data for training, which requires time-consuming and costly manual annotation by pathologists. Thus, it is critical to minimise the amount of data needed to reach the desired accuracy by maximising the efficiency of training. We propose an accurate, reliable and active (ARA) image classification framework and introduce a new Bayesian Convolutional Neural Network (ARA-CNN) for classifying histopathological images of colorectal cancer. The model achieves exceptional classification accuracy, outperforming other models trained on the same dataset. The network outputs an uncertainty measurement for each tested image. We show that uncertainty measures can be used to detect mislabelled training samples and can be employed in an efficient active learning workflow. Using a variational dropout-based entropy measure of uncertainty in the workflow speeds up the learning process by roughly 45%. Finally, we utilise our model to segment whole-slide images of colorectal tissue and compute segmentation-based spatial statistics.
| S-EPMC6778075 | biostudies-literature
Project description:Osteoarthritis, a disorder characterized by articular cartilage deterioration, varying degrees of inflammation, and chondrocyte apoptosis, is the most common chronic joint disease. To slow or reverse its progression, inflammation should be inhibited, and chondrocyte proliferation should be promoted. Tetrahedral framework nucleic acids can be internalized by chondrocytes (even inflammatory chondrocytes) and can enhance their proliferation and migration. Wogonin, a naturally occurring flavonoid, suppresses oxidative stress and inhibits inflammation. In this study, tetrahedral framework nucleic acids were successfully self-assembled and used to load wogonin. We confirmed the effective formation of tetrahedral framework nucleic acid/wogonin complexes by dynamic light scattering, zeta potential analysis, transmission electron microscopy, and fluorescence spectrophotometry. Tetrahedral framework nucleic acids, wogonin, and especially tetrahedral framework nucleic acid/wogonin complexes effectively alleviated inflammation in vitro and in vivo and prevented cartilage destruction. In addition, these materials remarkably downregulated the expression of inflammatory mediators and matrix metalloproteinases, upregulated chondrogenic markers, and promoted tissue inhibitor of metalloproteinase 1 and B-cell lymphoma 2 expression. In vivo, after treatment with tetrahedral framework nucleic acid/wogonin complexes, the bone mineral density in regenerated tissues was much higher than that found in the untreated groups. Histologically, the complexes enhanced new tissue regeneration, significantly suppressed chondrocyte apoptosis, and promoted chondrogenic marker expression. They also inhibited cell apoptosis, increased chondrogenic marker expression, and suppressed the expression of inflammatory mediators in osteoarthritis. Therefore, we believe that tetrahedral framework nucleic acid/wogonin complexes can be used as an injectable form of therapy for osteoarthritis.
| S-EPMC7010777 | biostudies-literature
Project description:Water in its three ambient phases plays the central thermodynamic role in the terrestrial climate system. Clouds control Earth's radiation balance, atmospheric water vapour is the strongest "greenhouse" gas, and non-equilibrium relative humidity at the air-sea interface drives evaporation and latent heat export from the ocean. In this paper, we examine the climatologically relevant atmospheric relative humidity, noting fundamental deficiencies in the definition of this key observable. The metrological history of this quantity is reviewed, problems with its current definition and measurement practice are analysed, and options for future improvements are discussed in conjunction with the recent seawater standard TEOS-10. It is concluded that the International Bureau of Weights and Measures, (BIPM), in cooperation with the International Association for the Properties of Water and Steam, IAPWS, along with other international organisations and institutions, can make significant contributions by developing and recommending state-of-the-art solutions for this long standing metrological problem, such as are suggested here.
