Standard Error Research Articles

Cardiopulmonary coupling predictors of blood pressure response to positive airway pressure therapy

The effect of continuous positive airway pressure (CPAP) treatment on reducing cardiovascular disease risk in sleep apnea subjects remains inconclusive. It is plausible that pathological respiratory chemoreflex activation (high loop gain) is a predictive signal biomarker. To determine whether narrow band (e-LFCNB%) metric derived from cardiopulmonary coupling analysis is related with blood pressure reduction after CPAP. A secondary analysis of the Apnea Positive Pressure Long-term Efficacy Study (APPLES). The elevated low frequency coupling - narrow band (e-LFCNB %) metric derived from cardiopulmonary coupling analysis detects periodic breathing (as a surrogate for high loop gain), and was estimated in baseline polysomnogram. Linear regression analysis was performed to identify the potential association between e-LFCNB% of total sleep time and the observed reduction in blood pressure following the specified treatment. A total of 388 subjects received CPAP and had e-LFCNB % measurements. At 2 months, 90/322 subjects had e-LFCNB ≥ 4% at baseline. At 6 months 137/313 subjects had e-LFCNB higher than 2% at baseline. For morning systolic blood pressure, e-LFCNB ≥ 4% [β: 2.534, standard error (SE): 1.198, p: 0.035] was positively related with the extent of systolic blood pressure reductions after 2 months CPAP treatment and e-LFCNB ≥ 2% was marginally related with systolic blood pressure decrement after 6 months (β: 2.162, SE: 1.173, p: 0.066). For the morning diastolic blood pressure, e-LFCNB ≥ 2% predicted reductions at 6 months of treatment (β: 1.883, SE: 0.888, p: 0.035). e-LFCNB % (probable high loop gain) was positively related to systolic blood pressure reduction (short-term) and diastolic blood pressure reduction (longer-term), following CPAP.

Reaction Time in Fibromyalgia Patients.

Fibromyalgia has unknown aetiology and is associated with reduced information processing speed and therefore prolonged reaction time. However, the processes underlying this are unknown. First, to compare the reaction time in a cohort of fibromyalgia patients and a matched group of normal controls. Second, to assess whether detailed symptoms of pain and autonomic function, as well as measures of tinnitus, fatigue, daytime sleepiness and Mycoplasma pneumoniae infection are predictors of reaction time in fibromyalgia. The between-groups mean serial five-choice reaction time difference was assessed in a cohort of fibromyalgia patients and in a matched group of normal controls in an analytical casecontrolled study. With the mean serial five-choice reaction time as the dependent variable for the fibromyalgia group, a mixed stepwise multiple linear regression was performed with inputs relating to pain, dysautonomia, tinnitus, fatigue, daytime sleepiness and Mycoplasma pneumoniae infection. The mean (standard error) serial five-choice reaction time for the fibromyalgia group was 448.4 (23.0) ms, compared with 386.3 (8.3) ms for the control group (p = 0.007). The final multiple linear regression model (p < 0.001; adjusted R2 = 0.772) contained 13 predictors: eight sensory pain and three affective pain parameters, and Mycoplasma pneumoniae IgG and IgA assay results. Certain sensory and affective pain parameters, as well as Mycoplasma pneumoniae infection, appear to be predictors of reaction time in fibromyalgia. Further research into the pathophysiological mechanisms by which they affect information processing is warranted and may shed light on the aetiology of fibromyalgia.

The CD244 rs3766379 variant showed no association with susceptibility to rheumatoid arthritis while soluble CD244 was associated with disease activity

