Using bootstrap to compare the validity of PRO measures in discriminating among CKD patients

BACKGROUND: Patient-reported outcome (PRO) research requires valid and sensitive measures. Relative Validity (RV) offers an objective way to compare the validity of different PRO measures in discriminating groups of patients or occasions. There is no significance test associated with RV. We applied bootstrap to estimate the confidence interval (CI) of RV to better interpret the differences in RV. METHODS: The CKD-specific legacy (KDQOL Burden, Symptom, and Effect), generic health scales (SF-12), and Kidney Disease Impact Scale (KDIS) were administrated to 453 CKD patients. ANOVA-based RV coefficients were computed to compare how well each scale discriminated between three clinically-defined severity groups (Dialysis \u3e Stage 3-5 \u3e Transplant). Bootstrap was used to construct CI to determine whether the differences in RV were significant in comparisons between each scale and the best legacy standard- KDQOL Burden. Factors of sample size, number of bootstrap replications, bootstrap method were varied to investigate their impacts. RESULTS: In comparison with KDQOL Burden (RV=1), using 95% CI, differences were non-significant for KDIS (RV=1.13), KDQOL Effect (RV=.99), SF-12 RP (RV=.77) and PF (RV=.70). SF-12 PCS (RV=.60) was at borderline. The other measures were significantly poorer in discriminating the patients. Sample size played a substantial role. 300 patients for 3 groups greatly reduced the standard errors compared to 100 patients. A larger sample size greatly increased the power of detecting the differences. The number of replications did not have consequential influence. The types of BCa and percentile intervals were preferred as all bootstrap distributions were skewed. The magnitude of chosen standard measure’s F-statistics appeared to have a noticeable impact on CI too. CONCLUSIONS: Bootstrapping appears to be valuable in comparing the validity of PRO measures from a statistical perspective. The significance test of RV was affected by the sample size, magnitude of RV, and F-statistic of standard measure

Dynamics and Impacts of Human-Algorithm Consensus in Logistics Scheduling: Evidence from A Field Experiment

Algorithms are being implemented to aid human decision-making and most studies on human-algorithm interactions focus on how to improve human-algorithm cooperation. However, excessive reliance on algorithms in decision-making may hinder the complementary value of humans and algorithms. There is a lack of empirical evidence on the impacts of human-algorithm consensus in collaborative decision-making. To address this gap, this paper reports a large-scale field experiment conducted by one of China\u27s largest logistics firms in the context of route scheduling. The experiment involved assigning routes to either a treatment group, where algorithms and human operators collaborated in decision-making, or a control group, where human operators made decisions independently. We plan to collect data to evaluate the effects of algorithm implementation and to analyze the patterns and effects of human-algorithm consensus in a long-term cooperation. Our study aims to contribute to the literature on human-algorithm interactions in operational decisions

Standardizing disease-specific quality of life measures across multiple chronic conditions: development and initial evaluation of the QOL Disease Impact Scale (QDIS(R))

BACKGROUND: To document the development and evaluation of the Quality of life Disease Impact Scale (QDIS(R)), a measure that standardizes item content and scoring across chronic conditions and provides a summary, norm-based QOL impact score for each disease. METHODS: A bank of 49 disease impact items was constructed from previously-used descriptions of health impact to represent ten frequently-measured quality of life (QOL) content areas and operational definitions successfully utilized in generic QOL surveys. In contrast to health in general, all items were administered with attribution to a specific disease (osteoarthritis, rheumatoid arthritis, angina, myocardial infarction, congestive heart failure, chronic kidney disease (CKD), diabetes, asthma, or COPD). Responses from 5418 adults were analyzed as five disease groups: arthritis, cardiovascular, CKD, diabetes, and respiratory. Unidimensionality, item parameter and scale-level invariance, reliability, validity and responsiveness to change during 9-month follow-up were evaluated by disease group and for all groups combined using multi-group confirmatory factor analysis (MGCFA), item response theory (IRT) and analysis of variance methods. QDIS was normed in an independent chronically ill US population sample (N = 4120). RESULTS: MGCFA confirmed a 1-factor model, justifying a summary score estimated using equal parameters for each item across disease groups. In support of standardized IRT-based scoring, correlations were very high between disease-specific and standardized IRT item slopes (r = 0.88-0.96), thresholds (r = 0.93-0.99) and person-level scores (r \u3e /= 0.99). Internal consistency, test-retest and person-level IRT reliability were consistently satisfactory across groups. In support of interpreting QDIS as a disease-specific measure, in comparison with generic measures, QDIS consistently discriminated markedly better across disease severity levels, correlated higher with other disease-specific measures in cross-sectional tests, and was more responsive in comparisons of groups with better, same or worse evaluations of disease-specific outcomes at the 9-month follow-up. CONCLUSIONS: Standardization of content and scoring across diseases was shown to be justified psychometrically and enabled the first summary measure of disease-specific QOL impact normed in the chronically ill population. This disease-specific approach substantially improves discriminant validity and responsiveness over generic measures and provides a basis for better understanding the relative QOL impact of multiple chronic conditions in research and clinical practice

