Browse
Submit Data
Databases
API
Help

Dataset Information

17 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Gram Staining: a Comparison of Two Automated Systems and Manual Staining.

ABSTRACT: Various Gram staining automated systems are available to accelerate and standardize the staining process, but a systematic comparison of different systems is largely lacking. The objective of this study was to evaluate two devices in comparison to manual Gram staining. Clinical samples (n = 500; University Hospital Münster, Germany; May to June 2020) were simultaneously Gram stained manually and with two automated Gram stainers (Previ Color Gram, bioMérieux, and ColorAX2, Axonlab). The quality was assessed based on four criteria: (i) homogeneous staining of bacteria/fungi, (ii) uniform staining of the background, (iii) absence of staining artifacts, and (iv) congruency between culture and microscopy. Each criterion was rated with 0 (absence) or 1 (presence) point to calculate a quality score (0 to 4 points). The costs for each staining procedure were calculated based on consumables and hands-on time (applying the average wage of a laboratory technician in the public service for Germany and the United States). The mean (± standard deviation [SD]) quality scores were comparable for manual staining (3.06 ± 0.91) and Previ Color Gram (3.04 ± 0.90; P = 0.6), while significantly lower scores were achieved by ColorAX2 (2.57 ± 1.09; P < 0.0001). The total cost per Gram stain was €1.13/$1.34 for Previ Color Gram, €0.80/$0.83 for manual, and €0.60/$0.71 for ColorAX2, respectively. The quality and costs per slide vary significantly between instruments of different manufacturers.

SUBMITTER: Frobose NJ

PROVIDER: S-EPMC7685888 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Comparison of Inoculation with the InoqulA and WASP Automated Systems with Manual Inoculation.

Project description:The quality of sample inoculation is critical for achieving an optimal yield of discrete colonies in both monomicrobial and polymicrobial samples to perform identification and antibiotic susceptibility testing. Consequently, we compared the performance between the InoqulA (BD Kiestra), the WASP (Copan), and manual inoculation methods. Defined mono- and polymicrobial samples of 4 bacterial species and cloudy urine specimens were inoculated on chromogenic agar by the InoqulA, the WASP, and manual methods. Images taken with ImagA (BD Kiestra) were analyzed with the VisionLab version 3.43 image analysis software to assess the quality of growth and to prevent subjective interpretation of the data. A 3- to 10-fold higher yield of discrete colonies was observed following automated inoculation with both the InoqulA and WASP systems than that with manual inoculation. The difference in performance between automated and manual inoculation was mainly observed at concentrations of >10(6) bacteria/ml. Inoculation with the InoqulA system allowed us to obtain significantly more discrete colonies than the WASP system at concentrations of >10(7) bacteria/ml. However, the level of difference observed was bacterial species dependent. Discrete colonies of bacteria present in 100- to 1,000-fold lower concentrations than the most concentrated populations in defined polymicrobial samples were not reproducibly recovered, even with the automated systems. The analysis of cloudy urine specimens showed that InoqulA inoculation provided a statistically significantly higher number of discrete colonies than that with WASP and manual inoculation. Consequently, the automated InoqulA inoculation greatly decreased the requirement for bacterial subculture and thus resulted in a significant reduction in the time to results, laboratory workload, and laboratory costs.

| S-EPMC4473203 | biostudies-literature

Automated sequential chromogenic IHC double staining with two HRP substrates.

Project description:Automated IHC double staining using diaminobenzidine and HRP Magenta is illustrated utilizing a new acidic block with sulfuric acid to prevent cross-reactivity. Residual cross-reactivity in double staining is determined to arise from chromogenic-bound antibodies and amplification system during the first part of the double staining.

| S-EPMC6245840 | biostudies-literature

A comparison of automated and manual co-registration for magnetoencephalography.

Project description:Magnetoencephalography (MEG) is a neuroimaging technique that accurately captures the rapid (sub-millisecond) activity of neuronal populations. Interpretation of functional data from MEG relies upon registration to the participant's anatomical MRI. The key remaining step is to transform the participant's MRI into the MEG head coordinate space. Although both automated and manual approaches to co-registration are available, the relative accuracy of two approaches has not been systematically evaluated. The goal of the present study was to compare the accuracy of manual and automated co-registration. Resting MEG and T1-weighted MRI data were collected from 90 participants. Automated and manual co-registration were performed on the same subjects, and the inter-method reliability of the two methods assessed using the intra-class correlation. Median co-registration error for both methods was within acceptable limits. Inter-method reliability was in the "good" range for co-registration error, and the "good" to "excellent" range for translation and rotation. These results suggest that the output of the automated co-registration procedure is comparable to that achieved using manual co-registration.

| S-EPMC7190172 | biostudies-literature

Comparison of Two Automated Targeted Metabolomics Programs to Manual Profiling by an Experienced Spectroscopist for 1H-NMR Spectra.

