Background: Enrichment or over-representation analysis is a common method used in bioinformatics studies of transcriptomics, metabolomics, and microbiome datasets. The key idea behind enrichment analysis is: given a set of significantly expressed genes (or metabolites), use that set to infer a smaller set of perturbed biological pathways or processes, in which those genes (or metabolites) play a role. Enrichment computations rely on collections of defined biological pathways and/or processes, which are usually drawn from pathway databases. Although practitioners of enrichment analysis take great care to employ statistical corrections (e.g., for multiple testing), they appear unaware that enrichment results are quite sensitive to the pathway definitions that the calculation uses.
Results: We show that alternative pathway definitions can alter enrichment p -values by up to nine orders of magnitude, whereas statistical corrections typically alter enrichment p -values by only two orders of magnitude. We present multiple examples where the smaller pathway definitions used in the EcoCyc database produces stronger enrichment p -values than the much larger pathway definitions used in the KEGG database; we demonstrate that to attain a given enrichment p -value, KEGG-based enrichment analyses require 1.3–2.0 times as many significantly expressed genes as does EcoCyc-based enrichment analyses. The large pathways in KEGG are problematic for another reason: they blur together multiple (as many as 21) biological processes. When such a KEGG pathway receives a high enrichment p -value, which of its component processes is perturbed is unclear, and thus the biological conclusions drawn from enrichment of large pathways are also in question.
Conclusions: The choice of pathway database used in enrichment analyses can have a much stronger effect on the enrichment results than the statistical corrections used in these analyses.
Article
Sleep and Circadian Regulation of the Autonomic Nervous System
Sleep and the autonomic nervous system (ANS) are intimately connected. The ANS is under the influence of circadian and sleep-dependent modulation. Forced desynchrony and constant routine protocols indicate strong circadian influences on heart rate (HR) and cardiac vagal activity, which fluctuate across 24 hours, with HR being lower, and vagal activity higher, during the nocturnal period. Sleep also influences ANS activity: during non-rapid-eye-movement (NREM) sleep, sympathetic activity is lower and vagal functioning is higher, compared to rapid-eye-movement (REM) sleep, where ANS activity is more similar to wakefulness. A change in ANS innervation of the heart and vasculature drives the wake-to-sleep reductions in blood pressure, HR, and systemic vascular resistance. The reduction in cardiovascular activity during sleep, prominent during NREM sleep, plays a key role in maintaining cardiovascular health, providing a “ cardiovascular holiday. ” Sleep-dependent as well as circadian regulation of vagal activity is evident very early in life and persists across adulthood. There is some evidence of sex differences in sleep-dependent vagal activity in adolescents as well as female hormone effects on nocturnal ANS measures, although further work is needed to determine the significance of these effects.
Transformer Based Molecule Encoding for Property Prediction
Neural methods of molecule property prediction require efficient encoding of structure and property relationship to be accurate. Recent work using graph algorithms shows limited generalization in the latent molecule encoding space. We build a Transformer-based molecule encoder and property predictor network with novel input featurization that performs significantly better than existing methods. We adapt our model to semi-supervised learning to further perform well on the limited experimental data usually available in practice.
Improving Implementation of Programs and Practices for Children with Disabilities
This report synthesizes findings of the Model Demonstration Coordination Center (MDCC), funded by the U.S. Department of Education, Office of Special Education Programs from 2005 to 2015. MDCC worked with 34 model demonstration and technology implementation grantees to identify characteristics of an effective implementation and intervention refinement process—one that moves a practice or tool from early testing to full implementation, sustained implementation, and wider adoption. Working with these 34 grantees provided MDCC with a valuable opportunity to examine experiences across a diverse set of interventions, settings, and populations as a basis for identifying strategies grantees have used to produce high-quality implementation and sustainment of interventions.
