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The tutelage of our mentors as scientists included the analogy that writing a good scientific paper was an exercise in storytelling that omitted unessential details that did not move the story forward or that detracted from the overall message. However, the advice to not get lost in the details had an important flaw. In science, it is the many details of the data themselves and the methods used to generate and analyze them that give conclusions their probative meaning. Facts may sometimes slow or distract from the clarity, tidiness, intrigue, or flow of the narrative, but nevertheless they are important for the assessment of what was done, the trustworthiness of the science, and the meaning of the findings. Nevertheless, many critical elements and facts about research studies may be omitted from the narrative and become hidden from scholarly scrutiny. We describe a bakers dozen shortfalls in which such elements that are pertinent to evaluating the validity of scientific studies are sometimes hidden in reports of the work. Such shortfalls may be intentional or unintentional or lie somewhere in between. Additionally, shortfalls may occur at the level of the individual or an institution or of the entire system itself. We conclude by proposing countermeasures to these shortfalls.

Antibodies are used in many areas of biomedical and clinical research, but many of these antibodies have not been adequately characterized, which casts doubt on the results reported in many scientific papers. This problem is compounded by a lack of suitable control experiments in many studies. In this article we review the history of the antibody characterization crisis, and we document efforts and initiatives to address the problem, notably for antibodies that target human proteins. We also present recommendations for a range of stakeholders - researchers, universities, journals, antibody vendors and repositories, scientific societies and funders - to increase the reproducibility of studies that rely on antibodies.

AimsAccurate cardiac chamber quantification is essential for clinical decisions and ideally should be consistent across different echocardiography systems. This study evaluates variations between the Philips EPIQ CVx (version 9.0.3) and Canon Aplio i900 (version 7.0) in measuring cardiac volumes, ventricular function, and valve structures.Methods and resultsIn this gender-balanced, single-centre study, 40 healthy volunteers (20 females and 20 males) aged 40 years and older (mean age 56.75 ± 11.57 years) were scanned alternately with both systems by the same sonographer using identical settings for both 2D and 4D acquisitions. We compared left ventricular (LV) and right ventricular (RV) volumes using paired t-tests, with significance set at P < 0.05. Correlation and Bland-Altman plots were used for quantities showing significant differences. Two board-certified cardiologists evaluated valve anatomy for each platform. The results showed no significant differences in LV end-systolic volume and LV ejection fraction between platforms. However, LV end-diastolic volume (LVEDV) differed significantly (biplane: P = 0.018; 4D: P = 0.028). Right ventricular (RV) measurements in 4D showed no significant differences, but there were notable disparities in 2D and 4D volumes within each platform (P < 0.01). Significant differences were also found in the LV systolic dyssynchrony index (P = 0.03), LV longitudinal strain (P = 0.04), LV twist (P = 0.004), and LV torsion (P = 0.005). Valve structure assessments varied, with more abnormalities noted on the Philips platform.ConclusionAlthough LV and RV volumetric measurements are generally comparable, significant differences in LVEDV, LV strain metrics, and 2D vs. 4D measurements exist. These variations should be considered when using different platforms for patient follow-ups.

BACKGROUND: Amyloidosis, a rare multisystem condition, often requires complex, multidisciplinary care. Its low prevalence underscores the importance of efforts to ensure the availability of high-quality patient education materials for better outcomes. ChatGPT (OpenAI) is a large language model powered by artificial intelligence that offers a potential avenue for disseminating accurate, reliable, and accessible educational resources for both patients and providers. Its user-friendly interface, engaging conversational responses, and the capability for users to ask follow-up questions make it a promising future tool in delivering accurate and tailored information to patients. OBJECTIVE: We performed a multidisciplinary assessment of the accuracy, reproducibility, and readability of ChatGPT in answering questions related to amyloidosis. METHODS: In total, 98 amyloidosis questions related to cardiology, gastroenterology, and neurology were curated from medical societies, institutions, and amyloidosis Facebook support groups and inputted into ChatGPT-3.5 and ChatGPT-4. Cardiology- and gastroenterology-related responses were independently graded by a board-certified cardiologist and gastroenterologist, respectively, who specialize in amyloidosis. These 2 reviewers (RG and DCK) also graded general questions for which disagreements were resolved with discussion. Neurology-related responses were graded by a board-certified neurologist (AAH) who specializes in amyloidosis. Reviewers used the following grading scale: (1) comprehensive, (2) correct but inadequate, (3) some correct and some incorrect, and (4) completely incorrect. Questions were stratified by categories for further analysis. Reproducibility was assessed by inputting each question twice into each model. The readability of ChatGPT-4 responses was also evaluated using the Textstat library in Python (Python Software Foundation) and the Textstat readability package in R software (R Foundation for Statistical Computing). RESULTS: ChatGPT-4 (n=98) provided 93 (95%) responses with accurate information, and 82 (84%) were comprehensive. ChatGPT-3.5 (n=83) provided 74 (89%) responses with accurate information, and 66 (79%) were comprehensive. When examined by question category, ChatGTP-4 and ChatGPT-3.5 provided 53 (95%) and 48 (86%) comprehensive responses, respectively, to general questions (n=56). When examined by subject, ChatGPT-4 and ChatGPT-3.5 performed best in response to cardiology questions (n=12) with both models producing 10 (83%) comprehensive responses. For gastroenterology (n=15), ChatGPT-4 received comprehensive grades for 9 (60%) responses, and ChatGPT-3.5 provided 8 (53%) responses. Overall, 96 of 98 (98%) responses for ChatGPT-4 and 73 of 83 (88%) for ChatGPT-3.5 were reproducible. The readability of ChatGPT-4s responses ranged from 10th to beyond graduate US grade levels with an average of 15.5 (SD 1.9). CONCLUSIONS: Large language models are a promising tool for accurate and reliable health information for patients living with amyloidosis. However, ChatGPTs responses exceeded the American Medical Associations recommended fifth- to sixth-grade reading level. Future studies focusing on improving response accuracy and readability are warranted. Prior to widespread implementation, the technologys limitations and ethical implications must be further explored to ensure patient safety and equitable implementation.

Metal halide perovskite solar cells (PSCs) are infamous for their batch-to-batch and lab-to-lab irreproducibility in terms of stability and performance. Reproducible fabrication of PSCs is a critical requirement for market viability and practical commercialization. PSC irreproducibility plagues all levels of the community; from institutional research laboratories, start-up companies, to large established corporations. In this work, the critical function of atmospheric humidity to regulate the crystallization and stabilization of formamidinium lead triiodide (FAPbI3) perovskites is unraveled. It is demonstrated that the humidity content during processing induces profound variations in perovskite stoichiometry, thermodynamic stability, and optoelectronic quality. Almost counterintuitively, it is shown that the presence of humidity is perhaps indispensable to reproduce phase-stable and efficient FAPbI3-based PSCs.

Resting state functional magnetic resonance imaging (rsfMRI) provides researchers and clinicians with a powerful tool to examine functional connectivity across large-scale brain networks, with ever-increasing applications to the study of neurological disorders, such as traumatic brain injury (TBI). While rsfMRI holds unparalleled promise in systems neurosciences, its acquisition and analytical methodology across research groups is variable, resulting in a literature that is challenging to integrate and interpret. The focus of this narrative review is to address the primary methodological issues including investigator decision points in the application of rsfMRI to study the consequences of TBI. As part of the ENIGMA Brain Injury working group, we have collaborated to identify a minimum set of recommendations that are designed to produce results that are reliable, harmonizable, and reproducible for the TBI imaging research community. Part one of this review provides the results of a literature search of current rsfMRI studies of TBI, highlighting key design considerations and data processing pipelines. Part two outlines seven data acquisition, processing, and analysis recommendations with the goal of maximizing study reliability and between-site comparability, while preserving investigator autonomy. Part three summarizes new directions and opportunities for future rsfMRI studies in TBI patients. The goal is to galvanize the TBI community to gain consensus for a set of rigorous and reproducible methods, and to increase analytical transparency and data sharing to address the reproducibility crisis in the field.