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Project description:In eukaryotic cells, miRNAs regulate a plethora of cellular functionalities ranging from cellular metabolisms, and development to the regulation of biological networks and pathways, both under homeostatic and pathological states like cancer.Despite their immense importance as key regulators of cellular processes, accurate and reliable estimation of miRNAs using Next Generation Sequencing is challenging, largely due to the limited availability of robust computational tools/methods/pipelines. Here, we introduce miRPipe, an end-to-end computational framework for the identification, characterization, and expression estimation of small RNAs, including the known and novel miRNAs and previously annotated pi-RNAs from small-RNA sequencing profiles. Our workflow detects unique novel miRNAs by incorporating the sequence information of seed and non-seed regions, concomitant with clustering analysis. This approach allows reliable and reproducible detection of unique novel miRNAs and functionally same miRNAs (paralogues). We validated the performance of miRPipe with the available state-of-the-art pipelines using both synthetic datasets generated using the newly developed miRSim tool and three cancer datasets (Chronic Lymphocytic Leukemia, Lung cancer, and breast cancer). In the experiment over the synthetic dataset, miRPipe is observed to outperform the existing state-of-the-art pipelines (accuracy: 95.23% and F 1-score: 94.17%). Analysis on all the three cancer datasets shows that miRPipe is able to extract more number of known dysregulated miRNAs or piRNAs from the datasets as compared to the existing pipelines.
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Project description:Viral capsids ensure viral genome integrity by protecting the enclosed nucleic acids. Interactions between the genome and capsid and between individual capsid proteins (i.e., capsid architecture) are intimate and are expected to be characterized by strong evolutionary conservation. For this reason, a capsid structure-based viral classification has been proposed as a way to bring order to the viral universe. The seeming lack of sufficient sequence similarity to reproduce this classification has made it difficult to reject structural convergence as the basis for the classification. We reinvestigate whether the structure-based classification for viral coat proteins making icosahedral virus capsids is in fact supported by previously undetected sequence similarity. Since codon choices can influence nascent protein folding cotranslationally, we searched for both amino acid and nucleotide sequence similarity. To demonstrate the sensitivity of the approach, we identify a candidate gene for the pandoravirus capsid protein. We show that the structure-based classification is strongly supported by amino acid and also nucleotide sequence similarities, suggesting that the similarities are due to common descent. The correspondence between structure-based and sequence-based analyses of the same proteins shown here allow them to be used in future analyses of the relationship between linear sequence information and macromolecular function, as well as between linear sequence and protein folds.IMPORTANCE Viral capsids protect nucleic acid genomes, which in turn encode capsid proteins. This tight coupling of protein shell and nucleic acids, together with strong functional constraints on capsid protein folding and architecture, leads to the hypothesis that capsid protein-coding nucleotide sequences may retain signatures of ancient viral evolution. We have been able to show that this is indeed the case, using the major capsid proteins of viruses forming icosahedral capsids. Importantly, we detected similarity at the nucleotide level between capsid protein-coding regions from viruses infecting cells belonging to all three domains of life, reproducing a previously established structure-based classification of icosahedral viral capsids.
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Project description:Accurate detection and analysis of somatic variants in cancer involve multiple third-party tools with complex dependencies and configurations, leading to laborious, error-prone, and time-consuming data conversions. This approach lacks accuracy, reproducibility, and portability, limiting clinical application. Musta was developed to address these issues as an end-to-end pipeline for detecting, classifying, and interpreting cancer mutations. Musta is based on a Python command-line tool designed to manage tumor-normal samples for precise somatic mutation analysis. The core is a Snakemake-based workflow that covers all key cancer genomics steps, including variant calling, mutational signature deconvolution, variant annotation, driver gene detection, pathway analysis, and tumor heterogeneity estimation. Musta is easy to install on any system via Docker, with a Makefile handling installation, configuration, and execution, allowing for full or partial pipeline runs. Musta has been validated at the CRS4-NGS Core facility and tested on large datasets from The Cancer Genome Atlas and the Beijing Institute of Genomics. Musta has proven robust and flexible for somatic variant analysis in cancer. It is user-friendly, requiring no specialized programming skills, and enables data processing with a single command line. Its reproducibility ensures consistent results across users following the same protocol.
| S-EPMC11311285 | biostudies-literature