Serum Biomarkers Reveal Long-term Cardiac Injury in Isoproterenol-treated African Green Monkeys
The assessment of cardiac toxicity is a major challenge in both drug development and clinical trials, and numerous marketed pharmaceuticals have been removed from the market due to unpredicted cardiac effects. Serum troponins are widely used indicators of cardiac injury; however, they are short-lived and have not been validated in preclinical animal models. In this study, we have used filter-aided sample preparation (FASP) and tandem mass tag (TMT) labeling to investigate serum protein alterations in isoproterenol-treated African green monkeys. Our results showed that the combination of FASP and TMT labeling provided highly reproducible and efficient sample preparation, which enables us to identify and quantify serum proteins with high confidence. We focused on the proteins that exhibit long-term alteration upon isoproterenol injection and discovered nine proteins exhibiting significant changes at 48 and 72 h postdosing. We further chose three proteins, serum amyloid A (SAA), frutose biphosphate aldolase A (FBAA), and fetuin A, for validation using enzyme-linked immunosorbent assay (ELISA). The serum concentration of SAA showed a ∼ 50 fold increase, while concentration of FBAA and fetuin A exhibited a significant decrease accompanying isoproterenol-induced cardiotoxicity. This work provides valuable insights for multimarker evaluation of long-term cardiac injury.
Safety and Pharmacokinetic of Single Dose Novel Oral Androgen 11β-Methyl-19-Nortestosterone-17β-dodecylcarbonate in Men
Context: 11β-Methyl-19-nortestosterone-17β-dodecylcarbonate (11β-MNTDC) is an orally bioavailable prodrug of 11β-methyl-19-nortestosterone (11β-MNT) with androgenic and progestational activity.
Objectives: (i) Quantify 11β-MNT binding to androgen and progesterone receptors. (ii) Evaluate safety, tolerability, and serum gonadotropin and testosterone suppression by 11β-MNTDC in men.
Design and setting: (i) In vitro receptor binding and transactivation studies and (ii) randomized, double-blind, placebo-controlled single-dose, dose-escalating phase I study at two academic medical centers.
Participants and intervention: Twelve healthy male volunteers were randomized (five active, one placebo) to escalating single oral doses (100, 200, 400, and 800 mg) of 11β-MNTDC or placebo given with or without food.
Main outcome measures: (i) In vitro 11β-MNT/11β-MNTDC human receptor binding and transactivation and (ii) safety and tolerability, pharmacokinetics, and quantification of serum gonadotropin and testosterone concentrations for 24 hours following dosing.
Results: 11β-MNT avidly binds and activates human androgen and progesterone receptors, but 11β-MNTDC has minimal activity. Single oral doses of 11β-MNTDC were well tolerated without serious adverse events. Administration of 11β-MNTDC with food markedly increased average 11β-MNTDC and 11β-MNT serum concentrations (P < 0.001 for all doses) compared with fasting with a significant dose-related effect on average serum drug concentrations (P < 0.0001). The 200-, 400-, and 800-mg doses significantly suppressed average serum testosterone concentrations (P < 0.05).
Conclusions: A single, oral dose of 11β-MNTDC up to 800 mg administered with food is safe and well tolerated in healthy men. The active drug 11β-MNT has androgenic and progestational activity, rapidly suppresses serum testosterone, and is a promising candidate for an effective once-daily oral male hormonal contraceptive.
How the COVID‐19 Pandemic Has Changed Our Lives: A Study of Psychological Correlates Across 59 Countries
Objective: This study examined the impact of the COVID‐19 pandemic and subsequent social restrictions or quarantines on the mental health of the global adult population.
Method: A sample of 6,882 individuals ( M age = 42.30; 78.8% female) from 59 countries completed an online survey asking about several pandemic‐related changes in life and psychological status.
Results: Of these participants, 25.4% and 19.5% reported moderate‐to‐severe depression (DASS‐21) and anxiety symptoms (GAD‐7), respectively. Demographic characteristics (e.g. higher‐income country), COVID‐19 exposure (e.g., having had unconfirmed COVID‐19 symptoms), government‐imposed quarantine level, and COVID‐19‐based life changes (e.g., having a hard time transitioning to working from home; increase in verbal arguments or conflict with other adult in home) explained 17.9% of the variance in depression and 21.5% in anxiety symptoms.