Most neuroimaging studies linking regional brain volumes with cognition correct for total intracranial volume (ICV), but methods used for this correction differ across studies. It is unknown whether different ICV correction methods yield consistent results. Using a brain-wide association approach in the MRI substudy of UK Biobank (N = 41,964; mean age = 64.5 years), we used regression models to estimate the associations of 58 regional brain volumetric measures with eight cognitive outcomes, comparing no correction and four ICV correction approaches. Approaches evaluated included: no correction; dividing regional volumes by ICV (proportional approach); including ICV as a covariate in the regression (adjustment approach); and regressing the regional volumes against ICV in different normative samples and using calculated residuals to determine associations (residual approach). We used Spearman-rank correlations and two consistency measures to quantify the extent to which associations were inconsistent across ICV correction approaches for each possible brain region and cognitive outcome pair across 2320 regression models. When the association between brain volume and cognitive performance was close to null, all approaches produced similar estimates close to the null. When associations between a regional volume and cognitive test were not null, the adjustment and residual approaches typically produced similar estimates, but these estimates were inconsistent with results from the crude and proportional approaches. For example, when using the crude approach, an increase of 0.114 (95% confidence interval [CI]: 0.103-0.125) in fluid intelligence was associated with each unit increase in hippocampal volume. However, when using the adjustment approach, the increase was 0.055 (95% CI: 0.043-0.068), while the proportional approach showed a decrease of -0.025 (95% CI: -0.035 to -0.014). Different commonly used methods to correct for ICV yielded inconsistent results. The proportional method diverges notably from other methods and results were sometimes biologically implausible. A simple regression adjustment for ICV produced biologically plausible associations.

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its Minimal Information for Studies of Extracellular Vesicles, which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly.

This article reviews and summarizes current reproduction and replication practices in political science. We first provide definitions for reproducibility and replicability. We then review data availability policies for 28 leading political science journals and present the results from a survey of editors about their willingness to publish comments and replications. We discuss new initiatives that seek to promote and generate high-quality reproductions and replications. Finally, we make the case for standards and practices that may help increase data availability, reproducibility, and replicability in political science.

The biomedical sciences must maintain and enhance a research culture that prioritizes rigour and transparency. The US National Institute of Neurological Disorders and Stroke convened a workshop entitled Catalyzing Communities of Research Rigor Champions that brought together a diverse group of leaders in promoting research rigour and transparency (identified as rigour champions) to discuss strategies, barriers and resources for catalyzing technical, cultural and educational changes in the biomedical sciences. This article summarizes 2 days of panels and discussions and provides an overview of critical barriers to research rigour, perspectives behind reform initiatives and considerations for stakeholders across science. Additionally, we describe applications of network science to foster, maintain and expand cultural changes related to scientific rigour and opportunities to embed rigourous practices into didactic courses, training experiences and degree programme requirements. We hope this piece provides a primer for the wider research community on current discussions and actions and inspires individuals to build, join or expand collaborative networks within their own institutions that prioritize rigourous research practices.

In this study, LiNaCO3‐ and (Li‐Na‐K)2CO3‐based porous carbon composites were synthesized from terephthalic acid, lithium hydroxide, sodium hydroxide, and potassium hydroxide at different calcination temperatures. These composite materials were characterized with X‐Ray diffraction, scanning electron microscopy, and nitrogen adsorption and desorption. According to their CO2 capture performance measured, LiNaC‐700 °C had the largest CO2 adsorption capacity of 66 mg CO2 g−1, while the CO2 capture capacity of other materials doped with three metal ions was only up to 8.57 mg CO2 g−1. Additionally, the CO2 adsorption capacity of each adsorbent was significantly higher than the N2 adsorption capacity, showing their high CO2 adsorption selectivity. Lithium‐containing carbonate‐based porous carbon materials (LiNaCO3‐ and (Li‐Na‐K)2CO3‐based porous carbon could effectively capture CO2 with excellent reproducibility. [ABSTRACT FROM AUTHOR]

Accurate detection is a prerequisite for effective prevention and control of Mycoplasma synoviae infection. ELISA is the most popular method for the clinical detection of M. synoviae because of its convenience, low cost, and high detection rate. However, the cross-reactivity of commercially available ELISA kits with other avian pathogen-positive sera needs to be addressed. The aim of this study was to establish an ELISA method with high specificity for the detection of anti- M. synoviae antibodies in chicken serum to evaluate the M. synoviae infection status on poultry farms. The recombinant MS087 (rMS087) protein was expressed in Escherichia coli BL21 (DE3) and purified by Ni2+ affinity chromatography. An antibody against rMS087 was generated by immunizing BALB/c mice. Bioinformatic analysis revealed that MS087 was conserved among M. synoviae strains. Western blotting and indirect immunofluorescence results indicated that MS087 was not only localized in the cytoplasm and on the membrane but also secreted by the organism. For the established ELISA method based on rMS087, the optimal antigen concentration, blocking buffer, blocking duration, serum dilution, serum incubation duration, secondary antibody dilution, secondary antibody incubation duration and colorimetric reaction duration were 2 μg/mL, 1% BSA, 3 h, 1:500, 1.5 h, 1:20,000, 2 h and 5 min, respectively. Validation of the rMS087-based ELISA revealed a cut-off value of 0.5. The coefficients of variation of both the intra-batch and inter-batch methods were less than 9%. The assay was able to differentiate positive serum against M. synoviae from antisera against nine other avian pathogens and was able to recognize M. synoviae -positive sera at a dilution of 1:1,000. Compared with the commercial ELISA method, the rMS087-based ELISA has the potential to recognize more positive sera against M. synoviae. Collectively, the rMS087-based ELISA is a reproducible, specific, and sensitive serological method for detecting antibodies against M. synoviae in chicken serum and has robust potential for large-scale serological epidemiology of M. synoviae infection on poultry farms. [ABSTRACT FROM AUTHOR]

This study introduces an agent‐based model (ABM) pedestrian simulation tool to assess the risk of close contact (6 feet) in dynamic indoor environments, specifically in urban settings with diverse social activities and spatial structures. Our approach uses machine learning‐based sensitivity analysis (SA) to identify factors impacting the number of individual contacts, such as individual stay time and area. In addition, we conducted an in‐depth quantitative analysis to evaluate how specific factors, such as the strategic placement of obstacles, dwell time, and stay time near the entrances, mitigate the number of contacts. This analysis provides valuable insights for developing practical guidelines to curb contact risks in indoor environments. Lastly, we share the model, validation methods, and associated data as an open‐source Python library, complete with comprehensive documentation. This aims at fostering collaborative research and enables the application of our model across various scenarios, contributing to the development of spatially explicit models. Such efforts enhance the understanding of contact risks in urban indoor settings and promote joint research efforts, thus advancing the field through shared knowledge and tools. [ABSTRACT FROM AUTHOR]

