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Journal of Chromatography. A Oct 2023The value of the concept of retention indices (RI) to the practice of gas chromatography (GC) is highlighted, where the RI of a compound is one component of the strategy... (Review)
Review
The value of the concept of retention indices (RI) to the practice of gas chromatography (GC) is highlighted, where the RI of a compound is one component of the strategy to identify the compound. The widespread reliance on GC and then on mass spectrometry for 'identification', may result in inadequate confirmation of molecular identity. However, RI do provide a useful tentative indication of the possible molecule(s). Thus, the RI value is a useful first measure of the molecule identity, and shown here to be valuable provided limitations are recognised. An author has a responsibility to correctly calculate the index and then use the values for (tentative) identification. Tables of reference RI values are useful in this respect, but finding an 'exact match' RI value does not confirm the identity. Hence, it is necessary to understand how the RI value may be incorrectly used in this respect. The reviewer of written research is charged with ensuring the index values are applied in a rigorous manner. Selected case studies from our own work, support the care that must be exercised when reporting RI values. In terms of advanced GC operations, mention is made of multidimensional gas chromatography and comprehensive two-dimensional gas chromatography to acquire RI values on both the first and second columns in the two-column separation experiment.
Topics: Gas Chromatography-Mass Spectrometry; Mass Spectrometry; Reference Values
PubMed: 37717451
DOI: 10.1016/j.chroma.2023.464376 -
Journal of Applied Clinical Medical... Aug 2023The purpose of this study was to investigate the impact of scanning orientation and lateral response artifact (LRA) effects on the dose-response of EBT4 films and...
The purpose of this study was to investigate the impact of scanning orientation and lateral response artifact (LRA) effects on the dose-response of EBT4 films and compare it with that of EBT3 films. Dose-response curves for EBT3 and EBT4 films in red-green-blue (RGB) color channels in portrait orientation were created for unexposed films and for films exposed to doses ranging from 0 to 1 000 cGy. Portrait and landscape orientations of the EBT3 and EBT4 films were scanned to investigate the scanning orientation effect in the red channel. EBT3 and EBT4 films were irradiated to assess the LRA in the red channel using a field size of 15 × 15 cm and delivered doses of 200, 400, and 600 cGy. Films were scanned at the edge of the scanner bed, and the measured doses were compared with the treatment planning system (TPS) calculated doses at a position 100 mm lateral to the scanner center. At a dose of 200 cGy, the differences in optical density (OD) in the red, green, and blue color channels between EBT3 and EBT4 films were 0.035 (24.8%), 0.042 (49.7%), and 0.022 (64.4%), respectively. The EBT4 film slightly improved the scanning orientation compared to the EBT3 film. The OD difference in the different scanning orientations for the EBT3 and EBT4 films was 0.015 (6.8%) and 0.007 (3.9%), respectively, at a dose of 200 cGy. This is equivalent to a 20 or 10 cGy variation at a dose of 200 cGy. Compared with the TPS calculation, the measurement doses for EBT3 and EBT4 films irradiated at 200 cGy were approximately 16% and 13% higher, respectively, at the 100 mm off-centered position. The EBT4 film showed an improvement concerning the impact of LRA compared with the EBT3 film. This study demonstrated that the response of EBT4 film to a dose in the blue channel was less sensitive and showed an improvement in the scanning orientation and LRA effects.
Topics: Humans; Artifacts; Film Dosimetry; Calibration
PubMed: 37086445
DOI: 10.1002/acm2.13992 -
Computerized Medical Imaging and... Jul 2023Deep learning-based models applied to digital pathology require large, curated datasets with high-quality (HQ) annotations to perform correctly. In many cases,...
Deep learning-based models applied to digital pathology require large, curated datasets with high-quality (HQ) annotations to perform correctly. In many cases, recruiting expert pathologists to annotate large databases is not feasible, and it is necessary to collect additional labeled data with varying label qualities, e.g., pathologists-in-training (henceforth, non-expert annotators). Learning from datasets with noisy labels is more challenging in medical applications since medical imaging datasets tend to have instance-dependent noise and suffer from high inter/intra-observer variability. In this paper, we design an uncertainty-driven labeling strategy with which we generate soft labels from 10 non-expert annotators for multi-class skin cancer classification. Based on this soft annotation, we propose an uncertainty estimation-based framework to handle these noisy labels. This framework is based on a novel formulation using a dual-branch min-max entropy calibration to penalize inexact labels during the training. Comprehensive experiments demonstrate the promising performance of our labeling strategy. Results show a consistent improvement by using soft labels with standard cross-entropy loss during training (∼4.0% F1-score) and increases when calibrating the model with the proposed min-max entropy calibration (∼6.6% F1-score). These improvements are produced at negligible cost, both in terms of annotation and calculation.
