Category: Statistics

Multivariate Behav Res. 2023 Jun 28:1-13. doi: 10.1080/00273171.2023.2217662. Online ahead of print.

ABSTRACT

In many psychometric applications, the relationship between the mean of an outcome and a quantitative covariate is too complex to be described by simple parametric functions; instead, flexible nonlinear relationships can be incorporated using penalized splines. Penalized splines can be conveniently represented as a linear mixed effects model (LMM), where the coefficients of the spline basis functions are random effects. The LMM representation of penalized splines makes the extension to multivariate outcomes relatively straightforward. In the LMM, no effect of the quantitative covariate on the outcome corresponds to the null hypothesis that a fixed effect and a variance component are both zero. Under the null, the usual asymptotic chi-square distribution of the likelihood ratio test for the variance component does not hold. Therefore, we propose three permutation tests for the likelihood ratio test statistic: one based on permuting the quantitative covariate, the other two based on permuting residuals. We compare via simulation the Type I error rate and power of the three permutation tests obtained from joint models for multiple outcomes, as well as a commonly used parametric test. The tests are illustrated using data from a stimulant use disorder psychosocial clinical trial.

PMID:37379399 | DOI:10.1080/00273171.2023.2217662

Sci Adv. 2023 Jun 28;9(26):eadf7170. doi: 10.1126/sciadv.adf7170. Epub 2023 Jun 28.

ABSTRACT

Collective behavior spans several orders of magnitude of biological organization, from cell colonies to flocks of birds. We used time-resolved tracking of individual glioblastoma cells to investigate collective motion in an ex vivo model of glioblastoma. At the population level, glioblastoma cells display weakly polarized motion in the (directional) velocities of single cells. Unexpectedly, fluctuations in velocities are correlated over distances many times the size of a cell. Correlation lengths scale linearly with the maximum end-to-end length of the population, indicating that they are scale-free and lack a characteristic decay scale other than the size of the system. Last, a data-driven maximum entropy model captures statistical features of the experimental data with only two free parameters: the effective length scale (n_c) and strength (J) of local pairwise interactions between tumor cells. These results show that glioblastoma assemblies exhibit scale-free correlations in the absence of polarization, suggesting that they may be poised near a critical point.

PMID:37379380 | DOI:10.1126/sciadv.adf7170

PLoS Comput Biol. 2023 Jun 28;19(6):e1011261. doi: 10.1371/journal.pcbi.1011261. Online ahead of print.

ABSTRACT

The recent advances in single-cell RNA sequencing (scRNA-seq) techniques have stimulated efforts to identify and characterize the cellular composition of complex tissues. With the advent of various sequencing techniques, automated cell-type annotation using a well-annotated scRNA-seq reference becomes popular. But it relies on the diversity of cell types in the reference, which may not capture all the cell types present in the query data of interest. There are generally unseen cell types in the query data of interest because most data atlases are obtained for different purposes and techniques. Identifying previously unseen cell types is essential for improving annotation accuracy and uncovering novel biological discoveries. To address this challenge, we propose mtANN (multiple-reference-based scRNA-seq data annotation), a new method to automatically annotate query data while accurately identifying unseen cell types with the aid of multiple references. Key innovations of mtANN include the integration of deep learning and ensemble learning to improve prediction accuracy, and the introduction of a new metric that considers three complementary aspects to distinguish between unseen cell types and shared cell types. Additionally, we provide a data-driven method to adaptively select a threshold for identifying previously unseen cell types. We demonstrate the advantages of mtANN over state-of-the-art methods for unseen cell-type identification and cell-type annotation on two benchmark dataset collections, as well as its predictive power on a collection of COVID-19 datasets. The source code and tutorial are available at https://github.com/Zhangxf-ccnu/mtANN.

PMID:37379341 | DOI:10.1371/journal.pcbi.1011261

PLoS Comput Biol. 2023 Jun 28;19(6):e1011263. doi: 10.1371/journal.pcbi.1011263. Online ahead of print.