Electrosynthetic reactions are performed in either custom‐made reactors that are developed and machined in‐house or commercially available systems that offer good reproducibility but come at a high cost. To bridge this divide between customizability and reproducibility, we have developed the Open‐ESyn, which is a suite of 3D‐printed components compatible with the popular ElectraSyn. This collection of parts increases the electrosynthesis that can be performed with the ElectraSyn, expanding, for example, the scale, temperature and the type of electrodes that can be used. The standardized reactor environment can be inexpensively recreated, thereby maintaining the reproducibility of the ElectraSyn ecosystem. [ABSTRACT FROM AUTHOR]

In the past decade, various recommendations have been published to enhance the methodological rigor and publication standards in psychological science. However, adhering to these recommendations may have limited impact on the reproducibility of causal effects as long as psychological phenomena continue to be viewed as decomposable into separate and additive statistical structures of causal relationships. In this article, we show that (a) psychological phenomena are patterns emerging from nondecomposable and nonisolable complex processes that obey idiosyncratic nonlinear dynamics, (b) these processual features jeopardize the chances of standard reproducibility of statistical results, and (c) these features call on researchers to reconsider what can and should be reproduced, that is, the psychological processes per se, and the signatures of their complexity and dynamics. Accordingly, we argue for a greater consideration of process causality of psychological phenomena reflected by key properties of complex dynamical systems (CDSs). This implies developing and testing formal models of psychological dynamics, which can be implemented by computer simulation. The scope of the CDS paradigm and its convergences with other paradigms are discussed regarding the reproducibility issue. Ironically, the CDS approach could account for both reproducibility and nonreproducibility of the statistical effects usually sought in mainstream psychological science. [ABSTRACT FROM AUTHOR]

Real-world evidence (RWE) studies are increasingly used to inform policy and clinical decisions. However, there remain concerns about the credibility and reproducibility of RWE studies. While there is universal agreement on the critical importance of transparent and reproducible science, the building blocks of open science practice that are common across many disciplines have not yet been built into routine workflows for pharmacoepidemiology and outcomes researchers. Observational researchers should highlight the level of transparency of their studies by providing a succinct statement addressing study transparency with the publication of every paper, poster, or presentation that reports on an RWE study. In this paper, we propose a framework for an explicit transparency statement that declares the level of transparency a given RWE study has achieved across 5 key domains: (1) protocol, (2) preregistration, (3) data, (4) code-sharing, and (5) reporting checklists. The transparency statement outlined in the present paper can be used by research teams to proudly display the open science practices that were used to generate evidence designed to inform public health policy and practice. While transparency does not guarantee validity, such a statement signals confidence from the research team in the scientific choices that were made. [ABSTRACT FROM AUTHOR]

Purpose: To assess and compare intrareader and interreader reproducibility of magnetic resonance imaging (MRI) diagnosis of female genital anomalies (FGAs) using the American Society for Reproductive Medicine-Mullerian anomalies classification 2021 (ASRM-MAC 2021) and European Society of Human Reproduction and Embryology-European Society for Gynecological Endoscopy (ESHRE-ESGE) 2016 classification. Methods: In this retrospective study, we searched our electronic MRI database from April 2021 to September 2023, selecting MRI studies with FGAs. Seventy-six consecutive studies were included and reviewed by 4 independent radiologists using both classifications. Studies were re-evaluated after 1 month. Reproducibility was assessed using kappa (κ) scores with 95% confidence intervals (CI). Results: Intrareader agreement for MRI diagnosis of FGAs was substantial to excellent, with κ scores ranging from 0.684 (95% CI, 0.534-0.834) to 0.985 (95% CI, 0.963-1.01) using the ASRM-MAC 2021 and from 0.743 (95% CI, 0.621-0.865) to 0.846 (95% CI, 0.719-0.973) using the ESHRE-ESGE 2016 classification. Pairwise interreader agreement was higher with the ASRM-MAC 2021, ranging from moderate (κ = 0.491; 95% CI, 0.341-0.642) to substantial (κ = 0.709; 95% CI, 0.597-0.821), compared to the ESHRE-ESGE 2016 classification, with weak (κ = 0.080; 95% CI, 0.068-0.228) to moderate (κ = 0.511; 95% CI, 0.344-0.678) agreement. Overall interreader agreement was moderate for both classifications (κ = 0.599; 95% CI, 0.562-0.638 for ASRM-MAC 2021 and κ = 0.429; 95% CI, 0.396-0.463 for ESHRE-ESGE 2016 classification), but with significant differences (non-overlapping CIs). Conclusion: The intrareader reproducibility was high for both classifications, whereas the interreader reproducibility was higher using the ASRM-MAC 2021, highlighting the impact of classification criteria on the reproducibility of MRI diagnosis of FGAs. [ABSTRACT FROM AUTHOR]

Defining the required trackability level of the target condition for the testing facility reconditioning unit represents an unresolved challenge in improving the reproducibility of load-based tests and corresponding performance rating standards development. To enhance the reproducibility of such testing methodology, this paper presents and discusses a new feed-forward compensation technique based on the development of a transfer function model for the delay and offset characteristics of the psychrometric room's air temperature and humidity modulations with reference to the target signal from the room emulator. It is demonstrated that the proposed methodology enables offset and delay reduction in the trackability of the return air condition within 60 s at different testing conditions, enhances the reproducibility of the test results to limit performance deviations to within 2 %, and achieves closely matched controlled parameter modulations during load-based tests. [ABSTRACT FROM AUTHOR]

Coronary computed tomography angiography (CCTA) enables detailed quantification and characterization of coronary atherosclerotic plaques, offering diagnostic and prognostic value. Interscan reproducibility studies on plaque volume measurements are limited. This study aims to assess the interscan reproducibility of coronary plaque quantification and the implications of clinical and technical characteristics on interscan reproducibility. CCTA was performed twice in 101 patients with known coronary artery disease at a 1-h interval. The scans were conducted using identical CCTA acquisition protocols. Coronary plaque volumes were quantified using a semi-automated software and performed on a per-lesion, per-vessel, and per-patient level. Median plaque volumes were comparable between the first and second CCTA scan. Interscan correlation was high for total plaque (TP), non-calcified plaque (NCP), and calcified plaque (CP) across all analyses (Pearson's coefficient 0.93–0.99), but lower for low-density non-calcified plaque (LD-NCP) volume measurements (Pearson's coefficient 0.74–0.77). Bland-Altman analyses demonstrated higher interscan agreement on a per-patient level compared to on per-vessel and per-lesion level. Interscan reproducibility on CP volumes was affected by CT image quality with narrower LoA in scans with the highest image quality score (p ​= ​0.003), or lowest image reconstructive iteration level (p ​< ​0.001). Limits of agreement were significantly narrower for TP, NCP, and CP volumes in LAD-lesions and vessels compared to non-LAD lesions and vessels (p ​≤ ​0.001). Overall reproducibility of repeated CCTA derived plaque measurements by a semi-automated software was modest, and was influenced by image quality, image reconstruction settings, and lesion location. [ABSTRACT FROM AUTHOR]

Machine learning techniques for causal effect estimation can enhance the reliability of epidemiologic analyses, reducing their dependence on correct model specifications. However, the stochastic nature of many machine learning algorithms implies that the results derived from such approaches may be influenced by the random seed that is set before model fitting. In this work, we highlight the substantial influence of random seeds on a popular approach for machine learning-based causal effect estimation, namely doubly robust estimators. We illustrate that varying seeds can yield divergent scientific interpretations of doubly robust estimates produced from the same dataset. We propose techniques for stabilizing results across random seeds and, through an extensive simulation study, demonstrate that these techniques effectively neutralize seed-related variability without compromising the statistical efficiency of the estimators. Based on these findings, we offer practical guidelines to minimize the influence of random seeds in real-world applications, and we encourage researchers to explore the variability due to random seeds when implementing any method that involves random steps. [ABSTRACT FROM AUTHOR]

