Compatibility rules of human enhancer and promoter sequences.

Gene regulation in the human genome is controlled by distal enhancers that activate specific nearby promoters1. A proposed model for this specificity is that promoters have sequence-encoded preferences for certain enhancers, for example, mediated by interacting sets of transcription factors or cofactors2. This 'biochemical compatibility' model has been supported by observations at individual human promoters and by genome-wide measurements in Drosophila3-9. However, the degree to which human enhancers and promoters are intrinsically compatible has not yet been systematically measured, and how their activities combine to control RNA expression remains unclear. Here we design a high-throughput reporter assay called enhancer × promoter self-transcribing active regulatory region sequencing (ExP STARR-seq) and applied it to examine the combinatorial compatibilities of 1,000 enhancer and 1,000 promoter sequences in human K562 cells. We identify simple rules for enhancer-promoter compatibility, whereby most enhancers activate all promoters by similar amounts, and intrinsic enhancer and promoter activities multiplicatively combine to determine RNA output (R2 = 0.82). In addition, two classes of enhancers and promoters show subtle preferential effects. Promoters of housekeeping genes contain built-in activating motifs for factors such as GABPA and YY1, which decrease the responsiveness of promoters to distal enhancers. Promoters of variably expressed genes lack these motifs and show stronger responsiveness to enhancers. Together, this systematic assessment of enhancer-promoter compatibility suggests a multiplicative model tuned by enhancer and promoter class to control gene transcription in the human genome.

Genome-wide enhancer maps link risk variants to disease genes.

Genome-wide association studies (GWAS) have identified thousands of noncoding loci that are associated with human diseases and complex traits, each of which could reveal insights into the mechanisms of disease1. Many of the underlying causal variants may affect enhancers2,3, but we lack accurate maps of enhancers and their target genes to interpret such variants. We recently developed the activity-by-contact (ABC) model to predict which enhancers regulate which genes and validated the model using CRISPR perturbations in several cell types4. Here we apply this ABC model to create enhancer-gene maps in 131 human cell types and tissues, and use these maps to interpret the functions of GWAS variants. Across 72 diseases and complex traits, ABC links 5,036 GWAS signals to 2,249 unique genes, including a class of 577 genes that appear to influence multiple phenotypes through variants in enhancers that act in different cell types. In inflammatory bowel disease (IBD), causal variants are enriched in predicted enhancers by more than 20-fold in particular cell types such as dendritic cells, and ABC achieves higher precision than other regulatory methods at connecting noncoding variants to target genes. These variant-to-function maps reveal an enhancer that contains an IBD risk variant and that regulates the expression of PPIF to alter the membrane potential of mitochondria in macrophages. Our study reveals principles of genome regulation, identifies genes that affect IBD and provides a resource and generalizable strategy to connect risk variants of common diseases to their molecular and cellular functions.

A Bayesian platform trial design with hybrid control based on multisource exchangeability modelling.

Enrolling patients to the standard of care (SOC) arm in randomized clinical trials, especially for rare diseases, can be very challenging due to the lack of resources, restricted patient population availability, and ethical considerations. As the therapeutic effect for the SOC is often well documented in historical trials, we propose a Bayesian platform trial design with hybrid control based on the multisource exchangeability modelling (MEM) framework to harness historical control data. The MEM approach provides a computationally efficient method to formally evaluate the exchangeability of study outcomes between different data sources and allows us to make better informed data borrowing decisions based on the exchangeability between historical and concurrent data. We conduct extensive simulation studies to evaluate the proposed hybrid design. We demonstrate the proposed design leads to significant sample size reduction for the internal control arm and borrows more information compared to competing Bayesian approaches when historical and internal data are compatible.

A Nomothetic Span Approach to the Construct Validation of Sustained Attention Consistency: Re-Analyzing Two Latent-Variable Studies of Performance Variability and Mind-Wandering Self-Reports.