Molecular basis for N-terminal acetylation by human NatE and its modulation by HYPK

The human N-terminal acetyltransferase E (NatE) contains NAA10 and NAA50 catalytic, and NAA15 auxiliary subunits and associates with HYPK, a protein with intrinsic NAA10 inhibitory activity. NatE co-translationally acetylates the N-terminus of half the proteome to mediate diverse biological processes, including protein half-life, localization, and interaction. The molecular basis for how NatE and HYPK cooperate is unknown. Here, we report the cryo-EM structures of human NatE and NatE/HYPK complexes and associated biochemistry. We reveal that NAA50 and HYPK exhibit negative cooperative binding to NAA15 in vitro and in human cells by inducing NAA15 shifts in opposing directions. NAA50 and HYPK each contribute to NAA10 activity inhibition through structural alteration of the NAA10 substrate-binding site. NAA50 activity is increased through NAA15 tethering, but is inhibited by HYPK through structural alteration of the NatE substrate-binding site. These studies reveal the molecular basis for coordinated N-terminal acetylation by NatE and HYPK.publishedVersio

Using the bootstrap to establish statistical significance for relative validity comparisons among patient-reported outcome measures

BACKGROUND: Relative validity (RV), a ratio of ANOVA F-statistics, is often used to compare the validity of patient-reported outcome (PRO) measures. We used the bootstrap to establish the statistical significance of the RV and to identify key factors affecting its significance. METHODS: Based on responses from 453 chronic kidney disease (CKD) patients to 16 CKD-specific and generic PRO measures, RVs were computed to determine how well each measure discriminated across clinically-defined groups of patients compared to the most discriminating (reference) measure. Statistical significance of RV was quantified by the 95% bootstrap confidence interval. Simulations examined the effects of sample size, denominator F-statistic, correlation between comparator and reference measures, and number of bootstrap replicates. RESULTS: The statistical significance of the RV increased as the magnitude of denominator F-statistic increased or as the correlation between comparator and reference measures increased. A denominator F-statistic of 57 conveyed sufficient power (80%) to detect an RV of 0.6 for two measures correlated at r = 0.7. Larger denominator F-statistics or higher correlations provided greater power. Larger sample size with a fixed denominator F-statistic or more bootstrap replicates (beyond 500) had minimal impact. CONCLUSIONS: The bootstrap is valuable for establishing the statistical significance of RV estimates. A reasonably large denominator F-statistic (F \u3e 57) is required for adequate power when using the RV to compare the validity of measures with small or moderate correlations (r \u3c 0.7). Substantially greater power can be achieved when comparing measures of a very high correlation (r \u3e 0.9)

Differential association of dietary scores with the risk of type 2 diabetes by metabotype

Purpose We aimed to examine the association between dietary patterns and type 2 diabetes mellitus (T2DM) while considering the potential effect modification by metabolic phenotypes (metabotypes). Additionally, we aimed to explore the association between dietary scores and prediabetes. Methods A total of 1460 participants (11.8% with T2DM) from the cross-sectional population-based KORA FF4 study were included. Participants, classified into three metabotype subgroups, had both their FSAm-NPS dietary index (underpinning the Nutri-Score) and ultra-processed foods (UPF) intake (using NOVA classification) calculated. Glucose tolerance status was assessed via oral glucose tolerance tests (OGTT) in non-diabetic participants and was classified according to the American Diabetes Association criteria. Logistic regression models were used for both the overall and metabotype-stratified analyses of dietary scores’ association with T2DM, and multinomial probit models for their association with prediabetes. Results Participants who had a diet with a higher FSAm-NPS dietary index (i.e., a lower diet quality) or a greater percentage of UPF consumption showed a positive association with T2DM. Stratified analyses demonstrated a strengthened association between UPF consumption and T2DM specifically in the metabolically most unfavorable metabotype (Odds Ratio, OR 1.92; 95% Confidence Interval, CI 1.35, 2.73). A diet with a higher FSAm-NPS dietary index was also positively associated with prediabetes (OR 1.19; 95% CI 1.04, 1.35). Conclusion Our study suggests different associations between poorer diet quality and T2DM across individuals exhibiting diverse metabotypes, pointing to the option for stratified dietary interventions in diabetes prevention

Confirmatory factor analysis of the thyroid-related quality of life questionnaire ThyPRO

Background and aim. Thyroid diseases are prevalent and chronic. With treatment, quality of life is restored in most, but not all patients. Construct validity of the thyroid-related quality of life questionnaire, ThyPRO, has been established by multi-trait scaling, but not evaluated with more elaborate methods. The purpose of the present study was to evaluate dimensionality of the ThyPRO scales and to attempt to understand possible item misfit through structural equation modeling for categorical data. Methods. The current 84-item version of ThyPRO consists of 13 scales, covering domains of physical (4 scales) and mental (2 scales) symptoms, function and well-being (3 scales) and participation/social function (4 scales). The data were collected from a cross-sectional sample of 907 thyroid patients. One-factor confirmatory models were fitted to each scale, and evaluated by model fit statistics (comparative fit index \u3e 0.95, root mean square error of approximation \u3c 0.08), magnitude of factor loadings, model residual correlations and modification indices (MI). Indications of multi-dimensionality were tested in bi-factor models. Possible item misfit was evaluated in a combined, investigational model. Results. Each ThyPRO scale was adequately represented by a unidimensional model after minor revisions. Eleven items were identified in the unidimensional models as potentially misfitting and were investigated further by multidimensional modeling. Conclusion. Elaborate psychometric modeling supported the construct validity of the ThyPRO. However, 11 potentially misfitting items and 18 items with local dependence to other items are candidates for removal in future item reduction processes

