Nested Models Research Articles

Incremental prognostic value of late gadolinium enhancement granularity in patients with hypertrophic cardiomyopathy

Abstract Background The prognostic stratification of hypertrophic cardiomyopathy (HCM) using cardiac magnetic resonance (CMR) is based on the extent of late gadolinium enhancement (LGE). To enhance risk stratification for sudden cardiac death (SCD), the ESC has recently added LGE extent in the guidelines, at ≥15% of LV mass. However, SCD has become an uncommon event in this population, and mortality is now mostly related to other phenotypes, such as atrial fibrillation, stroke, and heart failure. While previous studies have showed the prognostic value of LGE to predict all-cause mortality, the prognostic impact of additional LGE features is not well established. Therefore, we aimed to assess the incremental prognostic value of the granularity of LGE including extent, location, and pattern in patients with HCM to predict all-cause death. Methods Between 2008 and 2021, all patients referred for HCM assessment using CMR, without history of coronary artery disease (CAD) or clinical history of myocarditis were prospectively recruited in two French centers. The outcome was all-cause death using the French National Registry of Death. The concept of "LGE granularity" was defined as a comprehensive model combining all the following LGE features with extent (by segment), location (septal or others), and pattern (midwall and/or subepicardial). Using nested Cox proportional hazard models, the additional predictive value of LGE features was assessed by the C-statistic increment, the continuous net reclassification improvement (NRI), the integrative discrimination index (IDI) and the global Chi-2. Results Among the 2,672 included patients (52±7 years, 56% males), 862 (32%) had LGE. After a median (IQR) follow-up of 9 (7–11) years, 447 (17%) patients died. Survival curves show an increased risk for LGE presence (log-rank p<0.001, Figure 1A). After adjustment for traditional prognosticators in the overall population (N=2,672), the presence of LGE was strongly associated with all-cause death (adjusted hazard ratio (HR) 3.96, 95% CI: 3.26-4.80, p<0.001). In the subgroup of patients with LGE (n=862), survival curves showed that all parameters defining the LGE granularity were associated with a higher risk of all-cause death (all p<0.001, Figure 1B). A nested Cox model adjusted on traditional prognosticators showed that the LGE extent, location and pattern were all independently associated with all-cause death (all p<0.001, Figure 2). The model of "LGE granularity" combining all independently significative LGE features showed the best improvement in model discrimination and reclassification above traditional prognosticators (C-statistic improvement: 0.90; NRI=41.9%; IDI=13.2%, Chi-2 global=450, all p<0.001; LR-test p<0.001, Figure 2). Conclusion In a large cohort of HCM patients, the "LGE granularity" model combining the extent, location, and pattern of LGE had an incremental prognostic value over and above traditional prognosticators to predict all-cause death.Prognostic value of LGE granularityIncremental prognostic value LGE granula

Ophthalmological Examination and Imaging Features that Better Predict Risk of Angle Closure in Siblings

Characteristics of individuals with angle closure may be useful in targeted screening of family members. Here, we assess if findings gathered during examination and imaging of patients with a known angle closure diagnosis (probands) could better determine the risk of angle closure in the patients' siblings. Cross-sectional study of patients with known angle closure and their siblings. Participants, and Controls: South Indian patients (probands) 30 years and older with open angles, suspect primary angle closure (PACS), or primary angle closure/primary angle closure glaucoma (PAC/PACG), and a biological sibling age 30 years or older (n=292 proband/sibling pairs). Demographic data, relevant ocular history, and a comprehensive ophthalmic examination with Anterior Segment Optical Coherence Tomography (ASOCT) were obtained. Three clinically relevant models were created to analyze the contribution of specific proband factors in predicting sibling angle closure diagnosis, using demographic (age, gender), ocular exam (gonioscopy, optic nerve exam, visual acuity, intraocular pressure [IOP]), and ASOCT features to improve prediction beyond proband diagnosis alone evaluated by log likelihood ratio testing and statistical comparison of receiver operating characteristics (ROC). Sibling angle closure diagnostic accuracy. Demographic and ocular exam metrics did not improve the prediction of sibling angle closure for all three outcomes (sibling diagnosis: (1) PACS/PAC/PACG vs OA, (2) PAC/PACG vs PACS/OA, and (3) PAC/PACG vs PACS), adding no model improvement when compared to diagnosis alone. Models adding ASOCT metrics to the prior model including proband diagnosis, demographics and ocular exam measures led to significantly improved prediction of 2 of the 3 angle closure outcomes. Specifically, improvement was noted via likelihood ratio testing for prediction of PAC/PACG vs PACS/OA (p=0.01), or PAC/PACG vs PACS (p=0.001). For all 3 angle closure outcomes, ROC comparisons demonstrated significant improvement in AUC between the three models predicting sibling outcomes, demonstrating an increase in AUC with each successive nested model across all 3 sibling angle closure outcomes. Structural features of eyes with angle closure may assist in stratifying the risk of angle closure in patients' siblings. Further studies should consider evaluating this approach to achieve more targeted screenings.