Cluster of differentiation 244 (CD244), a member of the signaling lymphocytic activation molecule (SLAM) family, is one of the major cell surface receptors of the SLAM family with activating and inhibitory signaling potentials that is involved in the functional regulation of inflammatory reactions. It has recently been suggested that soluble CD244 levels are dysregulated in patients with rheumatoid arthritis (RA), but the evidence is not conclusive. Furthermore, the CD244 rs3766379 variant showed conflicting results regarding association with disease susceptibility. In this cross-sectional case-control study, serum CD244 concentration was determined in 123 RA patients and 60 controls using an enzyme-linked immunosorbent assay kit. The CD244 rs3766379 variant was also genotyped using real-time polymerase chain reaction principles. Results revealed that Log10-transformed serum concentrations (mean ± standard error) of soluble CD244 were significantly elevated in RA patients compared to controls (0.53 ± 0.04 vs. 0.29 ± 0.02 ng/mL; probability = 0.003), especially in patients with high disease activity (0.73 ± 0.12 vs. 0.29 ± 0.02 ng/mL; probability = 0.003), where CD244 showed reliable discrimination between patients and controls (area under the curve = 0.698; probability = 0.023). The rs3766379 allele and genotype frequencies showed no significant differences between patients and controls. Furthermore, this variant did not affect CD244 concentration. In conclusion, CD244 levels were up-regulated in the serum of patients with RA, particularly those with high disease activity. The CD244 rs3766379 variant was not associated with susceptibility to RA and had no effect on serum CD244 concentration.

Effects of anodal transcranial direct current stimulation on intracranial compliance in the subacute phase of stroke

ObjectivesTranscranial direct current stimulation (tDCS) increases cerebral blood flow. This study evaluated the effects of anodal tDCS (A-tDCS) on intracranial compliance (ICC) in patients with subacute stroke using a non-invasive method. MethodsThis was a randomized, proof-of-concept, double-blind, pilot study. Patients with ischemic stroke of the middle cerebral artery (MCA) were divided into the following two groups: 1) A-tDCS in the motor cortex on the affected side for 30min at 2mA, and 2) sham tDCS in the motor cortex on the affected side. The primary outcomes were intracranial compliance (P2/P1 ratio and time-to-peak [TTP]) and ICC normalization after the intervention (P2/P1 ratio <1). Secondary outcomes were systolic and diastolic blood pressures, heart rate, and peripheral oxygen saturation. ResultsNo significant differences were observed in the P2/P1 ratio (P = 0.509) and TTP (P = 0.480) between the groups. However, the A-tDCS group was significantly associated with a normal P2/P1 ratio after intervention (B = 2.583; standard error [SE]: 1.277; P = 0.043; corrected for age and stroke severity). No significant associations were observed between the groups and systolic blood pressure (F = 0.16; P = 0.902), diastolic blood pressure (F = 0.18; P = 0.892), heart rate (F = 0.11; P = 0.950), or peripheral oxygen saturation (F = 0.21; P = 0.750). ConclusionICC morphology normalization was observed in the A-tDCS group. However, no differences were observed in the P2/P1 ratio, TTP, or hemodynamic variables between the groups. A sample size of 66 patients with ischemic stroke of the MCA can be estimated using the observed effect size and standard α = 5% and β = 20% for future trials. Furthermore, this will aid in conducting the necessary randomized trials targeting these populations.

Postoperative Pain Comparison Between Alcohol-Assisted and Transepithelial Photorefractive Keratectomy Using Nepafenac Treatment: A Novel Study.

The study aimed to compare postoperative pain between alcohol-assisted and transepithelial photorefractive keratectomy in patients who received the novel analgesic preoperative nepafenac treatment 2days preoperatively and 3days postoperatively. Pain, stinging, tearing, light sensitivity, and stress levels were evaluated. The study included a retrospective analysis of 55 patients divided into two groups: bilateral alcohol-assisted photorefractive keratectomy (aa-PRK) and transepithelial photorefractive keratectomy (transepithelial-PRK). Nepafenac was administered for pain control for all patients, with patients receiving four drops for 2 days before the surgery and 3 days postoperatively per clinical instructions. Patients completed questionnaires on the day of the surgery and for the first 5 days postoperatively. Statistical analysis was performed using XLSTAT (version 2023.1.2). t-Test was used to analyze and compare pain and symptom levels and Fisher's exact test for categorical data. p-Values less than 0.05 were considered statistically significant. The study examined 55 patients (49% female) with a mean age of 25.11 ± 6.81years who had undergone bilateral surface refractive surgery to correct myopic errors. The mean baseline standard error (SE) was -3.16 ± 2.20 D. Among these patients, 27 patients underwent aa-PRK and 28 patients underwent transepithelial-PRK. Higher levels of pain were significant in the aa-PRK group (p = 0.003). However, there was no significant difference between the groups in the average levels of stinging, tearing, or light sensation. Additionally, stress levels decreased over time in both groups, with levels becoming almost equal after 5 days, and there was no significant difference in the average stress levels between the two groups. The study found that patients who underwent the transepithelial-PRK procedure had significantly lower pain levels compared with those who underwent aa-PRK after being treated with nepafenac per protocol. However, there was no significant difference between the two groups in terms of stinging, tearing, light sensation, and stress levels.