To demonstrate how post-publication peer reviews—using journal article reporting standards—could improve the design and write-up of kinesiology research, the authors performed a post-publication peer review on one systematic literature review published in 2020. Two raters (1st & 2nd authors) critically appraised the case article between April and May 2021. The latest Journal Article Reporting Standards by the American Psychological Association relevant to the review were used: i.e., Table 1 (quantitative research standards) and Table 9 (research synthesis standards). A standard fully met was deemed satisfactory. Per Krippendorff’s alpha-coefficient, inter-rater agreement was moderate for Table 1 (k-alpha = .57, raw-agreement = 72.2%) and poor for Table 9 (k-alpha = .09, raw-agreement = 53.6%). A 100% consensus was reached on all discrepancies. Results suggest the case article’s Abstract, Methods, and Discussion sections required clarification or more detail. Per Table 9 standards, four sections were largely incomplete: i.e., Abstract (100%- incomplete), Introduction (66%-incomplete), Methods (75%-incomplete), and Discussion (66%-incomplete). Case article strengths included tabular summary of studies analyzed in the systematic review and a cautionary comment about the review’s generalizability. The article’s write-up gave detail to help the reader understand the scope of the study and decisions made by the authors. However, adequate detail was not provided to assess the credibility of all claims made in the article. This could affect readers’ ability to obtain critical and nuanced understanding of the article’s topics. The results of this critique should encourage (continuing) education on journal article reporting standards for diverse stakeholders (e.g., authors, reviewers). [ABSTRACT FROM AUTHOR]

Objective: To assess the reproducibility of six ultrasound (US)‐determined shear wave (SW) viscoelastography parameters for assessment of mechanical properties of the liver in volunteers and patients with biopsy‐proven metabolic dysfunction‐associated steatotic liver disease (MASLD) or metabolic dysfunction‐associated steatohepatitis (MASH). Methods: This prospective, cross‐sectional, institutional review board‐approved study included 10 volunteers and 20 patients with MASLD or MASH who underwent liver US elastography twice, at least 2 weeks apart. SW speed (SWS), Young's modulus (E), shear modulus (G), SW attenuation (SWA), SW dispersion (SWD), and viscosity were computed from radiofrequency data recorded on a research US scanner. Linear mixed models were used to consider the sonographer on duty as a confounder. The reproducibility of measurements was assessed by intraclass correlation coefficient (ICC), coefficient of variation (CV), reproducibility coefficient (RDC), and Bland‐Altman analyses. Results: The sonographer performing the exam had no impact on viscoelastic parameters (P >.05). ICCs of SWS, E, G, SWA, SWD, and viscosity were, respectively, 0.89 (95% confidence intervals [CI]: 0.79‐0.95), 0.81 (95% CI: 0.79‐0.95), 0.90 (95% CI: 0.80‐0.95), 0.96 (95% CI: 0.93‐0.98), 0.78 (95% CI: 0.60‐0.89), and 0.90 (95% CI: 0.80‐0.95); CVs were 11.9, 23.3, 24.2, 10.1, 29.0, and 32.2%; RDCs were 33.0, 64.5, 66.9, 27.7, 80.3, and 89.2%, and Bland‐Altman mean biases and 95% limits of agreement were −0.05 (−0.45, 0.35) m/s, −0.61 (−5.33, 4.10) kPa, −0.25 (−2.06, 1.56) kPa, −0.01 (−0.27, 0.26) Np/m/Hz, −0.09 (−7.09, 6.91) m/s/kHz, and −0.33 (−2.60, 1.94) Pa/s, between the two visits. Conclusion: US‐determined viscoelastography parameters can be measured with high reproducibility and consistency between two visits 2 weeks apart on the same ultrasound machine. [ABSTRACT FROM AUTHOR]

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Respondent-driven sampling (RDS) is widely used to sample populations with higher risk of HIV infection for whom no sampling frames exist. However, few studies have been done to assess the consistency of RDS estimators in real world settings. We conducted an assessment study on the consistency of RDS estimators using data from the National HIV Behavioral Surveillance – People Who Inject Drugs surveys in Newark, New Jersey from 2005 to 2018. Population parameter estimates based on RDS-I, RDS-II, Gile's SS, and HCG were compared longitudinally and cross-sectionally. Population homophily statistics and differential recruitment statistics were estimated and compared. Convergence plots were used for RDS diagnosis. Sensitivity analyses were conducted on population size estimates and seeds biases. By comparing time-insensitive population parameters and population homophily statistics estimated by four RDS estimators, the study found that RDS-II and Gile's SS could provide longitudinally and cross-sectionally consistent estimates and population homophily statistics on gender and sexual orientation. Cross-sectional comparison of time-sensitive population parameter estimates also supported the consistency of RDS-II and Gile's SS. However, RDS-I and HCG did not perform well in those comparisons. In conclusion, RDS estimators may not address all inconsistencies, but RDS-II and Gile's SS are recommended to weight RDS samples given enough consistency was observed in them. [ABSTRACT FROM AUTHOR]

Scientists typically run experiments many times to find general patterns over multiple specific runs. The results of those runs vary, and the variance is often simply referred to as “noise”. We claim that it is highly important to separate the components that contribute to noise and to recognize to which degree they contribute to it. Consideration of the relative contributions of R (randomness), U (uncontrolled variables), and M (measurement error) helps to interpret data and can help to improve experimental designs. We explain this using a hypothetical example and point out that assumptions of what causes variability in the results of experiments are often made implicitly. Further, we demonstrate our point by showing how it can change the interpretation of real data. Because of a lack of explicit discussion of underlying assumptions, it is possible that sources of noise are misidentified to be either existent or non-existent. This can happen if, for example, measurement error is assumed when there is none, an assumption that would mask a real effect that could deserve further study. Despite these factors, the contribution of different factors to the overall noise is rarely considered, hampering scientific progress. [ABSTRACT FROM AUTHOR]

The editorial published in Frontiers in Cellular Neuroscience on October 17, 2024, focuses on revisiting mouse models of traumatic brain injuries, specifically looking at intracellular mechanisms. The article discusses the importance of mouse models in TBI research due to limitations in human clinical studies. It highlights the relevance and shortcomings of existing TBI mouse models and investigates dysregulated intracellular mechanisms in the injured brain. The research aims to improve understanding and potential treatments for TBI, emphasizing the need for further studies on translational outcomes. [Extracted from the article]

Introduction: Machine Learning (ML) has emerged as a promising approach in healthcare, outperforming traditional statistical techniques. However, to establish ML as a reliable tool in clinical practice, adherence to best practices in data handling, and modeling design and assessment is crucial. In this work, we summarize and strictly adhere to such practices to ensure reproducible and reliable ML. Specifically, we focus on Alzheimer's Disease (AD) detection, a challenging problem in healthcare. Additionally, we investigate the impact of modeling choices, including different data augmentation techniques and model complexity, on overall performance. Methods: We utilize Magnetic Resonance Imaging (MRI) data from the ADNI corpus to address a binary classification problem using 3D Convolutional Neural Networks (CNNs). Data processing and modeling are specifically tailored to address data scarcity and minimize computational overhead. Within this framework, we train 15 predictive models, considering three different data augmentation strategies and five distinct 3D CNN architectures with varying convolutional layers counts. The augmentation strategies involve affine transformations, such as zoom, shift, and rotation, applied either concurrently or separately. Results: The combined effect of data augmentation and model complexity results in up to 10% variation in prediction accuracy. Notably, when affine transformation are applied separately, the model achieves higher accuracy, regardless the chosen architecture. Across all strategies, the model accuracy exhibits a concave behavior as the number of convolutional layers increases, peaking at an intermediate value. The best model reaches excellent performance both on the internal and additional external testing set. Discussions: Our work underscores the critical importance of adhering to rigorous experimental practices in the field of ML applied to healthcare. The results clearly demonstrate how data augmentation and model depth—often overlooked factors– can dramatically impact final performance if not thoroughly investigated. This highlights both the necessity of exploring neglected modeling aspects and the need to comprehensively report all modeling choices to ensure reproducibility and facilitate meaningful comparisons across studies. [ABSTRACT FROM AUTHOR]