Project description:Automated programs that carry out targeted metabolite identification and quantification using proton nuclear magnetic resonance spectra can overcome time and cost barriers that limit metabolomics use. However, their performance needs to be comparable to that of an experienced spectroscopist. A previously analyzed pediatric sepsis data set of serum samples was used to compare results generated by the automated programs rDolphin and BATMAN with the results obtained by manual profiling for 58 identified metabolites. Metabolites were selected using Student's t-tests and evaluated with several performance metrics. The manual profiling results had the highest performance metrics values, especially for sensitivity (76.9%), area under the receiver operating characteristic curve (0.90), precision (62.5%), and testing accuracy based on a neural net (88.6%). All three approaches had high specificity values (77.7-86.7%). Manual profiling by an expert spectroscopist outperformed two open-source automated programs, indicating that further development is needed to achieve acceptable performance levels.

| S-EPMC8949809 | biostudies-literature

Comparison of oocyte vitrification using a semi-automated or a manual closed system in human siblings

Project description:To study the efficiency of a semi-automated technique of oocyte vitrification as compared with a manual method and transcriptomic landscape associated with the oocyte vitrification.

2022-12-01 | GSE205417 | GEO

Somatostatin receptor immunohistochemistry in neuroendocrine tumors: comparison between manual and automated evaluation.

Project description:BackgroundManual evaluation of somatostatin receptor (SSTR) immunohistochemistry (IHC) is a time-consuming and cost-intensive procedure. Aim of the study was to compare manual evaluation of SSTR subtype IHC to an automated software-based analysis, and to in-vivo imaging by SSTR-based PET/CT.MethodsWe examined 25 gastroenteropancreatic neuroendocrine tumor (GEP-NET) patients and correlated their in-vivo SSTR-PET/CT data (determined by the standardized uptake values SUVmax,-mean) with the corresponding ex-vivo IHC data of SSTR subtype (1, 2A, 4, 5) expression. Exactly the same lesions were imaged by PET/CT, resected and analyzed by IHC in each patient. After manual evaluation, the IHC slides were digitized and automatically evaluated for SSTR expression by Definiens XD software. A virtual IHC score "BB1" was created for comparing the manual and automated analysis of SSTR expression.ResultsBB1 showed a significant correlation with the corresponding conventionally determined Her2/neu score of the SSTR-subtypes 2A (rs: 0.57), 4 (rs: 0.44) and 5 (rs: 0.43). BB1 of SSTR2A also significantly correlated with the SUVmax (rs: 0.41) and the SUVmean (rs: 0.50). Likewise, a significant correlation was seen between the conventionally evaluated SSTR2A status and the SUVmax (rs: 0.42) and SUVmean (rs: 0.62).ConclusionOur data demonstrate that the evaluation of the SSTR status by automated analysis (BB1 score), using digitized histopathology slides ("virtual microscopy"), corresponds well with the SSTR2A, 4 and 5 expression as determined by conventional manual histopathology. The BB1 score also exhibited a significant association to the SSTR-PET/CT data in accordance with the high affinity profile of the SSTR analogues used for imaging.

| S-EPMC4152058 | biostudies-literature

A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes.

Project description:Large databases of high-resolution structural MR images are being assembled to quantitatively examine the relationships between brain anatomy, disease progression, treatment regimens, and genetic influences upon brain structure. Quantifying brain structures in such large databases cannot be practically accomplished by expert neuroanatomists using hand-tracing. Rather, this research will depend upon automated methods that reliably and accurately segment and quantify dozens of brain regions. At present, there is little guidance available to help clinical research groups in choosing such tools. Thus, our goal was to compare the performance of two popular and fully automated tools, FSL/FIRST and FreeSurfer, to expert hand tracing in the measurement of the hippocampus and amygdala. Volumes derived from each automated measurement were compared to hand tracing for percent volume overlap, percent volume difference, across-sample correlation, and 3-D group-level shape analysis. In addition, sample size estimates for conducting between-group studies were computed for a range of effect sizes. Compared to hand tracing, hippocampal measurements with FreeSurfer exhibited greater volume overlap, smaller volume difference, and higher correlation than FIRST, and sample size estimates with FreeSurfer were closer to hand tracing. Amygdala measurement with FreeSurfer was also more highly correlated to hand tracing than FIRST, but exhibited a greater volume difference than FIRST. Both techniques had comparable volume overlap and similar sample size estimates. Compared to hand tracing, a 3-D shape analysis of the hippocampus showed FreeSurfer was more accurate than FIRST, particularly in the head and tail. However, FIRST more accurately represented the amygdala shape than FreeSurfer, which inflated its anterior and posterior surfaces.

| S-EPMC2714773 | biostudies-literature

Home sleep apnea testing: comparison of manual and automated scoring across international sleep centers.