Optimization and Uncertainty Analysis of Hybrid Energy Systems Using Monte Carlo Simulation Integrated with Genetic Algorithm

This study investigates the optimization of hybrid energy systems (HES) composed of wind turbines, battery banks, and diesel generators, focusing on addressing the challenges posed by wind speed uncertainty. This research contributes significantly to the field by developing a novel methodology that combines uncertainty analysis with hybrid optimization techniques to improve the reliability and cost-effectiveness of HES. The findings revealed that initial simulations without renewable energy sources result in high diesel consumption, with fuel usage reaching 534,810 liters per year and associated carbon emissions totaling 797,070 kg/year. Through optimization, an economically viable configuration is identified, consisting of 37 battery banks, two 250 kW wind turbines, and a 340-kW diesel generator, achieving an Annualized System Cost (ASC) of $166,500 and a Cost of Energy (COE) of $0.1480/kWh. The Monte Carlo simulations indicate a most probable COE of $0.1450/kWh for the wind turbine/battery/diesel system, occurring with an 8.3% probability, while approximately 90% of COE values fall below $0.1669/kWh. The average COE is $0.14834/kWh, with a minimum of $0.12163/kWh. The Renewable Energy Fraction (REF) spans from 28% to 97%, with an average of 64% and a standard deviation error of 9.6% at a 95% confidence level. The results underscore the potential implications for informing policymakers and industry leaders about the design and evaluation of HES under uncertain environmental conditions. By addressing the limitations of current approaches, this work contributes valuable insights into the economic, environmental, and social dimensions of hybrid renewable energy systems.

Cross-cultural adaptation and measurement properties of the Brazilian Portuguese Version of the Parkinson’s Disease Sleep Scale (PDSS-2)

ObjectivesThe Parkinson’s Disease Sleep Scale-2 (PDSS-2) is an updated tool designed to identify specific sleep disturbances in individuals with Parkinson’s disease (PD). However, for its application in Brazil, a process of cross-cultural adaptation and validation of measurement properties was required. MethodsThis methodological study adapted the PDSS-2 to Brazilian Portuguese (PDSS-2-Br) and assessed its measurement properties (Internal consistency, test-retest reliability, measurement error, construct validity, and interpretability). The adapted scale was then tested on 2 occasions within an interval of 7 days, to 50 individuals with PD. Test–retest reliability was evaluated using kappa statistics (k) for the individual items, intraclass correlation coefficient (ICC) for the total scores, standard error of measurement (SEM), minimal detectable change (MDC) and Bland-Altman plot. Construct validity was assessed through Spearman correlation coefficients between the PDSS-2-Br and independent variables, while interpretability was evaluated by examining ceiling and floor effects. ResultsPDSS-2-Br showed satisfactory semantic, idiomatic, cultural, and conceptual equivalence. It also demonstrated good internal consistency (α=0.64), adequate test-retest reliability between items (κw 0.42-0.94, 95% CI=0.30-0.95) and total score (ICC=0.94; 95% CI=0.89-0.96), acceptable measurement error (SEM, 2.07 points; MDC, 5.74 points), absence of ceiling and floor effects, and 87,5% of pre-defined hypotheses were confirmed, indicating adequate construct validity (Spearman correlations coefficients for the rs=0.50, p<0.001) of the PDSS-2-Br. ConclusionThe measurement properties of the PDSS-2-Br are equivalent to those of the original version, and the scale has been validated and confirmed as reliable to measure sleep disorders among the Brazilian population with PD.