The ability to sustain attention consistency is frequently assessed using either objective behavioral measures, such as reaction time (RT) variability, or subjective self-report measures, such as rates of task-unrelated thought (TUT). The current studies examined whether the individual-difference covariation in these measures provides a more construct valid assessment of attention consistency than does either alone. We argue that performance and self-report measures mutually validate each other; each measurement approach has its own sources of error, so their shared variance should best reflect the attention consistency construct. We reanalyzed two latent-variable studies where RT variability and TUTs were measured in multiple tasks (Kane et al. in J Exp Psychol Gen 145:1017-1048, 2016; Unsworth et al. in J Exp Psychol Gen 150:1303-1331, 2021), along with several nomological network constructs to test the convergent and discriminant validity of a general attention consistency factor. Confirmatory factor analyses assessing bifactor (preregistered) and hierarchical (non-preregistered) models suggested that attention consistency can be modeled as the shared variance among objective and subjective measures. This attention consistency factor was related to working memory capacity, attention (interference) control, processing speed, state motivation and alertness, and self-reported cognitive failures and positive schizotypy. Although bifactor models of general attention consistency provide the most compelling construct validity evidence for a specific ability to sustain attention, multiverse analyses of outlier decisions suggested they are less robust than hierarchical models. The results provide evidence for the general ability to sustain attention consistency and suggestions for improving its measurement.

Current Understanding of Sodium N-(8-[2-Hydroxylbenzoyl] Amino) Caprylate (SNAC) as an Absorption Enhancer: The Oral Semaglutide Experience.

Oral administration of peptide therapeutics faces challenges because of the distinct environment of the gastrointestinal tract. An oral formulation of semaglutide, a glucagon-like peptide 1 receptor agonist, was approved by the U.S. Food and Drug Administration in 2019 as a peptide therapy for the treatment of type 2 diabetes. Oral semaglutide uses sodium N-(8-[2-hydroxybenzoyl] amino) caprylate (SNAC) technology to enhance the absorption of semaglutide in the stomach and protect it from degradation by gastric enzymes. This article presents a summary of studies investigating SNAC technology as an absorption enhancer for a number of molecules and, in particular, explores how SNAC, once coformulated with oral semaglutide, facilitates increased absorption and bioavailability. Practical advice and dispensing information for pharmacists is also provided.

A compressed large language model embedding dataset of ICD 10 CM descriptions.

This paper presents novel datasets providing numerical representations of ICD-10-CM codes by generating description embeddings using a large language model followed by a dimension reduction via autoencoder. The embeddings serve as informative input features for machine learning models by capturing relationships among categories and preserving inherent context information. The model generating the data was validated in two ways. First, the dimension reduction was validated using an autoencoder, and secondly, a supervised model was created to estimate the ICD-10-CM hierarchical categories. Results show that the dimension of the data can be reduced to as few as 10 dimensions while maintaining the ability to reproduce the original embeddings, with the fidelity decreasing as the reduced-dimension representation decreases. Multiple compression levels are provided, allowing users to choose as per their requirements, download and use without any other setup. The readily available datasets of ICD-10-CM codes are anticipated to be highly valuable for researchers in biomedical informatics, enabling more advanced analyses in the field. This approach has the potential to significantly improve the utility of ICD-10-CM codes in the biomedical domain.

A Natural Language Processing and Machine Learning Approach to Identification of Incidental Radiology Findings in Trauma Patients Discharged from the Emergency Department.