ABSTRACT

The spread of SARS-CoV-2 has been geographically uneven. To understand the drivers of this spatial variation in SARS-CoV-2 transmission, in particular the role of stochasticity, we used the early stages of the SARS-CoV-2 invasion in Washington state as a case study. We analysed spatially-resolved COVID-19 epidemiological data using two distinct statistical analyses. The first analysis involved using hierarchical clustering on the matrix of correlations between county-level case report time series to identify geographical patterns in the spread of SARS-CoV-2 across the state. In the second analysis, we used a stochastic transmission model to perform likelihood-based inference on hospitalised cases from five counties in the Puget Sound region. Our clustering analysis identifies five distinct clusters and clear spatial patterning. Four of the clusters correspond to different geographical regions, with the final cluster spanning the state. Our inferential analysis suggests that a high degree of connectivity across the region is necessary for the model to explain the rapid inter-county spread observed early in the pandemic. In addition, our approach allows us to quantify the impact of stochastic events in determining the subsequent epidemic. We find that atypically rapid transmission during January and February 2020 is necessary to explain the observed epidemic trajectories in King and Snohomish counties, demonstrating a persisting impact of stochastic events. Our results highlight the limited utility of epidemiological measures calculated over broad spatial scales. Furthermore, our results make clear the challenges with predicting epidemic spread within spatially extensive metropolitan areas, and indicate the need for high-resolution mobility and epidemiological data.

PMID:37379328 | DOI:10.1371/journal.pcbi.1011263

PLoS Biol. 2023 Jun 28;21(6):e3002164. doi: 10.1371/journal.pbio.3002164. Online ahead of print.

ABSTRACT

A defining property of circadian clocks is temperature compensation, characterized by the resilience of their near 24-hour free-running periods against changes in environmental temperature within the physiological range. While temperature compensation is evolutionary conserved across different taxa of life and has been studied within many model organisms, its molecular underpinnings remain elusive. Posttranscriptional regulations such as temperature-sensitive alternative splicing or phosphorylation have been described as underlying reactions. Here, we show that knockdown of cleavage and polyadenylation specificity factor subunit 6 (CPSF6), a key regulator of 3′-end cleavage and polyadenylation, significantly alters circadian temperature compensation in human U-2 OS cells. We apply a combination of 3′-end-RNA-seq and mass spectrometry-based proteomics to globally quantify changes in 3′ UTR length as well as gene and protein expression between wild-type and CPSF6 knockdown cells and their dependency on temperature. Since changes in temperature compensation behavior should be reflected in alterations of temperature responses within one or all of the 3 regulatory layers, we statistically assess differential responses upon changes in ambient temperature between wild-type and CPSF6 knockdown cells. By this means, we reveal candidate genes underlying circadian temperature compensation, including eukaryotic translation initiation factor 2 subunit 1 (EIF2S1).

PMID:37379316 | DOI:10.1371/journal.pbio.3002164

PLoS One. 2023 Jun 28;18(6):e0287589. doi: 10.1371/journal.pone.0287589. eCollection 2023.

ABSTRACT

The success of personal non-pharmaceutical interventions as a public health strategy requires a high level of compliance from individuals in private social settings. Strategies to increase compliance in these hard-to-reach settings depend upon a comprehensive understanding of the patterns and predictors of protective social behavior. Social cognitive models of protective behavior emphasize the contribution of individual-level factors while social-ecological models emphasize the contribution of environmental factors. This study draws on 28 waves of survey data from the Understanding Coronavirus in America survey to measure patterns of adherence to two protective social behaviors-private social-distancing behavior and private masking behavior-during the COVID-19 pandemic and to assess the role individual and environmental factors play in predicting adherence. Results show that patterns of adherence fall into three categories marked by high, moderate, and low levels of adherence, with just under half of respondents exhibiting a high level of adherence. Health beliefs emerge as the single strongest predictor of adherence. All other environmental and individual-level predictors have relatively poor predictive power or primarily indirect effects.

PMID:37379315 | DOI:10.1371/journal.pone.0287589

PLoS One. 2023 Jun 28;18(6):e0287175. doi: 10.1371/journal.pone.0287175. eCollection 2023.

ABSTRACT

INTRODUCTION: We performed a systematic review and meta-analysis on the incidence of secondary tethered spinal cord (TSC) between prenatal and postnatal closure in patients with MMC. The objectives was to understand the incidence of secondary TSC after prenatal surgery for MMC compared to postnatal surgery for MMC.