Intra-rater Reliability of B-mode Ultrasound in the Measurement of Soft Tissue Thickness and Composition over the Lateral Proximal Femur

ObjectivesComprehensive characterization of soft tissue composition and distribution over the lateral proximal femur is necessary to improve our understanding of fall-related hip fractures; however, a protocol that produces reliable data is needed. Accordingly, the aim of this study was to assess the intra-rater reliability of B-mode ultrasound measured muscle, adipose, and total soft tissue thicknesses over the lateral proximal femur in a simulated sideways fall configuration. MethodsTwenty-five young adults (12 males, 13 females, age (SD) = 20.8 (1.9) years) underwent B-mode ultrasound imaging of 12 locations over their lateral proximal femur while in a side-lying position. Side-lying was chosen to allow imaging of the tissues impacted during a lateral fall event. Muscle, adipose, and total soft tissue thicknesses were measured at each location (further grouped into posterolateral, lateral, and anterolateral locations for statistical analysis) and two-way mixed model absolute agreement intraclass correlation coefficients (ICCs) and standard error of measurement were used to assess reliability of tissue type, location, and sex. ResultsICCs were excellent (ICC > 0.9) for each tissue type, measurement location, and sex. There were interactions between tissue type, measurement location, and sex on reliability. While measures of adipose thickness were excellent across all conditions, reliability of muscle and total soft tissue thickness measurements were dependent on measurement location and sex. ConclusionsThis ultrasound imaging protocol demonstrated good-to-excellent reliability of soft tissue-specific thickness measurements over the lateral proximal femur. This protocol has implications for subject-specific hip fracture risk screening tools and biomechanical models of impact dynamics that incorporate biofidelic soft tissue morphology.

Development, Validity, and Reliability of Adolescent Motivation Inventory-Cerebral Palsy

Objectives: Motivation is the most influential factor in the drive and performance of adolescents with cerebral palsy (CP). As identification and analysis of volition in Iranian adolescents with CP seem to be essential, designing appropriate tools for assessing their motivation is crucial. To achieve this goal, we developed an adolescent motivation inventory-CP (AMI-CP) and evaluated its psychometric properties. Methods: In the first phase, item generation was conducted. Next, in the second phase, face and content validities of the items were assessed. Moreover, construct validity was assessed by exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). A total of 304 adolescents with CP participated in the EFA, while 210 adolescents with CP participated in the CFA. Afterward, convergent and discriminant validities of the inventory were measured. Moreover, reliability was evaluated by calculating Cronbach α, McDonald’s omega, average inter-item correlation, composite, and test re-test reliability. Lastly, the standard error of measurement (SEM) and the minimum detectable change (MDC) were applied. Results: Five factors with 22 items were extracted by EFA, accounting for 50.42% of the variance. The results of model fit indexes confirmed the goodness-of-fit of the final model with 20 items. In addition, the AMI-CP had a Cronbach α value of 0.75 and an intra-class correlation coefficient of 0.94. Moreover, the SEM and MDC of the inventory were 2.63 and 7.31, respectively. Discussion: The AMI-CP is a helpful measure of motivation in adolescents with CP. This inventory can enhance the assessment of the CP adolescents’ motivation by evaluating values, interests, personal causation, and physical and social environments.

Modelling global mesozooplankton biomass using machine learning

Mesozooplankton are a crucial link between primary producers and higher trophic levels and play a vital role in marine food webs, biological carbon pumps, and sustaining fishery resources. However, the global distribution of mesozooplankton biomass and the relevant controlling mechanisms remain elusive. We compared four machine learning algorithms (Boosted Regression Trees, Random Forest, Artificial Neural Network, and Support Vector Machine) to model the spatiotemporal distributions of global mesozooplankton biomass. These algorithms were trained on a compiled dataset of published mesozooplankton biomass observations with corresponding environmental predictors from contemporaneous satellite observations (temperature, chlorophyll, salinity, and mixed layer depth). We found that Random Forest achieved the best predictive accuracy with R2 and RMSE (Root Mean Standard Error) of 0.57 and 0.39, respectively. Also, the global distribution of mesozooplankton biomass predicted by the Random Forest model was more consistent with the observational data than other models. We used the Random Forest model to create a global map of mesozooplankton biomass which serves as a reference for validating process-based ecosystem models. The model outputs confirm that environmental factors, especially surface Chl a, a proxy for prey availability, significantly correlate with the spatiotemporal distribution of mesozooplankton biomass. The scaling relationship between the mesozooplankton biomass and Chl a can be used as an emergent constraint for model validation and development. Moreover, our model predicts that the global mesozooplankton biomass will decrease by 3% by the end of this century under the “business-as-usual” scenarios, potentially reducing fishery production and carbon sequestration. Our study contributes to predicting global mesozooplankton biomass and provides deep insights into the underlying environmental impacts on the distribution of mesozooplankton biomass.