Conclusions: In addition to posing a high risk to physical health, the COVID‐19 pandemic has robustly affected global mental health, so it is essential to ensure that mental health services reach individuals showing pandemic‐related depression and anxiety symptoms.
Effects of forehead cooling and supportive care on menopause-related sleep difficulties, hot flashes and menopausal symptoms: A pilot study.
Objective/Background: This pilot study explored the efficacy of a novel forehead cooling device for perceived sleep difficulties and hot flashes in menopausal-age women.
Participants: 20 women (55.1 ± 4.2 years; 19 post-menopausal) with insomnia symptoms and self-reported two or more hot flashes per day.
Methods: Participants completed daily assessments of sleep and hot flashes (via diaries) across 1 baseline week and 4 weeks of open-label, in-home, nightly treatment with a forehead cooling device (15–18°C) along with sleep hygiene instructions. They also completed ratings of insomnia and menopausal symptoms using standardized questionnaires.
Results: Women reported reductions in sleep onset latency (SOL), wakefulness after sleep onset (WASO), and nocturnal hot flash severity during the first week of treatment (SOL: 25.7 ± 18.4 min; WASO: 36.3 ± 27.3 min; hot flash severity: 3.0 ± 2.8) compared with baseline (SOL: 38 ± 26.3 min; WASO: 52.2 ± 35.6 min; hot flash severity: 6.8 ± 3.7), with further improvements after 2–4 weeks of use ( p < .001). There were also clinically meaningful reductions in insomnia severity and hot flash-related daily interference and lower psychological and physical symptom scores on the Greene climacteric scale after treatment (all p’s<0.001). Conclusions: This exploratory, naturalistic, pilot study shows that nightly use of a forehead cooling device produces improvements in self-reported sleep and reductions in insomnia, hot flash, and other menopausal, symptoms. Controlled studies are warranted to determine the role of this therapy in the management of sleep difficulties and menopausal symptoms in women. Further mechanistic studies are needed to understand the physiological impact of forehead cooling on sleep and menopausal symptoms.
Shining a Light on Algebra I Access and Success: Embracing Equity at All Levels
This REL Appalachia blog summarizes a recent IES report, examining Algebra I course taking pathways and outcomes based on students’ performance on Virginia’s grade 5 statewide math test, which showed significant equity gaps. The blog further encourages systematic data analysis related to course taking access and student success and includes practical advice on accomplishing this, including ideas on specific data points to pull and use.
Early Childhood Integrated Data Analytic Self-Assessment Rubric
The ECIDS toolkit has seven components (e.g. Purpose and Vision, Planning and Management, Stakeholder Engagement, etc.) and is useful as a self-assessment tool and roadmap for improving ECIDS. ECDataWorks and partner states propose developing an ECIDS data analytic self-assessment tool for states that focuses on the process of translating ECIDS data to information to action. This process typically involves the design, development, and implementation of analytic tools. Designing, developing, and implementing analytic tools is challenging for several reasons
Dropout prevention in the time of COVID-19
Students on the path toward dropping out of high school often exhibit signals that they are at risk well before they stop engaging in school. As school closures due to COVID-19 separate students from structured routines and educational supports, the number of disengaged students may continue to grow. Educators should be aware of and look for signs of disengagement and act to maximize engagement and supports for at-risk students during COVID-19 closures.
Racial Differences in Special Education Identification and Placement: Evidence Across Three States
In this article, Todd Grindal, Laura Schifter, Gabriel Schwartz, and Thomas Hehir examine race/ethnicity differences in students’ special education identification and subsequent placement in segregated educational settings. Using individual-level data on the full population of K–12 public school students in three states, the authors find that racial and ethnic disparities in identification persist within income categories and are stronger for those disabilities that are typically identified in a school setting, such as learning disabilities or emotional disabilities, than those more often identified by a health-care provider, such as blindness or deafness. Also, Black and Hispanic students with disabilities were more likely to be placed in a substantially separate setting, compared to white students, regardless of income status. These results suggest that low-income status is insufficient to explain observed inequalities in the rate at which students of color are identified for special education and placed in substantially separate settings. A better understanding of the ways income status and race contribute to students’ interactions with the special education system are critical for building a more equitable and just K–12 education system.
