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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]

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]

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]

Model distillation has been a popular method for producing interpretable machine learning. It uses an interpretable "student" model to mimic the predictions made by the black box "teacher" model. However, when the student model is sensitive to the variability of the data sets used for training even when keeping the teacher fixed, the corresponded interpretation is not reliable. Existing strategies stabilize model distillation by checking whether a large enough sample of pseudo-data is generated to reliably reproduce student models, but methods to do so have so far been developed separately for each specific class of student model. In this paper, we develop a generic approach for stable model distillation based on central limit theorem for the estimated fidelity of the student to the teacher. We start with a collection of candidate student models and search for candidates that reasonably agree with the teacher. Then we construct a multiple testing framework to select a sample size such that the consistent student model would be selected under different pseudo samples. We demonstrate the application of our proposed approach on three commonly used intelligible models: decision trees, falling rule lists and symbolic regression. Finally, we conduct simulation experiments on Mammographic Mass and Breast Cancer datasets and illustrate the testing procedure throughout a theoretical analysis with Markov process. The code is publicly available at https://github.com/yunzhe-zhou/GenericDistillation. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to assess the reliability of lower limb muscle function (knee extensor/flexor peak torque, rate of torque development (RTD), impulse, and countermovement jump (CMJ) performance) and sprint performance (acceleration capacity). Methods: CMJ performance was evaluated on a force plate. MVIC, RTD and impulse variables were investigated using a portable isometric dynamometer and sprint performance was assessed with dual-beam photocells in elite female athletes. Results: CMJ test variables maximal vertical jump height, peak and mean power, concentric work, and body center of mass displacement demonstrated good-to-excellent test–retest correlations between Test 1 and Test 2 (ICC ≥ 0.70, CWw-s = 3.4–11.0%). Peak MVIC torque for the knee extensors and flexors demonstrated excellent test–retest correlations (both ICC = 0.84) along with CVw-s values of 6.8 and 6.0%, respectively. Late-phase (0–100 ms, 0–200 ms) RTD for the knee flexors demonstrated excellent test–retest correlations (ICC = 0.89–0.91, CVw-s = 4.8–8.5%). Sprint times at 10- and 20-m demonstrated excellent test–retest reproducibility (ICC = 0.83 and ICC = 0.90, respectively) with CVw-s values of 1.9 and 1.5%. For 5-m sprint times, test–retest reproducibility was good (ICC = 0.71) with CVw-s of 2.8%. Sprint testing performed while dribbling a handball improved (p < 0.05) from test to retest at 5-, 10- and 20-m. Conclusion: In conclusion, the force plate, the mobile isometric dynamometer, and dual-beam photocells provide reproducible tools for field-based testing of countermovement jump performance, knee extensor and flexor strength and sprint performance. [ABSTRACT FROM AUTHOR]

Naturalistic body stimuli are necessary for understanding many aspects of human psychology, yet there are no centralized databases of body stimuli. Furthermore, there are a high number of independently developed stimulus sets lacking in standardization and reproducibility potential, and a general lack of organization, contributing to issues of both replicability and generalizability in body-related research. We conducted a comprehensive scoping review to index and explore existing naturalistic whole-body stimuli. Our research questions were as follows: (1) What sets of naturalistic human whole-body stimuli are present in the literature? And (2) On what factors (e.g., demographics, emotion expression) do these stimuli vary? To be included, stimulus sets had to (1) include human bodies as stimuli; (2) be photographs, videos, or other depictions of real human bodies (not computer generated, drawn, etc.); (3) include the whole body (defined as torso, arms, and legs); and (4) could include edited images, but still had to be recognizable as human bodies. We identified a relatively large number of existing stimulus sets (N = 79) which offered relative variability in terms of main manipulated factors and the degree of visual information included (i.e., inclusion of heads and/or faces). However, stimulus sets were demographically homogenous, skewed towards White, young adult, and female bodies. We identified significant issues in reporting and availability practices, posing a challenge to the generalizability, reliability, and reproducibility of body-related research. Accordingly, we urge researchers to adopt transparent and accessible practices and to take steps to diversify body stimuli. [ABSTRACT FROM AUTHOR]

Psychological science has thrived thanks to new methods and innovative practices. Journals, including Behavior Research Methods (BRM), continue to support the dissemination and evaluation of research assets including data, software/hardware, statistical code, and databases of stimuli. However, such research assets rarely allow for computational reproducibility, meaning they are difficult to reuse. Therefore, in this preregistered report, we explore how BRM's authors and BRM structures shape the landscape of functional research assets. Our broad research questions concern: (1) How quickly methods and analytical techniques reported in BRM can be used and developed further by other scientists; (2) Whether functionality has improved following changes to BRM journal policy in support of computational reproducibility; (3) Whether we can disentangle such policy changes from changes in reproducibility over time. We randomly sampled equal numbers of papers (N = 204) published in BRM before and after the implementation of policy changes. Pairs of researchers recorded how long it took to ensure assets (data, software/hardware, statistical code, and materials) were fully operational. They also coded the completeness and reusability of the assets. While improvements were observed in all measures, only changes to completeness were altered significantly following the policy changes (d =.37). The effects varied between different types of research assets, with data sets from surveys/experiments showing the largest improvements in completeness and reusability. Perhaps more importantly, changes to policy do appear to have improved the life span of research products by reducing natural decline. We conclude with a discussion of how, in the future, research and policy might better support computational reproducibility within and beyond psychological science. [ABSTRACT FROM AUTHOR]

Passive smartphone measures hold significant potential and are increasingly employed in psychological and biomedical research to capture an individual's behavior. These measures involve the near-continuous and unobtrusive collection of data from smartphones without requiring active input from participants. For example, GPS sensors are used to determine the (social) context of a person, and accelerometers to measure movement. However, utilizing passive smartphone measures presents methodological challenges during data collection and analysis. Researchers must make multiple decisions when working with such measures, which can result in different conclusions. Unfortunately, the transparency of these decision-making processes is often lacking. The implementation of open science practices is only beginning to emerge in digital phenotyping studies and varies widely across studies. Well-intentioned researchers may fail to report on some decisions due to the variety of choices that must be made. To address this issue and enhance reproducibility in digital phenotyping studies, we propose the adoption of preregistration as a way forward. Although there have been some attempts to preregister digital phenotyping studies, a template for registering such studies is currently missing. This could be problematic due to the high level of complexity that requires a well-structured template. Therefore, our objective was to develop a preregistration template that is easy to use and understandable for researchers. Additionally, we explain this template and provide resources to assist researchers in making informed decisions regarding data collection, cleaning, and analysis. Overall, we aim to make researchers' choices explicit, enhance transparency, and elevate the standards for studies utilizing passive smartphone measures. [ABSTRACT FROM AUTHOR]