STUDY OBJECTIVE: Patients undergoing diagnostic imaging studies in the emergency department (ED) commonly have incidental findings, which may represent unrecognized serious medical conditions, including cancer. Recognition of incidental findings frequently relies on manual review of textual radiology reports and can be overlooked in a busy clinical environment. Our study aimed to develop and validate a supervised machine learning model using natural language processing to automate the recognition of incidental findings in radiology reports of patients discharged from the ED. METHODS: We performed a retrospective analysis of computed tomography (CT) reports from trauma patients discharged home across an integrated health system in 2019. Two independent annotators manually labeled CT reports for the presence of an incidental finding as a reference standard. We used regular expressions to derive and validate a random forest model using open-source and machine learning software. Final model performance was assessed across different ED types. RESULTS: The study CT reports were divided into derivation (690 reports) and validation (282 reports) sets, with a prevalence of incidental findings of 22.3%, and 22.7%, respectively. The random forest model had an area under the curve of 0.88 (95% confidence interval [CI], 0.84 to 0.92) on the derivation set and 0.92 (95% CI, 0.88 to 0.96) on the validation set. The final model was found to have a sensitivity of 92.2%, a specificity of 79.4%, and a negative predictive value of 97.2%. Similarly, strong model performance was found when stratified to a dedicated trauma center, high-volume, and low-volume community EDs. CONCLUSION: Machine learning and natural language processing can classify incidental findings in CT reports of ED patients with high sensitivity and high negative predictive value across a broad range of ED settings. These findings suggest the utility of natural language processing in automating the review of free-text reports to identify incidental findings and may facilitate interventions to improve timely follow-up.

Intratumoral injection of the seasonal flu shot converts immunologically cold tumors to hot and serves as an immunotherapy for cancer.

Reprogramming the tumor microenvironment to increase immune-mediated responses is currently of intense interest. Patients with immune-infiltrated "hot" tumors demonstrate higher treatment response rates and improved survival. However, only the minority of tumors are hot, and a limited proportion of patients benefit from immunotherapies. Innovative approaches that make tumors hot can have immediate impact particularly if they repurpose drugs with additional cancer-unrelated benefits. The seasonal influenza vaccine is recommended for all persons over 6 mo without prohibitive contraindications, including most cancer patients. Here, we report that unadjuvanted seasonal influenza vaccination via intratumoral, but not intramuscular, injection converts "cold" tumors to hot, generates systemic CD8+ T cell-mediated antitumor immunity, and sensitizes resistant tumors to checkpoint blockade. Importantly, intratumoral vaccination also provides protection against subsequent active influenza virus lung infection. Surprisingly, a squalene-based adjuvanted vaccine maintains intratumoral regulatory B cells and fails to improve antitumor responses, even while protecting against active influenza virus lung infection. Adjuvant removal, B cell depletion, or IL-10 blockade recovers its antitumor effectiveness. Our findings propose that antipathogen vaccines may be utilized for both infection prevention and repurposing as a cancer immunotherapy.

Impact of DaxibotulinumtoxinA for Injection on Brow Position and Frontalis Muscle Activity Following Treatment of Glabellar Lines.

BACKGROUND: Botulinum toxin type A (BoNTA) injections for the treatment of facial lines may lead to pleasant or undesirable changes in eyebrow height and position. OBJECTIVES: The aim of this study was to evaluate the impact of glabellar injection of DaxibotulinumtoxinA for Injection (DAXI), a novel BoNTA formulation, on eyebrow position and frontalis activity. METHODS: This study involved the post hoc analysis of adult patients from the Phase 2a forehead lines (FHL, N = 60) and open-label safety (OLS, N = 175) studies who received a single dose of DAXI 40 U to the glabella and for whom facial photographs were taken at rest and at maximum eyebrow elevation. Median vertical and horizontal displacement of the brows and median forehead strain (an objective quantitative assessment of frontalis activity) from baseline to 2 weeks after glabellar DAXI injection were measured. RESULTS: Two weeks after glabellar DAXI injection, vertical eyebrow movement (at rest) of the lateral brow was observed. In both studies, vertical movement was greatest in the lateral (0.6-0.9 mm) and mid (0.5-0.7 mm) brow regions; movement in the medial brow was negligible (0-0.23 mm). In both studies, a graded reduction in forehead strain was observed 2 weeks post glabellar DAXI injection, with the greatest reduction being in the lower segment (FHL, -73%; OLS, -82%). Treatment with DAXI showed improvements in FHL wrinkle severity. CONCLUSIONS: Glabellar injection of DAXI showed a positive reduction in dynamic frontalis activity that maintained or had a positive effect on eyebrow position. Vertical movement of the brow was suggestive of an improved eyebrow shape with a mild lateral arch.

