Development and Psychometric Properties of the Health Belief Model Scale for Premature Birth Prevention (HBM-PBP) for Women of Childbearing Age.

Purpose: This study aimed to develop the Health Belief Model scale for premature birth prevention (HBM-PBP) and evaluated its psychometric properties in women of childbearing age. Methods: This study employed a cross-sectional design and included 724 women of childbearing age with intentions of future childbirth or in their first trimester of pregnancy. An item pool was formulated from the literature and in-depth interviews based on the health belief model. Content validation was conducted by experts and through cognitive interviews with women of childbearing age. Construct and concurrent validity and reliability were evaluated using factor analysis, Pearson's correlation analysis, and Cronbach's alpha. Results: The HBM-PBP consisted of 96 items, including perceived susceptibility (21 items, 5 subscales), severity (26 items, 5 subscales), benefits (27 items, 5 subscales), and barriers (22 items, 5 subscales). Convergent and discriminant validity were supported. The Cronbach's alpha coefficient of the domains ranged from 0.87 to 0.94. Conclusion: The HBM-PBP is a valid and reliable measurement scale with good psychometric properties. It can be used to measure health beliefs in women, either as a whole or in individual domains. Health professionals can leverage the HBM-PBP to discern women's health beliefs on premature birth, facilitating tailored interventions and educational efforts.

Deep Learning-based Hierarchical Brain Segmentation with Preliminary Analysis of the Repeatability and Reproducibility.

PURPOSE: We developed new deep learning-based hierarchical brain segmentation (DLHBS) method that can segment T1-weighted MR images (T1WI) into 107 brain subregions and calculate the volume of each subregion. This study aimed to evaluate the repeatability and reproducibility of volume estimation using DLHBS and compare them with those of representative brain segmentation tools such as statistical parametric mapping (SPM) and FreeSurfer (FS). METHODS: Hierarchical segmentation using multiple deep learning models was employed to segment brain subregions within a clinically feasible processing time. The T1WI and brain mask pairs in 486 subjects were used as training data for training of the deep learning segmentation models. Training data were generated using a multi-atlas registration-based method. The high quality of training data was confirmed through visual evaluation and manual correction by neuroradiologists. The brain 3D-T1WI scan-rescan data of the 11 healthy subjects were obtained using three MRI scanners for evaluating the repeatability and reproducibility. The volumes of the eight ROIs-including gray matter, white matter, cerebrospinal fluid, hippocampus, orbital gyrus, cerebellum posterior lobe, putamen, and thalamus-obtained using DLHBS, SPM 12 with default settings, and FS with the "recon-all" pipeline. These volumes were then used for evaluation of repeatability and reproducibility. RESULTS: In the volume measurements, the bilateral thalamus showed higher repeatability with DLHBS compared with SPM. Furthermore, DLHBS demonstrated higher repeatability than FS in across all eight ROIs. Additionally, higher reproducibility was observed with DLHBS in both hemispheres of six ROIs when compared with SPM and in five ROIs compared with FS. The lower repeatability and reproducibility in DLHBS were not observed in any comparisons. CONCLUSION: Our results showed that the best performance in both repeatability and reproducibility was found in DLHBS compared with SPM and FS.

Preliminary protocol for measuring the reproducibility and accuracy of flow values on digital PET/CT systems in [15O]H2O myocardial perfusion imaging using a flow phantom.