Response of rice's hydraulic transport and photosynthetic capacity to drought-flood abrupt alternation

Knowledge of the potential interactive effects of drought and flooding on the maximum carboxylation rate at 25°C (Vmax25) and maximum hydraulic conductance (Kmax) is essential for the precise modeling of crop growth, water-carbon cycling, and crop yield formation. However, the lack of data on drought–flood abrupt alternation (DF) experiments and appropriate models to calibrate parameters without the need to specify photosynthetic and hydraulic transport capacity a priori make it difficult to further our understanding of the potential interaction effects on Vmax25 and Kmax. Hence, this study aimed to investigate the potential effects of interactions between the preceding drought and the subsequent flooding on Vmax25 and Kmax. We propose a nested optimization model for calibrating photosynthetic and hydraulic conductance capacity while simultaneously modeling carbon assimilation rate and stomatal conductance. A two-year DF experiment for rice from 2017 to 2018 was conducted to validate the new framework at the Key Laboratory of Water Resources and Hydropower of Anhui Province, Bengbu, China. The results show that reasonable Kmax and Vmax25 from gas exchange data can be extracted with the proposed nested model framework. We find two distinct interactions between the prior drought and the subsequent flooding on Vmax25 and Kmax: (1) the antagonistic effect of the preceding mild drought on the subsequent-flood-induced reduction of hydraulic transport and photosynthetic capacity, and (2) the synergistic effect of the subsequent flooding on the preceding drought-induced reduction in hydraulic transport and photosynthetic capacity. Revealing the interaction of drought and flooding on Kmax and Vmax25 of rice under DF events helps to understand rice’s response to compound water stress on multiple timescales and the stomatal and non-stomatal co-limitations, and these findings can be used as valuable guidelines for accurately predicting the impact of future extreme weather events on agricultural production.

Modelling long-term operational dynamics of grid-connected hydro- photovoltaic hybrid systems

The development of variable renewable energy sources (VRESs), such as wind and solar photovoltaic (PV), has become a strategic choice for ensuring the security of electricity supplies and the decarbonization of power systems. The hybridization of hydropower with VRESs is an important measure for guaranteeing the smooth and cost-effective integration of VRESs into the power system. However, the highly variable weather- and climate-driven spatial and temporal fluctuations in VRES performance have significant potential to affect the optimal trajectory of hydropower operations. Therefore, it is essential to understand how hydropower responds to VRESs over long-term horizons, thereby allowing informed operation decisions to be made for hybrid generation systems (HGSs). In this study, a long- and short-term nested operation model is developed for hydropower operations considering PV integration. Specifically, the long-term model determines the day-by-day hydropower production over many years, and the short-term model simulates the day-ahead generation scheduling and real-time operation processes of the HGS. Performance metrics are established for evaluating the complementary operation in comparison with separate operation of hydropower and PV plants. China's two representative hydro-PV HGSs (Zhongyu and Longyangxia) are selected as case studies. The results indicate that the hybrid generation of hydropower and PV could, on average, increase total electricity generation by 11.33 %, reduce the load loss rate by 9.31 %, and decrease the PV curtailment rate by 36.60 %. However, hydro-PV hybridization may lead to an increase of 9.22 % in the water spillage rate and a decrease of 0.094 kWh/m3 in the water–electricity conversion coefficient. Therefore, hybrid generation of hydropower and PV could further enhance energy yield and supply reliability. Also, the importance of improving hydropower flexibility is highlighted.

