Meaningful Associations Research Articles

Prioritizing Context-Dependent Cancer Gene Signatures in Networks.

There are numerous ways of portraying cancer complexity based on combining multiple types of data. A common approach involves developing signatures from gene expression profiles to highlight a few key reproducible features that provide insight into cancer risk, progression, or recurrence. Normally, a selection of such features is made through relevance or significance, given a reference context. In the case of highly metastatic cancers, numerous gene signatures have been published with varying levels of validation. Then, integrating the signatures could potentially lead to a more comprehensive view of the connection between cancer and its phenotypes by covering annotations not fully explored in individual studies. This broader understanding of disease phenotypes would improve the predictive accuracy of statistical models used to identify meaningful associations. We present an example of this approach by reconciling a great number of published signatures into meta-signatures relevant to Osteosarcoma (OS) metastasis. We generate a well-annotated and interpretable interactome network from integrated OS gene expression signatures and identify key nodes that regulate essential aspects of metastasis. While the connected signatures link diverse prognostic measurements for OS, the proposed approach is applicable to any type of cancer.

Relationship between dynamic capability view and organizational resilience: Findings from a symmetric approach

The COVID-19 outbreak has underscored the importance of strengthening an organization’s resilience and adaptive capability. In emerging and uncertain conditions, firms must adopt new capabilities to develop and survive unstable and unforeseen crises. The purpose of this study is to examine the difference between organizational resilience and the antecedents that are validated using a quantitative survey. The respondents consist of 157 top employees from 21 private service firms at the managerial level in Bangladesh. The proposed relationship is measured using the partial least squares structural equation modeling (PLS-SEM), a symmetric approach, using SmartPLS 4 software. The findings help to produce the path coefficient with organizational resilience that can lead to sustainable environments in highly turbulent conditions. The PLS-SEM analysis indicates that the antecedents of flexibility, agility, and redundancy have a strong and meaningful association with organizational resilience in response to disruptions. Therefore, this paper shows evidence that the measurement scales more effectively account for uncertainty in achieving resilience, supporting the role of the dynamic capability view.

Distinct network patterns emerge from Cartesian and XOR epistasis models: a comparative network science analysis

BackgroundEpistasis, the phenomenon where the effect of one gene (or variant) is masked or modified by one or more other genes, significantly contributes to the phenotypic variance of complex traits. Traditionally, epistasis has been modeled using the Cartesian epistatic model, a multiplicative approach based on standard statistical regression. However, a recent study investigating epistasis in obesity-related traits has identified potential limitations of the Cartesian epistatic model, revealing that it likely only detects a fraction of the genetic interactions occurring in natural systems. In contrast, the exclusive-or (XOR) epistatic model has shown promise in detecting a broader range of epistatic interactions and revealing more biologically relevant functions associated with interacting variants. To investigate whether the XOR epistatic model also forms distinct network structures compared to the Cartesian model, we applied network science to examine genetic interactions underlying body mass index (BMI) in rats (Rattus norvegicus).ResultsOur comparative analysis of XOR and Cartesian epistatic models in rats reveals distinct topological characteristics. The XOR model exhibits enhanced sensitivity to epistatic interactions between the network communities found in the Cartesian epistatic network, facilitating the identification of novel trait-related biological functions via community-based enrichment analysis. Additionally, the XOR network features triangle network motifs, indicative of higher-order epistatic interactions. This research also evaluates the impact of linkage disequilibrium (LD)-based edge pruning on network-based epistasis analysis, finding that LD-based edge pruning may lead to increased network fragmentation, which may hinder the effectiveness of network analysis for the investigation of epistasis. We confirmed through network permutation analysis that most XOR and Cartesian epistatic networks derived from the data display distinct structural properties compared to randomly shuffled networks.ConclusionsCollectively, these findings highlight the XOR model’s ability to uncover meaningful biological associations and higher-order epistasis derived from lower-order network topologies. The introduction of community-based enrichment analysis and motif-based epistatic discovery emphasize network science as a critical approach for advancing epistasis research and understanding complex genetic architectures.