BACKGROUND: Several factors may decrease the accuracy of quantitative PET myocardial perfusion imaging (MPI). It is therefore essential to ensure that myocardial blood flow (MBF) values are reproducible and accurate, and to design systematic protocols to achieve this. Until now, no systematic phantom protocols have been available to assess the technical factors affecting measurement accuracy and reproducibility in MPI. MATERIALS AND METHODS: We implemented a standard measurement protocol, which applies a flow phantom in order to compare image-derived flow values with respect to a ground truth flow value with [15O]H2O MPI performed on both a Discovery MI (DMI-20, GE Healthcare) and a Biograph Vision 600 (Vision-600, Siemens Healthineers) system. Both systems have automatic [15O]H2O radio water generators (Hidex Oy) individually installed, allowing us to also study the differences occurring due to two different bolus delivery systems. To investigate the technical factors contributing to the modelled flow values, we extracted the [15O]H2O bolus profiles, the flow values from the kinetic modeling (Qin and Qout), and finally calculated their differences between test-retest measurements on both systems. RESULTS: The measurements performed on the DMI-20 system produced Qin and Qout values corresponging to each other as well as to the reference flow value across all test-retest measurements. The repeatability differences on DMI-20 were 2.1% ± 2.6% and 3.3% ± 4.1% for Qin and Qout, respectively. On Vision-600 they were 10% ± 8.4% and 11% ± 10% for Qin and Qout, respectively. The measurements performed on the Vision-600 system showed more variation between Qin and Qout values across test-retest measurements and exceeded 15% difference in 7/24 of the measurements. CONCLUSIONS: A preliminary protocol for measuring the accuracy and reproducibility of flow values in [15O]H2O MPI between digital PET/CT systems was assessed. The test-retest reproducibility falls below 15% in majority of the measurements conducted between two individual injector systems and two digital PET/CT systems. This study highlights the importance of implementing a standardized bolus injection and delivery protocol and importance of assessing technical factors affecting flow value reproducibility, which should be carefully investigated in a multi-center setting.

Implementing ABCD studyⓇ MRI sequences for multi-site cohort studies: Practical guide to necessary steps, preprocessing methods, and challenges.

Large multi-site studies that combine magnetic resonance imaging (MRI) data across research sites present exceptional opportunities to advance neuroscience research. However, scanner or site variability and non-standardised image acquisition protocols, data processing and analysis pipelines can adversely affect the reliability and repeatability of MRI derived brain measures. We implemented a standardised MRI protocol based on that used in the Adolescent Brain Cognition Development (ABCD)Ⓡ study in two sites, and across four MRI scanners. Twice repeated measurements of a single healthy volunteer were obtained in two sites and in four 3T MRI scanners (vendors: Siemens, Philips, and GE). Imaging data included anatomical scans (T1 weighted, T2 weighted), diffusion weighted imaging (DWI) and resting state functional MRI (rs-fMRI). Standardised containerized pipelines were utilised to pre-process the data and different image quality metrics and test-retest variability of different brain metrics were evaluated. The implementation of the MRI protocols was possible with minor adjustments in acquisition (e.g. repetition time (TR), higher b-values) and exporting (DICOM formats) of images due to different technical performance of the scanners. This study provides practical insights into the implementation of standardised sequences and data processing for multisite studies, showcase the benefits of containerised preprocessing tools, and highlights the need for careful optimisation of multisite image acquisition.

Challenges and limitations in applying radiomics to PET imaging: Possible opportunities and avenues for research.

Radiomics, the high-throughput extraction of quantitative imaging features from medical images, holds immense potential for advancing precision medicine in oncology and beyond. While radiomics applied to positron emission tomography (PET) imaging offers unique insights into tumor biology and treatment response, it is imperative to elucidate the challenges and constraints inherent in this domain to facilitate their translation into clinical practice. This review examines the challenges and limitations of applying radiomics to PET imaging, synthesizing findings from the last five years (2019-2023) and highlights the significance of addressing these challenges to realize the full clinical potential of radiomics in oncology and molecular imaging. A comprehensive search was conducted across multiple electronic databases, including PubMed, Scopus, and Web of Science, using keywords relevant to radiomics issues in PET imaging. Only studies published in peer-reviewed journals were eligible for inclusion in this review. Although many studies have highlighted the potential of radiomics in predicting treatment response, assessing tumor heterogeneity, enabling risk stratification, and personalized therapy selection, various challenges regarding the practical implementation of the proposed models still need to be addressed. This review illustrates the challenges and limitations of radiomics in PET imaging across various cancer types, encompassing both phantom and clinical investigations. The analyzed studies highlight the importance of reproducible segmentation methods, standardized pre-processing and post-processing methodologies, and the need to create large multicenter studies registered in a centralized database to promote the continuous validation and clinical integration of radiomics into PET imaging.