Information provision and financial incentives in Catalonia's public primary care (2010–2019): an interrupted time series analysis

The relative efficacy of information provision versus financial incentives in improving primary care quality remains a critical, unresolved question. We investigated these two strategies in Catalonia's public primary care system from 2010 to 2019: an innovative online platform providing real-time quality indicator information and targeted economic incentives for achieving indicator goals. We conducted a comprehensive interrupted time series regression analysis on data from 272 primary care practices (5,628,080 patients). This analysis used linear regression models with Newey-West standard errors, and a sensitivity analysis including logit transformations to address ceiling effects. We evaluated 1) immediate post-intervention changes (step changes) in indicator results and inter-practice variability (coefficient of variation, CV), and 2) shifts in pre-intervention trends (slopes). We scrutinized 39 indicators after rigorous quality control: 23 novel (12 informed, 11 incentivized) and 16 derived from existing incentivized indicators. Robustness checks included 14 consistently incentivized and 10 non-intervened indicators. Overall, we assessed 63 indicators: 18 control, 13 follow-up, 9 quaternary prevention, 7 treatment, 7 diagnosis, 6 screening and 3 vaccination indicators. Informed indicators showed positive impacts in 75% (9/12) of cases, and incentivized indicators in 64% (7/11) of cases. Incentivized indicators displayed improvements in annual trends ranging from 6.66 to 1.25 percentage points, with step changes up to 8.87 percentage points. Information led to step changes ranging from 19.67 to 1.07 percentage points, along with trend improvements between 1.09 and 0.34 percentage points annually. Both interventions were associated with step reductions in variability (up to-0.18 CV reduction) and significant trend improvements. Derived indicators showed limited improvements in results or variability (31%, 5/16), with minor step increases up to 2.22 percentage points. Our findings reveal that information provision alone can match or even surpass the impact of financial incentives in improving care quality and reducing practice variability. This challenges conventional wisdom and offers a cost-effective, scalable approach to primary care quality enhancement, with far-reaching implications for global health policy. European Union, Horizon Europe.

Detecting overfitting by examining residuals in autoregressive models

The aim of this study is to see how overfitting can be detected using non-rigorous analysis of residuals. The well-known statistical packages was used to simulate data from stationary autoregressive models with Gaussian white noise with mean 0 and variance one. In order to see the effect of realization size on our findings, the sample size 50 was used as an example of small realization and the sample size 500 was used as an example of large realization. The method of maximum likelihood was used in the fitting of autoregressive models to the simulated data which is available in the statistical package R. Interesting and promising results were obtained. Our study seems to suggest that comparing estimates with their standard errors is the only reliable criterion in spotting or detecting overfitting. To make sure that the defect in the behavior of the residuals is due only to the over, we used only the same class of models in the simulation and the fitting.

Impact of Select Variables on Tangible Book Value Multiple of U.S. Regional Banks