A "Goldilocks zone" for mind-wandering reports? A secondary data analysis of how few thought probes are enough for reliable and valid measurement.

Mind-wandering assessment relies heavily on the thought probe technique as a reliable and valid method to assess momentary task-unrelated thought (TUT), but there is little guidance available to help researchers decide how many probes to include within a task. Too few probes may lead to unreliable measurement, but too many probes might artificially disrupt normal thought flow and produce reactive effects. Is there a "Goldilocks zone" for how few thought probes can be used to reliably and validly assess individual differences in mind-wandering propensity? We address this question by reanalyzing two published datasets (Study 1, n = 541; Study 2, ns ≈ 260 per condition) in which thought probes were presented in multiple tasks. Our primary analyses randomly sampled probes in increments of two for each subject in each task. A series of confirmatory factor analyses for each probe "bin" size tested whether the latent correlations between TUT rate and theoretically relevant constructs like working memory capacity, attention-control ability, disorganized schizotypy, and retrospective self-reported mind wandering changed as more probes assessed the TUT rate. TUT rates were remarkably similar across increasing probe-bin sizes and zero-order correlations within and between tasks stabilized at 8-10 probes; moreover, TUT-rate correlations with other latent variables stabilized at about 8 thought probes. Our provisional recommendation (with caveats) is that researchers may use as few as 8 thought probes in prototypical cognitive tasks to gain reliable and valid information about individual differences in TUT rate.

Bayesian local exchangeability design for phase II basket trials.

We propose an information borrowing strategy for the design and monitoring of phase II basket trials based on the local multisource exchangeability assumption between baskets (disease types). In our proposed local-MEM framework, information borrowing is only allowed to occur locally, that is, among baskets with similar response rate and the amount of information borrowing is determined by the level of similarity in response rate, whereas baskets not considered similar are not allowed to share information. We construct a two-stage design for phase II basket trials using the proposed strategy. The proposed method is compared to competing Bayesian methods and Simon's two-stage design in a variety of simulation scenarios. We demonstrate the proposed method is able to maintain the family-wise type I error rate at a reasonable level and has desirable basket-wise power compared to Simon's two-stage design. In addition, our method is computationally efficient compared to existing Bayesian methods in that the posterior profiles of interest can be derived explicitly without the need for sampling algorithms. R scripts to implement the proposed method are available at https://github.com/yilinyl/Bayesian-localMEM.

Incidental Radiology Findings on Computed Tomography Studies in Emergency Department Patients: A Systematic Review and Meta-Analysis.

STUDY OBJECTIVE: An incidental finding is defined as a newly discovered mass or lesion detected on imaging performed for an unrelated reason. The identification of an incidental finding may be an opportunity for the early detection of a serious medical condition, including a malignancy. However, little is known about the prevalence of incidental findings in the emergency department (ED) setting and the strategies that can be used to mitigate the risk associated with them in the ED. This study aimed to estimate the overall prevalence of incidental findings and to summarize the currently described measures to mitigate the risks associated with incidental findings. METHODS: On November 22, 2020, a systematic literature search of PubMed, EMBASE, and Scopus was performed for studies that were published in peer-reviewed journals and reported the prevalence of incidental findings in computed tomography (CT) scans in patients in the ED. Patients who received CT scans that included the head, neck, chest, or abdomen/pelvis were included. The study characteristics, overall prevalence of incidental findings, prevalence of incidental findings by body region, and prespecified subgroups were extracted. The criteria used for risk stratification within individual studies were also extracted. Pooled estimates were calculated using a random-effects meta-analysis. RESULTS: A total of 1,385 studies were identified, and 69 studies met the inclusion criteria. The included studies represented 147,763 ED encounters or radiology reports across 16 countries, and 83% of studies were observational, cross-sectional studies. A total of 35 studies (50.7%) were in trauma patients. A large degree of heterogeneity was observed across the included studies. The overall pooled prevalence estimate for any incidental finding was 31.3% (95% confidence interval 24.4% to 39.1%). We found great variation in the methods described to mitigate the risk associated with incidental findings, including a lack of standardized risk stratification, inconsistent documentation practices, and only a small subset of studies describing prospective interventions aimed at improving the recognition and management of incidental findings from the ED. CONCLUSION: In patients in the ED receiving CT scans, incidental findings are commonly encountered across a broad range of ED chief complaints. This review highlights the existence of great heterogeneity in the definitions used to classify incidental findings. Future studies are needed to determine a clinically feasible categorization standard or terminology for commonly encountered incidental findings in the ED setting to standardize classification and documentation.