The interplay between teacher beliefs, instructional practices, and students’ reading achievement: national evidence from PIRLS 2021 using path analysis

BackgroundReading and reading comprehension are crucial skills, yet many students in grade 4 struggle with them. To address this, several instructional practices have gained popularity. For one, explicit reading strategy instruction (ERSI) is deemed useful, given the finding that successful readers tend to employ reading strategies. As a second example, differentiated reading instruction (DRI) is believed to improve all students’ reading comprehension. Indeed, a one-size-fits-all approach may not work for all students, considering their different reader profiles. Despite the importance of ERSI and DRI, much uncertainty remains about what happens in the classroom and why. One way to understand teacher instructional practices such as ERSI and DRI, is by applying psychological behavioural theories to the teaching context. They provide a framework to predict human behaviour based on human characteristics and beliefs. Educational research points to teachers’ self-efficacy (TSE) and attitudes (TA) as particularly important concepts, especially in the field of science. However, associations between TA, TSE, instructional practices and students’ reading achievement remain insufficiently studied. This study addresses this knowledge gap by exploring the interplay between TSE and TA regarding ERSI and DRI, the implementation of these practices, and students’ reading achievement.MethodsDigitalPIRLS 2021 data from Belgium (Flanders) were used. To gather information about ERSI, DRI, TA and TSE, national adaptations were made to the teacher questionnaires. Three nested path models with a two-level design (students nested into classes) were estimated.ResultsThis study indicates that teachers with higher TSE and more positive TA in ERSI and DRI implement these practices more frequently. Positive TA regarding ERSI and DRI also correspond to positive TSE regarding these instructional practices. Furthermore, ERSI and DRI implementation are positively related. Finally, no significant associations between teacher beliefs, instructional practices, and students’ reading comprehension were found.ConclusionWhereas TSE and TA are considered highly context-dependent, uncertainty remains about TSE and TA regarding ERSI and DRI. The results highlight the importance of subject-specific TSE and TA for teachers’ instructional practices. Ultimately, the findings emphasize the necessity of supporting teachers in developing their TSE and TA towards reading comprehension instruction.

Predictors of a positive attitude towards rural practice in female osteopathic medical students.

Women outnumber men in medical school. Given the growing need for rural physicians and the underrepresentation of women in rural medicine, understanding predictors of rural practice among female students is imperative for addressing future healthcare workforce shortages in rural areas. Utilizing current evidence, medical schools should seek to admit students with a rural background and interest in pursuing a primary care specialty; however, whether this holds true for female osteopathic medical students is unknown. This study aims to determine if a rural background, a plan to practice family medicine, and motivation toward civic duty are associated with attitudes toward eventual practice of rural medicine in female osteopathic medical students. An anonymous online survey was administered to actively enrolled female students at Arkansas Colleges ofHealth Education College of Osteopathic Medicine. The survey assessed the respondents' presence of a rural background, degree of civic-mindedness, intention to practice family medicine, and attitudes to rural work and life. Demographics of ethnicity and year of study in medical school were also collected. In total, 129 students responded to the survey, with 97 complete responses for analysis. Hierarchical regression was utilized to compare nested models and interpret interactions. Of the 97 survey respondents, 34.0 % described themselves as first-year students, 37.1 % as second-year students, 16.5 % as third-year students, and 12.4 % as fourth-year students. Linear regression modeling indicated that for female medical students at Arkansas Colleges of Health Education, having a rural background had no relationship with their attitude toward practicing in a rural setting, β=-0.97, standard error (SE)=1.96, t=-0.49, p>0.05, CI [-4.86, 2.92]. Civic-mindedness had a positive relationship with their attitude toward practicing in a rural setting, β=0.17, SE=0.07, t=2.44, p=0.016, CI [0.03, 0.31], accounting for 4.57 % of its variance. Plan to practice family medicine was positively associated with a student's attitude toward practicing in a rural setting, β=4.38, SE=0.85, t=5.15, p<0.001, CI [2.69, 6.07], accounting for 20.25 % of its variance. Civic-mindedness appeared to moderate the relationship between planning to practice family medicine and attitudes toward practicing in a rural setting, F(1, 91) = 3.91, p=0.05, R 2=0.31. The p value for this interaction term was 0.05, but its effect size measure and graphical representation revealed a substantive effect. The regression analysis showed that, for thewomen in this study, the greater the student's civic-mindedness, the more favorable her attitude toward practicing in a rural setting. Additionally, the stronger thestudent's plan to practice family medicine, the more favorable her attitude toward eventual rural practice was. Lastly, the student's civic-mindedness influenced the predictive value of having a plan to practice family medicine.