The functional heterogeneity of non-suicidal self-injury: insights from latent profile analysis

BackgroundThe functional aspects of non-suicidal self-injury (NSSI) among adolescents represent a complex phenomenon requiring deeper understanding. While research has identified various NSSI functions, including emotional regulation, attention-seeking, and social avoidance, the field lacks comprehensive analysis of how these functions cluster into distinct profiles. Understanding these functional profiles is crucial for developing targeted interventions.MethodA cross-sectional study of 1,783 adolescents (1,464 girls, 318 boys) aged 12–18 years was conducted across 14 psychiatric or general hospitals in nine Chinese provinces. Participants completed the Functional Assessment of Self-Mutilation (FASM), which assesses 22 distinct NSSI functions across three primary dimensions: emotional regulation, attention-seeking, and social avoidance. Additional measures included the Patient Health Questionnaire (PHQ-9) for depression and Generalized Anxiety Disorder Scale (GAD-7) for anxiety symptoms. Latent profile analysis was employed to identify distinct patterns in NSSI functions, with model selection based on fit indices including AIC, BIC, entropy, and LMRT.ResultsLatent profile analysis revealed four distinct functional profiles: low attention-seeking-high social avoidance (LA-HS, 19.7%), high attention-seeking-high social avoidance (HA-HS, 9.5%), low attention-seeking and social avoidance (LA-LS, 57.8%), and high attention-seeking-low social avoidance (HA-LS, 13.0%). The HA-HS profile demonstrated the most severe clinical presentation, showing significantly elevated scores in NSSI frequency (M = 26.160, SD = 9.771), anxiety (GAD-7: M = 16.265, SD = 4.951), and depression (PHQ-9: M = 20.612, SD = 6.003). The LA-HS profile showed the second-highest severity (NSSI: M = 25.800, SD = 10.058; GAD-7: M = 14.775, SD = 5.376; PHQ-9: M = 19.966, SD = 5.938). Both profiles also demonstrated significantly higher rates of suicidal ideation (HA-HS: 77.6%; LA-HS: 79.2%) compared to other profiles.ConclusionsOur findings reveal distinct patterns in how adolescents utilize NSSI functionally, particularly regarding attention-seeking and social avoidance dimensions. These functional profiles show meaningful associations with psychological outcomes, suggesting that understanding NSSI functions, rather than just behaviors, may be crucial for assessment and intervention. The identification of these distinct functional profiles among Chinese adolescents highlights the importance of function-specific approaches in clinical assessment and treatment planning.

Weight-adjusted-waist index: an innovative indicator of breast cancer hazard

BackgroundCentral obesity and breast cancer (BC) have been identified as relevant by empirical research. The weight-adjusted-waist index (WWI) is a novel methodology for quantifying central obesity. Inspection of the association between WWI and BC in American adult women was the primary goal of the current investigation.MethodsCross-sectional assessments were conducted on information gathered from 10,193 National Health and Nutrition Examination Survey (NHANES) participants from 2011 to 2018. The waist circumference was divided by the square root of the body’s mass to compute WWI. Data were assessed via descriptive statistics to present data distributions according to BC grouping and WWI grouping, receiver operating characteristic curves (ROCs) to evaluate the obesity indicators’ applied value, logistic regression to reflect associations between WWI and BC prevalence, and restricted cubic splines (RCSs) and subgroup analysis forest plots to visualise and complement the relationships.ResultsThis study enrolled 10,193 participants whose WWI ranged from 8.38 to 14.41, 259 of whom were diagnosed with BC, and the results revealed significant differences in baseline characteristics between the groups. With an area under the curve (AUC) value (95% confidence interval) (CI)of 0.611 (0.577–0.644), WWI was a promising indicator of BC with good application value rather than waist circumference (WC), body mass index (BMI), or waist-height ratio (WHtR). WWI and BC laid out a substantial relationship, yielding an odds ratio (OR) of 1.54 and a 95% CI of (1.34, 1.79), which remained at 1.19 (1.00, 1.42) after considerable adjustments were made, according to the logistic regression analysis. Compared with the lowest quartile of WWI, the highest quartile had a 62% greater in the probability of suffering from BC. With the RCS’s inverted U-shape highlighting the importance of considering the nonlinear nature of the relationship and subgroup analyses reflecting variations among populations, all the results demonstrated that WWI was a well-suggestive indicator of BC hazard.ConclusionThe current investigation revealed a meaningful association between the prevalence of BC and WWI, which was superior to other obesity indicators, albeit one that was more complex than the positive relationship initially derived. There existed a turning point for BC prevalence at WWI of approximately 12 cm/√kg. Nevertheless, maintaining WWI in the lower range is critical for preventing and administering BC and minimizing disease risk.