Aims: This study explores the relationship between regional banks' Price-to-Tangible Book Value (P/TBV) multiple and metrics such as profitability, liquidity, capital adequacy, asset quality, leverage, and operational efficiency. Study Design: A longitudinal panel data analysis of 101 regional U.S. banks, covering the financial years from 2003 to 2023. It employs fixed effects, random effects, and pooled OLS regression models to determine the drivers of P/TBV multiple. The analysis controls for time-specific factors such as pre – and post – financial crisis periods, enabling a more comprehensive evaluation of valuation trends over different economic cycles. Results: All three models were statistically significant in identifying the determinants of P/TBV. However, the fixed effects model was deemed the most appropriate, as confirmed by the Hausman test (p &lt; 0.001), which demonstrated its consistency over the random effects model. Additionally, the F-test (p &lt; 0.001) indicated the relevance of the fixed effects model over the pooled OLS model by highlighting the significance of individual effects. The fixed effects model and the fixed effects model with robust standard errors revealed that return on equity and bank efficiency positively influenced P/TBV, while asset size, non-performing loans, leverage, and dividend yield had significant negative effect. The model also showed higher valuations for regional banks in the pre-2008 financial crisis period compared to the post-crisis era. Additionally, upon accounting for the impact of heteroscedasticity, the statistical significance of loan-to-deposit ratio variable noted in the fixed effects model turns out to be insignificant. Conclusion: Financial stability, profitability, capital, and asset quality are crucial in determining regional bank valuations. The insights from this study will help bank managers identify key focus areas to optimize valuation and pricing strategies, ensuring that banks can align internal financial health with broader market dynamics for sustainable growth. Additionally, the findings will benefit investors by providing a deeper understanding of the financial factors driving bank valuations, enabling more informed investment decisions. While this research does not directly address the impact of macroeconomic variables on regional banks' valuations, it highlights an area that merits further investigation in future research.

LASSO-type instrumental variable selection methods with an application to Mendelian randomization.

Valid instrumental variables (IVs) must not directly impact the outcome variable and must also be uncorrelated with nonmeasured variables. However, in practice, IVs are likely to be invalid. The existing methods can lead to large bias relative to standard errors in situations with many weak and invalid instruments. In this paper, we derive a LASSO procedure for the k-class IV estimation methods in the linear IV model. In addition, we propose the jackknife IV method by using LASSO to address the problem of many weak invalid instruments in the case of heteroscedastic data. The proposed methods are robust for estimating causal effects in the presence of many invalid and valid instruments, with theoretical assurances of their execution. In addition, two-step numerical algorithms are developed for the estimation of causal effects. The performance of the proposed estimators is demonstrated via Monte Carlo simulations as well as an empirical application. We use Mendelian randomization as an application, wherein we estimate the causal effect of body mass index on the health-related quality of life index using single nucleotide polymorphisms as instruments for body mass index.

Reliability of Sensorimotor Control Tests in Individuals with Adolescent Idiopathic Scoliosis

Background: The presence of sensorimotor control deficits in adolescent idiopathic scoliosis compared to typically developed adolescents is supported by the literature but lacks reliability studies for assessment in this population. This study aimed to assess the reliability of eight sensorimotor control tests, in terms of static and dynamic balance, joint position sense (JPS) tests of the extremities and the spine, and a functional upper extremity proprioceptive test in adolescent idiopathic scoliosis subjects. Methods: Sixty adolescent idiopathic scoliosis subjects were divided into four groups. Each group underwent two tests by the same examiner, repeated at 15 min intervals. Reliability was measured using the intraclass correlation coefficient (ICC), standard error of measurement (SEM), and smallest detectable difference (SDD). Results: The results showed high reliability for the upper extremity functional proprioception test, for the dynamic and static balance test, and for the spinal lateral flexion joint position sense test in both directions. On the other hand, the shoulder external rotation, knee extension, elbow flexion, and spinal flexion joint position sense tests demonstrated poor reliability in adolescent idiopathic scoliosis subjects. Conclusions: Therapists are recommended to use the functional upper extremity proprioception test, the Fukuda test, the static balance test using a force footplate, and the spinal lateral flexion joint position sense test for assessing treatment progress in this population.

Patient-Reported Outcomes in RLBP1 Retinal Dystrophy: Longitudinal Assessment in a Prospective Natural History Study.