Local regulation of gene expression by lncRNA promoters, transcription and splicing.

Mammalian genomes are pervasively transcribed to produce thousands of long non-coding RNAs (lncRNAs). A few of these lncRNAs have been shown to recruit regulatory complexes through RNA-protein interactions to influence the expression of nearby genes, and it has been suggested that many other lncRNAs can also act as local regulators. Such local functions could explain the observation that lncRNA expression is often correlated with the expression of nearby genes. However, these correlations have been challenging to dissect and could alternatively result from processes that are not mediated by the lncRNA transcripts themselves. For example, some gene promoters have been proposed to have dual functions as enhancers, and the process of transcription itself may contribute to gene regulation by recruiting activating factors or remodelling nucleosomes. Here we use genetic manipulation in mouse cell lines to dissect 12 genomic loci that produce lncRNAs and find that 5 of these loci influence the expression of a neighbouring gene in cis. Notably, none of these effects requires the specific lncRNA transcripts themselves and instead involves general processes associated with their production, including enhancer-like activity of gene promoters, the process of transcription, and the splicing of the transcript. Furthermore, such effects are not limited to lncRNA loci: we find that four out of six protein-coding loci also influence the expression of a neighbour. These results demonstrate that cross-talk among neighbouring genes is a prevalent phenomenon that can involve multiple mechanisms and cis-regulatory signals, including a role for RNA splice sites. These mechanisms may explain the function and evolution of some genomic loci that produce lncRNAs and broadly contribute to the regulation of both coding and non-coding genes.

Bayesian basket trial design with false-discovery rate control.

BACKGROUND: Recent advances in developing "tumor agnostic" oncology therapies have identified molecular targets that define patient subpopulations in a manner that supersedes conventional criteria for cancer classification. These successes have produced effective targeted therapies that are administered to patients regardless of their tumor histology. Trials have evolved as well with master protocol designs. By blending translational and clinical science, basket trials in particular are well-suited to investigate and develop targeted therapies among multiple cancer histologies. However, basket trials intrinsically involve more complex design decisions, including issues of multiple testing across baskets, and guidance for investigators is needed. METHODS: The sensitivity of the multisource exchangeability model to prior specification under differing degrees of response heterogeneity is explored through simulation. Then, a multisource exchangeability model design that incorporates control of the false-discovery rate is presented and a simulation study compares the operating characteristics to a design where the family-wise error rate is controlled and to the frequentist approach of treating the baskets as independent. Simulations are based on the original design of a real-world clinical trial, the SUMMIT trial, which investigated Neratinib treatment for a variety of solid tumors. The methods studied here are specific to single-arm phase II trials with binary outcomes. RESULTS: Values of prior probability of exchangeability in the multisource exchangeability model between 0.1 and 0.3 provide the best trade-offs between gain in precision and bias, especially when per-basket sample size is below 30. Application of these calibration results to a re-analysis of the SUMMIT trial showed that the breast basket exceeded the null response rate with posterior probability of 0.999 while having low posterior probability of exchangeability with all other baskets. Simulations based on the design of the SUMMIT trial revealed that there is meaningful improvement in power even in baskets with small sample size when the false-discovery rate is controlled as opposed to the family-wise error rate. For example, when only the breast basket was active, with a sample size of 25, the power was 0.76 when the false-discovery rate was controlled at 0.05 but only 0.56 when the family-wise error rate was controlled at 0.05, indicating that impractical sample sizes for the phase II setting would be needed to achieve acceptable power while controlling the family-wise error rate in this setting of a trial with 10 baskets. CONCLUSION: Selection of the prior exchangeability probability based on calibration and incorporation of false-discovery rate control result in multisource exchangeability model designs with high power to detect promising treatments in the context of phase II basket trials.