Conceptualisation and empirical verification of the affective role of the teacher

ABSTRACT The affective role is an integral aspect of the teacher’s professional role, but has not received adequate scrutiny. The aim of this research was to conceptualise the construct of the affective role of the teacher (AfRT). In study 1, qualitative content analysis was employed to identify potential components of the AfRT from literature. Study 2 involved operationalising these aspects through interview with teachers, questionnaire for students, and classroom observations. In addition, preliminary conceptualisation was refined based on results obtained from 10 both highly and less favoured teachers. Study 3 proposed conceptualisation comprising 17 components, utilising a sample of 100 seventh-grade teachers.. Employing the exploratory and confirmatory factor analysis, and mutitrait-multimethod approach, a three-factor solution of the AfRT was tested, along with more restrictive nested models. The results suggest three core dimensions of the AfRT: Emotional awareness and management, Emotional connection, and Emotional attitude. Implications for teacher education and evaluation are discussed.

The Physical Progress of a Professional Scottish Soccer Academy Over a Ten-Year Period.

Increases in high-intensity locomotor activity of match play have been recorded in elite soccer. This places an onus on academy practitioners to develop players for the future demands of the game. At an academy level, locomotor data are not available for analysis over a longitudinal period, and thus changes can only be assessed with physical attribute assessment. The aim of the present study is to establish if changes in physical capacity were observed in a professional Scottish soccer academy over a ten-year period. A retrospective analysis was completed where linear mixed effect (LME) models were individually fitted to explain variation across each measure of physical capacity. Model selection was undertaken with likelihood ratio tests where the initial complex models were compared to simpler nested models to arrive at the final model by maximum likelihood. The main findings were that most recent players' sprint test data revealed a significant improvement in 5m, 10m and 20m sprint performance, greater increases in CMJ performance in older age groups, and greater increases in YYIR1 performance at U13 and U14. Most physical results showed increased performance with greater relative height and weight. Players recruited more recently to academies are fitter than they were previously. Reference values within clubs that establish first team requirements will contribute to appropriate planning and implementation of training.

How estimating nuisance parameters can reduce the variance (with consistent variance estimation).

We often estimate a parameter of interest when the identifying conditions involve a finite-dimensional nuisance parameter . Examples from causal inference are inverse probability weighting, marginal structural models and structural nested models, which all lead to unbiased estimating equations. This article presents a consistent sandwich estimator for the variance of estimators that solve unbiased estimating equations including which is also estimated by solving unbiased estimating equations. This article presents four additional results for settings where solves (partial) score equations and does not depend on . This includes many causal inference settings where describes the treatment probabilities, missing data settings where describes the missingness probabilities, and measurement error settings where describes the error distribution. These four additional results are: (1) Counter-intuitively, the asymptotic variance of is typically smaller when is estimated. (2) If estimating is ignored, the sandwich estimator for the variance of is conservative. (3) A consistent sandwich estimator for the variance of . (4) If with the true plugged in is efficient, the asymptotic variance of does not depend on whether is estimated. To illustrate we use observational data to calculate confidence intervals for (1) the effect of cazavi versus colistin on bacterial infections and (2) how the effect of antiretroviral treatment depends on its initiation time in HIV-infected patients.