To evaluate the performance of two non-disease-specific patient-reported outcome (PRO) instruments, the National Eye Institute Visual Function Questionnaire-25 (VFQ-25) and the Low Luminance Questionnaire (LLQ), in patients with retinaldehyde-binding protein 1 retinal dystrophy (RLBP1 RD). PROs were assessed using the VFQ-25 and LLQ. Rasch analysis was conducted to estimate person and item measures of the VFQ-25 and LLQ questionnaires to determine the association between the two PROs. In addition, the association between these two instruments and their correlations to weighted measures of visual function and disease progression were analyzed in this three-year PRO-focused sub-study of a five-year prospective natural history study. Forty-two patients participated, with most of them having completed at least two PRO follow-up visits at least one year apart. The mean VFQ-25 scores were lowest for distance activities (39.2-49.0) and peripheral vision (37.5-52.4), with mean LLQ subscale scores generally low (<41), except for the emotional distress subscale. Using Rasch analysis, calibrated item and person measures along with their standard errors were estimated for both ePROs. This indicated that the distribution of the VFQ-25 and LLQ item measures well covered the distribution of person function in this group. This suggests that the item difficulties well cover the person-level performance in this population. As well, the two PROs showed a strong and significant correlation at all assessed time points as assessed with Pearson correlation coefficient (0.81, 0.91, 0.81 and 0.87 at baseline, 1/1.5, 2/2.5 (P < 0.001) and 3/3.5 years (P = 0.002)). The composite scores of both PRO questionnaires strongly correlated with clinical measures of visual function. At 2 to 2.5 years of follow-up, meaningful statistically significant declines in peripheral vision (both VFQ-25 and LLQ), distance vision (VFQ-25), and extreme lighting in dark and bright light (LLQ) subscales were noted. This study demonstrated a strong association between VFQ-25 and LLQ scores and their association with clinical measures of visual function. PRO instruments can provide insights into the specific disabilities of this unique patient population and help to guide appropriate outcome measures for future clinical trials.

Utility of fat-free adipose tissue correction formula for tracking body composition changes with dual-energy X-ray absorptiometry.

Fat loss is often the target of weight loss interventions; however, preservation of lean soft tissue (LST) may be more important for health and weight maintenance. Though some LST loss may be inevitable when tracking body composition changes using dual-energy X-ray absorptiometry (DXA), correcting for the fat-free component of adipose tissue (FFAT) in DXA-derived LST (DXALST) has been proposed. This analysis sought to evaluate differences between DXALST and FFAT-corrected LST (FFATLST) amongst varied populations and interventions to understand application of the correction formula on LST outcomes. 226 subjects were analyzed across five prior studies. Three studies evaluated combined nutrition and exercise (high-intensity interval training [HIIT] or high-intensity resistance training [HIRT]) interventions, including HIIT + HIRT with pre- and post-nutrient timing (HIITRT), HIIT + essential amino acids (HIITAA), and HIRT + protein (HIRTPRO). Remaining studies evaluated HIIT (HIITOW) and protein following bariatric surgery (BARPRO). Pre and post total body DXA scans were used to measure DXALST, body mass, and fat mass (FM). The correction formula was applied to calculate FFATLST. Paired sample t-tests were used to evaluate differences between DXALST and FFATLST change scores (Δ) across all subjects, within each study and intervention. Significant differences between ΔDXALST and ΔFFATLST were observed for BARPRO (mean difference [MD; ΔDXALST-ΔFFATLST] ± standard error [SE]: -3.5 ± 1.2 kg, p < 0.001), as well as HIRTPRO (-0.1 ± 0.2 kg, p = 0.004). When evaluating LST, the FFAT correction may be specifically applicable to cases of significant weight loss (>10% of original weight) or body recomposition (≥2% FM loss and ≥2% LST gain).

Advancements and limitations in polygenic risk score methods for genomic prediction: a scoping review.