Surface-enhanced Raman scattering (SERS) remains a significant area of research since it's discovery 50 years ago. The surface-based technique has been used in a wide variety of fields, most prominently in chemical detection, cellular imaging and medical diagnostics, offering high sensitivity and specificity when probing and quantifying a chosen analyte or monitoring nanoparticle uptake and accumulation. However, despite its promise, SERS is mostly confined to academic laboratories and is not recognised as a gold standard analytical technique. This is due to the variations that are observed in SERS measurements, mainly caused by poorly characterised SERS substrates, lack of universal calibration methods and uncorrelated results. To convince the wider scientific community that SERS should be a routinely used analytical technique, the field is now focusing on methods that will increase the reproducibility of the SERS signals and how to validate the results with more well-established techniques. This review explores the difficulties experienced by SERS users, the methods adopted to reduce variation and suggestions of best practices and strategies that should be adopted if one is to achieve absolute quantification. [ABSTRACT FROM AUTHOR]

This study aimed to (1) replicate a deep-learning-based model for cerebral aneurysm segmentation in TOF-MRAs, (2) improve the approach by testing various fully automatic pre-processing pipelines, and (3) rigorously validate the model's transferability on independent, external test-datasets. A convolutional neural network was trained on 235 TOF-MRAs acquired on local scanners from a single vendor to segment intracranial aneurysms. Different pre-processing pipelines including bias field correction, resampling, cropping and intensity-normalization were compared regarding their effect on model performance. The models were tested on independent, external same-vendor and other-vendor test-datasets, each comprised of 70 TOF-MRAs, including patients with and without aneurysms. The best-performing model achieved excellent results on the external same-vendor test-dataset, surpassing the results of the previous publication with an improved sensitivity (0.97 vs. ~ 0.86), a higher Dice score coefficient (DSC, 0.60 ± 0.25 vs. 0.53 ± 0.31), and an improved false-positive rate (0.87 ± 1.35 vs. ~ 2.7 FPs/case). The model further showed excellent performance in the external other-vendor test-datasets (DSC 0.65 ± 0.26; sensitivity 0.92, 0.96 ± 2.38 FPs/case). Specificity was 0.38 and 0.53, respectively. Raising the voxel-size from 0.5 × 0.5×0.5 mm to 1 × 1×1 mm reduced the false-positive rate seven-fold. This study successfully replicated core principles of a previous approach for detecting and segmenting cerebral aneurysms in TOF-MRAs with a robust, fully automatable pre-processing pipeline. The model demonstrated robust transferability on two independent external datasets using TOF-MRAs from the same scanner vendor as the training dataset and from other vendors. These findings are very encouraging regarding the clinical application of such an approach. [ABSTRACT FROM AUTHOR]

Purpose: Preclinical imaging, with translational potential, lacks a standardized method for defining volumes of interest (VOIs), impacting data reproducibility. The aim of this study was to determine the interobserver variability of VOI sizes and standard uptake values (SUVmean and SUVmax) of different organs using the same [18F]FDG-PET and PET/CT datasets analyzed by multiple observers. In addition, the effect of a standardized analysis approach was evaluated. Procedures: In total, 12 observers (4 beginners and 8 experts) analyzed identical preclinical [18F]FDG-PET-only and PET/CT datasets according to their local default image analysis protocols for multiple organs. Furthermore, a standardized protocol was defined, including detailed information on the respective VOI size and position for multiple organs, and all observers reanalyzed the PET/CT datasets following this protocol. Results: Without standardization, significant differences in the SUVmean and SUVmax were found among the observers. Coregistering CT images with PET images improved the comparability to a limited extent. The introduction of a standardized protocol that details the VOI size and position for multiple organs reduced interobserver variability and enhanced comparability. Conclusions: The protocol offered clear guidelines and was particularly beneficial for beginners, resulting in improved comparability of SUVmean and SUVmax values for various organs. The study suggested that incorporating an additional VOI template could further enhance the comparability of the findings in preclinical imaging analyses. [ABSTRACT FROM AUTHOR]

A guideline is proposed that comprises the minimum items to be reported in research studies involving an eye tracker and human or non-human primate participant(s). This guideline was developed over a 3-year period using a consensus-based process via an open invitation to the international eye tracking community. This guideline will be reviewed at maximum intervals of 4 years. [ABSTRACT FROM AUTHOR]

Objective: Performance assessments of quantitative determinations of proton density fat fraction (PDFF) have largely focused on the range between 0 and 50%. We evaluate PDFF in a two-site phantom study across the full 0–100% PDFF range. Materials and methods: We used commercially available 3D chemical-shift-encoded water-fat MRI sequences from three MRI system vendors at 1.5T and 3T and conducted the study across two sites. A spherical phantom housing 18 vials spanning the full 0–100% PDFF range was used. Data at each site were acquired using default parameters to determine same-day and different-day intra-scanner repeatability, and inter-system and inter-site reproducibility, in addition to linear regression between reference and measured PDFF values. Results: Across all systems, results demonstrated strong linearity and minimal bias. For 1.5T systems, a pooled slope of 0.99 with a 95% confidence interval (CI) of 0.981–0.997 and a pooled intercept of 0.61% PDFF with a 95% CI of 0.17–1.04 were obtained. Results for pooled 3T data included a slope of 1.00 (95% CI 0.995–1.005) and an intercept of 0.69% PDFF (95% CI 0.39–0.97). Inter-site and inter-system reproducibility coefficients ranged from 2.9 to 6.2 (in units of PDFF), while intra-scanner same-day and different-day repeatability ranged from 0.6 to 7.8. Discussion: PDFF across the 0–100% range can be reliably estimated using current commercial offerings at 1.5T and 3T. [ABSTRACT FROM AUTHOR]

The application of deep learning (DL) in medicine introduces transformative tools with the potential to enhance prognosis, diagnosis, and treatment planning. However, ensuring transparent documentation is essential for researchers to enhance reproducibility and refine techniques. Our study addresses the unique challenges presented by DL in medical imaging by developing a comprehensive checklist using the Delphi method to enhance reproducibility and reliability in this dynamic field. We compiled a preliminary checklist based on a comprehensive review of existing checklists and relevant literature. A panel of 11 experts in medical imaging and DL assessed these items using Likert scales, with two survey rounds to refine responses and gauge consensus. We also employed the content validity ratio with a cutoff of 0.59 to determine item face and content validity. Round 1 included a 27-item questionnaire, with 12 items demonstrating high consensus for face and content validity that were then left out of round 2. Round 2 involved refining the checklist, resulting in an additional 17 items. In the last round, 3 items were deemed non-essential or infeasible, while 2 newly suggested items received unanimous agreement for inclusion, resulting in a final 26-item DL model reporting checklist derived from the Delphi process. The 26-item checklist facilitates the reproducible reporting of DL tools and enables scientists to replicate the study's results. [ABSTRACT FROM AUTHOR]