The evaluation of depression prevalence and its association with obesity phenotypes in a community-dwelling aged population

BackgroundDepression is one of the most debilitating mental disorders and a risk factor for many other chronic diseases that are commonly seen in the geriatric population. It has been claimed in previous studies that depression can be associated with obesity in this age group, but there is no common consensus between their results.AimThis study aims to evaluate the association between depression metabolic syndrome and obesity phenotypes in community-dwelling older adults living in the East of Iran.Method and materialsAs a part of the Birjand Longitudinal Aging Study, this retrospective cross-sectional study was conducted on participants older than 60. They were categorized based on their body mass index and components of metabolic syndrome into four phenotypes: metabolic non-healthy obese (MNHO), metabolic healthy obese (MHO), metabolic healthy non-obese (MHNO), and metabolic non-healthy non-obese (MNHNO). The relative risk ratio (RRR) of the obesity phenotypes, the severity of depressive symptoms, and the 95% confidence intervals (95% CI) were evaluated by univariate and multinomial logistic regression.ResultsOf 1344 eligible participants, 268 (19.94%) had depression. Moderate, moderate-severe, and severe depression were observed in 179 (13.32%), 67 (4.99%), and 22 (1.64%) participants, respectively. Our findings showed a non-significant increase in the RRR of mild depressive symptoms in MNHO (RRR:1.22, 95% CI 0.56–2.66) and severe symptoms in MNHNO (RRR:1.20, 95% CI 0.02–63.17) females. However, in male participants, the RRR of moderate-severe depressive symptoms only increased non-significantly for the MNHO category (RRR:1.34, 95% CI 0.45–3.98).ConclusionWe did not observe a meaningful association between depressive symptoms and obesity phenotypes. Also, other than malnutrition or its risk, various severities of depressive symptoms correlate with different sociodemographic and medical risk factors among male and female senior citizens.

Application of a localized morphometrics approach to imaging-derived brain phenotypes for genotype-phenotype associations in pediatric mental health and neurodevelopmental disorders.

Quantitative global or regional brain imaging measurements, known as imaging-specific or -derived phenotypes (IDPs), are commonly used in genotype-phenotype association studies to explore the genomic architecture of the brain and how it may be affected by neurological diseases (e.g., Alzheimer's disease), mental health (e.g., depression), and neurodevelopmental disorders (e.g., attention-deficit hyperactivity disorder [ADHD]). For this purpose, medical images have been used as IDPs using a voxel-wise or global approach via principal component analysis. However, these methods have limitations related to multiple testing or the inability to isolate high variation regions, respectively. To address these limitations, this study investigates a localized, principal component analysis-like approach for dimensionality reduction of cross-sectional T1-weighted MRI datasets utilizing diffeomorphic morphometry. This approach can reduce the dimensionality of images while preserving spatial information and enables the inclusion of spatial locality in the analysis. In doing so, this method can be used to explore morphometric brain changes across specific components and spatial scales of interest and to identify associations with genome regions in a multivariate genome-wide association study. For a first clinical feasibility study, this method was applied to data from the Adolescent Brain Cognitive Development (ABCD) study, including adolescents with ADHD (n = 1,359), obsessive-compulsive disorder (n = 1,752), and depression (n = 1,766). Meaningful associations of specific morphometric features with genome regions were identified with the data and corresponded to previous found brain regions in the respective mental health and neurodevelopmental disorder cohorts. In summary, the localized, principal component analysis-like approach can reduce the dimensionality of medical images while still being able to identify meaningful local brain region alterations that are associated with genomic markers across multiple scales. The proposed method can be applied to various image types and can be easily integrated in many genotype-phenotype association study setups.