Project description:PurposeTo determine the agreement between the manual scoring of home sleep apnea tests (HSATs) by international sleep technologists and automated scoring systems.MethodsFifteen HSATs, previously recorded using a type 3 monitor, were saved in European Data Format. The studies were scored by nine experienced technologists from the sleep centers of the Sleep Apnea Global Interdisciplinary Consortium (SAGIC) using the locally available software. Each study was scored separately by human scorers using the nasal pressure (NP), flow derived from the NP signal (transformed NP), or respiratory inductive plethysmography (RIP) flow. The same procedure was followed using two automated scoring systems: Remlogic (RLG) and Noxturnal (NOX).ResultsThe intra-class correlation coefficients (ICCs) of the apnea-hypopnea index (AHI) scoring using the NP, transformed NP, and RIP flow were 0.96 [95% CI 0.93-0.99], 0.98 [0.96-0.99], and 0.97 [0.95-0.99], respectively. Using the NP signal, the mean differences in AHI between the average of the manual scoring and the automated systems were - 0.9 ± 3.1/h (AHIRLG vs AHIMANUAL) and - 1.3 ± 2.6/h (AHINOX vs AHIMANUAL). Using the transformed NP, the mean differences in AHI were - 1.9 ± 3.3/h (AHIRLG vs AHIMANUAL) and 1.6 ± 3.0/h (AHINOX vs AHIMANUAL). Using the RIP flow, the mean differences in AHI were - 2.7 ± 4.5/h (AHIRLG vs AHIMANUAL) and 2.3 ± 3.4/h (AHINOX vs AHIMANUAL).ConclusionsThere is very strong agreement in the scoring of the AHI for HSATs between the automated systems and experienced international technologists. Automated scoring of HSATs using commercially available software may be useful to standardize scoring in future endeavors involving international sleep centers.

| S-EPMC6615031 | biostudies-literature

Comparison of automated and manual quantification methods for neuromelanin-sensitive MRI in Parkinson's disease.

Project description:Neuromelanin-sensitive magnetic resonance imaging quantitative analysis methods have provided promising biomarkers that can noninvasively quantify degeneration of the substantia nigra in patients with Parkinson's disease. However, there is a need to systematically evaluate the performance of manual and automated quantification approaches. We evaluate whether spatial, signal-intensity, or subject specific abnormality measures using either atlas based or manually traced identification of the substantia nigra better differentiate patients with Parkinson's disease from healthy controls using logistic regression models and receiver operating characteristics. Inference was performed using bootstrap analyses to calculate 95% confidence interval bounds. Pairwise comparisons were performed by generating 10,000 permutations, refitting the models, and calculating a paired difference between metrics. Thirty-one patients with Parkinson's disease and 22 healthy controls were included in the analyses. Signal intensity measures significantly outperformed spatial and subject specific abnormality measures, with the top performers exhibiting excellent ability to differentiate patients with Parkinson's disease and healthy controls (balanced accuracy = 0.89; area under the curve = 0.81; sensitivity =0.86; and specificity = 0.83). Atlas identified substantia nigra metrics performed significantly better than manual tracing metrics. These results provide clear support for the use of automated signal intensity metrics and additional recommendations. Future work is necessary to evaluate whether the same metrics can best differentiate atypical parkinsonism, perform similarly in de novo and mid-stage cohorts, and serve as longitudinal monitoring biomarkers.

| S-EPMC10789205 | biostudies-literature

A comparison of manual and automated neural architecture search for white matter tract segmentation.

Project description:Segmentation of white matter tracts in diffusion magnetic resonance images is an important first step in many imaging studies of the brain in health and disease. Similar to medical image segmentation in general, a popular approach to white matter tract segmentation is to use U-Net based artificial neural network architectures. Despite many suggested improvements to the U-Net architecture in recent years, there is a lack of systematic comparison of architectural variants for white matter tract segmentation. In this paper, we evaluate multiple U-Net based architectures specifically for this purpose. We compare the results of these networks to those achieved by our own various architecture changes, as well as to new U-Net architectures designed automatically via neural architecture search (NAS). To the best of our knowledge, this is the first study to systematically compare multiple U-Net based architectures for white matter tract segmentation, and the first to use NAS. We find that the recently proposed medical imaging segmentation network UNet3+ slightly outperforms the current state of the art for white matter tract segmentation, and achieves a notably better mean Dice score for segmentation of the fornix (+ 0.01 and + 0.006 mean Dice increase for left and right fornix respectively), a tract that the current state of the art model struggles to segment. UNet3+ also outperforms the current state of the art when little training data is available. Additionally, manual architecture search found that a minor segmentation improvement is observed when an additional, deeper layer is added to the U-shape of UNet3+. However, all networks, including those designed via NAS, achieve similar results, suggesting that there may be benefit in exploring networks that deviate from the general U-Net paradigm.

| S-EPMC9884270 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data