A nested model for AI design and validation

The growing AI field faces trust, transparency, fairness, and discrimination challenges. Despite the need for new regulations, there is a mismatch between regulatory science and AI, preventing a consistent framework. A five-layer nested model for AI design and validation aims to address these issues and streamline AI application design and validation, improving fairness, trust, and AI adoption. This model aligns with regulations, addresses AI practitioners' daily challenges, and offers prescriptive guidance for determining appropriate evaluation approaches by identifying unique validity threats. We have three recommendations motivated by this model: (1) Authors should distinguish between layers when claiming contributions to clarify the specific areas in which the contribution is made and to avoid confusion; (2) authors should explicitly state upstream assumptions to ensure that the context and limitations of their AI system are clearly understood, (3) AI venues should promote thorough testing and validation of AI systems and their compliance with regulatory requirements.

Exploring the Benefits of Boundarylessness: Pathways From Boundaryless Career Orientation to Insecurity and Engagement

The increasing demand for flexibility and adaptability among workers underscores the necessity to explore the outcomes of enhanced proactivity in employees. This study explores the role of job crafting and career competencies (i.e., knowing why, knowing how, and knowing whom) in the relationship between boundaryless career orientation and opposite indicators of subjective career success (i.e., work engagement and job insecurity). Data collected on a sample of 1431 Italian workers (75.5% females; Mage = 37.95) were tested using nested models via Structural Equation Modeling. The results provided support for a significant serial mediation pathway from boundaryless career orientation to work engagement and perceived job insecurity through the subsequent role of job crafting and career competencies. This study sheds light on the protective role of a boundaryless career orientation in fueling a proactive attitude to navigate the progressive fading of traditional career paths and employment stability while sustaining workers’ engagement.

Longitudinal Analysis of Cancer Family Caregiver Perception of Sleep Difficulty During Home Hospice.

Sleep difficulty in caregivers is associated with poor physical and psychological outcomes. The purpose of this study was to describe family caregivers' perception of sleep difficulty through the hospice trajectory after a cancer diagnosis as predicted by age, sex, self-report of anxiety or depression, and cohabitation. We conducted a secondary analysis of longitudinal data using multilevel modeling with nested model comparisons. Beginning with an unconditional growth model, predictors were added to nested models to test differential impact. Caregivers (n = 164) were predominately white (n = 160; 97%) and female (n = 113, 69%). We hypothesized that age, sex, history of anxiety or depression, and cohabitation would predict sleep difficulty. The cohabitation predictor model was a statistically significant model for caregiver perception of sleep difficulty that worsened throughout hospice caregiving (b = .184, 2 = 7.199, P = 0.027) but age, sex, and history of depression or anxiety did not improve model fit. Our findings indicate that family caregivers who cohabitate exhibit increased perception of sleep difficulty over the course of hospice. Future studies and interventions for hospice family caregivers' sleep should consider cohabitation between the patient and the caregiver as a significant predictor of sleep difficulty to observe and potentially mediate the negative outcomes associated with caregiver sleep difficulty. Further, determining the underlying reasons for sleep difficulty in cohabitation (e.g., patient symptoms or treatments) should be explored.

Limited Bedding and Nesting as a Model for Early-Life Adversity in Mice.

Early-life adversity (ELA), such as abuse, neglect, lack of resources, and an unpredictable home environment, is a known risk factor for developing neuropsychiatric disorders such as depression. Animal models for ELA have been used to study the impact of chronic stress on brain development, and typically rely on manipulating the quality and/or quantity of maternal care, as this is the major source of early-life experiences in mammals, including humans. Here, a detailed protocol for employing the Limited Bedding and Nesting (LBN) model in mice is provided. This model mimics a low-resource environment, which provokes fragmented and unpredictable patterns of maternal care during a critical developmental window (postnatal days 2-9) by limiting the amount of nesting materials given to the dam to build a nest for her pups and separating the mice from the bedding via a mesh platform in the cage. Representative data are provided to illustrate the changes in maternal behavior, as well as the diminished pup weights and long-term changes in basal corticosterone levels, that result from the LBN model. As adults, offspring rearedin the LBN environment have been shown to exhibit an aberrant stress response, cognitive deficits, and anhedonia-like behavior. Therefore, this model is an important tool to define how the maturation of stress-sensitive brain circuits is altered by ELA and results in long-term behavioral changes that confer vulnerability to mental disorders.

