New relevance and significance measures to replace p-values.
Ontology highlight
ABSTRACT:
SUBMITTER: Stahel WA
PROVIDER: S-EPMC8208587 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Disrupted l-methionine (Met) metabolism can lead to hepatic, neurological and cardiovascular dysfunction in humans. Aberrant methyl group flux likely contributes to the development of these pathologies, but when patients also become hypermethionemic, additional toxicological mechanisms may be relevant.Following a discussion of the causes of hypermethionemia in humans, evidence for the toxicological roles and clinical significance of the Met transmethylation (TM), transamination (TA) and sulfoxidation (SO) pathways will be presented.Recent data from freshly isolated mouse hepatocytes (FIMHs) confirmed previous in vivo results in rodents that Met TM is a detoxification pathway while Met TA leads to toxicity. Gender-related differences in Met accumulation and metabolism in FIMHs correlated with gender differences in toxicity. Data obtained from FIMHs also implicated Met SO in Met metabolism and toxicity. Currently, little is known about the mechanisms and biological significance of Met sulfoxidation in humans.In hypermethionemic patients, clinical and dietary interventions should focus on increasing Met TM and decreasing Met TA and SO. Novel biomarkers of hypermethionemia in humans that correlate with pathological end points are needed to better understand the impact of the condition.
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Project description:The arrival of modern brain imaging technologies has provided new opportunities for examining the biological essence of human intelligence as well as the relationship between brain size and cognition. Thanks to these advances, we can now state that the relationship between brain size and intelligence has never been well understood. This view is supported by findings showing that cognition is correlated more with brain tissues than sheer brain size. The complexity of cellular and molecular organization of neural connections actually determines the computational capacity of the brain. In this review article, we determine that while genotypes are responsible for defining the theoretical limits of intelligence, what is primarily responsible for determining whether those limits are reached or exceeded is experience (environmental influence). Therefore, we contend that the gene-environment interplay defines the intelligent quotient of an individual.
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Project description:It has been suggested that clinician-rated scales and self-report questionnaires may be interchangeable in the measurement of depression severity, but it has not been tested whether clinically significant information is lost when assessment is restricted to either clinician-rated or self-report instruments. The aim of this study is to test whether self-report provides information relevant to short-term treatment outcomes that is not captured by clinician-rating and vice versa.In genome-based drugs for depression (GENDEP), 811 patients with major depressive disorder treated with escitalopram or nortriptyline were assessed with the clinician-rated Montgomery-Åsberg Depression Rating Scale (MADRS), Hamilton Rating Scale for Depression (HRSD), and the self-report Beck Depression Inventory (BDI). In sequenced treatment alternatives to relieve depression (STAR*D), 4,041 patients treated with citalopram were assessed with the clinician-rated and self-report versions of the Quick Inventory of Depressive Symptomatology (QIDS-C and QIDS-SR) in addition to HRSD.In GENDEP, baseline BDI significantly predicted outcome on MADRS/HRSD after adjusting for baseline MADRS/HRSD, explaining additional 3 to 4% of variation in the clinician-rated outcomes (both P < .001). Likewise, each clinician-rated scale significantly predicted outcome on BDI after adjusting for baseline BDI and explained additional 1% of variance in the self-reported outcome (both P < .001). The results were confirmed in STAR*D, where self-report and clinician-rated versions of the same instrument each uniquely contributed to the prediction of treatment outcome.Complete assessment of depression should include both clinician-rated scales and self-reported measures.
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Project description:Background Researchers often misinterpret and misrepresent statistical outputs. This abuse has led to a large literature on modification or replacement of testing thresholds and P-values with confidence intervals, Bayes factors, and other devices. Because the core problems appear cognitive rather than statistical, we review some simple methods to aid researchers in interpreting statistical outputs. These methods emphasize logical and information concepts over probability, and thus may be more robust to common misinterpretations than are traditional descriptions. Methods We use the Shannon transform of the P-value p, also known as the binary surprisal or S-value s?=??log2(p), to provide a measure of the information supplied by the testing procedure, and to help calibrate intuitions against simple physical experiments like coin tossing. We also use tables or graphs of test statistics for alternative hypotheses, and interval estimates for different percentile levels, to thwart fallacies arising from arbitrary dichotomies. Finally, we reinterpret P-values and interval estimates in unconditional terms, which describe compatibility of data with the entire set of analysis assumptions. We illustrate these methods with a reanalysis of data from an existing record-based cohort study. Conclusions In line with other recent recommendations, we advise that teaching materials and research reports discuss P-values as measures of compatibility rather than significance, compute P-values for alternative hypotheses whenever they are computed for null hypotheses, and interpret interval estimates as showing values of high compatibility with data, rather than regions of confidence. Our recommendations emphasize cognitive devices for displaying the compatibility of the observed data with various hypotheses of interest, rather than focusing on single hypothesis tests or interval estimates. We believe these simple reforms are well worth the minor effort they require.