Arrhythmogenic Cardiomyopathy: Towards Genotype Based Diagnoses and Management.

Arrhythmogenic cardiomyopathy (ACM) is a genetically heterogeneous inherited cardiomyopathy with an estimated prevalence of 1:5000-10 000 that predisposes patients to life-threatening ventricular arrhythmias (VA) and sudden cardiac death (SCD). ACM diagnostic criteria and risk prediction models, particularly for arrhythmogenic right ventricular cardiomyopathy (ARVC), the most common form of ACM, are typically genotype-agnostic, but numerous studies have established clinically meaningful genotype-phenotype associations. Early signs of ACM onset differ by genotype indicating the need for genotype-specific diagnostic criteria and family screening paradigms. Likewise, risk factors for SCD vary by genetic subtype, indicating that genotype-specific guidelines for management are also warranted. Of particular importance, genotype-specific therapeutic approaches are being developed. Results from a randomized controlled trial for flecainide use in ARVC patients are currently pending. Research in a plakophilin-2-deficient mouse model suggests this antiarrhythmic drug may be particularly useful for patients with likely pathogenic or pathogenic (LP/P) PKP2 variants. Additionally, the first gene therapy clinical trials in ARVC patients harboring LP/P PKP2 variants are currently underway. This review aims to provide clinicians caring for ACM patients with an up-to-date overview of the current literature in genotype-specific natural history of disease and management of ACM patients and describe scientific advances that have led to upcoming clinical trials.

Evaluation of bone mineral density and biochemical markers in pediatric patients with phenylketonuria

ObjectivesPhenylketonuria is a hereditary condition caused by the deficiency of the enzyme phenylalanine hydroxylase, leading to abnormal phenylalanine metabolism. Managing phenylketonuria involves implementing dietary interventions to control phenylalanine levels and prevent complications. However, these treatments can lead to long-lasting negative effects, including impacts on bone health and abnormal biochemical test findings. The aim of the study was to examine the relationship between biological markers and bone density in individuals with phenylketonuria. MethodsThis cross-sectional study was conducted out at Motahari Hospital in Urmia, Iran. The study involved 19 patients with phenylketonuria, examining their demographic information, laboratory findings, and bone density by statistical methods. ResultsThe study examined the association between age and bone densitometry outcomes, along with the connection between different biochemical markers and bone densitometry results. The analysis showed no statistically significant link between age and bone densitometry data (P-value = 0.31). The p-values for correlation between bone densitometry and serum calcium, serum phosphorus, phenylalanine, alkaline phosphatase, and 25-hydroxyvitamin D₃ were found to be 0.30, 0.27, 0.57, 0.86, and 0.95, respectively. The only significant relationship was between the result of bone densitometry and alkaline phosphatase levels in the age group below 8 years with a correlation of 0.720 (P-value = 0.01). ConclusionsThe study revealed no association between bone densitometry and levels of serum calcium, serum phosphorus, phenylalanine, and 25-hydroxyvitamin D₃. The only meaningful association was between bone densitometry and alkaline phosphatase in the age group below 8 years.

INTERPERSONAL SKILLS AND ADOLESCENTS’ SOCIAL ADJUSTMENT: THE IMPLICATION OF THE TEACHING LEARNING PROCESS IN THE UNIVERSITY OF BUEA, CAMEROON