The role of hyponymy and context concreteness in compound word processing

ABSTRACT This paper describes the effects of hyponymy and emotion on the comprehension and production of compound words. The research subjects are over 2000 concatenated compounds of English taken from the LADEC database (Gagné et al. 2019). The study builds on the research carried out in Charitonidis (2022), according to which context concreteness for the second constituent was a significant positive predictor of lexical decision and naming times from the English Lexicon Project (ELP) and the British Lexicon Project (BLP). In the present paper, the hyponymy norms from Gagné et al. (2020) were added in the analysis. The results show that both hyponymy and context concreteness for the second constituent are relevant. In addition, all models including both variables have a better fit than nested models omitting one of these variables. There is thus strong evidence that both hyponymy and context concreteness for the second constituent are obligatory parameters in compound word processing.

Evaluation of the psychometric properties of the health care providers’ pain and impairment relationship scale (HC-PAIRS) in health professionals and university students from Chile and Colombia

BackgroundChronic back pain is a frequent and disabling health problem. There is evidence that ignorance and erroneous beliefs about chronic low back pain among health professionals interfere in the treatment of people who suffer from it. The Health Care Providers' Pain and Impairment Relationship Scale (HC-PAIRS) has been one of the most used scale to assess these misbeliefs, but no studies have been reported in Latin America. Method: We studied the factorial structure of the HC-PAIRS in health personnel and health sciences university students in two Latin American countries: Colombia (n = 930) and Chile (n = 190). Spain's data was taken of the original study of the Spanish version of the HC-PAIRS (171 Physiotherapy students). Additionally, the measurement invariance of this scale among Chile, Colombia and Spain was evaluated by calculating three nested models: configural, metric and scalar. We used a Confirmatory Factor Analysis (CFA) in both Latin American samples, with Maximum Likelihood Robust (MLR) estimation to estimate the parameters. For the final model in each sample, reliability was assessed with the Composite Reliability (CR) index, and to obtain the proportion of variance explained by the scale the Average Variance Extracted (AVE) was calculated. ResultsThe one-factor solution shows an acceptable fit in both countries after deleting items 1, 6, and 14. For the resulting scale, the CR value is adequate, but the AVE is low. There is scalar invariance between Chile and Colombia, but not between these two countries and Spain. ConclusionsHC-PAIRS is useful for detecting misconceptions about the relationship between chronic low back pain that would cause health personnel to give wrong recommendations to patients. However, it has psychometric weaknesses, and it is advisable to obtain other evidence of validity.

Variation in Triage to Pediatric vs Adult ICUs Among Adolescents and Young Adults With Asthma Exacerbations

BackgroundOver 90,000 children and adults in the United States are hospitalized with an asthma exacerbation annually, and between 5-34% of these hospitalizations include an admission to an intensive care unit (ICU). It is unclear how adolescent and young adults with severe asthma exacerbations are triaged in the inpatient setting between pediatric (PICUs) and adult ICUs. Using a large multicenter United States cohort, we characterized how hospitals triage adolescents and young adults with asthma exacerbations between PICUs and adult ICUs. Research QuestionHow do hospitals across the United States triage adolescents and young adults with asthma exacerbations between PICUs and adult ICUs? Study Design and MethodsThis was a retrospective cohort study from 2016 to 2022 using the enhanced-claims PINC AI database. Participants were patients aged 12-26 hospitalized with asthma exacerbation and admitted to a PICU or adult ICU. We used nested hierarchical multivariable regression models to quantify changes in the intraclass correlation coefficient (a measure of variation in triage decisions attributable to hospital of admission after accounting for covariables). ResultsAnalyses included 3,946 admissions from 93 hospitals. Stratified by age, the percent of patients admitted to PICUs dropped by 26.9% between age 17 to age 18. In the nested models, the ICC had a large decrease going from the empty model (28.7%) to the age-adjusted model (4.5%) but was similar between the age-adjusted and fully adjusted model (3.4%). InterpretationAmong adolescents and young adults with asthma exacerbations, age ≤18 years was a strong determinant of PICU triage. Further research is needed to understand differences in asthma care and outcomes between PICUs and adult ICUs, as well as how intermediate care units affect triage decision-making from wards and the emergency department.