This study applies equivalence testing methods on a representative sample of published empirical structural equation modeling studies in the psychological sciences and assesses the extent to which reported fit results are replicated when compared to those obtained via traditional methods. Results of 382 models from a sample of 242 articles published in 5 top ranked journals from the general field of Developmental Psychology were reported. The results indicated that a sizeable number of models designated in the original studies as 'good' were in fact not reproducible when examined through an equivalence testing lens. These questionable models displayed substantial discrepancy with the data and should not have qualified for further consideration because they were simply not plausible models. Implications of the results and suggestions for best modeling practices within the psychological sciences are discussed. [ABSTRACT FROM AUTHOR]

Endoscopic dissection is the first-choice treatment for superficial pT1 colorectal adenocarcinoma (sCRC). Complementary surgery decision is influenced by histopronostic factors. Prognostic significance and reproducibility of each factor are not well established. The role of immunohistochemistry (IHC) and digital pathology in this context is unknown. Our aims were (1) to evaluate each histopronostic factor reproducibility comparing HES and IHC ± digital pathology and (2) to evaluate how the different techniques would affect indications for additional surgery. We performed a single-centre retrospective study of 98 patients treated between 2010 and 2019 in Hospices Civils de Lyon, France. We analyzed physical or digital slides of HES and keratin/desmin immunostaining of 98 sCRC dissection specimens. Three pathologists evaluate the histopronostic factors including submucosal invasion depth (SMI) measured using different recommended methods. Assessment of SMI with Ueno or JSCCR methods showed good to excellent interobserver reproducibility (IOR) (ICCs of 0.858 to 0.925) using HES staining and IHC. Assessment of budding on HES sections was poorly reproducible compared to IHC which exhibit moderate IOR (κ = 0.714). IHC increased high-grade budding detection. For lymphovascular invasion and poor differentiation, the IOR was poor (κ = 0.141, 0.196 and 0.313 respectively). IHC gave a better reproducibility for further treatment indication according to JSCCR criteria (κ = 0.763) or forthcoming European guidelines (κ = 0.659). Digital pathology was equivalent to the microscope for all analyses. Histopronostic factor reproducibility in sCRC is moderate. Immunohistochemistry may facilitate the evaluation of certain criteria and improve the reproducibility of treatment decisions. [ABSTRACT FROM AUTHOR]

Metrology is the science of measurement and its applications, whereas biometrology is the science of biological measurement and its applications. Biometrology aims to achieve accuracy and consistency of biological measurements by focusing on the development of metrological traceability, biological reference measurement procedures, and reference materials. Irreproducibility of biological and multi-omics research results from different laboratories, platforms, and analysis methods is hampering the translation of research into clinical uses and can often be attributed to the lack of biologists' attention to the general principles of metrology. In this paper, the progresses of biometrology including metrology on nucleic acid, protein, and cell measurements and its impacts on the improvement of reliability and comparability in biological research are reviewed. Challenges in obtaining more reliable biological and multi-omics measurements due to the lack of primary reference measurement procedures and new standards for biological reference materials faced by biometrology are discussed. In the future, in addition to establishing reliable reference measurement procedures, developing reference materials from single or multiple parameters to multi-omics scale should be emphasized. Thinking in way of biometrology is warranted for facilitating the translation of high-throughput omics research into clinical practices. [ABSTRACT FROM AUTHOR]

The increasing use of neuroimaging in clinical research has driven the creation of many large imaging datasets. However, these datasets often rely on inconsistent naming conventions in image file headers to describe acquisition, and time-consuming manual curation is necessary. Therefore, we sought to automate the process of classifying and organizing magnetic resonance imaging (MRI) data according to acquisition types common to the clinical routine, as well as automate the transformation of raw, unstructured images into Brain Imaging Data Structure (BIDS) datasets. To do this, we trained an XGBoost model to classify MRI acquisition types using relatively few acquisition parameters that are automatically stored by the MRI scanner in image file metadata, which are then mapped to the naming conventions prescribed by BIDS to transform the input images to the BIDS structure. The model recognizes MRI types with 99.475% accuracy, as well as a micro/macro-averaged precision of 0.9995/0.994, a micro/macro-averaged recall of 0.9995/0.989, and a micro/macro-averaged F1 of 0.9995/0.991. Our approach accurately and quickly classifies MRI types and transforms unstructured data into standardized structures with little-to-no user intervention, reducing the barrier of entry for clinical scientists and increasing the accessibility of existing neuroimaging data. [ABSTRACT FROM AUTHOR]

Enzyme-linked immunosorbent assays (ELISA) have been widely used to detect disease-related antigens in clinical and research laboratories. One of the main drawbacks of ELISA is the utilization of physical adsorption for immobilizing antibodies on a surface, causing low sensitivity, reproducibility, and precision. In this study, we applied a BC-MAP linker composed of antibody-immobilizing BC domains of protein A and surface-adhesive mussel adhesive protein (MAP) to an ELISA platform to overcome these limitations. The performance of ELISA using BC-MAP linker was compared with that of untreated ELISA. BC-MAP proteins were reproducibly coated to the surface while exposing BC domains, resulting in twofold higher sensitivity and improved reproducibility of ELISA compared to the untreated ELISA utilizing physical adsorption of antibodies. Thus, the proposed method could be successfully used in ELISA platforms to diagnose and manage diseases. [ABSTRACT FROM AUTHOR]

The anteversion of the stem is occasionally intentionally changed by the surgeon for patients with smaller femoral neck anteversion during total hip arthroplasty (THA). However, the reproducibility of preoperative planning with increasing anteversion has been rarely assessed. The present study investigated it using two types of stems. This retrospective study included patients who underwent primary posterolateral THA using taper-wedge (TS group; 73 hips) and anatomical (AS group; 70 hips) stems. Characteristics of sex and age were matched in the two groups by propensity score matching. In both groups, the relationship between the preoperative three-dimensional planning and postoperative stem position, and the relationship between postoperative stem position and femoral neck anteversion (FNA) were evaluated. In the TS group, there were no significant differences in average stem anteversion (SA) between preoperative planning and postoperative placement (36.1° ± 7.0° and 36.6° ± 11.1°, respectively: p = 0.651). The absolute error of SA was 8.1° ± 6.4°. In the AS group, the postoperative SA was significantly smaller than the preoperative planning SA (22.7° ± 11.6° and 30.0° ± 9.3°, respectively: p < 0.001). The absolute error of SA was 9.0° ± 5.8°. The postoperative SA was significantly larger than the FNA in the TS group (36.6° ± 11.1° and 26.3° ± 10.9°, respectively: p < 0.001). However, no significant differences between the two were observed in the AS group (23.7° ± 10.1° and 22.7° ± 11.6°, respectively: p = 0.253). The preoperative planning of intentional increasing anteversion did not show high reproducibility with taper-wedge and anatomical stems. The anatomical stem was placed according to the femoral medullary canal regardless of preoperative planning with increased SA. [ABSTRACT FROM AUTHOR]