Topics: Uncertainty; Calibration; Databases, Factual; Entropy; Histological Techniques
PubMed: 37087899
DOI: 10.1016/j.compmedimag.2023.102231 -
Frontiers in Immunology 2023Coronary heart disease (CHD) is one of the major cardiovascular diseases, a common chronic disease in the elderly and a major cause of disability and death in the world.... (Randomized Controlled Trial)
Randomized Controlled Trial
OBJECTIVE
Coronary heart disease (CHD) is one of the major cardiovascular diseases, a common chronic disease in the elderly and a major cause of disability and death in the world. Currently, intensive care unit (ICU) patients have a high probability of concomitant coronary artery disease, and the mortality of this category of patients in the ICU is receiving increasing attention. Therefore, the aim of this study was to verify whether the composite inflammatory indicators are significantly associated with ICU mortality in ICU patients with CHD and to develop a simple personalized prediction model.
METHOD
7115 patients from the Multi-Parameter Intelligent Monitoring in Intensive Care Database IV were randomly assigned to the training cohort (n = 5692) and internal validation cohort (n = 1423), and 701 patients from the eICU Collaborative Research Database served as the external validation cohort. The association between various inflammatory indicators and ICU mortality was determined by multivariate Logistic regression analysis and Cox proportional hazards model. Subsequently, a novel predictive model for mortality in ICU patients with CHD was developed in the training cohort and performance was evaluated in the internal and external validation cohorts.
RESULTS
Various inflammatory indicators were demonstrated to be significantly associated with ICU mortality, 30-day ICU mortality, and 90-day ICU mortality in ICU patients with CHD by Logistic regression analysis and Cox proportional hazards model. The area under the curve of the novel predictive model for ICU mortality in ICU patients with CHD was 0.885 for the internal validation cohort and 0.726 for the external validation cohort. The calibration curve showed that the predicted probabilities of the model matched the actual observed probabilities. Furthermore, the decision curve analysis showed that the novel prediction model had a high net clinical benefit.
CONCLUSION
In ICU patients with CHD, various inflammatory indicators were independent risk factors for ICU mortality. We constructed a novel predictive model of ICU mortality risk in ICU patients with CHD that had great potential to guide clinical decision-making.
Topics: Aged; Humans; Critical Illness; Intensive Care Units; Critical Care; Coronary Artery Disease; Calibration
PubMed: 38035097
DOI: 10.3389/fimmu.2023.1295377 -
Nature Communications Jul 2023Brain-computer interfaces (BCIs) have attracted considerable attention in motor and language rehabilitation. Most devices use cap-based non-invasive, headband-based...
Brain-computer interfaces (BCIs) have attracted considerable attention in motor and language rehabilitation. Most devices use cap-based non-invasive, headband-based commercial products or microneedle-based invasive approaches, which are constrained for inconvenience, limited applications, inflammation risks and even irreversible damage to soft tissues. Here, we propose in-ear visual and auditory BCIs based on in-ear bioelectronics, named as SpiralE, which can adaptively expand and spiral along the auditory meatus under electrothermal actuation to ensure conformal contact. Participants achieve offline accuracies of 95% in 9-target steady state visual evoked potential (SSVEP) BCI classification and type target phrases successfully in a calibration-free 40-target online SSVEP speller experiment. Interestingly, in-ear SSVEPs exhibit significant 2 harmonic tendencies, indicating that in-ear sensing may be complementary for studying harmonic spatial distributions in SSVEP studies. Moreover, natural speech auditory classification accuracy can reach 84% in cocktail party experiments. The SpiralE provides innovative concepts for designing 3D flexible bioelectronics and assists the development of biomedical engineering and neural monitoring.