Probabilistic Nested Model Selection in Pharmacokinetic Analysis of DCE-MRI Data in Animal Model of Cerebral Tumor.

Best current practice in the analysis of dynamic contrast enhanced (DCE)-MRI is to employ a voxel-by-voxel model selection from a hierarchy of nested models. This nested model selection (NMS) assumes that the observed time-trace of contrast-agent (CA) concentration within a voxel, corresponds to a singular physiologically nested model. However, admixtures of different models may exist within a voxel's CA time-trace. This study introduces an unsupervised feature engineering technique (Kohonen-Self-Organizing-Map (K-SOM)) to estimate the voxel-wise probability of each nested model. Sixty-six immune-compromised-RNU rats were implanted with human U-251N cancer cells, and DCE-MRI data were acquired from all the rat brains. The time-trace of change in the longitudinalrelaxivity for all animals' brain voxels was calculated. DCE-MRI pharmacokinetic (PK) analysis was performed using NMS to estimate three model regions: Model-1: normal vasculature without leakage, Model-2: tumor tissues with leakage without back-flux to the vasculature, Model-3: tumor vessels with leakage and back-flux. Approximately two hundred thirty thousand (229,314) normalized profiles of animals' brain voxels along with their NMS results were used to build a K-SOM (topology-size: 8×8, with competitive-learning algorithm) and probability map of each model. K-fold nested-cross-validation (NCV, k=10) was used to evaluate the performance of the K-SOM probabilistic-NMS (PNMS) technique against the NMS technique. The K-SOM PNMS's estimation for the leaky tumor regions were strongly similar (Dice-Similarity-Coefficient, DSC=0.774 [CI: 0.731-0.823], and 0.866 [CI: 0.828-0.912] for Models 2 and 3, respectively) to their respective NMS regions. The mean-percent-differences (MPDs, NCV, k=10) for the estimated permeability parameters by the two techniques were: -28%, +18%, and +24%, for , and , respectively. The KSOM-PNMS technique produced microvasculature parameters and NMS regions less impacted by the arterial-input-function dispersion effect. This study introduces an unsupervised model-averaging technique (K-SOM) to estimate the contribution of different nested-models in PK analysis and provides a faster estimate of permeability parameters.

The how and how much of technology use in the classroom: A motivational approach to teachers' technology use

AbstractTechnology in the classroom can facilitate learning, but little is known about how the motivational climate set by teachers shapes its impacts on students. Informed by self‐determination theory, the current study explored technology use in English language classrooms to understand how autonomy‐supportive and structured teaching styles influenced positive outcomes of classroom technology use. Teachers (N = 101) reported on technology use and motivational styles, and students (N = 550) aged 9–16 years reported on basic psychological needs satisfaction (autonomy, relatedness and competence) and academic well‐being (interest and effort). Findings of nested models showed no direct benefits for the amount of technology use; more autonomous teaching style and low structure linked to students' need satisfaction and interest. Beyond these main effects, when teachers were more autonomous, using technology enhanced student need satisfaction and interest; the combination of both was most beneficial for these student outcomes. Counter to expectations, when teachers had low structure technology use enhanced their impact on students. Findings suggest that to optimize student well‐being and interest in learning, teachers benefit from combining autonomy‐supportive education styles and technology use.

Kidney Volume and Risk of Incident Kidney Outcomes.