When analyzing data, researchers make some choices that are either arbitrary, based on subjective beliefs about the data-generating process, or for which equally justifiable alternative choices could have been made. This wide range of data-analytic choices can be abused and has been one of the underlying causes of the replication crisis in several fields. Recently, the introduction of multiverse analysis provides researchers with a method to evaluate the stability of the results across reasonable choices that could be made when analyzing data. Multiverse analysis is confined to a descriptive role, lacking a proper and comprehensive inferential procedure. Recently, specification curve analysis adds an inferential procedure to multiverse analysis, but this approach is limited to simple cases related to the linear model, and only allows researchers to infer whether at least one specification rejects the null hypothesis, but not which specifications should be selected. In this paper, we present a Post-selection Inference approach to Multiverse Analysis (PIMA) which is a flexible and general inferential approach that considers for all possible models, i.e., the multiverse of reasonable analyses. The approach allows for a wide range of data specifications (i.e., preprocessing) and any generalized linear model; it allows testing the null hypothesis that a given predictor is not associated with the outcome, by combining information from all reasonable models of multiverse analysis, and provides strong control of the family-wise error rate allowing researchers to claim that the null hypothesis can be rejected for any specification that shows a significant effect. The inferential proposal is based on a conditional resampling procedure. We formally prove that the Type I error rate is controlled, and compute the statistical power of the test through a simulation study. Finally, we apply the PIMA procedure to the analysis of a real dataset on the self-reported hesitancy for the COronaVIrus Disease 2019 (COVID-19) vaccine before and after the 2020 lockdown in Italy. We conclude with practical recommendations to be considered when implementing the proposed procedure. [ABSTRACT FROM AUTHOR]

This study explores the effect of the experimenter’s gender/sex and its interaction with the participant’s gender/sex as potential contributors to the replicability crisis, particularly in the man-gendered domain of VR. 75 young men and women from Western France were randomly evaluated by either a man or a woman during a 13-min immersion in a first-person shooter game. Self-administered questionnaires were used to measure variables commonly assessed during VR experiments (sense of presence, cybersickness, video game experience, flow). MANOVAs, ANOVAs and post-hoc comparisons were used. Results indicate that men and women differ in their reports of cybersickness and video game experience when rated by men, whereas they report similar measures when rated by women. These findings are interpreted as consequences of the psychosocial stress triggered by the interaction between the two genders/sexes, as well as the gender conformity effect induced, particularly in women, by the presence of a man in a masculine domain. Corroborating this interpretation, the subjective measure of flow, which is not linked to video games and/or computers, does not seem to be affected by this experimental effect. Methodological precautions are highlighted, notably the brief systematic description of the experimenter, and future exploratory and confirmatory studies are outlined. [ABSTRACT FROM AUTHOR]

This study aims to experimentally assess repeatability and reproducibility of direct tensile strength (DTS) tests with deformability measurements on two types of rocks: Blanco Mera granite (Spain) and Cotta sandstone (Germany). The tests were conducted in four rock mechanics laboratories located in different countries (Canada, Germany, Spain and Sweden). A total of 51 tests were performed on cylindrical specimens of the two rocks, using different test equipment and measuring devices. Mean and standard deviation DTS values were determined in the four laboratories for the granite (5.70 ± 0.32, 6.06 ± 0.11, 3.84 ± 0.50 and 6.76 ± 0.10 MPa) and for the sandstone (1.88 ± 0.07, 1.96 ± 0.06, 1.15 ± 0.32 and 1.74 ± 0.19 MPa), together with Young's moduli and Poisson's ratios in tension, being statistically analysed to evaluate the variability and compare the main results obtained from the participating laboratories. The findings indicate that the DTS test with deformability measurements on cylindrical rock specimens is operationally feasible. However, certain shortcomings have been identified during the course of the experiments with the existing methodologies, such as the one suggested by the ISRM for DTS tests. The results have also shown to be sensitive to appropriate test and strain measurement configurations. The objective of this study was to shed light on these issues and provide new insights for potential future improvements of the existing testing methods. Highlights: An experimental assessment of reproducibility and repeatability of direct tensile strength tests was carried out. Tests were conducted on two rocks (granite, sandstone), in four laboratories located in Canada, Germany, Spain and Sweden. Direct tensile strength test with deformability measurements on cylindrical rock specimens was found operationally feasible. Some shortcomings in current methodologies have been found, such as inappropriate loading rates or no recommendations for deformability measurements. This work provides new insights for potential future improvements of the existing testing methods. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the inter-day reliability of time-domain, frequency-domain, and nonlinear HRV metrics in healthy highly active younger and older adults. The study also assessed the effect of age on the HRV metrics. Methods: Forty-four older adults (34 M, 10F; 59 ± 5 years; V ˙ O 2peak = 40.9 ± 7.6 ml kg−1 min−1) and twenty-two younger adults (16 M, 6F; 22 ± 4 years; V ˙ O 2peak = 47.2 ± 12.8 ml kg−1 min−1) attended the laboratory. Visit one assessed aerobic fitness through an exercise test. In visits two and three, participants completed a 30-min supine RR interval measurement to derive the HRV metrics. Results: The younger group (YG) and older group (OG) demonstrated poor to good day-to-day relative and absolute reliability for all HRV metrics (OG, ICCs = 0.33 to 0.69 and between day CVs = 3.8 to 29.2%; YG, ICCs = 0.37 to 0.93 and between day CVs = 3.5 to 36.5%). There was a significant reduction in ApEn (P < 0.001), SampEn (P = 0.031), RMSSD (P < 0.001), SDNN (P < 0.001), LF power (P < 0.001) and HF power (P < 0.001), HRV metrics with ageing. There was no significant effect of age the complexity metrics DFA α1 (P = 0.107), α2 (P = 0.147) and CI-8 (P = 0.493). Conclusion: HRV metrics are reproducible between days in both healthy highly active younger and older adults. There is a decline in linear and nonlinear HRV metrics with age, albeit there being no age-related change in the nonlinear metrics, DFA α1, α2 and CI-8. [ABSTRACT FROM AUTHOR]