Topics: Humans; Brain-Computer Interfaces; Evoked Potentials, Visual; Electroencephalography; Calibration; Language; Photic Stimulation; Algorithms
PubMed: 37452047
DOI: 10.1038/s41467-023-39814-6 -
Journal of Cellular and Molecular... Feb 2024Non-alcoholic fatty liver disease (NAFLD) is a major chronic liver disease worldwide. Cuproptosis has recently been reported as a form of cell death that appears to...
Non-alcoholic fatty liver disease (NAFLD) is a major chronic liver disease worldwide. Cuproptosis has recently been reported as a form of cell death that appears to drive the progression of a variety of diseases. This study aimed to explore cuproptosis-related molecular clusters and construct a prediction model. The gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. The associations between molecular clusters of cuproptosis-related genes and immune cell infiltration were investigated using 50 NAFLD samples. Furthermore, cluster-specific differentially expressed genes were identified by the WGCNA algorithm. External datasets were used to verify and screen feature genes, and nomograms, calibration curves and decision curve analysis (DCA) were performed to verify the performance of the prediction model. Finally, a NAFLD-diet mouse model was constructed to further verify the predictive analysis, thus providing new insights into the prediction of NAFLD clusters and risks. The role of cuproptosis in the development of non-alcoholic fatty liver disease and immune cell infiltration was explored. Non-alcoholic fatty liver disease was divided into two cuproptosis-related molecular clusters by unsupervised clustering. Three characteristic genes (ENO3, SLC16A1 and LEPR) were selected by machine learning and external data set validation. In addition, the accuracy of the nomogram, calibration curve and decision curve analysis in predicting NAFLD clusters was also verified. Further animal and cell experiments confirmed the difference in their expression in the NAFLD mouse model and Mouse hepatocyte cell line. The present study explored the relationship between non-alcoholic fatty liver disease and cuproptosis, providing new ideas and targets for individual treatment of the disease.
Topics: Animals; Mice; Non-alcoholic Fatty Liver Disease; Algorithms; Calibration; Cell Death; Cell Line; Disease Models, Animal; Apoptosis
PubMed: 38169083
DOI: 10.1111/jcmm.18091 -
PeerJ 2023Marine heatwaves and regional coral bleaching events have become more frequent and severe across the world's oceans over the last several decades due to global climate... (Review)
Review
Marine heatwaves and regional coral bleaching events have become more frequent and severe across the world's oceans over the last several decades due to global climate change. Observational studies have documented spatiotemporal variation in the responses of reef-building corals to thermal stress within and among taxa across geographic scales. Although many tools exist for predicting, detecting, and quantifying coral bleaching, it remains difficult to compare bleaching severity (, percent cover of bleached surface areas) among studies and across species or regions. For this review, we compiled over 2,100 coral bleaching observations representing 87 reef-building coral genera and 250 species of common morphological groups from a total of 74 peer-reviewed scientific articles, encompassing three broad geographic regions (Atlantic, Indian, and Pacific Oceans). While bleaching severity was found to vary by region, genus, and morphology, we found that both genera and morphologies responded differently to thermal stress across regions. These patterns were complicated by (i) inconsistent methods and response metrics across studies; (ii) differing ecological scales of observations (, individual colony-level vs. population or community-level); and (iii) temporal variability in surveys with respect to the onset of thermal stress and the chronology of bleaching episodes. To improve cross-study comparisons, we recommend that future surveys prioritize measuring bleaching in the same individual coral colonies over time and incorporate the severity and timing of warming into their analyses. By reevaluating and standardizing the ways in which coral bleaching is quantified, researchers will be able to track responses to marine heatwaves with increased rigor, precision, and accuracy.
Topics: Animals; Coral Reefs; Coral Bleaching; Temperature; Anthozoa; Reference Standards
PubMed: 37810774
DOI: 10.7717/peerj.16100 -
Analytical and Bioanalytical Chemistry Jul 2023The emergence of mass spectrometry (MS)-based methods to quantify proteins for clinical applications has led to the need for accurate and consistent measurements. To...