ABSTRACT Billions of fishes are kept in captivity for research and food production world‐wide, with a strong impetus for maintaining high welfare standards. Accordingly, the importance of empirical research into the welfare and husbandry of captive fishes is increasingly acknowledged in both science and aquaculture, alongside growing public and governmental interest. Physical enrichment can have an important influence on welfare in of captive fishes, but many questions remain. Here, we summarise the current state of research and outline knowledge gaps in the area of physical enrichment, which is a fundamental aspect to improving welfare of captive fishes. To explore the level of research interest this area across time we conducted a series of surveys, using the number of papers published per year as a metric. These surveys highlight that work on fish welfare, while representing a relatively low proportion of fish research overall, is increasing rapidly. For species that are of aquaculture importance or used commonly as laboratory subjects, we show a positive relationship between general research interest and number of welfare‐related papers. However, for many, particularly relatively less studied, species the proportion of papers on enrichment remains low, with a slower increase compared to welfare‐related papers in general. In terms of common metrics used to quantify fish welfare, there is a reliance on growth and behaviour, with scope for inclusion and combination of a more comprehensive range of reproducible measures. We finish by highlighting recent progress, promising areas for future research and suggestions for advances in this area. [ABSTRACT FROM AUTHOR]

Background Purpose Materials and methods Results Conclusion Coronary artery disease (CAD) has one of the highest mortality rates in humans worldwide. Single‐photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) provides clinicians with myocardial metabolic information non‐invasively. However, there are some limitations to interpreting SPECT images performed by physicians or automatic quantitative approaches. Radiomics analyzes images objectively by extracting quantitative features and can potentially reveal biological characteristics that the human eye cannot detect. However, the reproducibility and repeatability of some radiomic features can be highly susceptible to segmentation and imaging conditions.We aimed to assess the reproducibility of radiomic features extracted from uncorrected MPI‐SPECT images reconstructed with 15 different settings before and after ComBat harmonization, along with evaluating the effectiveness of ComBat in realigning feature distributions.A total of 200 patients (50% normal and 50% abnormal) including rest and stress (without attenuation and scatter corrections) MPI‐SPECT images were included. Images were reconstructed using 15 combinations of filter cut‐off frequencies, filter orders, filter types, reconstruction algorithms, number of iterations and subsets resulting in 6000 images. Image segmentation was performed on the left ventricle in the first reconstruction for each patient and applied to 14 others. A total of 93 radiomic features were extracted from the segmented area, and ComBat was used to harmonize them. The intraclass correlation coefficient (ICC) and overall concordance correlation coefficient (OCCC) tests were performed before and after ComBat to examine the impact of each parameter on feature robustness and to assess harmonization efficiency. The ANOVA and the Kruskal–Wallis tests were performed to evaluate the effectiveness of ComBat in correcting feature distributions. In addition, the Student's t‐test, Wilcoxon rank‐sum, and signed‐rank tests were implemented to assess the significance level of the impacts made by each parameter of different batches and patient groups (normal vs. abnormal) on radiomic features.Before applying ComBat, the majority of features (ICC: 82, OCCC: 61) achieved high reproducibility (ICC/OCCC ≥ 0.900) under every batch except Reconstruction. The largest and smallest number of poor features (ICC/OCCC < 0.500) were obtained by IterationSubset and Order batches, respectively. The most reliable features were from the first‐order (FO) and gray‐level co‐occurrence matrix (GLCM) families. Following harmonization, the minimum number of robust features increased (ICC: 84, OCCC: 78). Applying ComBat showed that Order and Reconstruction were the least and the most responsive batches, respectively. The most robust families, in a descending order, were found to be FO, neighborhood gray‐tone difference matrix (NGTDM), GLCM, gray‐level run length matrix (GLRLM), gray‐level size zone matrix (GLSZM), and gray‐level dependence matrix (GLDM) under Cut‐off, Filter, and Order batches. The Wilcoxon rank‐sum test showed that the number of robust features significantly differed under most batches in the Normal and Abnormal groups.The majority of radiomic features show high levels of robustness across different OSEM reconstruction parameters in uncorrected MPI‐SPECT. ComBat is effective in realigning feature distributions and enhancing radiomic features reproducibility. [ABSTRACT FROM AUTHOR]

Chemical exchange saturation transfer (CEST) imaging may provide novel contrast for the diagnosis, prognosis, and monitoring of the progression or treatment of neurological applications. However, the reproducibility of prominent CEST contrasts like amide CEST and nuclear Overhauser enhancement (NOE) CEST must be characterized in healthy brain gray matter (GM) and white matter (GM) prior to clinical implementation. The objective of this study was to characterize the reproducibility of four different CEST contrasts in the healthy human brain. Using a 3T MRI scanner, two 3D CEST scans were acquired in 12 healthy subjects (7 females, mean age (± SD) 26 ± 4 years) approximately 10 days apart. Scan-rescan reproducibility was measured for four contrasts: amine/amide concentration-independent detection (AACID), Amide*, and inverse magnetization transfer ratio (MTRRex) contrast for amide and NOE. Reproducibility was evaluated between- and within-subjects using coefficients of variation (CV) and the percent difference between measurements. AACID and NOE-MTRRex contrasts demonstrated the lowest within-subject CVs (0.8–1.2% and 1.6-2.0%, respectively), between-subject CVs (1.2–2.1% and 3.4–4.2%, respectively), and percent difference (1.2–1.4% and 2.2–2.8%, respectively) for both GM and WM. AACID and NOE-MTRRex contrasts demonstrated the highest reproducibility and represented stable measurements suitable for characterizing changes in brain tissue caused by pathological processes. [ABSTRACT FROM AUTHOR]

A concern in the field of autism electroencephalography (EEG) biomarker discovery is their lack of reproducibility. In the present study, we considered the problem of learning reproducible associations between multiple features of resting state (RS) neural activity and autism, using EEG data collected during a RS paradigm from 36 to 96 month-old children diagnosed with autism (N = 224) and neurotypical children (N = 69). Specifically, EEG spectral power and functional connectivity features were used as inputs to a regularized generalized linear model trained to predict diagnostic group (autism versus neurotypical). To evaluate our model, we proposed a procedure that quantified both the predictive generalization and reproducibility of learned associations produced by the model. When prioritizing both model predictive performance and reproducibility of associations, a highly reproducible profile of associations emerged. This profile revealed a distinct pattern of increased gamma power and connectivity in occipital and posterior midline regions associated with an autism diagnosis. Conversely, model selection based on predictive performance alone resulted in non-robust associations. Finally, we built a custom machine learning model that further empirically improved robustness of learned associations. Our results highlight the need for model selection criteria that maximize the scientific utility provided by reproducibility instead of predictive performance. [ABSTRACT FROM AUTHOR]