A suitable mixing rule is important for vapor liquid equilibrium (VLE) investigations for mixed refrigerants. In this work, a new excess free energy mixing rule (MRv) was proposed at zero pressure based on the linear relationship between dimensionless parameter 1/(u–1) and α. MRv mixing rule was explicit adopted variable liquid molar volume. The applicable temperature range of MRv could be extended by means of an empirical method to estimate the liquid molar volume for components at high temperatures. Three mixing rules modified Huron-Vidal mixing rule (MHV1), Wong-Sandler mixing rule (WS), and MRv at two reference pressures were used to compare the VLE data in the calculation of 37 mixed refrigerants. Results demonstrated that MRv had a relatively similar accuracy to MHV1 and WS for component and pressure calculation. Moreover, the average excess Gibbs free energy using the MRv mixing rule for the 37 selected mixed refrigerants (0.0013) was much lower than those using the MHV1 (0.0078) and WS (0.0809) mixing rules, which was very valuable for the design and optimization of thermodynamic systems using mixed refrigerants. [ABSTRACT FROM AUTHOR]

The nasal potential difference test (nPD) is an electrophysiological measurement which is altered in patients and animal models with cystic fibrosis (CF). Because protocols and outcomes vary substantially between laboratories, there are concerns over its validity and precision. We performed a systematic literature review (SR) of the nPD to answer the following review questions: A. Is the nasal potential difference similarly affected in CF patients and animal models?", and B. "Is the nPD in human patients and animal models of CF similarly affected by various changes in the experimental set-up?". The review protocol was preregistered on PROSPERO (CRD42021236047). We searched PubMed and Embase with comprehensive search strings. Two independent reviewers screened all references for inclusion and extracted all data. Included were studies about CF which described in vivo nPD measurements in separate CF and control groups. Risk of bias was assessed, and three meta-analyses were performed. We included 130 references describing nPD values for CF and control subjects, which confirmed substantial variation in the experimental design and nPD outcome between groups. The meta-analyses showed a clear difference in baseline nPD values between CF and control subjects, both in animals and in humans. However, baseline nPD values were, on average, lower in animal than in human studies. Reporting of experimental details was poor for both animal and human studies, and urgently needs to improve to ensure reproducibility of experiments within and between species. [ABSTRACT FROM AUTHOR]

Laser-induced graphene (LIG) has received much attention in recent years as a possible transducer material for electroanalytical sensors. Its simplicity of fabrication and good electrochemical performance are typically highlighted. However, we found that unmodified and untreated LIG electrodes had a limited shelf-life for certain electroanalytical applications, likely due to the adsorption of adventitious hydrocarbons from the storage environment. Electrode responses did not change immediately after exposure to ambient conditions but over longer periods of time, probably due to the immense specific surface area of the LIG material. LIG shelf-life is seldomly discussed prominently in the literature, yet overall trends for solutions to this challenge can be identified. Such findings from the literature regarding the long-term storage stability of LIG electrodes, pure and modified, are discussed here along with explanations for likely protective mechanisms. Specifically, applying a protective coating on LIG electrodes after manufacture is possibly the easiest method to preserve electrode functionality and should be identified as a trend for well-performing LIG electrodes in the future. Furthermore, suggested influences of the accompanying LIG microstructure/morphology on electrode characteristics are evaluated. [ABSTRACT FROM AUTHOR]

Background: Quality assurance (QA) and quality control (QC) practices are key tenets that facilitate study and data quality across all applications of untargeted metabolomics. These important practices will strengthen this field and accelerate its success. The Best Practices Working Group (WG) within the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) focuses on community use of QA/QC practices and protocols and aims to identify, catalogue, harmonize, and disseminate current best practices in untargeted metabolomics through community-driven activities. Aim of review: A present goal of the Best Practices WG is to develop a working strategy, or roadmap, that guides the actions of practitioners and progress in the field. The framework in which mQACC operates promotes the harmonization and dissemination of current best QA/QC practice guidance and encourages widespread adoption of these essential QA/QC activities for liquid chromatography-mass spectrometry. Key scientific concepts of review: Community engagement and QA/QC information gathering activities have been occurring through conference workshops, virtual and in-person interactive forum discussions, and community surveys. Seven principal QC stages prioritized by internal discussions of the Best Practices WG have received participant input, feedback and discussion. We outline these stages, each involving a multitude of activities, as the framework for identifying QA/QC best practices. The ultimate planned product of these endeavors is a "living guidance" document of current QA/QC best practices for untargeted metabolomics that will grow and change with the evolution of the field. [ABSTRACT FROM AUTHOR]

While grouping/read-across is widely used to fill data gaps, chemical registration dossiers are often rejected due to weak category justifications based on structural similarity only. Metabolomics provides a route to robust chemical categories via evidence of shared molecular effects across source and target substances. To gain international acceptance, this approach must demonstrate high reliability, and best-practice guidance is required. The MetAbolomics ring Trial for CHemical groupING (MATCHING), comprising six industrial, government and academic ring-trial partners, evaluated inter-laboratory reproducibility and worked towards best-practice. An independent team selected eight substances (WY-14643, 4-chloro-3-nitroaniline, 17α-methyl-testosterone, trenbolone, aniline, dichlorprop-p, 2-chloroaniline, fenofibrate); ring-trial partners were blinded to their identities and modes-of-action. Plasma samples were derived from 28-day rat tests (two doses per substance), aliquoted, and distributed to partners. Each partner applied their preferred liquid chromatography–mass spectrometry (LC–MS) metabolomics workflows to acquire, process, quality assess, statistically analyze and report their grouping results to the European Chemicals Agency, to ensure the blinding conditions of the ring trial. Five of six partners, whose metabolomics datasets passed quality control, correctly identified the grouping of eight test substances into three categories, for both male and female rats. Strikingly, this was achieved even though a range of metabolomics approaches were used. Through assessing intrastudy quality-control samples, the sixth partner observed high technical variation and was unable to group the substances. By comparing workflows, we conclude that some heterogeneity in metabolomics methods is not detrimental to consistent grouping, and that assessing data quality prior to grouping is essential. We recommend development of international guidance for quality-control acceptance criteria. This study demonstrates the reliability of metabolomics for chemical grouping and works towards best-practice. [ABSTRACT FROM AUTHOR]

Since the introduction of the Oddy test in 1973, many museums and cultural institutions have put the method in use, developing their own versions and protocols. Currently the 3-in-1 version, temperature at 60 ºC and 2 g of tested material are set as common practice; however, other variables of the test are not standardized. The purpose of this study is to examine current versions of the Oddy test, to identify differences in the results derived from variations in the procedures, and ultimately raising awareness within the conservation community to work together towards a standardized protocol. In this article, we review the available information on the methodological differences in Oddy test protocols published in the literature related to glassware cleaning, coupon preparation, reaction vessel setup and rating of materials. Based on the review, and to highlight the many variables that could affect the results of the test, seven European cultural institutions working under the H2020 IPERION HS project performed a comparative 3-in-1 Oddy test by blindly evaluating the same ten materials. Each institution used its own test methodology but some guidelines were advised: (1) Detergents as a cleaning procedure for glassware, (2) P600 sandpaper or micromesh pad close to 1500 to prepare metal coupons and (3) 1:100 as water–air ratio. Despite this, differences between institutions' results were still observed. Some of them are due to the differences in the coupons preparation, either in the sanding pattern or in the edge area. In order to separate the contribution of the experimental setup and the subjectivity of the evaluation in the discrepancies, coupons from all institutions have been rated by a single team of judges with experience in the Oddy Test. Results show that differences in the evaluation criteria play a relevant role in the discrepancies of the results, especially for institutions with less experience in the test. These results highlight the need to further standardize the methodology and criteria for visual assessment. Nevertheless, the Oddy test has been found to be reliable for the identification of materials that produce emissions hazardous for the conservation of cultural assets. [ABSTRACT FROM AUTHOR]