The study investigated interpersonal skills as determinants of adolescents’ social adjustment in the University of Buea. The study employed a cross-sectional survey research design, specifically utilizing a sample survey approach. The research focused on a population of 5,736 adolescent students across three faculties. To determine an appropriate sample size, the researchers applied the Krejcie and Morgan model, which indicated that 361 students would constitute a representative sample. The sampling process combined purposive sampling to identify the population of interest, followed by random selection of individual participants. For data collection, the researchers developed and administered a questionnaire that included both open-ended and closed-ended questions. The data management process began with entering the collected data into EpiData version 3.1. To ensure data quality, the researchers then conducted rigorous data cleaning and validation checks using SPSS version 23.0, which helped identify and address any invalid codes in the dataset. To establish the reliability of the research instrument, the team assessed the internal consistency of responses using Cronbach's Alpha reliability coefficient. The statistical analysis employed two main tests: Chi-square analysis was used to examine and compare descriptive differences in the data, while Spearman's rho correlation test was selected for hypothesis testing due to the normal distribution of the data. This comprehensive methodological approach allowed the researchers to systematically collect, process, and analyze data while maintaining scientific rigor throughout the study. The combination of purposive and random sampling techniques helped ensure both the relevance and representativeness of the sample, while the statistical tests chosen were appropriate for the nature of the data and research objectives. The data analysis incorporated both descriptive and inferential statistical methods to examine the relationship between social adjustment and interpersonal relationships among university adolescents. The fundings yielded a statistically significant positive correlation (R = 0.411, p < 0.01) between interpersonal relationship formation and social adjustment outcomes in the university environment. This moderate correlation coefficient indicates that adolescent students who successfully establish and maintain quality interpersonal relationships demonstrate enhanced social adjustment within the university context. The strength of this correlation (R = 0.411) suggests a meaningful association between these variables, though it also indicates that other factors are likely to contribute to social adjustment outcomes. This empirical evidence underscores the importance of interpersonal relationship development as a key facilitator of successful social adaptation among adolescent university students.

Regionalization of intestinal microbiota and metabolites in the small intestine of the Bactrian camel.

Peyer's patches (PPs) are crucial antigen-inductive sites of intestinal mucosal immunity. Prior research indicated that, in contrast to other ruminants, PPs in the small intestine of Bactrian camels are found in the duodenum, jejunum, and ileum and display polymorphism. Using this information, we analyzed the microbial and metabolic characteristics in various segments of the Bactrian camel's small intestine to further elucidate how the immune system varies across different regions. In this study, the microbiota and metabolite of 36 intestinal mucosal samples, including duodenal (D-PPs), jejunal (J-PPs), and ileal PPs (I-PPs), were profiled for six Bactrian camels using 16S rRNA gene sequencing and liquid chromatography with tandem mass spectrometry (LC-MS/MS). To confirm meaningful associations, we conducted connection analyses on the significantly different objects identified in each group's results. ELISA was used to analyze the levels of IgA, IgG, and IgM in the same tissues. The microbiota and metabolite profiles of J-PPs and I-PPs were found to be similar, whereas those of D-PPs were more distinct. In J-PPs and I-PPs, the dominant bacterial genera included Clostridium, Turicibacter, and Shigella. In contrast, D-PPs had a significant increase in the abundance of Prevotella, Fibrobacter, and Succinobacter. Regarding the metabolomics, D-PPs exhibited high levels of polypeptides, acetylcholine, and histamine. On the other hand, J-PPs and I-PPs were characterized by an enrichment of free amino acids, such as L-arginine, L-glutamic acid, and L-serine. These metabolic differences mainly involve amino acid production and metabolic processes. Furthermore, the distribution of intestinal immunoglobulins highlighted the specificity of D-PPs. Our results indicated that proinflammatory microbes and metabolites were significantly enriched in D-PPs. In contrast, J-PPs and I-PPs contained substances that more effectively enhance immune responses, as evidenced by the differential distribution of IgA, IgG, and IgM. The intestinal microenvironment of Bactrian camels displays distinct regional disparities, which we propose are associated with variations in immunological function throughout different segments of the small intestine. This study highlights the specific traits of the intestinal microbiota and metabolites in Bactrian camels, offering a valuable reference for understanding the relationship between regional intestinal immunity and the general health and disease of the host.

An iterative approach for estimating domain-specific cognitive abilities from large scale online cognitive data.