A Systematic Online Living Evidence Summary of experimental Alzheimer's disease research.

BACKGROUND: Despite extensive investment, the development of effective treatments for Alzheimer's disease (AD) has been largely unsuccessful. To improve translation, it is crucial to ensure the quality and reproducibility of foundational evidence generated from laboratory models. Systematic reviews play a key role in providing an unbiased overview of the evidence, assessing rigor and reporting, and identifying factors that influence reproducibility. However, the sheer pace of evidence generation is prohibitive to evidence synthesis and assessment. NEW METHOD: To address these challenges, we have developed AD-SOLES, an integrated workflow of automated tools that collect, curate, and visualise the totality of evidence from in vivo experiments. RESULTS: AD-SOLES is a publicly accessible interactive dashboard aiming to surface and expose data from in vivo experiments. It summarises the latest evidence, tracks reporting quality and transparency, and allows research users to easily locate evidence relevant to their specific research question. COMPARISON WITH EXISTING METHODS: Using automated screening methodologies within AD-SOLES, systematic reviews can begin at an accelerated starting point compared to traditional approaches. Furthermore, through text-mining approaches within the full-text of publications, users can identify research of interest using specific models, outcomes, or interventions without relying on details in the title and/or abstract. CONCLUSIONS: By automating the collection, curation, and visualisation of evidence from in vivo experiments, AD-SOLES addresses the challenges posed by the rapid pace of evidence generation. AD-SOLES aims to offer guidance for research improvement, reduce research waste, highlight knowledge gaps, and support informed decisionmaking for researchers, funders, patients, and the public.

Comparison of the repeatability and reproducibility of corneal thickness mapping using optical coherence tomography according to tear film break-up time.

BACKGROUND: To compare the repeatability and reproducibility of corneal and corneal epithelial thickness mapping using anterior segment optical coherence tomography (AS-OCT) according to tear film break-up time (TBUT). METHODS: The included eyes were divided into three subgroups according to TBUT (group 1: TBUT ≤ 5 s, group 2: 5 s < TBUT ≤ 10 s, and group 3: TBUT > 10 s). All eyes were imaged separately thrice by two operators to obtain the thickness maps (TMs) of the cornea and corneal epithelium based on spatial zones encompassing a 9-mm-diameter area. Each TM consisted of 25 areas. Intraoperator (repeatability) and interoperator (reproducibility) standard deviations (Sws), coefficients of variation (CoVs), and intraclass correlation coefficients (ICCs) among the tests were calculated and compared in all the areas. RESULTS: Altogether, 132 eyes of 67 subjects were included (50, 47, and 35 eyes in groups 1, 2, and 3; respectively). The ICCs of corneal epithelial thickness and corneal thickness were > 0.75 in most of the areas. Pairwise comparisons showed that AS-OCT exhibited lower repeatability in group 1 than in groups 2 and 3 (P < 0.05). However groups 2 and 3 showed similar results. Sws and CoVs of corneal epithelial thickness exhibited no significant interoperator differences. While no significant differences were observed in corneal thickness in most of the areas. CONCLUSIONS: TBUT significantly influences the repeatability of corneal and corneal epithelial thickness measurements. Poor tear film stability requires careful evaluation of corneal epithelial thickness.

Sample size calculation for data reliability and diagnostic performance: a go-to review.