Purpose: Steatotic liver disease (SLD) has become the most common cause of chronic liver disease. Nevertheless, the non-invasive quantitative diagnosis of steatosis is still lacking in clinical practice. This study aimed to evaluate the reproducibility of the new parameter for steatosis quantification named ultrasound-derived fat fraction (UDFF). Materials and methods: The UDFF values were independently executed by two operators in two periods. In the process, repeated measurements of the same patient were performed by the same operator under different conditions (liver segments, respiration, positions, and dietary). Finally, the results of some subjects (28) were compared with the MRI-derived proton density fat fraction (PDFF). The concordance analysis was mainly achieved by the intraclass correlation coefficient (ICC) and Bland–Altman. Results: One hundred-five participants were included in the study. UDFF had good reliability in measuring the adult liver (ICCintra-observer = 0.96, ICCinter-observer = 0.94). Meanwhile, the ICC of the two operators increased over time. The variable measurement states did not influence the UDFF values on the surface, but they affected the coefficient of variation (Cov) of the results. Segment 8 (S8), end-expiratory, supine, and fasting images had the most minor variability. On the other hand, the UDFF value of S8 displayed satisfied consistency with PDFF (mean difference, −0.24 ± 1.44), and the results of both S5 (mean difference: −0.56 ± 3.95) and S8 (mean difference: 0.73 ± 1.87) agreed well with the whole-liver PDFF. Conclusion: UDFF measurements had good reproducibility. Furthermore, the state of S8, end-expiration, supine, and fasting might be the more stable measurement approach. Critical relevance statement: UDFF is the quantitative ultrasound parameter of hepatic steatosis and has good reproducibility. It can show more robust performance under specific measurement conditions (S8, end-expiratory, supine, and fasting). Trial registration: The research protocol was registered at the Chinese Clinical Trial Registry on October 9, 2023 (http://www.chictr.org.cn/). The registration number is ChiCTR 2300076457. Key Points: There is a lack of non-invasive quantitative measurement options for hepatic steatosis. UDFF demonstrated excellent reproducibility in measuring hepatic steatosis. S8, end-expiratory, supine, and fasting may be the more stable measuring condition. Training could improve the operators' measurement stability. Variable measurement state affects the repeatability of the UDFF values (Cov). [ABSTRACT FROM AUTHOR]

Critical to the foundation of scientific research, the reproducibility of studies and their results is a fundamental element, ensuring the credibility of the findings and fostering trust. Maps play an important role here, as they are used across disciplines to visualize complex insights and outcomes from a wide range of studies. Due to their relevance in this context, it is essential to be able to reproduce maps as well, and consequently, to assess whether a map reproduction was successful. In this paper, we present our research on which aspects affect the success of map reproduction and how to assess map reproduction based on the visual differences between the original and the reproduced map. We collected data from two focus groups and an online survey to gain a deeper understanding of how geoscientists and map experts conceptualize map reproduction, which factors they consider relevant in this process, and how strong their impact is relative to each other. We analyzed this data qualitatively and quantitatively to create a conceptual model that describes the assessment of map reproduction and a set of criteria that influence the success of the reproduction. With these contributions, we aim to provide an initial toolkit for systematically assessing the success of map reproduction attempts. [ABSTRACT FROM AUTHOR]

Background and objective: The primary cilium is a small protrusion found on most mammalian cells. It acts as a cellular antenna, being involved in various cell signaling pathways. The length of the primary cilium affects its function. To study the impact of physical or chemical stimuli on cilia, their lengths must be determined easily and reproducibly. Methods: We have developed and evaluated an open-source R package called detectCilia to detect and measure primary cilia automatically. As a case study to demonstrate the capability of our tool, we compared the influence of 4 different cell culture media compositions on the lengths of primary cilia in human chondrocytes. These media compositions include (1) insulin-transferrin-selenium (ITS); (2) ITS and dexamethasone (Dexa); (3) ITS, Dexa, insulin-like growth factor 1 (IGF-1), and transforming growth factor beta 1 (TGF-β1); and (4) fetal bovine serum (FBS). Results: The assessment of detectCilia included a comparison with 2 similar tools: ACDC (Automated Cilia Detection in Cells) and CiliaQ. Several differences and advantages of our package make it a valuable addition to these tools. In the case study, we have observed variations in the ciliary lengths associated with using different media compositions. Conclusions: We conclude that detectCilia can automatically and reproducibly detect and measure primary cilia in confocal microscopy images with low false-positive rates without requiring extensive user interaction. [ABSTRACT FROM AUTHOR]

Having the ability to reproduce empirical results is foundational to the scientific process. Increasingly, there is an emphasis within the research community to create workflows which are not only reproducible but also replicable in that analytical approaches can be applied to new data. However, a disproportionate number of technical solutions designed to foster reproducibility and replicability have focused on data analysis, particularly within geography. This paper argues for greater attention on a phase of the research process which precedes analysis and is often taken for granted – that of data acquisition. Through code examples using the R Project for Statistical Computing, this paper demonstrates a path toward replicable spatial data acquisition for both secondary and primary data acquisition, with a focus on crowdsourced geographic information. The modular approach demonstrated is flexible in that it allows for straightforward replication but also enables extension to new spatial questions. Such work is valuable because it conserves labor, promotes research provenance, and allows for more robust analyses. [ABSTRACT FROM AUTHOR]

Background and Purpose Experimental Approach Key Results Conclusion and Implications Irwin tests are key preclinical study elements for characterising drug‐induced neurological side effects. This multicentre study aimed to assess the robustness of Irwin tests across multinational sites during three stages of protocol harmonisation. The projects were part of the Enhanced Quality in Preclinical Data framework, aiming to increase success rates in transition from preclinical testing to clinical application.Female and male NMRI mice were assigned to one of three groups (vehicle, MK‐801 0.1 and 0.3 mg kg−1). Irwin scores were assessed at baseline and multiple times following intraperitoneal injection of MK‐801 using local protocols (Stage 1), shared protocols with harmonised environmental design (Stage 2) and fully harmonised Irwin scoring protocols (Stage 3).The analysis based on the four functional domains (motor, autonomic, sedation and excitation) revealed substantial data variability in Stages 1 and 2. Although there was still marked overall heterogeneity between sites in Stage 3 after complete harmonisation of the Irwin scoring scheme, heterogeneity was only moderate within functional domains. When comparing treatment groups versus vehicle, we found large effect sizes in the motor domain and subtle to moderate effects in the excitation‐related and autonomic domains.The pronounced interlaboratory variability in Irwin datasets for the CNS‐active compound MK‐801 needs to be carefully considered when making decisions during drug development. While environmental and general study design had a minor impact, the study suggests that harmonisation of parameters and their scoring can limit variability and increase robustness. [ABSTRACT FROM AUTHOR]

The rapid advancement in the field of medical imaging presents a challenge in keeping up to date with the necessary objective evaluations and optimizations for safe and effective use in clinical settings. These evaluations are traditionally done using clinical imaging trials, which while effective, pose several limitations including high costs, ethical considerations for repetitive experiments, time constraints, and lack of ground truth. To tackle these issues, virtual trials (aka in silico trials) have emerged as a promising alternative, using computational models of human subjects and imaging devices, and observer models/analysis to carry out experiments. To facilitate the widespread use of virtual trials within the medical imaging research community, a major need is to establish a common consensus framework that all can use. Based on the ongoing efforts of an AAPM Task Group (TG387), this article provides a comprehensive overview of the requirements for establishing virtual imaging trial frameworks, paving the way toward their widespread use within the medical imaging research community. These requirements include credibility, reproducibility, and accessibility. Credibility assessment involves verification, validation, uncertainty quantification, and sensitivity analysis, ensuring the accuracy and realism of computational models. A proper credibility assessment requires a clear context of use and the questions that the study is intended to objectively answer. For reproducibility and accessibility, this article highlights the need for detailed documentation, user‐friendly software packages, and standard input/output formats. Challenges in data and software sharing, including proprietary data and inconsistent file formats, are discussed. Recommended solutions to enhance accessibility include containerized environments and data‐sharing hubs, along with following standards such as CDISC (Clinical Data Interchange Standards Consortium). By addressing challenges associated with credibility, reproducibility, and accessibility, virtual imaging trials can be positioned as a powerful and inclusive resource, advancing medical imaging innovation and regulatory science. [ABSTRACT FROM AUTHOR]