Low total kidney volume (TKV) is a risk factor for chronic kidney disease (CKD). However, evaluations of nonlinear relationships, incident events, causal inference, and prognostic utility beyond traditional biomarkers are lacking. TKV, height-adjusted TKV, and body surface area-adjusted TKV (BSA-TKV) of 34,595 White British ancestry participants were derived from the UK Biobank. Association with incident CKD, acute kidney injury (AKI), and cardiovascular events were assessed with Cox proportional hazard models. Prognostic thresholds for CKD risk stratification were identified using a modified Mazumdar method with bootstrap resampling. Two-sample Mendelian randomization was performed to assess the bidirectional association of genetically predicted TKV with kidney and cardiovascular traits. Adjusted for eGFR and albuminuria, a lower TKV of 10 mL was associated with a 6% higher risk of incident CKD (hazard ratio [HR] 1.06, 95% confidence interval [CI] 1.03 to 1.08, P = 5.8 x 10-6) in contrast to no association with incident AKI (HR 1.00, 95% CI 0.98 to 1.02, P = 0.66). Comparison of nested models demonstrated improved accuracy over the CKD Prognosis Consortium Incident CKD Risk Score with the addition of BSA-TKV or prognostic thresholds at 119 (10th percentile) and 145 mL/m2 (50th percentile). In Mendelian randomization, a lower genetically predicted TKV by 10 mL was associated with 10% higher CKD risk (odds ratio [OR] 1.10, 95% CI 1.06 to 1.14, P = 1.3 x 10-7). Reciprocally, an elevated risk of genetically predicted CKD by 2-fold was associated with a lower TKV by 7.88 mL (95% CI -9.81 to -5.95, P = 1.2 x 10-15). There were no significant observational or Mendelian randomization associations of TKV with cardiovascular complications. Kidney volume was associated with incident CKD independent of traditional risk factors including baseline eGFR and albuminuria. Mendelian randomization demonstrated a bidirectional relationship between kidney volume and CKD.

Changes over a decade of fitness within a Scottish soccer academy and the impact of first team relegation on academy physical profiles

Introduction: academy soccer practitioners have a responsibility to prepare youth players for the demands of first team. The development of physical capabilities to sustain the high intensity locomotor activities that have been reported in elite soccer is essential. Challenges exist monitoring locomotor targets as resource limitations mean that often academies will not have locomotor data, instead relying on physiological testing to assess whether a player is ready for first team transition. Physiological testing results have a direct relationship with locomotor activity. Physical development has been shown over various longitudinal periods with established progression in speed, change of direction, lower body power and endurance in elite Austrian youths, increases in VO2max in an elite regional French academy and in the interval shuttle run test of over 50% in elite Dutch academy. The success of a club’s academy can lead to increased resource allocation however some organisational challenges such as relegation can have a severe financial impact. The initial aim of the present study was to establish whether previously observed changes in physical capacity were observed in a professional Scottish soccer academy over a ten-year period. A further aim was to assess the impact of first team relegation on academy physical profiles considering the resource implications of relegation. Methodology: a retrospective analysis was completed where Linear Mixed Effect (LME) Models were fitted to explain variation across each measure of physical capacity. Model selection was undertaken with Likelihood Ratio Tests where initial complex models were compared to simpler nested models to arrive at the final model by maximum likelihood. The impact of relegation was assessed by LME models to assess whether physical capacity measures changed post relegation. Ethical approval was granted. Results: 5 m best time reduced by 0.0055 s per year (t = −11.8, p &lt; 0.001), 10 m best time reduced by 0.008 s per year (t = −9.2, p &lt; 0.001), 20 m best time reduced by 0.011 s per year (t = −7.8, p &lt; 0.001). CMJ increased each year depended on age group with the older cohorts showing greater improvement and the YYIR1 distance increased each year varying across age group. Performance of aforementioned physical capacity measures significantly reduced with relegation, except 20 m best time (t = −1.4, p = 0.16). Application: reference values within clubs that establish first team requirements will contribute to appropriate transition strategies. By conducting analyses related to uncontrollable challenges, practitioners can use these results to protect against criticism and withdrawal of resource when physical progression is negatively impacted.