Sample size, namely the number of subjects that should be included in a study to reach the desired endpoint and statistical power, is a fundamental concept of scientific research. Indeed, sample size must be planned a priori, and tailored to the main endpoint of the study, to avoid including too many subjects, thus possibly exposing them to additional risks while also wasting time and resources, or too few subjects, failing to reach the desired purpose. We offer a simple, go-to review of methods for sample size calculation for studies concerning data reliability (repeatability/reproducibility) and diagnostic performance. For studies concerning data reliability, we considered Cohen's κ or intraclass correlation coefficient (ICC) for hypothesis testing, estimation of Cohen's κ or ICC, and Bland-Altman analyses. With regards to diagnostic performance, we considered accuracy or sensitivity/specificity versus reference standards, the comparison of diagnostic performances, and the comparisons of areas under the receiver operating characteristics curve. Finally, we considered the special cases of dropouts or retrospective case exclusions, multiple endpoints, lack of prior data estimates, and the selection of unusual thresholds for α and ß errors. For the most frequent cases, we provide example of software freely available on the Internet.Relevance statement Sample size calculation is a fundamental factor influencing the quality of studies on repeatability/reproducibility and diagnostic performance in radiology.Key points• Sample size is a concept related to precision and statistical power.• It has ethical implications, especially when patients are exposed to risks.• Sample size should always be calculated before starting a study.• This review offers simple, go-to methods for sample size calculations.

Interobserver variability in the histopathological evaluation of melanoma: analysis of 60 case reports.

INTRODUCTION: Since the field of dermatopathology is not an exact science, it is prone to personal subjectivity, which sometimes causes disagreements on the diagnosis and assessment of some histological features. In the case of melanoma, some variables such as regression are associated with low interobserver agreement. On the contrary, other variables such as the measurement of Breslow thickness show high reproducibility. OBJECTIVE: The main objective of our study was to investigate multiple features of 60 consecutive cases of melanoma to establish interobserver reproducibility. METHODS AND MAIN RESULTS: We conducted an observational and descriptive study at Hospital de Manises, Valencia, Spain, IVO Foundation, Valencia, Spain, and Hospital 12 de Octubre, Madrid, Spain. The mean level of agreement of all study variables was moderate (Cohen's kappa coefficient statistic = 0.5). The highest agreement corresponded to polypoid morphology, pigmentation, ulceration, and solar elastosis. On the other hand, the lowest level agreement was reached for the presence of cellular pleomorphism and tumor necrosis. CONCLUSIONS: Our mean level of agreement was moderate, which reflects that some of the measured characteristics such as cellular pleomorphism or the presence of necrosis cannot be used for future studies or must be redefined and their reproducibility, reestablished. When conducting a research study, it is necessary to analyze the study variables to demonstrate their validity to measure or classify a certain feature. It is also advisable to warrant that that the variables are reproducible to be able to use them for other studies or in the routine clinical practice.

Test-retest reliability and minimal detectable change of four functional tests in community-dwelling older adults with high risk of falls.

Objectives: This study aimed to quantify test-retest reliability and minimal detectable change (MDC) of the four commonly used functional tests in older adults with a high risk of falling. Patients and methods: The cross-sectional study was conducted with 30 community-dwelling older adults (26 females, 4 males; mean age: 73.7±6.0 years; range, 65 to 88 years) with a high fall risk identified by the Thai falls risk assessment test between November 2018 and May 2019. Data from the 10-m walk test at a comfortable gait speed (CGS) and fast gait speed (FGS), timed up and go (TUG) test, five times sit to stand test (FTSST), and 6-min walk test (6MWT) were collected twice for each participant. The interval between test sessions was one week. Test-retest reliability was analyzed by the intraclass correlation coefficient (ICC). Standard error of measurement (SEM) and MDC at the 95% confidence interval (MDC95) were also calculated. Results: The four functional tests had ICC in the range of 0.92 to 0.97. The SEM values of the CGS, FGS, TUG, FTSST, and 6MWT were 0.06 m/sec, 0.04 m/sec, 1.10 sec, 1.30 sec, and 20.60 m, respectively. The MDC95 values of the CGS, FGS, TUG, FTSST, and 6MWT were 0.16 m/sec, 0.12 m/sec, 3.00 sec, 3.50 sec, and 57.20 m, respectively. Conclusion: All functional tests demonstrated excellent test-retest reliability. The SEM and MDC95 of all functional tests were established. These findings can help clinicians interpret the effectiveness of interventions and determine changes in functional ability over time in older adults at high risk of falls.