Background: The Bethesda System for Reporting Thyroid Cytology (TBSRTC) recommended for the interpretation of needle aspiration cytology of the thyroid, is the most widely used worldwide. Studies have shown that the disagreement between observers, especially in the Bethesda III and IV diagnostic categories, is not insignificant at 10%–40%. In the TBSRTC 2023 version, some definitions were removed and simplified, and molecular pathology was proposed as a complement to cytopathology. The current availability of molecular tests is limited because they can be performed in a few centers and are expensive. Therefore, our study investigated intra- and inter-observer agreement according to TBSRTC 2023 using only immunohistochemically BRAFV600E antibodies. Materials and Methods: The study included 173 cases with aspiration cytology evaluated between 2019 and 2022. The immunohistochemical procedure applied BRAFV600E (RM8) monoclonal antibody to cell block sections. All slides were assessed and categorized by three different observers. Data were interpreted using Cohen's kappa and Fleiss's kappa test in the Statistical Package for Social Sciences Windows 2021 program. Results: For the applied RM8 antibody, sensitivity was 64.71% and specificity was 87.27%. In terms of diagnostic categories, inter-observer agreement was good for Bethesda II (K = 0.606) and moderate for Bethesda III (K = 0.429), Bethesda IV (K = 0.523), Bethesda V (K = 0,464), and Bethesda VI (K = 0.544), respectively. Conclusion: In conclusion, the study reveals that the 2023 version of TBSRTC provides improvement, especially in the categories of uncertain diagnosis, but is still insufficient to improve cytological diagnostic accuracy, at which point molecular analyses become even more important. [ABSTRACT FROM AUTHOR]

Anti-AAV neutralizing Abs (NAbs) titer is usually measured by cell-based microneutralization (MN) assay and is crucial for patient screening in AAV-based gene therapy clinical trials. However, achieving uniform operation and comparable results among different laboratories remains challenging. Here, we established a standardized MN assay for anti-AAV9 NAbs in human sera or plasma and transferred the method to the other two research teams. Then, we validated its parameters and tested a set of eight human samples in blind across all laboratories. The end-point titer, defined by a transduction inhibition of 50% (IC50), was calculated using curve-fit modelling. A mouse neutralizing monoclonal antibody in human negative serum was used for system quality control (QC), requiring inter-assay titer variation of <4-fold difference or geometric coefficient of variation (%GCV) of <50%. The assay demonstrated a sensitivity of 54 ng/mL and no cross-reactivity to 20 μg/mL anti-AAV8 MoAb. The intra-assay and inter-assay variation for the low positive QC were 7–35% and 22–41%, respectively. The titers of the blind samples showed excellent reproducibility within and among laboratories, with a %GCV of 18–59% and 23–46%, respectively. This study provides a commonly transferrable MN assay for evaluating anti-AAV9 NAbs in humans, supporting its application in clinical trials. [ABSTRACT FROM AUTHOR]

The article "The Replication Crisis: A Persistent Challenge in Biomedical Research" published in the Bangladesh Journal of Medical Science discusses the ongoing replication crisis in scientific research, particularly in fields like psychology. The crisis undermines the credibility of studies, wastes resources, and may lead to misguided clinical trials. Various factors contribute to this issue, such as publication bias and poor study design. The scientific community has implemented initiatives like preregistration of studies to address these challenges and improve research practices. [Extracted from the article]

Background: Mandibular range of motion (MROM) variables are widely used to evaluate oral function. Objective: The aim of this study was to establish the reliability of MROM variables in healthy children. Methods: In this cross‐sectional study, healthy children were examined 2 weeks apart. The following MROM variables were established: active maximum interincisal opening (AMIO), passive maximum interincisal opening (PMIO), protrusion and left and right laterotrusion. The reliability of the MROM measurements was determined by analysing the intra‐class correlation coefficient (ICC), standard error of measurement (SEM), smallest detectable change (SDC) and limits of agreement (LoA). Results: A total of 167 healthy children were examined. The ICC indicated good reliability for AMIO (0.885); excellent reliability for PMIO (0.925); and moderate reliability for protrusion (0.578), laterotrusion left (0.601) and laterotrusion right (0.634). The SDC was 0.9 mm for AMIO, 0.4 mm for PMIO, 2.2 mm for protrusion, 1.6 mm for laterotrusion left and 1.4 mm for laterotrusion right. The LoA was −5.67 to 5.82 for AMIO, −3.90 to 3.57 for PMIO, −3.89 to 3.55 for protrusion, −2.99 to 2.77 for laterotrusion left, and − 2.71 to 2.77 for laterotrusion right. Conclusions: AMIO and PMIO measurements are both highly reliable in healthy children. The low SDC indicate that AMIO and PMIO are promising longitudinal measurements. Protrusion and laterotrusion measurements had moderate reliability. These results support our clinical recommendation to measure AMIO rather than PMIO, as PMIO is more difficult and more time‐consuming to perform than AMIO. [ABSTRACT FROM AUTHOR]

Background: T1-weighted (T1W) magnetic resonance imaging (MRI) using the delay alternating with nutation for excitation-sampling perfection with application-optimized contrasts using different flip angle evolution (DANTE-SPACE) is the preferred imaging technique for evaluation of the vessel wall. Purpose: To evaluate the intra- and inter-rater reproducibility of carotid wall segmentation on T1W DANTE-SPACE in patients with symptomatic (acute stroke or transient ischemic attack) internal carotid artery (ICA) stenosis. Material and Methods: This prospective study included 25 patients with acute (≤3 months) stroke or transient ischemic attack and 50%–99% stenosis of the ICA. All patients underwent 3.0-T high-resolution carotid MRI. Two radiologists independently performed the manual segmentation of the vessel wall and inner lumen of the bilateral carotid artery on DANTE-SPACE. The intraclass correlation coefficient (ICC), Dice similarity coefficient (DSC), and Hausdorff distance (HD) were calculated. Results: The ICCs for intra-rater reproducibility of carotid wall volume, inner lumen volume, and normalized wall index were 0.965, 0.990, and 0.962, respectively. The ICCs for inter-rater reproducibility of carotid wall volume, inner lumen, and normalized wall index were 0.856, 0.981, and 0.904. DSC and HD for intra- and inter-rater reproducibility of carotid wall segmentation were as follows: 0.873 and 0.809 (DSC); and 0.079 and 0.118 (HD), respectively. For evaluation of reproducibility only in the carotid artery with symptomatic stenosis, the ICCs for intra- and inter-rater reproducibility indicated all perfect agreement. Conclusion: T1W DANTE-SPACE is a reproducible sequence for evaluation of the carotid wall using carotid MRI in patients with symptomatic ICA stenosis. [ABSTRACT FROM AUTHOR]