Input data collection, quality assurance and preparation are central but time_consuming steps in environmental modeling. Errors due to manual processing of model input data can result in an incorrect representation of an environmental system and may consequently lead to implausible model simulations. Correct input data preparation and thorough quality check at an early stage of the model setup procedure are essential to build confidence in model simulation results. Typically, in environmental model applications, many steps in the input data preparation phase have to be repeated with the inflow of new, additional or corrected data. In this study, we selected the widely used SWAT + ecohydrological model as an illustrative example to investigate challenges related to input data preparation. To assist in these tasks, we developed an R package named SWATprepR, which provides functions for typical and repeating SWAT + model input data preparation tasks. The package supports the preparation of weather input files, atmospheric deposition, soil parameters, crop rotations, and observed (control or calibration) data, to name a few, presently with focus on European applications. The SWATprepR functions are integrated in R script workflows and can help SWAT + modelers to avoid repetitive tasks, secure reproducibility and transparently document the data processing steps. Application of the package is illustrated with a test case of a SWAT + model for a small catchment in central Poland. [ABSTRACT FROM AUTHOR]

Purpose: Submaximal exercise tests (SET) are an easier to conduct and less physically demanding alternative to cardiopulmonary exercise testing for assessment of pre-operative fitness. Assessment of heart rate recovery (HRR) following SETs offers an easily obtained marker of vagal reactivation and sympathetic withdrawal and therefore provides an indication of an individual’s fitness. This study sought to assess the reproducibility of HRR across different workloads and modalities of SET. Methods: Thirty-four healthy volunteers were recruited to undergo two SETs at 40% and 60% of their predicted maximal workload. A second group of thirty-one healthy volunteers were recruited to undergo three SETs of differing modalities; Cycle ergometry, Step and Shuttle Walk tests. HRR was quantified using the conventional indices HRR1 and HRR2 (calculated as heart rate (HR) on exercise cessation minus HR at 1 and 2 min of rest) and a novel area under the HRR vs. time curve (HRRAUC) method. Reproducibility of results was assessed using intra-class correlation coefficient (ICC) and limits of agreements. Results: The results showed that HRR1 and HRR2 were poorly reproducible across differing workloads and exercise modalities (ICC < 0.45 for all comparisons) whereas HRRAUC proved to be at least moderately reproducible (ICC > 0.52 for all comparisons). Conclusions: These results suggest that HRRAUC may be a superior way of quantifying HRR following SETs, adding objectivity to SET results. Quantifying HRRAUC could prove to have useful clinical applications for pre-operative risk assessment, assessing fitness to undergo treatment and monitoring disease progression. [ABSTRACT FROM AUTHOR]

Knowledge Graphs (KGs) present factual information about domains of interest. They are used in a wide variety of applications and in different domains, serving as powerful backbones for organizing and extracting knowledge from complex data. In both industry and academia, a variety of platforms have been proposed for managing Knowledge Graphs. To use the full potential of KGs within these platforms, it is essential to have proper provenance management to understand where certain information in a KG stems from. This plays an important role in increasing trust and supporting open science principles. It enables reproducibility and updatability of KGs. In this paper, we propose a framework for provenance management of KG generation within a web portal. We present how our framework captures, stores, and retrieves provenance information. Our provenance representation is aligned with the standardized W3C Provenance Ontology. Through our framework, we can rerun the KG generation process over the same or different source data. With this, we support four applications: reproducibility, altered rerun, undo operation, and provenance retrieval. In summary, our framework aligns with the core principles of open science. By promoting transparency and reproducibility, it enhances the reliability and trustworthiness of research outcomes. [ABSTRACT FROM AUTHOR]

Despite algorithmic advancements in the field of machine learning, a need for improvement in the infrastructure supporting machine learning development and research has become increasingly apparent. Machine learning experiments usually tend to be more ad-hoc in nature, and results are communicated most often in the form of a publication. Experimental details are often omitted due to size or time constraints, or simply because the complexity in terms of technical setup or parametrization became intractable. Even access to code bases, disregard important properties of the environment and experimental setup, like for example random generators or computing infrastructure. At the same time, tracking and communicating an often inherently exploratory scientific process is a task with considerable effort. We explored different venues to tackle these issues from a data science engineering point of view. The efforts resulted in PyPads, a framework providing an infrastructure to extend experimental setups with logging, communication and analysis features in a mostly non-intrusive way. PyPads can be extended to different Python-based frameworks, utilizing community driven, descriptive metadata in an effort to harmonize library specific logs in an ontology. Meanwhile, we also try to emphasize similarities to practices in software engineering, which have turned out to be essential in practical applications. [ABSTRACT FROM AUTHOR]

Fact-checking agencies assess and score the truthfulness of politicians’ claims to foster their electoral accountability. Fact-checking is sometimes presented as a quasi-scientific activity, based on reproducible verification protocols that would guarantee an unbiased assessment. We will study these verification protocols and discuss under which conditions fact-checking could achieve effective reproducibility. Through an analysis of the methodological norms in verification protocols, we will argue that achieving reproducible fact-checking may not help much in rendering politicians accountable. Political fact-checkers do not deliver either reproducibility or accountability today, and there are reasons to think that traditional quality journalism may serve liberal democracies better. [ABSTRACT FROM AUTHOR]