Online cognitive tasks are gaining traction as scalable and cost-effective alternatives to traditional supervised assessments. However, variability in peoples' home devices, visual and motor abilities, and speed-accuracy biases confound the specificity with which online tasks can measure cognitive abilities. To address these limitations, we developed IDoCT (Iterative Decomposition of Cognitive Tasks), a method for estimating domain-specific cognitive abilities and trial-difficulty scales from task performance timecourses in a data-driven manner while accounting for device and visuomotor latencies, unspecific cognitive processes and speed-accuracy trade-offs. IDoCT can operate with any computerised task where cognitive difficulty varies across trials. Using data from 388,757 adults, we show that IDoCT successfully dissociates cognitive abilities from these confounding factors. The resultant cognitive scores exhibit stronger dissociation of psychometric factors, improved cross-participants distributions, and meaningful demographic's associations. We propose that IDoCT can enhance the precision of online cognitive assessments, especially in large scale clinical and research applications.

Study on the Influence of Physical Activity Intensity and Maturation on Sports Injuries in Children and Adolescents

Intensive training combined with a growing body can predispose children to sports injuries. Our aim was to identify the importance of physical activity (PA) intensity and maturity as predictors of injury in youth. Information about injuries was collected using a questionnaire (LESADO), the PA intensity was assessed via accelerometry, and maturity was assessed using the Tanner–Whitehouse III bone age method and maturity offset. A total of 121 participants aged between 10 and 18 years were selected from four different schools. Regression analyses were used to determine the significant predictors of the injury profile. Only the injury type presented significant results. The time spent on moderate PA (χ2(2) = 6.701, p = 0.035) and bone age (χ2(2) = 7.196, p = 0.027) were the final predictors. The odds of having a strain or a fracture relative to a sprain increased 1.04 times for each minute of time spent on moderate PA. Likewise, the odds of having a strain or a fracture relative to a sprain decreased by 1.7 times per year of bone age. The PA intensity and bone age proved to be injury predictors in the growing athletes, with more predictive power in injury type. No meaningful associations were found for the injury occurrence, injury rate and body area injury location.

Characterization of Disease Patterns in Children with Intracranial Abscesses for Enhanced Clinical Decision-Making.

Intracranial suppurative infections in pediatric patients, while rare, pose a significant risk to patient mortality. Early recognition and fast initiation of diagnosis and treatment are crucial to prevent fatal outcomes. Between December 2022 and May 2023, a significant cluster of nine cases emerged, each necessitating neurosurgical intervention. This series highlights an important trend in clinical outcomes and raises questions about underlying factors contributing to this pattern. The need for surgical procedures in all instances suggests a commonality in severity, warranting further investigation into potential causes and preventative measures. This retrospective monocentric study aims to explore the clinical features associated with these cases to identify specific disease patterns that can expedite management in clinical practice. Cramer's V effect size was employed to evaluate combinations of clinical features, followed by Fisher's exact test applied to a constructed contingency table. A p-value was assessed for significance analysis, with combinations achieving a Cramer's V value of 0.7 or higher being classified as exhibiting very strong correlations. The analysis revealed distinct patterns of clinical features among children diagnosed with intracranial abscesses. Significant associations were identified, including correlations between sinusitis and Streptococcus pyogenes, and fever accompanied by affected temporal, frontal, and frontobasal lobe regions. Despite the generally limited statistical analysis of pediatric intracranial abscesses in the existing literature, this study provides meaningful significant associations between clinical features, delineating specific disease patterns for children with intracranial abscesses. By addressing this gap, the findings contribute valuable insights and offer a framework that could enhance clinical decision-making and support timely disease management in pediatric cases.

A machine learning approach to site groundwater contamination monitoring wells

Effective monitoring of groundwater contamination is crucial to protect human livelihoods and ecosystems. This paper presents a machine learning-based approach to improve groundwater monitoring networks by providing predictions of groundwater contamination in space. The method is demonstrated through a practical application in Central Spain, where nitrate was used as a proxy for groundwater contamination. Predictive mapping identifies the spatial markers for groundwater contamination based on twenty-four predictor variables and a dataset of 213 existing monitoring boreholes. Tree-based algorithms found meaningful associations between the explanatory variables and known nitrate concentrations. Comparing the outcomes of the algorithms with the areas officially delineated as vulnerable to nitrate suggests that machine learning algorithms are able to predict groundwater contamination. The extra trees algorithm outperformed decision trees, random forest, gradient boosting, and AdaBoost classifiers, with an area under the curve score in excess of 0.88. Major predictors for groundwater contamination were depth to the water table, lithology, distance to rivers, and distance to livestock farms. Predictive mapping suggests that there are unmonitored regions to the northeast and to the southwest of Madrid’s metropolitan area that present similar markers to monitored regions known to be contaminated. These unmonitored areas should be prioritized in future attempts to improve the network. From a research perspective, the main conclusion of this work is that machine learning techniques can be used as a technique to automate the siting of monitoring boreholes. Practical applications should nevertheless be overseen by an expert eye to guarantee the quality of the outcomes.