Null hypothesis significance testing is a statistical tool commonly employed throughout laboratory animal research. When experimental results are reported, the reproducibility of the results is of utmost importance. Establishing standard, robust, and adequately powered statistical methodology in the analysis of laboratory animal data is critical to ensure reproducible and valid results. Simulation studies are a reliable method for assessing the power of statistical tests, however, biologists may not be familiar with simulation studies for power despite their efficacy and accessibility. Through an example of simulated Harlan Sprague-Dawley (HSD) rat organ weight data, we highlight the importance of conducting power analyses in laboratory animal research. Using simulations to determine statistical power prior to an experiment is a financially and ethically sound way to validate statistical tests and to help ensure reproducibility of findings in line with the 4R principles of animal welfare. [ABSTRACT FROM AUTHOR]

This systematic review aimed to summarise and analyse the evidence on the reliability and validity of linear tranducers (LTs) in exercises of different nature and different modes of execution. This systematic review was carried out under PRISMA guidelines, and was carried out using three databases (PubMed, Web of Sciences, and Scopus). Of the 351 initially found, 21 were included in the qualitative synthesis. The results reflected that linear position transducers (LPTs) were valid and reliable in monitoring movement velocity in non-plyometric exercises. However, precision and reliability were lower in execution protocols without isometric phase and in the execution of exercises in multiple planes of movement, with greater measurement errors at higher sampling frequencies. On the other hand, linear velocity transducers (LVTs) proved to be valid and reliable in measuring velocity during plyometric and non-plyometric exercises performed on the Smith machine, with less variation in measurement in the latter. Finally, the use of peak values is recommended, since they are less dependent on the technological errors of LTs. Therefore, the performance of non-plyometric exercises, carried out in the Smith machine and with an isometric phase in the execution of the movement, will help to minimise the technological error of the LTs. [ABSTRACT FROM AUTHOR]

The current controversy surrounding research replication in biomedical and psychosocial sciences often overlooks the uncertainties surrounding both the original and replication studies. Overemphasizing single attempts as definitive replication successes or failures, as exemplified by media coverage of the landmark Reproducibility Project: Psychology, fosters misleading dichotomies and erodes public trust. To avoid such unintended consequences, science communicators should more clearly articulate statistical variation and other uncertainty sources in replication, while emphasizing the cumulative nature of science in general and replication in particular. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate radiomics features' reproducibility using inter-package/inter-observer measurement analysis in renal masses (RMs) based on MRI and to employ machine learning (ML) models for RM characterization. Methods: 32 Patients (23M/9F; age 61.8 ± 10.6 years) with RMs (25 renal cell carcinomas (RCC)/7 benign masses; mean size, 3.43 ± 1.73 cm) undergoing resection were prospectively recruited. All patients underwent 1.5 T MRI with T2-weighted (T2-WI), diffusion-weighted (DWI)/apparent diffusion coefficient (ADC), and pre-/post-contrast-enhanced T1-weighted imaging (T1-WI). RMs were manually segmented using volume of interest (VOI) on T2-WI, DWI/ADC, and T1-WI pre-/post-contrast imaging (1-min, 3-min post-injection) by two independent observers using two radiomics software packages for inter-package and inter-observer assessments of shape/histogram/texture features common to both packages (104 features; n = 26 patients). Intra-class correlation coefficients (ICCs) were calculated to assess inter-observer and inter-package reproducibility of radiomics measurements [good (ICC ≥ 0.8)/moderate (ICC = 0.5–0.8)/poor (ICC < 0.5)]. ML models were employed using reproducible features (between observers and packages, ICC > 0.8) to distinguish RCC from benign RM. Results: Inter-package comparisons demonstrated that radiomics features from T1-WI-post-contrast had the highest proportion of good/moderate ICCs (54.8–58.6% for T1-WI-1 min), while most features extracted from T2-WI, T1-WI-pre-contrast, and ADC exhibited poor ICCs. Inter-observer comparisons found that radiomics measurements from T1-WI pre/post-contrast and T2-WI had the greatest proportion of features with good/moderate ICCs (95.3–99.1% T1-WI-post-contrast 1-min), while ADC measurements yielded mostly poor ICCs. ML models generated an AUC of 0.71 [95% confidence interval = 0.67–0.75] for diagnosis of RCC vs. benign RM. Conclusion: Radiomics features extracted from T1-WI-post-contrast demonstrated greater inter-package and inter-observer reproducibility compared to ADC, with fair accuracy for distinguishing RCC from benign RM. Clinical relevance: Knowledge of reproducibility of MRI radiomics features obtained on renal masses will aid in future study design and may enhance the diagnostic utility of radiomics models for renal mass characterization. [ABSTRACT FROM AUTHOR]

Computer code plays a vital role in modern science, from the conception and design of experiments through to final data analyses. Open sharing of code has been widely discussed as being advantageous to the scientific process, allowing experiments to be more easily replicated, helping with error detection, and reducing wasted effort and resources. In the case of psychology, the code used to present stimuli is a fundamental component of many experiments. It is not known, however, the degree to which researchers are sharing this type of code. To estimate this, we conducted a survey of 400 psychology papers published between 2016 and 2021, identifying those working with the open-source tools Psychtoolbox and PsychoPy that openly share stimulus presentation code. For those that did, we established if it would run following download and also appraised the code's usability in terms of style and documentation. It was found that only 8.4% of papers shared stimulus code, compared to 17.9% sharing analysis code and 31.7% sharing data. Of shared code, 70% ran directly or after minor corrections. For code that did not run, the main error was missing dependencies (66.7%). The usability of the code was moderate, with low levels of code annotation and minimal documentation provided. These results suggest that stimulus presentation code sharing lags behind other forms of code and data sharing, potentially due to less emphasis on such code in open-science discussions and in journal policies. The results also highlight a need for improved documentation to maximize code utility. [ABSTRACT FROM AUTHOR]

Although radiomics has revealed an intriguing perspective for quantitative radiology, the impact of scanning parameters on its outcomes must be considered. In this study, the effects of changes in the region of interest (ROI) sizes, Hounsfield Unit (HU), and resolution of computed tomography (CT) on feature reproducibility have been investigated. The GAMMEX 464 phantom was used to evaluate the reproducibility of radiomics features across different ROI sizes, HU, and resolution. Data were acquired using a consistent system setup, with the phantom repositioned for each scan. The first acquisition series examined the effects of different ROI sizes and resolutions (1, 3, and 5 mm) on feature reproducibility. The second series assessed the impact of different HU and resolution. Segmentation and feature extraction were performed using LIFEx 7.1.0 software, focusing on textural radiomics features. Statistical analysis involved calculating the coefficient of variation (COV) to categorize feature variability. COV <5 % was considered highly stable. Out of the 32 textural features studied, the analysis of changes in ROI size with a resolution of 1 mm, 3 mm, and 5 mm revealed that 16, 17, and 18 features had high reproducibility, with a COV<5 %. Polyethylene, acrylic, and water also demonstrated stable textural features across changes in scan parameters and image resolutions, with 4 reproducible features in all resolutions. The grey-level run length matrix (GLRLM) and grey-level zone length matrix (GLZLM) radiomics groups were highly stable in the context of variations in scan parameters and different materials. The results of this study highlight the importance of standardizing radiomics studies to reduce the influence of pre-analysis steps on feature values. This standardization is crucial for guaranteeing the consistency of radiomics features under various imaging conditions. Additional research is required to enhance these results. To ensure the reproducibility and reliability of radiomics features, it is imperative to standardize scanning parameters and pre-analysis protocols. This standardization will enhance the consistency of radiomics applications in both clinical and research environments. [ABSTRACT FROM AUTHOR]