The haplotype network revealed a regional pattern in the distribution of this species. The results indicate that the observed variation in coloration patterns is associated with a high degree of phenotypic plasticity in G. paraguensis. These findings emphasize the importance of using an integrative approach for a more accurate diagnosis of Gymnotus, in particular, the species marketed as live bait for the fisheries of the upper Paraguay River basin in the Brazilian Pantanal.Objective To identify subgroups of urban youth based on their self- and teacher-reported mental health symptoms, and to explore characteristics of these subgroups.Methods Cross-sectional data from 426 eighth-grade students (Mage = 13.22 years; 70.1% Black/African American; 58.7% female) across 20 Baltimore City public schools were analyzed using latent profile analysis and latent regressions. Variables for latent profile analysis included self-reported symptoms (i.e., anxiety, depression, trauma, interpersonal issues, social problems, and behavioral dysfunction) and teacher-reported symptoms (i.e., externalizing, internalizing, and problems in social and emotional competence). #link# Regressions used profile membership to predict trauma exposure, coping mechanisms, and substance use.Results A 3-profile solution was found from the latent profile analysis. The profile with high student- and teacher-reported symptoms had more trauma exposures, greater use of maladaptive coping mechanisms, and higher substance use.Conclusions The current study may help in the identification of urban youth who are at risk of developing multiple co-occurring psychological disorders to target for prevention efforts.Clinical examination has become an important method of disease diagnosis, curative effect evaluation, prognosis judgment and health monitoring, and the biological reference interval is the reference standard to interpret test results and analyses of test information. In clinical tests, the reference interval is often affected by race, sex, age, geographical location and growth and development, so it is very important to establish a suitable reference interval for each laboratory. It is a huge and arduous task for each laboratory to establish its own reference interval. It is unrealistic for different measurement systems to establish reference intervals. According to the C28-A3c guideline from the Clinical and Laboratory Standards Institute (CLSI), clinical laboratories can appropriately transfer the reference intervals provided by other laboratories. This paper reviews whether the biomarkers in multiregional laboratories can transfer reference intervals between different measurement systems to expand the application of reference interval databases and ensure the accuracy and consistency of the test results.Log-rank tests have been widely used to compare two survival curves in biomedical research. We describe a unified approach to power and sample size calculation for the unweighted and weighted log-rank tests in superiority, noninferiority and equivalence trials. It is suitable for both time-driven and event-driven trials. A numerical algorithm is suggested. It allows flexible specification of the patient accrual distribution, baseline hazards, and proportional or nonproportional hazards patterns, and enables efficient sample size calculation when there are a range of choices for the patient accrual pattern and trial duration. A confidence interval method is proposed for the trial duration of an event-driven trial. We point out potential issues with several popular sample size formulae. Under proportional hazards, the power of a survival trial is commonly believed to be determined by the number of observed events. The belief is roughly valid for noninferiority and equivalence trials with similar survival and censoring distributions between two groups, and for superiority trials with balanced group sizes. In unbalanced learn more , the power depends also on other factors such as data maturity. Surprisingly, the log-rank test usually yields slightly higher power than the Wald test from the Cox model under proportional hazards in simulations. We consider various nonproportional hazards patterns induced by delayed effects, cure fractions, and/or treatment switching. Explicit power formulae are derived for the combination test that takes the maximum of two or more weighted log-rank tests to handle uncertain nonproportional hazards patterns. Numerical examples are presented for illustration.When plasma triglyceride is assessed in standard laboratories, it is a measurement of plasma glycerol after hydrolysis of triglycerides into fatty acids and glycerol. In most patients, the plasma level of free glycerol will only marginally influence the measurement of plasma triglyceride. However, in rare cases elevated free glycerol concentrations causes pseudohypertriglyceridemia and blanking for free glycerol becomes important. In this study, we investigated the plasma free glycerol level in 100 adult men with mild to moderate hypertriglyceridemia to assess the need for providing a free glycerol measurement in our clinical biochemistry department. The plasma samples were obtained in our blood sampling facility that receives both in- and outpatients. The highest plasma level of free glycerol observed was 300 µmol/L and in 99% of the investigated men the inclusion of plasma free glycerol in the measurement of plasma triglyceride cause a less than 10% false increase in plasma triglyceride. A weak positive correlation between the plasma levels of free glycerol and triglyceride was observed. When subdividing the cohort into mild and moderate hypertriglyceridemia, the positive correlation was only maintained in the moderate hypertriglyceridemia group that also demonstrated a 23% higher plasma glycerol level than men with mild hypertriglyceridemia. We conclude that even though glycerol blanking is relevant in rare occasions, then this study does not support providing such a measurement in our department. The positive correlation between free glycerol and triglyceride in this cohort likely reflects a shared association with metabolic dysregulation.