Reproducible Research Practices in Magnetic Resonance Neuroimaging: A Review Informed by Advanced Language Models.

MRI has progressed significantly with the introduction of advanced computational methods and novel imaging techniques, but their wider adoption hinges on their reproducibility. This concise review synthesizes reproducible research insights from recent MRI articles to examine the current state of reproducibility in neuroimaging, highlighting key trends and challenges. It also provides a custom generative pretrained transformer (GPT) model, designed specifically for aiding in an automated analysis and synthesis of information pertaining to the reproducibility insights associated with the articles at the core of this review.

Comparison of gene set scoring methods for reproducible evaluation of tuberculosis gene signatures.

BACKGROUND: Blood-based transcriptional gene signatures for tuberculosis (TB) have been developed with potential use to diagnose disease. However, an unresolved issue is whether gene set enrichment analysis of the signature transcripts alone is sufficient for prediction and differentiation or whether it is necessary to use the original model created when the signature was derived. Intra-method comparison is complicated by the unavailability of original training data and missing details about the original trained model. To facilitate the utilization of these signatures in TB research, comparisons between gene set scoring methods cross-data validation of original model implementations are needed. METHODS: We compared the performance of 19 TB gene signatures across 24 transcriptomic datasets using both rrebuilt original models and gene set scoring methods. Existing gene set scoring methods, including ssGSEA, GSVA, PLAGE, Singscore, and Zscore, were used as alternative approaches to obtain the profile scores. The area under the ROC curve (AUC) value was computed to measure performance. Correlation analysis and Wilcoxon paired tests were used to compare the performance of enrichment methods with the original models. RESULTS: For many signatures, the predictions from gene set scoring methods were highly correlated and statistically equivalent to the results given by the original models. In some cases, PLAGE outperformed the original models when considering signatures' weighted mean AUC values and the AUC results within individual studies. CONCLUSION: Gene set enrichment scoring of existing gene sets can distinguish patients with active TB disease from other clinical conditions with equivalent or improved accuracy compared to the original methods and models. These data justify using gene set scoring methods of published TB gene signatures for predicting TB risk and treatment outcomes, especially when original models are difficult to apply or implement.

Framework for personalized prediction of treatment response in relapsing-remitting multiple sclerosis: a replication study in independent data.

BACKGROUND: Individualizing and optimizing treatment of relapsing-remitting multiple sclerosis patients is a challenging problem, which would benefit from a clinically valid decision support. Stühler et al. presented black box models for this aim which were developed and internally evaluated in a German registry but lacked external validation. METHODS: In patients from the French OFSEP registry, we independently built and validated models predicting being free of relapse and free of confirmed disability progression (CDP), following the methodological roadmap and predictors reported by Stühler. Hierarchical Bayesian models were fit to predict the outcomes under 6 disease-modifying treatments given the individual disease course up to the moment of treatment change. Data was temporally split on 2017, and models were developed in patients treated earlier (n = 5517). Calibration curves, discrimination, mean squared error (MSE) and relative percentage of root MSE (RMSE%) were assessed by external validation of models in more-recent patients (n = 3768). Non-Bayesian fixed-effects GLMs were also applied and their outcomes were compared to these of the Bayesian ones. For both, we modelled the number of on-therapy relapses with a negative binomial distribution, and CDP occurrence with a binomial distribution. RESULTS: The performance of our temporally-validated relapse model (MSE: 0.326, C-Index: 0.639) is potentially superior to that of Stühler's (MSE: 0.784, C-index: 0.608). Calibration plots revealed miscalibration. Our CDP model (MSE: 0.072, C-Index: 0.777) was also better than its counterpart (MSE: 0.131, C-index: 0.554). Results from non-Bayesian fixed-effects GLM models were similar to the Bayesian ones. CONCLUSIONS: The relapse and CDP models rebuilt and externally validated in independent data could compare and strengthen the credibility of the Stühler models. Their model-building strategy was replicable.