Owing to globalization, the popular indigenous products from various ethnical backgrounds are increasingly making their presence felt all over the world. This opens up a new arena for food technologists to conduct intensive research and developmental activities on the indigenous products. In this study, six popular Indian rice products viz. plain rice, pulao, kheer, idli, khichdi and pakoda were formulated and evaluated for their proximate composition, sensory attributes and textural parameters. Out of these, kheer with semi-fluid consistency had the highest moisture content and the lowest protein and fiber contents. Kheer is similar to rice pudding consumed in the U.S.A. and Europe. Fat content was the highest in pakoda being a crispy fried product. Khichdi being a cereal pulse combination product had the highest protein content. Khichdi is also the national dish of India. The overall acceptability scores were high for pakoda, pulao and kheer which were 8.60, 7.90 and 7.30, respectively. Electromyographic analysis was conducted for in vivo textural evaluation of formulated rice products. The analysis showed reproducible masticatory behavior of human subjects within an EMG session. Twenty-five masticatory parameters, which could establish significant (p < 0.05) differences between textural perceptions among the formulated rice products, were used for cluster analysis followed by principal component analysis (PCA). The PCA resulted in one principal component which could explain data variance of up to 93%. Further, significant positive correlations were found between EMG parameters and sensory textural attributes indicating applicability of electromyography for comprehensive textural evaluation of formulated rice products. [ABSTRACT FROM AUTHOR]

Over the past two decades, advances in computational power and data availability combined with increased accessibility to pre-trained models have led to an exponential rise in machine learning (ML) publications. While ML may have the potential to transform healthcare, this sharp increase in ML research output without focus on methodological rigor and standard reporting guidelines has fueled a reproducibility crisis. In addition, the rapidly growing complexity of these models compromises their interpretability, which currently impedes their successful and widespread clinical adoption. In medicine, where failure of such models may have severe implications for patients' health, the high requirements for accuracy, robustness, and interpretability confront ML researchers with a unique set of challenges. In this review, we discuss the semantics of reproducibility and interpretability, as well as related issues and challenges, and outline possible solutions to counteracting the "black box". To foster reproducibility, standard reporting guidelines need to be further developed and data or code sharing encouraged. Editors and reviewers may equally play a critical role by establishing high methodological standards and thus preventing the dissemination of low-quality ML publications. To foster interpretable learning, the use of simpler models more suitable for medical data can inform the clinician how results are generated based on input data. Model-agnostic explanation tools, sensitivity analysis, and hidden layer representations constitute further promising approaches to increase interpretability. Balancing model performance and interpretability are important to ensure clinical applicability. We have now reached a critical moment for ML in medicine, where addressing these issues and implementing appropriate solutions will be vital for the future evolution of the field. [ABSTRACT FROM AUTHOR]

Purpose: The International Ki67 Working Group (IKWG) has developed training for immunohistochemistry (IHC) scoring reproducibility and recommends cut points of ≤ 5% and ≥ 30% for prognosis in ER+, HER2−, stage I/II breast cancer. We examined scoring reproducibility following IKWG training and evaluated these cut points for selecting patients for further testing with the 21-gene Recurrence Score (RS) assay. Methods: We included 307 women aged 50+ years with node-negative, ER+PR+HER2− breast cancer and with available RS results. Slides from the diagnostic biopsy were stained for Ki67 and scored using digital image analysis (IA). Two IHC pathologists underwent IKWG training and visually scored slides, blinded to each other and IA readings. Interobserver reproducibility was examined using intraclass correlation (ICC) and Kappa statistics. Results: Depending on reader, 8.8–16.0% of our cohort had Ki67 ≤ 5% and 11.4–22.5% had scores ≥ 30%. The ICC for Ki67 scores by the two pathologists was 0.82 (95% CI 0.78–0.85); it was 0.79 (95% CI 0.74–0.83) for pathologist 1 and IA and 0.76 (95% CI 0.71–0.80) for pathologist 2 and IA. For Ki67 scores ≤ 5%, the percentages with RS < 26 were 92.6%, 91.8%, and 90.9% for pathologist 1, pathologist 2, and IA, respectively. For Ki67 scores ≥ 30%, the percentages with RS ≥ 26 were 41.5%, 51.4%, and 27.5%, respectively. Conclusion: The IKWG's Ki67 training resulted in moderate to strong reproducibility across readers but cut points had only moderate overlap with RS cut points, especially for Ki67 ≥ 30% and RS ≥ 26; thus, their clinical utility for a 21-gene assay testing pathway remains unclear. [ABSTRACT FROM AUTHOR]

Knowledge pertaining to scholarly publishing is not limited to information held within academic papers, and within a complex publishing environment that is in constant flux due to challenges and threats, there is interest in knowing how journals are adjusting to these parameters. The Internet Archive is a free and easy way to archive information that is found on websites. We recently argued for its use in the archival of website-based citations, and expand those arguments herein to focus on the importance to archive journal editorial boards, for three reasons: first, journals might not have any formal mechanisms to register changes in the editorial constitution of the board; second, there is historical importance in appreciating changes to editorial board constituency, including changes to gender representation; and third, changes might be made opaquely to hide or masquerade information that is intricately linked to the historical aspect of that journal. Our interest is thus not only within a historical prism, but also from a bibliometric point of view, given that the editorial board defines—to some extent—the journal's content by serving as its gatekeepers of quality. We attempted to archive the editorial board pages of 46 journal editorial board URLs, achieving 100% mementos. [ABSTRACT FROM AUTHOR]

The objective of this study was to evaluate the intra- and inter-rater reliability and agreement between conditions with and without a special device (SD) in the evaluation of the patellar tendon (PT) cross-sectional area (CSA). Forty trained adult volunteers participated in the study. With the knee positioned at 90°, the ultrasound probe was placed in the transverse plane at 25, 50, and 75% of the PT length. Two raters and one analyzer obtained the images. We use a two-way ANOVA with a significance level of α = 0.05. No significant differences were found between raters or conditions. Intra-rater reliability ranged from moderate to good. Inter-rater reliability without the SD ranged from low to good, improving from moderate to good when the SD was used. Evaluation of the PT ends showed a lower coefficient of variation with the SD. We observed a moderate correlation at the ends and a strong correlation in the middle between conditions. The mean difference in the three positions is small (~ 0.013 cm2/ ~ 1.7%) with an upper limit of 43.2% and a lower limit of 32.5%. Therefore, we conclude that the use of the SD can be employed for evaluating the PT ends, while for the central region, it becomes optional. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the reproducibility of radiomics features derived via different pre-processing settings from paired T2-weighted imaging (T2WI) prostate lesions acquired within a short interval, to select the setting that yields the highest number of reproducible features, and to evaluate the impact of disease characteristics (i.e., clinical variables) on features reproducibility. Materials and methods: A dataset of 50 patients imaged using T2WI at 2 consecutive examinations was used. The dataset was pre-processed using 48 different settings. A total of 107 radiomics features were extracted from manual delineations of 74 lesions. The inter-scan reproducibility of each feature was measured using the intra-class correlation coefficient (ICC), with ICC values > 0.75 considered good. Statistical differences were assessed using Mann–Whitney U and Kruskal–Wallis tests. Results: The pre-processing parameters strongly influenced the reproducibility of radiomics features of T2WI prostate lesions. The setting that yielded the highest number of features (25 features) with high reproducibility was the relative discretization with a fixed bin number of 64, no signal intensity normalization, and outlier filtering by excluding outliers. Disease characteristics did not significantly impact the reproducibility of radiomics features. Conclusion: The reproducibility of T2WI radiomics features was significantly influenced by pre-processing parameters, but not by disease characteristics. The selected pre-processing setting yielded 25 reproducible features. [ABSTRACT FROM AUTHOR]