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Project description:BackgroundAssessing the outcome of motif mining algorithms is an essential task, as the number of reported motifs can be very large. Significance measures play a central role in automatically ranking those motifs, and therefore alleviating the analysis work. Spotting the most interesting and relevant motifs is then dependent on the choice of the right measures. The combined use of several measures may provide more robust results. However caution has to be taken in order to avoid spurious evaluations.ResultsFrom the set of conducted experiments, it was verified that several of the selected significance measures show a very similar behavior in a wide range of situations therefore providing redundant information. Some measures have proved to be more appropriate to rank highly conserved motifs, while others are more appropriate for weakly conserved ones. Support appears as a very important feature to be considered for correct motif ranking. We observed that not all the measures are suitable for situations with poorly balanced class information, like for instance, when positive data is significantly less than negative data. Finally, a visualization scheme was proposed that, when several measures are applied, enables an easy identification of high scoring motifs.ConclusionIn this work we have surveyed and categorized 14 significance measures for pattern evaluation. Their ability to rank three types of deterministic motifs was evaluated. Measures were applied in different testing conditions, where relations were identified. This study provides some pertinent insights on the choice of the right set of significance measures for the evaluation of deterministic motifs extracted from protein databases.
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Project description:BackgroundIn recent decades, novel echocardiographic measures have constantly emerged. It is still unclear which echocardiographic measures have the most significant prognostic value in the general population. Accordingly, the aim of this study was to compare the prognostic value of a large panel of echocardiographic measures to identify the most promising measures.MethodsA total of 1,497 Framingham study participants (mean age, 65 years; 55.4% women) who underwent echocardiographic measurements of left ventricular ejection fraction, left ventricular mass index, global longitudinal strain, global circumferential strain, mitral annular plane systolic excursion, mitral E/e' ratio, maximum and minimum left atrial (LA) volume index, LA emptying fraction, and left ventricular longitudinal synchrony were evaluated. These measures were related to the incidence of two composite outcomes: cardiovascular disease (CVD) or death and atrial fibrillation (AF) or congestive heart failure (CHF).ResultsOn follow-up (mean, 8.3 years), there were 241 CVD events or deaths and 139 AF or CHF events. In multivariate-adjusted Cox models, higher LA emptying fraction was associated with a lower risk (hazard ratios per SD, 0.80 and 0.70 for CVD or death and AF or CHF, respectively; P ≤ .001 for both) while higher minimum LA volume index (hazard ratios per SD, 1.32 and 1.70 for CVD or death and AF or CHF, respectively; P ≤ .001 for both) and maximum LA volume index (hazard ratios per SD, 1.26 and 1.54 for CVD or death and AF or CHF, respectively; P ≤ .002 for both) were associated with a higher risk for both composite outcomes.ConclusionsIn this community-based sample, LA volumes and function were the best echocardiographic predictors of clinical outcomes. Therefore, these values should be considered for inclusion in standard echocardiographic assessments for the purpose of risk stratification.
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Project description:Three studies (N = 887) tested the hypothesis that value consistency predicts intended coronavirus disease-2019 (COVID-19) health behaviors and overrides other utility-based motivational factors. Accordingly, Study 1 showed that intentions of social distancing were higher if it was perceived as more value-consistent. The higher value consistency, the less self-interest inconsistency, and the perceived efficacy of social distancing mattered for intentions. On the other hand, Study 2 failed to induce value consistency experimentally. However, correlative results show a moderation pattern similar to Study 1 regarding social distancing intentions, policy support, and devaluation of transgressors. In Study 3, higher value consistency of vaccination reduced the experimental effect of prosocial efficacy but not the effect of self-interest efficacy of the vaccine. The findings are discussed regarding theoretical implications for the interplay of values and utility in motivation. In addition, implications for the potentially ambivalent effects of appealing to values to increase compliance are discussed.
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Project description: Not available
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Project description:To report population-based percentile reference values for selected spinal mobility measures in a nationally representative sample of 5,001 US adults ages 20-69 years who were examined in the 2009-2010 US National Health and Nutrition Examination Survey (NHANES).Occiput-to-wall distance (OWD), thoracic expansion (TE), and anterior lumbar flexion (ALF; by modified Schober test) were measured by trained examiners in a standardized manner. TE was measured at the xiphisternal level, while the lower reference point for ALF was a line marked at the level of the superior margin of the lateral iliac crests. We report reference values based on the 95th percentile for the OWD and the 5th percentile for TE and ALF, as well as other summary statistics for these measures, in the study population.An OWD of >0 was present in 3.8% of the participants, while 8.8% of them had out-of-range values for TE based on the commonly used threshold of 2.5 cm. The 95th percentile of the OWD measurement was 0, while the 5th percentile for TE and ALF were 1.9 cm and 2 cm, respectively. The spinal measures were significantly associated with sex, age, ethnicity, height, and body mass index (BMI). Exclusion of individuals with severe obesity (BMI >35 kg/m(2) ) changed the proposed reference values for TE and ALF to 2.2 cm and 1.9 cm, respectively.We verified a reference value of 0 for the OWD in the general population. Using the reported population-based percentile values, new reference values for TE and ALF can be derived.
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Project description:Recovering gene regulatory networks from expression data is a challenging problem in systems biology that provides valuable information on the regulatory mechanisms of cells. A number of algorithms based on computational models are currently used to recover network topology. However, most of these algorithms have limitations. For example, many models tend to be complicated because of the "large p, small n" problem. In this paper, we propose a novel regulatory network inference method called the maximum-relevance and maximum-significance network (MRMSn) method, which converts the problem of recovering networks into a problem of how to select the regulator genes for each gene. To solve the latter problem, we present an algorithm that is based on information theory and selects the regulator genes for a specific gene by maximizing the relevance and significance. A first-order incremental search algorithm is used to search for regulator genes. Eventually, a strict constraint is adopted to adjust all of the regulatory relationships according to the obtained regulator genes and thus obtain the complete network structure. We performed our method on five different datasets and compared our method to five state-of-the-art methods for network inference based on information theory. The results confirm the effectiveness of our method.
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