Dissociable Contributions of Goal-Relevant Evidence and Goal-Irrelevant Familiarity to Individual and Developmental Differences in Conflict Recognition.

Recent studies using the diffusion decision model find that performance across many cognitive control tasks can be largely attributed to a task-general efficiency of evidence accumulation (EEA) factor that reflects individuals' ability to selectively gather evidence relevant to task goals. However, estimates of EEA from an n-back "conflict recognition" paradigm in the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study, a large, diverse sample of youth, appear to contradict these findings. EEA estimates from "lure" trials-which present stimuli that are familiar (i.e., presented previously) but do not meet formal criteria for being a target-show inconsistent relations with EEA estimates from other trials and display atypical v-shaped bivariate distributions, suggesting many individuals are responding based largely on stimulus familiarity rather than goal-relevant stimulus features. We present a new formal model of evidence integration in conflict recognition tasks that distinguishes individuals' EEA for goal-relevant evidence from their use of goal-irrelevant familiarity. We then investigate developmental, cognitive, and clinical correlates of these novel parameters. Parameters for EEA and goal-irrelevant familiarity-based processing showed strong correlations across levels of n-back load, suggesting they are task-general dimensions that influence individuals' performance regardless of working memory demands. Only EEA showed large, robust developmental differences in the ABCD sample and an independent age-diverse sample. EEA also exhibited higher test-retest reliability and uniquely meaningful associations with clinically relevant dimensions. These findings establish a principled modeling framework for characterizing conflict recognition mechanisms and have several broader implications for research on individual and developmental differences in cognitive control.

Clinical value of comprehensive genomic profiling on clinical trial enrollment for patients with advanced solid tumors.

The use of biomarker testing to inform treatment decisions has emerged as a standard of care in multiple cancer types. However, the rates of patients with genomic testing results in hand to inform treatment decision-making remain variable. Here, we studied the impact of comprehensive genomic profiling (CGP) on clinical trial enrollment rates in patients with advanced-stage non-small cell lung, colorectal, breast, and prostate cancer using a real-world clinicogenomic database. On average, clinical trial enrollment in the therapy line immediately after CGP report receipt was 5.4%, which represents a 3.0 percentage point increase compared to therapy lines preceding CGP report receipt, supporting a meaningful association between CGP report availability and increased clinical trial enrollment.

Frailty and quality of life in italian older adults: implications for public health interventions

Abstract Background The increasing focus on frailty in older adults underscores the significance of a timely multidimensional assessments and early detection to avert adverse outcomes. The primary aim is to integrate digital technologies, specifically online assessment tools, for the identification of frailty and the assessment of Quality of Life (QoL) in elderly individuals. Methods A nationwide multicentric study was conducted. Seven Italian centers and regions evaluated frailty in older adults residing in the community, through a prospective observational cohort study. The chosen questionnaires, Sunfrail+ and SF-12, were implemented through an easily accessible online tool, swiftly generating final scores for each test. The cross-sectional analysis included 503 older adults. The cut off to define a person “frail” is 3 positive alerts in Sunfrail baseline items, according to the literature. Results In this sample an average of 2.31 positive alerts were generated. Significant associations were established between the number of positive warnings and SF-12 physical and mental indexes, indicated by X2=53.1 (p < 0.001) and X2=25.1 (p < 0.001), respectively. The difference between two groups (frail and not frail) in relation to QoL is statistical significantly (U di Mann Whithney p < 0.001). Mean QoL mental and physical indexes are 46.3 and 39.3 in frailty group, versus 51.7 and 46.5 in non frailty group, respectively. The correlation is conceptually consistent: as frailty increases, QoL decreases. Conclusions The frailty assessment associated with the QoL assessment provides relevant information to monitor the impact of prevention interventions at community level. The assessment of frailty leads the prevention intervention whose impact could be assessed also through QoL tools. This study underlines a meaningful association between assessment tools, substantiated by conceptual correlations. Key messages • Sunfrail and SF-12 are easily accessible online tool useful for identification of frailty and the assessment of Quality of Life (QoL) in elderly individuals. • The older population in Europe is increasing a timely assessment of frailty must be a public health priority.