Searches as data: archiving and sharing search strategies using an institutional data repository.

Background: By defining search strategies and related database exports as code/scripts and data, librarians and information professionals can expand the mandate of research data management (RDM) infrastructure to include this work. This new initiative aimed to create a space in McGill University's institutional data repository for our librarians to deposit and share their search strategies for knowledge syntheses (KS). Case Presentation: The authors, a health sciences librarian and an RDM specialist, created a repository collection of librarian-authored knowledge synthesis (KS) searches in McGill University's Borealis Dataverse collection. We developed and hosted a half-day "Dataverse-a-thon" where we worked with a team of health sciences librarians to develop a standardized KS data management plan (DMP), search reporting documentation, Dataverse software training, and howto guidance for the repository. Conclusion: In addition to better documentation and tracking of KS searches at our institution, the KS Dataverse collection enables sharing of searches among colleagues with discoverable metadata fields for searching within deposited searches. While the initial creation of the DMP and documentation took about six hours, the subsequent deposit of search strategies into the institutional data repository requires minimal effort (e.g., 5-10 minutes on average per deposit). The Dataverse collection also empowers librarians to retain intellectual ownership over search strategies as valuable stand-alone research outputs and raise the visibility of their labor. Overall, institutional data repositories provide specific benefits in facilitating compliance both with PRISMA-S guidance and with RDM best practices.

BD SurePath Direct to Slide (DTS) cervical cytology: Migrating the benefits of liquid-based cytology to low-resource settings.

OBJECTIVES: The benefits of liquid-based cytology (LBC) in routine cervical cancer screening are often associated with the availability of instrumented platforms and economic considerations. A low-cost alternative to LBC in low-volume settings remains an unmet need. METHODS: A multisite evaluation of the BD SurePath (SurePath) LBC Direct to Slide (DTS) method was conducted. The DTS preparations were evaluated across 3 sites. Cytology features for DTS preparation included predetermined thresholds for total cellularity, cell distribution, cellular preservation, and stain quality. Rare event detection was evaluated using SiHa cells spiked into pools from negative cytology specimens. Concordance between Bethesda classification results was evaluated for SurePath LBC and DTS methods using routinely collected SurePath specimens in a split-sample study design. RESULTS: The DTS specimens met criteria for total cellularity, cell distribution, cellular preservation, and stain quality in more than 98% of all cases. Rare event detection was observed with an average detection of 5 SiHa cells per 2 mL of specimen. Concordant cervical cytology classifications were observed between SurePath LBC and DTS methods. CONCLUSIONS: The results demonstrate that the DTS process is suitable for routine cervical cytology evaluation. The procedure is reproducible and detected abnormal cervical cells in concordance with standard SurePath LBC preparation.

ExMove: An open-source toolkit for processing and exploring animal-tracking data in R.