This scoping review aims to identify and evaluate the landscape of Polygenic Risk Score (PRS)-based methods for genomic prediction from 2013 to 2023, highlighting their advancements, key concepts, and existing gaps in knowledge, research, and technology. Over the past decade, various PRS-based methods have emerged, each employing different statistical frameworks aimed at enhancing prediction accuracy, processing speed and memory efficiency. Despite notable advancements, challenges persist, including unrealistic assumptions regarding sample sizes and the polygenicity of traits necessary for accurate predictions, as well as limitations in exploring hyper-parameter spaces and considering environmental interactions. We included studies focusing on PRS-based methods for risk prediction that underwent methodological evaluations using valid approaches and released computational tools/software. Additionally, we restricted our selection to studies involving human participants that were published in English language. This review followed the standard protocol recommended by Joanna Briggs Institute Reviewer's Manual, systematically searching Ovid MEDLINE, Ovid Embase, Scopus and Web of Science databases. Additionally, searches included grey literature sources like pre-print servers such as bioRxiv, and articles recommended by experts to ensure comprehensive and diverse coverage of relevant records. This study identified 34 studies detailing 37 genomic prediction methods, the majority of which rely on linkage disequilibrium (LD) information and necessitate hyper-parameter tuning. Nine methods integrate functional/gene annotation, while 12 are suitable for cross-ancestry genomic prediction, with only one considering gene-environment (GxE) interaction. While some methods require individual-level data, most leverage summary statistics, offering flexibility. Despite progress, challenges remain. These include computational complexity and the need for large sample sizes for high prediction accuracy. Furthermore, recent methods exhibit varying effectiveness across traits, with absolute accuracies often falling short of clinical utility. Transferability across ancestries varies, influenced by trait heritability and diversity of training data, while handling admixed populations remains challenging. Additionally, the absence of standard error measurements for individual PRSs, crucial in clinical settings, underscores a critical gap. Another issue is the lack of customizable graphical visualization tools among current software packages. While genomic prediction methods have advanced significantly, there is still room for improvement. Addressing current challenges and embracing future research directions will lead to the development of more universally applicable, robust, and clinically relevant genomic prediction tools.

Robust Estimation for Threshold Autoregressive Moving-Average Models

Threshold autoregressive moving-average (TARMA) models extend the popular TAR model and are among the few parametric time series specifications to include a moving average in a nonlinear setting. The state dependent reactions to shocks is particularly appealing in Economics and Finance. However, no theory is currently available when the data present heavy tails or anomalous observations. Here we provide the first theoretical framework for robust M-estimation for TARMA models and study its practical relevance. Under mild conditions, we show that the robust estimator for the threshold parameter is super-consistent, while the estimators for autoregressive and moving-average parameters are strongly consistent and asymptotically normal. The Monte Carlo study shows that the M-estimator is superior, in terms of both bias and variance, to the least squares estimator, which can be heavily affected by outliers. The findings suggest that robust M-estimation should be generally preferred to the least squares method. We apply our methodology to a set of commodity price time series; the robust TARMA fit presents smaller standard errors and superior forecasting accuracy. The results support the hypothesis of a two-regime non-linearity characterized by slow expansions and fast contractions.

The impact of a 20-h rotating watch schedule on cognitive and mood states in submarine operations.

This is the first study to provide valuable insights into the effects of the Israeli Navy's 20-h rotating watch schedule on submariners' alertness, mood states, risk-taking behaviours, and sleep. Specifically, we assessed the impact of the non-circadian-aligned schedule on cognitive performance, mood, and behavioural outcomes in a highly controlled submarine environment. A total of 20 male submariners participated in an at-sea mission, where their cognitive performance, mood states, risk-taking propensity, and caffeine consumption were measured. A psychomotor vigilance task (PVT) assessed alertness, the propensity for risky behaviour (Evaluation of Risks Scale) measured risk-taking behaviours, and the Profile of Mood States evaluated mood disturbances. Actigraphy was used to monitor sleep times. Data were analysed according to seven watch schedule segments. Submariners slept a mean (standard error of the mean [SEM]) of 8.3 (0.2) h/24 h, fragmented into 3.7 (0.8) h epochs. Caffeine consumption decreased at sea (mean [SEM] 149.3 [6.0] mg) compared to land (mean [SEM] 205.5 [7.2] mg; p = 0.027). In the PVT, premature responses significantly increased during Watch VI (5:00-8:00 p.m.) and Watch VII (8:00 p.m.-12:00 a.m.; p = 0.014). In the mood subscales, tension was significantly higher during Watch II (4:00-8:00 a.m.; p = 0.002), indicating greater stress. Risk-taking propensity significantly increased during afternoon shifts (p = 0.050). The 20-h watch schedule led to fragmented sleep, reduced alertness in the evening, worsened mood states in the early morning, and increased risk-taking propensity in the afternoon. These findings suggest the need for the Israeli Navy to establish evidence-based caffeine guidelines and optimise the watch schedule to improve submariners' sleep, performance, and overall well-being.