Associations between general practice and outpatient care continuity in people with multimorbidity

Abstract Background Relational continuity in primary and secondary care is linked to better health outcomes for patients, but it is unclear whether metrics of continuity in each setting are associated. Our study examined the association between relational continuity in general practice (GP) and continuity of hospital outpatient specialties in people with clusters of multimorbidity. Methods We used GP records from the Clinical Practice Research Datalink, linked to Hospital Episode Statistics outpatient records. Included were patients ≥18 years, with two or more of 212 Long-Term Conditions (LTCs), registered throughout 2019 and with at least three GP and three outpatient appointments. The Continuity of Care Index (COCI) was calculated separately for visits to the same i) GP and ii) hospital specialty, where 0 represents no continuity and 1 represents all visits to the same GP or specialty. We assessed the association between the indices using univariable and multivariable fractional logit regression. We calculated expected COCI scores for each LTC and assessed variation in the COCI between LTCs assigned to one of 15 clusters of co-occurring diseases derived previously. A sensitivity analysis repeated analysis using the Sequential Continuity (SECON) score, which captures longitudinal continuity. Results Of 1,135,903 patients, 56.2% were ≥60 years. The median (IQR) COCI in GP was 0.22 (0.11-0.40) and in outpatients was 0.33 (0.20-0.52). Although statistically significant (p < 0.001) the relationship between the two measures was clinically insignificant in both univariable and multivariable models. No strong relationships were found between COCI scores and LTC clusters. Similar patterns were found using the SECON score. Conclusions We found no strong association between continuity of care in GP and outpatient settings, and no clear patterns with LTC clusters. This suggests that lack of continuity in secondary care is not compensated for by increased continuity of care in primary care. Key messages • We found no meaningful association between measures of continuity of care in general practice and hospital outpatient settings. • Our findings suggest that lack of continuity of outpatient care is not compensated for by increased continuity in primary care.

Postprandial Symptoms in a Mixed-Meal-Test after Bariatric Surgery: Clinical Experience and a Critical Review of Dumping Syndrome Definition and Management

Plain Language SummaryDumping syndrome (DS) is a set of symptoms, which may occur in patients after bariatric surgery (weight loss surgery). These symptoms occur after meals and are attributed to a fast passage of food through the surgically altered stomach and intestine. The symptoms of DS include fainting, the need to lie down, shortness of breath, and dizziness. Current recommendations suggest measuring heart rate, taking laboratory measurements and comparing these to diagnostic criteria during a provocation test with a glucose solution. We have been using a so-called Mixed-Meal Test to evaluate the patients’ symptoms at our clinic. Patients would eat a meal designed according to recommendations for patients after bariatric surgery, made of curd, oats, apple sauce, and walnuts. Then, their symptoms, blood pressure, and blood samples would be collected for 180 min. We looked at the data from all 56 tests, we had performed at our clinic, and compared the measurements, which we had obtained, to the diagnostic criteria and symptoms reported. While all patients reported symptoms at home, only 28% reported typical symptoms during the test. We did not find meaningful associations between measurements taken by us and symptoms reported by patients. This study shows that many patients do not display typical symptoms under controlled conditions. At the same time, the diagnostic criteria seem to be unrelated to symptoms. It is not the first study showing discrepancies between measurements, diagnostic criteria, and symptoms. The current tests used for diagnosing DS may not be clinically useful and the whole concept of DS after bariatric surgery may need to be reevaluated.