Ongoing technological advances have led to a rapid increase in the number, type and scope of animal-tracking studies. In response, many software tools have been developed to analyse animal movement data. These tools generally focus on movement modelling, but the steps required to clean raw data files from different tracking devices have been largely ignored. Such pre-processing steps are often time-consuming and involve a steep learning curve but are crucial for the creation of high-quality, standardised and shareable data. Moreover, decisions made at this early stage can substantially influence subsequent analyses, and in the current age of reproducibility crisis, the transparency of this process is vital. Here we present an open-access, reproducible toolkit written in the programming language R for processing raw data files into a single cleaned data set for analyses and upload to online tracking databases (found here: https://github.com/ExMove/ExMove). The toolkit comprises well-documented and flexible code to facilitate data processing and user understanding, both of which can increase user confidence and improve the uptake of sharing open and reproducible code. Additionally, we provide an overview website (found here: https://exmove.github.io/) and a Shiny app to help users visualise tracking data and assist with parameter determination during data cleaning. The toolkit is generalisable to different data formats and device types, uses modern 'tidy coding' practices, and relies on a few well-maintained packages. Among these, we perform spatial manipulations using the package sf. Overall, by collating all required steps from data collection to archiving on open access databases into a single, robust pipeline, our toolkit provides a valuable resource for anyone conducting animal movement analyses and represents an important step towards increased standardisation and reproducibility in animal movement ecology.

Evaluation of somatic copy number variation detection by NGS technologies and bioinformatics tools on a hyper-diploid cancer genome.

BACKGROUND: Copy number variation (CNV) is a key genetic characteristic for cancer diagnostics and can be used as a biomarker for the selection of therapeutic treatments. Using data sets established in our previous study, we benchmark the performance of cancer CNV calling by six most recent and commonly used software tools on their detection accuracy, sensitivity, and reproducibility. In comparison to other orthogonal methods, such as microarray and Bionano, we also explore the consistency of CNV calling across different technologies on a challenging genome. RESULTS: While consistent results are observed for copy gain, loss, and loss of heterozygosity (LOH) calls across sequencing centers, CNV callers, and different technologies, variation of CNV calls are mostly affected by the determination of genome ploidy. Using consensus results from six CNV callers and confirmation from three orthogonal methods, we establish a high confident CNV call set for the reference cancer cell line (HCC1395). CONCLUSIONS: NGS technologies and current bioinformatics tools can offer reliable results for detection of copy gain, loss, and LOH. However, when working with a hyper-diploid genome, some software tools can call excessive copy gain or loss due to inaccurate assessment of genome ploidy. With performance matrices on various experimental conditions, this study raises awareness within the cancer research community for the selection of sequencing platforms, sample preparation, sequencing coverage, and the choice of CNV detection tools.

Individual variability and consistency of post-exercise energy and macronutrient intake, appetite sensations, and food reward in healthy adults.

Limited evidence is available about the variability of appetitive responses within individuals after an acute bout of exercise. The present study aimed to assess the consistency and individual variability of post-exercise appetitive responses in healthy individuals. Twenty participants (10 females, 23.9 ± 4.1 years, 22.5 ± 2.0 kg m-2) joined the laboratory to perform four sessions separated by a minimum of 5 days: i) a control session with a rest period before and an ad libitum lunch (REST), and ii) three identical exercise sessions (EX) with a 30-min moderate-intensity (60-70% of predicted maximal heart rate) walking bout ending 25 min before the ad libitum lunch. Subjective appetite sensations were assessed before and after the meal at regular intervals, and satiety quotients were calculated. Food reward was assessed by the Leeds Food Preference Questionnaire before and after lunch. For each EX session, the difference with the REST session was calculated (Δ = EX - REST). Energy and macronutrient intake were consistent in response to exercise (all intraclass correlation coefficients (ICC) > 0.8) while results showed that post-exercise subjective appetite sensations and satiety quotients varied across the three EX sessions (almost all ICC < 0.7). Food reward was overall consistent in response to exercise before the test meal but not after. When considering the changes (Δ), the results showed no or poor consistency for most of the appetitive outcomes. To conclude, energy and macronutrient intake, as well as pre-meal food reward, are consistent after exercise in healthy individuals, while subjective appetite sensations are not stable within individuals across the sessions. Regarding the variations from REST to EX sessions, the results suggest that the individual changes observed are only random day-to-day variations.

Clinically relevant estimation of minimal number of trials for the uncontrolled manifold analysis.