Standard transthoracic echocardiography is considered the non-invasive gold standard for the diagnosis of most cardiac diseases. Defining reproducibility, repeatability, and reliability of this exam is imperative to reduce errors in clinical evaluations. The present study aimed at: (1) evaluating the reproducibility and repeatability of 15 echocardiographic parameters in dogs by analyzing measurements obtained from several operators with different levels of experience and comparing them to the ones obtained from two board-certified operators (gold standards - GSs); (2) assessing whether different formative paths have an influence on the variability of the echocardiographic measurements. Fifty-one operators have been included in this study, along with two diplomates of the European College of Veterinary Internal Medicine - Cardiology. Ten dogs were enrolled, 5 Golden Retrievers and 5 Cavalier King Charles Spaniels. Echocardiographic examination was performed on each dog by one GS and several operators on the same day. Results show the highest deviation from the GS and a poor inter-operator reproducibility for the M-mode measurements of the interventricular septum and the left ventricular free wall. Differently, M-mode-obtained internal diameters of the left ventricle in systole and diastole, and measurements of the aortic annulus and root show moderate to excellent intra- and inter-operator reliability and a good concordance with the GSs, demonstrating that all the operators correctly assess left ventricular systolic function and dilation, and evaluate the aortic valve. Furthermore, a specialist clinical activity, more than the acquired theoretical knowledge, affects the reliability of the echocardiographic examination by reducing the difference from the GS' measurements. [ABSTRACT FROM AUTHOR]

Process capabilities are usually distorted by the gage errors which yield two different values, i.e., the observed ( O C p ) and the actual process capability index ( A C p ). This study highlights the relationships between the A C p and O C p through the signal-to-noise ratio (SNR) to jointly assess the two capability indices and the gauge. Specifically, it will be possible to inform about the likelihoods that a process capability is measured by an imperfect gauge. In our analysis, both probability distributions of the estimated A C ^ p and O C ^ p will be presented in closed forms as a function of the SNR. Besides, benchmark values of the SNR are established, therefore, instead of relying on different SNR margins to judge the measurement system, we describe the system by a characteristic curve (called α-β curve). The curve is a visual representation that demonstrates the precision of the measurement gauge. Here, the selection of α or β specifies the critical capability value. Moreover, the two types of errors (I&II) are also established to find the chances that the measurements have been made under the assumption of actual or observed distributions. To test and validate our analysis, two literature case studies have been selected for further investigation. It was found that the variance of the observed capability is always lower than the actual capability owed to left skewness in the distribution of the observed index. The analysis also shows that depending solely on SNR values may not verify if the data was collected using a faulty gauge. [ABSTRACT FROM AUTHOR]

Clarivate's Highly Cited Researchers (HCR) list is one of the most important quantitative performance indicators in science and influences individual careers and also the reputation of research institutions. However, many researchers and representatives of institutions and funding agencies are not familiar with the method that is applied to generate the HCR lists. We therefore provide a detailed description of Clarivate's method and give an example to illustrate how HCR are identified. While Clarivate provides the complete HCR lists and a detailed description of the method used for identifying HCR, the detailed analysis with actual numbers is not published. It is therefore not entirely transparent how exactly the HCR were identified, and which authors were excluded from the initial list, e.g. due to scientific misconduct. It is also impossible to check the analysis for errors. Given the prestige and weight that is attributed to Clarivate's HCR list, we call for transparency of the data and analysis behind the HCR list. [ABSTRACT FROM AUTHOR]

A technique is developed to quantify the ultra-trace 231Pa (35–3904 ag) concentration in seawater using multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS). The method is a modification of the process developed by Shen et al. (Anal Chem 75(5):1075–1079, 2003. https://doi.org/10.1021/ac026247r) and extends it to the application of very low levels of actinides, and the 35 ag 231Pa can be measured with a precision of 15%. The total process blank for the water column was 0.02 ag/g, while the values of the large and small particles were ~ 30 ag/g. The ionization efficiency (ions generated/atom loaded) varies from 0.7 to 2.4%. The measurement time is 2–5 min. The amount of 231Pa needed to produce 231Pa data with an uncertainty of ± 0.8–15% is 35–3904 ag (~ 0.9 × 105 to 10 × 106 atoms). Replicate measurements of known standards and seawater samples demonstrate that the analytical precision approximates that expected from counting statistics, and that based on detection limits of 52 ag, 55 ag, and 28 ag, protactinium can be detected in a minimum seawater sample size of ~ 2.6 L for small suspended particulate matter (> 0.8 μm and < 51 μm), ~ 3.0 L for large suspended particulate matter (> 51 μm), and ~ 56 mL for filtered (< 0.45 μm) seawater. The concentration of 231Pa (several attograms per liter) can be determined with an uncertainty of ± 2–8% (2σ) for suspended particulate matter filtered from ~ 60 L of seawater. For the dissolved fraction, ~ 1 L of seawater yields 231Pa measurements with a precision of 0.8–10%. The sample size requirements are several orders of magnitude less than traditional decay-counting techniques, and the precision is better than that previously reported for ICP-MS techniques. Our technique can also be applied to other environmental samples, including river, lake, and cave water samples. [ABSTRACT FROM AUTHOR]

Green extraction of supercritical liquid CO2 (SCFE-CO2) using co-solvent methanol can produce a more complete phenolic acid composition and a higher quantity when compared to those without using co-solvent. The extract was devoid of toxicity. SCFE-CO2 is carried out by putting 100 g of Quercus infectoria gall of size 0.3 mm into extraction tube at temperature of 60 °C and the pressure of 20 MPa with a CO2 flow rate of 25 ml/min using co-solvent methanol with variation of flow speed 0.05, 0.5, 1.5, 3, and 6 for 60 min. The extract is analyzed using LC–MS/MS, the total phenolic content is determined using the Folin-Ceocateu method, and the toxicity value is determined using the Vero cell. According to the results, the green method of extracting SCFE-CO2 with methanol co-solvent can produce a peak and identify about 27 phenolic compounds, and increasing the rate of flow of methane co-solvent will greatly affect the outcome of the extraction to a flow rate of 0.5 ml/min, while adding a co-solvent with a flow speed above 0.5 does not affect the result. Repeated extraction of some of the largest phenolic peaks provide phenol content with minimal extract variability (div. sd. 0.1%), and the addition of soluble methanol will also increase the TPC concentration but does not increase the IC50 toxicity value above 1000. [ABSTRACT FROM AUTHOR]