A standardized framework for testing the performance of sleep-tracking technology: Step-by-step guidelines and open-source code
Sleep-tracking devices, particularly within the consumer sleep technology (CST) space, are increasingly used in both research and clinical settings, providing new opportunities for large-scale data collection in highly ecological conditions. Due to the fast pace of the CST industry combined with the lack of a standardized framework to evaluate the performance of sleep trackers, their accuracy and reliability in measuring sleep remains largely unknown. Here, we provide a step-by-step analytical framework for evaluating the performance of sleep trackers (including standard actigraphy), as compared to gold-standard polysomnography (PSG) or other reference methods. The analytical guidelines are based on recent recommendations for evaluating and using CST from our group and others (de Zambotti, Cellini, Goldstone, Colrain & Baker, 2019; Depner et al., 2019), and include raw data organization as well as critical analytical procedures, including discrepancy analysis, Bland-Altman plots, and epoch-by-epoch analysis. Analytical steps are accompanied by open-source R functions (depicted at https://sri-human-sleep.github.io/sleep-trackers-performance/AnalyticalPipeline_v1.0.0.html). In addition, an empirical sample dataset is used to describe and discuss the main outcomes of the proposed pipeline. The guidelines and the accompanying functions are aimed at standardizing the testing of CSTs performance, to not only increase the replicability of validation studies, but also to provide ready-to-use tools to researchers and clinicians. All in all, this work can help to increase the efficiency, interpretation, and quality of validation studies, and to improve the informed adoption of CST in research and clinical settings.
What foundational skills matter for Algebra I success?
Algebra I is considered a gateway course for advanced math. Consequently, there has been a trend toward enrolling students in Algebra I earlier in the middle grades in order to increase opportunities for students to take more advanced math courses in high school. The challenge for educators lies in determining which students are ready to take Algebra I in middle school and which students need more time to develop foundational knowledge and skills before taking Algebra I. To inform strategies that address this challenge, educators from the Missouri Department of Elementary and Secondary Education partnered with Regional Educational Laboratory Central to investigate the specific foundational knowledge and skills that are associated with achievement in Algebra I. This study examined whether student knowledge in five domains of math assessed in grade 7 was associated with Algebra I achievement. The study found that students’ scores in all five of the grade 7 domains were related to Algebra I achievement, but their performance in the expressions, equations, and inequalities domain was most strongly related. The number sense and operations domain was more strongly associated with Algebra I achievement for English learner students than it was for students without this designation. No clear differences in these associations were found between students who were receiving special education services and those who were not.
Measuring Chinese middle school students’ motivation using the Reduced Instructional Materials Motivation Survey (RIMMS): A validation study in the adaptive learning setting
Valid measures of student motivation can inform the design of learning environments to engage students and maximize learning gains. This study validates a measure of student motivation, the Reduced Instructional Materials Motivation Survey (RIMMS), with a sample of Chinese middle school students using an adaptive learning system in math. Participants were 429 students from 21 provinces in China. Their ages ranged from 14 to 17 years old, and most were in 9th grade. A confirmatory factor analysis (CFA) validated the RIMMS in this context by demonstrating that RIMMS responses retained the intended four-factor structure: attention, relevance, confidence, and satisfaction. To illustrate the utility of measuring student motivation, this study identifies factors of motivation that are strongest for specific student subgroups. Students who expected to attend elite high schools rated the adaptive learning system higher on all four RIMMS motivation factors compared to students who did not expect to attend elite high schools. Lower parental education levels were associated with higher ratings on three RIMMS factors. This study contributes to the field’s understanding of student motivation in adaptive learning settings.