The emergence of mass spectrometry (MS)-based methods to quantify proteins for clinical applications has led to the need for accurate and consistent measurements. To meet the clinical needs of MS-based protein results, it is important that the results are traceable to higher-order standards and methods and have defined uncertainty values. Therefore, we outline a comprehensive approach for the estimation of measurement uncertainty of a MS-based procedure for the quantification of a protein biomarker. Using a bottom-up approach, which is the model outlined in the "Guide to the Expression of Uncertainty of Measurement" (GUM), we evaluated the uncertainty components of a MS-based measurement procedure for a protein biomarker in a complex matrix. The cause-and-effect diagram of the procedure is used to identify each uncertainty component, and statistical equations are derived to determine the overall combined uncertainty. Evaluation of the uncertainty components not only enables the calculation of the measurement uncertainty but can also be used to determine if the procedure needs improvement. To demonstrate the use of the bottom-up approach, the overall combined uncertainty is estimated for the National Institute of Standards and Technology (NIST) candidate reference measurement procedure for albumin in human urine. The results of the uncertainty approach are applied to the determination of uncertainty for the certified value for albumin in candidate NIST Standard Reference Material® (SRM) 3666. This study provides a framework for measurement uncertainty estimation of a MS-based protein procedure by identifying the uncertainty components of the procedure to derive the overall combined uncertainty.
Topics: Humans; Tandem Mass Spectrometry; Chromatography, Liquid; Uncertainty; Reference Standards; Albumins
PubMed: 37231301
DOI: 10.1007/s00216-023-04705-8 -
Journal of Radiological Protection :... May 2024The aim of this study is to propose diagnostic reference levels (DRLs) values for mammography in Switzerland. For the data collection, a survey was conducted among a...
The aim of this study is to propose diagnostic reference levels (DRLs) values for mammography in Switzerland. For the data collection, a survey was conducted among a sufficient number of centres, including five University hospitals, several cantonal hospitals, and large private clinics, covering all linguistic regions of Switzerland to be representative of the clinical practice. The data gathered contained the mean glandular dose (MGD), the compressed breast thickness (CBT), the mammography model and the examination parameters for each acquisition. The data collected was sorted into the following categories: 2D or digital breast tomosynthesis (DBT) examination, craniocaudal (CC) or mediolateral oblique (MLO) projection, and eight categories of CBT ranging from 20 mm to 100 mm in 10 mm intervals. A total of 24 762 acquisitions were gathered in 31 centres on 36 mammography units from six manufacturers. The analysis showed that the data reflects the practice in Switzerland. The results revealed that the MGD is larger for DBT than for 2D acquisitions for the same CBT. From 20-30 mm to 90-100 mm of CBT, the 75th percentile of the MGD values obtained increased from 0.81 mGy to 2.55 mGy for 2D CC acquisitions, from 0.83 mGy to 2.96 mGy for 2D MLO acquisitions, from 1.22 mGy to 3.66 mGy for DBT CC acquisitions and from 1.33 mGy to 4.04 mGy for DBT MLO acquisitions. The results of the survey allow us to propose Swiss DRLs for mammography according to the examination type (2D/DBT), projection (CC/MLO) and CBT. The proposed values are very satisfactory in comparison with other studies.
Topics: Mammography; Switzerland; Humans; Female; Radiation Dosage; Diagnostic Reference Levels; Breast Neoplasms; Reference Values
PubMed: 38530290
DOI: 10.1088/1361-6498/ad37c8 -
Nature Communications Nov 2023Lean muscle mass (LMM) is an important aspect of human health. Temporalis muscle thickness is a promising LMM marker but has had limited utility due to its unknown...
Lean muscle mass (LMM) is an important aspect of human health. Temporalis muscle thickness is a promising LMM marker but has had limited utility due to its unknown normal growth trajectory and reference ranges and lack of standardized measurement. Here, we develop an automated deep learning pipeline to accurately measure temporalis muscle thickness (iTMT) from routine brain magnetic resonance imaging (MRI). We apply iTMT to 23,876 MRIs of healthy subjects, ages 4 through 35, and generate sex-specific iTMT normal growth charts with percentiles. We find that iTMT was associated with specific physiologic traits, including caloric intake, physical activity, sex hormone levels, and presence of malignancy. We validate iTMT across multiple demographic groups and in children with brain tumors and demonstrate feasibility for individualized longitudinal monitoring. The iTMT pipeline provides unprecedented insights into temporalis muscle growth during human development and enables the use of LMM tracking to inform clinical decision-making.
Topics: Male; Female; Humans; Child; Growth Charts; Temporal Muscle
PubMed: 37945573
DOI: 10.1038/s41467-023-42501-1