The capsule of Porphyromonas gingivalis reduces the immune response of human gingival fibroblasts

BACKGROUND: Periodontitis is a bacterial infection of the periodontal tissues. The Gram-negative anaerobic bacterium Porphyromonas gingivalis is considered a major causative agent. One of the virulence factors of P. gingivalis is capsular polysaccharide (CPS). Non-encapsulated strains have been shown to be less virulent in mouse models than encapsulated strains. RESULTS: To examine the role of the CPS in host-pathogen interactions we constructed an insertional isogenic P. gingivalis knockout in the epimerase-coding gene epsC that is located at the end of the CPS biosynthesis locus. This mutant was subsequently shown to be non-encapsulated. K1 capsule biosynthesis could be restored by in trans expression of an intact epsC gene. We used the epsC mutant, the W83 wild type strain and the complemented mutant to challenge human gingival fibroblasts to examine the immune response by quantification of IL-1β, IL-6 and IL-8 transcription levels. For each of the cytokines significantly higher expression levels were found when fibroblasts were challenged with the epsC mutant compared to those challenged with the W83 wild type, ranging from two times higher for IL-1β to five times higher for IL-8. CONCLUSIONS: These experiments provide the first evidence that P. gingivalis CPS acts as an interface between the pathogen and the host that may reduce the host's pro-inflammatory immune response. The higher virulence of encapsulated strains may be caused by this phenomenon which enables the bacteria to evade the immune system

The Molecular Mechanism of \u3cem\u3eN\u3c/em\u3e-Acetylglucosamine Side-Chain Attachment to the Lancefield Group A Carbohydrate in \u3cem\u3eStreptococcus pyogenes\u3c/em\u3e

In many Lactobacillales species (i.e. lactic acid bacteria), peptidoglycan is decorated by polyrhamnose polysaccharides that are critical for cell envelope integrity and cell shape and also represent key antigenic determinants. Despite the biological importance of these polysaccharides, their biosynthetic pathways have received limited attention. The important human pathogen, Streptococcus pyogenes, synthesizes a key antigenic surface polymer, the Lancefield group A carbohydrate (GAC). GAC is covalently attached to peptidoglycan and consists of a polyrhamnose polymer, with N-acetylglucosamine (GlcNAc) side chains, which is an essential virulence determinant. The molecular details of the mechanism of polyrhamnose modification with GlcNAc are currently unknown. In this report, using molecular genetics, analytical chemistry, and mass spectrometry analysis, we demonstrated that GAC biosynthesis requires two distinct undecaprenol-linked GlcNAc-lipid intermediates: GlcNAc-pyrophosphoryl-undecaprenol (GlcNAc-P-P-Und) produced by the GlcNAc-phosphate transferase GacO and GlcNAc-phosphate-undecaprenol (GlcNAc-P-Und) produced by the glycosyltransferase GacI. Further investigations revealed that the GAC polyrhamnose backbone is assembled on GlcNAc-P-P-Und. Our results also suggested that a GT-C glycosyltransferase, GacL, transfers GlcNAc from GlcNAc-P-Und to polyrhamnose. Moreover, GacJ, a small membrane-associated protein, formed a complex with GacI and significantly stimulated its catalytic activity. Of note, we observed that GacI homologs perform a similar function in Streptococcus agalactiae and Enterococcus faecalis. In conclusion, the elucidation of GAC biosynthesis in S. pyogenes reported here enhances our understanding of how other Gram-positive bacteria produce essential components of their cell wall

Climate change adaptation strategies to support Australia's estuarine and coastal marine ecosystems

Scientists from James Cook University, CSIRO and Griffith University collaborated to develop a process for planning Climate Change Adaptation actions to support the resilience and productivity of Australia's estuarine and coastal marine ecosystems into the future. This 3 year project involved extensive review of Climate Change Adaptation strategies from across the world and evaluated their usefulness under Australian conditions through reviewing case studies, through interviews with workers from all levels of science and management from across Australia, and by reviewing modelling tools and using advanced qualitative modelling. The project was developed in response to the threats to the fisheries values, biodiversity and ecosystem functions posed by Climate Change on Australia’s estuarine and coastal marine ecosystems that are already heavily impacted by changes in land and water use. This was undertaken in the recognition that large-scale strategy thinking was necessary for a country with a great diversity of estuary and coastal marine ecosystems, plant and animal assemblages, climates, and region-specific threats and matters of contention. The project developed a set of general principles to help direct estuarine and coastal adaptation strategies whatever the particular situation – to help guide, but not constrain, the development of informed adaptation policies, plans and actions