Movement biomarkers are crucial for assessing sensorimotor impairments and tracking the effects of interventions over time. The Uncontrolled Manifold (UCM) analysis has been proposed as a novel biomarker for evaluating movement stability and coordination in various motor tasks across neurological and musculoskeletal disorders. Through inter-trial analysis, the UCM partitions the variance of elemental variables (e.g., finger forces) into components that affect (VORT) and do not affect (VUCM) a performance variable (e.g., total force). A third index, ΔV, is computed as the normalized difference between VORT and VUCM. However, the minimum number of trials required to achieve stable UCM estimates, considering its clinimetric properties, is unknown. This study aimed to determine the minimal number (N) of trials for UCM estimates by computing bootstrap estimates of standard errors (SE) at different N trials using thresholds based on the minimal detectable change (MDC, i.e., the minimum change in an outcome measure beyond measurement error). Thirteen adults (24.6 ± 1.1 years old) performed a finger-pressing coordination task. We computed the 95 % confidence intervals (CI) of bootstrap SE distributions for each UCM estimate and detected the lowest number of trials with the 95 % CI of SE below each MDC threshold. We found the minimal N of trials required was VUCM = 14, VORT = 4 and ΔV = 18. Our findings highlight that a relatively low number of trials (i.e., N = 18) are sufficient to compute all UCM estimates beyond the MDC, supporting the use of the UCM framework in clinical settings where many repetitions of a motor task are not practical.

Evaluation of the Allplex HPV assay's adherence to international guidelines for cervical cancer screening in clinician-collected samples.

Clinically validated human papillomavirus (HPV) assays are crucial in cervical cancer screening. In this study, we evaluated the Allplex HPV HR Detection assay (Seegene, SouthKorea) for its clinical accuracy and reproducibility according to the international criteria, using the RealTime High Risk HPV m2000 assay (Abbott, USA) as standard comparator. The Allplex HPV HR assay exhibits significant non-inferior sensitivity to detect cervical intraepithelial neoplasia grade (CIN) 2 or worse (CIN2+) with a ratio of 1.00 (95% CI: 0.97-1.03, P = 0.006), insignificant non-inferior sensitivity to detect CIN3+ with a ratio of 1.00 (95% CI: 0.88-1.13, P = 0.098), and non-inferior specificity to exclude CIN2+ with a ratio of 0.99 (95% CI: 0.99-1.00, P < 0.001) compared to the standard comparator. In addition, the assay shows an excellent reproducibility within the same laboratory [96.5% (95% CI: 94.6-97.9) with a kappa value of 0.91 (95% CI: 0.87-0.95)] and between laboratories [96.7% (95% CI: 94.8-98.0) with a kappa value of 0.91 (95% CI: 0.87-0.95)] for overall high-risk HPV positivity as well as for each individual HPV type. Pooling our study data with those of another independent study supports the consistency of our findings. We conclude that both the clinical accuracy to detect cervical precancer and the reproducibility of Allplex HPV HR Detection assay fulfill the international validation criteria of use in cervical cancer screening.IMPORTANCEThe clinical validation of human papillomavirus (HPV) assays in accordance with well-established international guidelines is crucial to ensure that only validated assays are used in the context of screening (Meijer et al., Int J Cancer, 2009). The guidelines, developed by an international consortium, require that a novel HPV assay has non-inferior accuracy against a standard comparator test for the detection of cervical intraepithelial neoplasia grade (CIN) 2 or worse (CIN2+). Additionally, a new HPV assay should meet specific criteria for both intra- and inter-laboratory reproducibility to ensure the assay consistently exhibits technical precision and robust performance. Pooling our study data with those of another independent study supports the consistency of our findings. In conclusion, both the clinical accuracy to detect cervical precancer and the reproducibility of Allplex HPV HR Detection assay fulfill the international validation criteria of use in cervical cancer screening.