The Occurrence and Burden of Hypophosphatasia in an Ambulatory Care Endocrinology Practice.

OBJECTIVE: Hypophosphatasia (HPP) is an inherited disease resulting from loss-of-function mutations in the ALPL gene encoding tissue-nonspecific alkaline phosphatase. The presentation and severity of the disease are highly variable, ranging from perinatal onset with high mortality rates to adult identification with low mortality rates and symptoms ranging from minimal to severe. Moderate forms of HPP typically manifest during middle age and are often undiagnosed. The objective of this study was to determine the occurrence and burden of HPP in an ambulatory care endocrinology practice. METHODS: Potential subjects were identified with a computerized text search of patient electronic medical records. Search terms included serum alkaline phosphatase (ALP) levels of ≤40 U/L. Records of patients with at least 2 low ALP levels were reviewed manually to identify potential patients with a history consistent with hypophosphatasia. RESULTS: In total, 315 patients with ALP levels ≤40 U/L were identified from an estimated 20 000 patient records. Fifty-six patients with a single low level were excluded from further review. The remaining 259 patients were reviewed, 10 of whom had histories consistent with HPP. None of the identified 10 patients was currently being treated or had previously been treated for HPP. Information about these patients was shared with their respective providers, along with the recommendation to proceed with further evaluation to confirm the diagnosis of HPP. CONCLUSION: Hypophosphatasia is an uncommon condition with variable presentation, often resulting in a missed diagnosis. Surveillance of practices by identifying patients with low ALP levels is a rational screening approach to identifying potential patients with HPP.

Individual differences in task-unrelated thought in university classrooms.

This study investigated what academic traits, attitudes, and habits predict individual differences in task-unrelated thought (TUT) during lectures, and whether this TUT propensity mediates associations between academic individual differences and course outcomes (final grade and situational interest evoked by material). Undergraduates (N = 851) from ten psychology classes at two US universities responded to thought probes presented during two early-course lectures; they also indicated sitting in the front, middle, or back of the classroom. At each probe, students categorized their thought content, such as indicating on-task thought or TUT. Students also completed online, academic-self-report questionnaires at the beginning of the course and a situational interest questionnaire at the end. Average TUT rate was 24% but individuals' rates varied widely (SD = 18%). TUT rates also increased substantially from the front to back of the classroom, and modestly from the first to second half of class periods. Multiple-group analyses (with ten classroom groups) indicated that: (a) classroom media-multitasking habits, initial interest in the course topic, and everyday propensity for mind-wandering and boredom accounted for unique variance in TUT rate (beyond other predictors); (b) TUT rate accounted for unique (modest) variance in course grades and situational interest; and (c) classroom media multitasking and propensity for mind-wandering and boredom had indirect associations with course grades via TUT rate, and these predictor variables, along with initial interest, had indirect associations with end-of-term situational interest via TUT rate. Some academic traits and behaviors predict course outcomes in part because they predict off-task thought during class.

Robust prediction of individual creative ability from brain functional connectivity.

People's ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis-connectome-based predictive modeling-to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences (r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems-intrinsic functional networks that tend to work in opposition-suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks.

Circadian Rhythm Analysis Using Wearable Device Data: Novel Penalized Machine Learning Approach.

BACKGROUND: Wearable devices have been widely used in clinical studies to study daily activity patterns, but the analysis remains a major obstacle for researchers. OBJECTIVE: This study proposes a novel method to characterize sleep-activity rhythms using actigraphy and further use it to describe early childhood daily rhythm formation and examine its association with physical development. METHODS: We developed a machine learning-based Penalized Multiband Learning (PML) algorithm to sequentially infer dominant periodicities based on the Fast Fourier Transform (FFT) algorithm and further characterize daily rhythms. We implemented and applied the algorithm to Actiwatch data collected from a cohort of 262 healthy infants at ages 6, 12, 18, and 24 months, with 159, 101, 111, and 141 participants at each time point, respectively. Autocorrelation analysis and Fisher test in harmonic analysis with Bonferroni correction were applied for comparison with the PML. The association between activity rhythm features and early childhood motor development, assessed using the Peabody Developmental Motor Scales-Second Edition (PDMS-2), was studied through linear regression analysis. RESULTS: The PML results showed that 1-day periodicity was most dominant at 6 and 12 months, whereas one-day, one-third-day, and half-day periodicities were most dominant at 18 and 24 months. These periodicities were all significant in the Fisher test, with one-fourth-day periodicity also significant at 12 months. Autocorrelation effectively detected 1-day periodicity but not the other periodicities. At 6 months, PDMS-2 was associated with the assessment seasons. At 12 months, PDMS-2 was associated with the assessment seasons and FFT signals at one-third-day periodicity (P<.001) and half-day periodicity (P=.04), respectively. In particular, the subcategories of stationary, locomotion, and gross motor were associated with the FFT signals at one-third-day periodicity (P<.001). CONCLUSIONS: The proposed PML algorithm can effectively conduct circadian rhythm analysis using time-series wearable device data. The application of the method effectively characterized sleep-wake rhythm development and identified the association between daily rhythm formation and motor development during early childhood.

Testing the construct validity of competing measurement approaches to probed mind-wandering reports.

Psychology faces a measurement crisis, and mind-wandering research is not immune. The present study explored the construct validity of probed mind-wandering reports (i.e., reports of task-unrelated thought [TUT]) with a combined experimental and individual-differences approach. We examined laboratory data from over 1000 undergraduates at two U.S. institutions, who responded to one of four different thought-probe types across two cognitive tasks. We asked a fundamental measurement question: Do different probe types yield different results, either in terms of average reports (average TUT rates, TUT-report confidence ratings), or in terms of TUT-report associations, such as TUT rate or confidence stability across tasks, or between TUT reports and other consciousness-related constructs (retrospective mind-wandering ratings, executive-control performance, and broad questionnaire trait assessments of distractibility-restlessness and positive-constructive daydreaming)? Our primary analyses compared probes that asked subjects to report on different dimensions of experience: TUT-content probes asked about what they'd been mind-wandering about, TUT-intentionality probes asked about why they were mind-wandering, and TUT-depth probes asked about the extent (on a rating scale) of their mind-wandering. Our secondary analyses compared thought-content probes that did versus didn't offer an option to report performance-evaluative thoughts. Our findings provide some "good news"-that some mind-wandering findings are robust across probing methods-and some "bad news"-that some findings are not robust across methods and that some commonly used probing methods may not tell us what we think they do. Our results lead us to provisionally recommend content-report probes rather than intentionality- or depth-report probes for most mind-wandering research.

Two-stage randomized trial design for testing treatment, preference, and self-selection effects for count outcomes.

While the traditional clinical trial design lays emphasis on testing the treatment effect between randomly assigned groups, it ignores the role of patient preference for a particular treatment in the trial. Yet, for healthcare providers who seek to optimize the patient-centered treatment strategy, the evaluation of a patient's psychology toward each treatment could be a key consideration. The two-stage randomized trial design allows researchers to test patient's preference and selection effects, in addition to the treatment effect. The current methodology for the two-stage design is limited to continuous and binary outcomes; this article extends the model to include count outcomes. The test statistics for preference, selection, and treatment effects are derived. Closed-form sample size formulae are presented for each effect. Simulations are presented to demonstrate the properties of the unstratified and stratified designs. Finally, we apply methods to the use of antimicrobials at the end of life to demonstrate the applicability of the methods.