MATERIAL AND METHODS: On May 4, 2023, a systematic search was conducted in Medline, Embase, and the Cochrane Library to gather relevant data. Primary studies focusing on repair type, lesion level, and TSC were included, while non-English or non-Dutch reports, case reports, conference abstracts, editorials, letters, comments, and animal studies were excluded. Two reviewers assessed the included studies for bias risk, following PRISMA guidelines. TSC frequency in MMC closure types was determined, and the relationship between TSC occurrence and closure technique was analyzed using relative risk and Fisher’s exact test. Subgroup analysis revealed relative risk differences based on study designs and follow-up periods. A total of ten studies, involving 2,724 patients, were assessed. Among them, 2,293 patients underwent postnatal closure, while 431 received prenatal closure for the MMC defect. In the prenatal closure group, TSC occurred in 21.6% (n = 93), compared to 18.8% (n = 432) in the postnatal closure group. The relative risk (RR) of TSC in patients with prenatal MMC closure versus postnatal MMC closure was 1.145 (95%CI 0.939 to 1.398). Fisher’s exact test indicated a statistically non-significant association (p = 0.106) between TSC and closure technique. When considering only RCT and controlled cohort studies, the overall RR for TSC was 1.308 (95%CI 1.007 to 1.698) with a non-significant association (p = .053). For studies focusing on children up until early puberty (maximum 12 years follow-up), the RR for tethering was 1.104 (95%CI 0.876 to 1.391), with a non-significant association (p = 0.409).

CONCLUSION AND DISCUSSION: This review found no significant increase in relative risk of TSC between prenatal and postnatal closure in MMC patients, but a trend of increased TSC in the prenatal group. More long-term data on TSC after fetal closure is needed for better counseling and outcomes in MMC.

PMID:37379312 | DOI:10.1371/journal.pone.0287175

PLoS One. 2023 Jun 28;18(6):e0286637. doi: 10.1371/journal.pone.0286637. eCollection 2023.

ABSTRACT

Ukraine is an important global exporter of grain, especially to several countries with vulnerable food systems. The war in Ukraine may disrupt global food supply by limiting the planting, growth, and harvest of crops, or disrupting grain supply logistics. We apply a novel statistical modelling approach to satellite images of cropland in Ukraine for fast inference and exploration of cropping patterns and their influences in challenging environments. We also present satellite-derived cargo shipping activity as an accompaniment to these outputs to better explore the outcomes. Cropland Gross Primary Productivity in 2022 was 0.25gC/m2 lower than the 2010-2021 baseline period (p < 0.001). Similarly, cumulative annual cargo shipping activity ports in the Odesa and Mariupol regions were 45% and 62% lower in 2022 than in 2021, respectively. This suggests that cropland primary productivity has suffered during the conflict, and reliance on a few key port areas introduces vulnerability to the value chain.

PMID:37379308 | DOI:10.1371/journal.pone.0286637

PLoS One. 2023 Jun 28;18(6):e0287601. doi: 10.1371/journal.pone.0287601. eCollection 2023.

ABSTRACT

The recent legalization of sports wagering in many regions of North America has renewed attention on the practice of sports betting. Although considerable effort has been previously devoted to the analysis of sportsbook odds setting and public betting trends, the principles governing optimal wagering have received less focus. Here the key decisions facing the sports bettor are cast in terms of the probability distribution of the outcome variable and the sportsbook’s proposition. Knowledge of the median outcome is shown to be a sufficient condition for optimal prediction in a given match, but additional quantiles are necessary to optimally select the subset of matches to wager on (i.e., those in which one of the outcomes yields a positive expected profit). Upper and lower bounds on wagering accuracy are derived, and the conditions required for statistical estimators to attain the upper bound are provided. To relate the theory to a real-world betting market, an empirical analysis of over 5000 matches from the National Football League is conducted. It is found that the point spreads and totals proposed by sportsbooks capture 86% and 79% of the variability in the median outcome, respectively. The data suggests that, in most cases, a sportsbook bias of only a single point from the true median is sufficient to permit a positive expected profit. Collectively, these findings provide a statistical framework that may be utilized by the betting public to guide decision-making.

PMID:37379305 | DOI:10.1371/journal.pone.0287601

PLoS One. 2023 Jun 28;18(6):e0284854. doi: 10.1371/journal.pone.0284854. eCollection 2023.

ABSTRACT

The novel coronavirus disease (COVID-19) pandemic has affected several countries worldwide, resulting in a considerable strain on healthcare systems and increased trend of self-medication practices. This study aims to evaluate the awareness of COVID-19 and the prevalence of self-medication during the pandemic among residents in Mogadishu, Somalia. A cross-sectional study was conducted using a structured and pretested questionnaire between May 2020 and January 2021. Participants from various disciplines were randomly recruited within the study location and interviewed about their self-medication practices during the pandemic. Descriptive statistics were used to summarise the respondents’ information and responses to the questionnaire items. Associations between participants’ demographic characteristics and specific items relating to self-medication practices were analysed using the Chi-square test. A total of 350 residents participated in the study. Approximately 63% of the participants reported having practised COVID-19 related self-medication with the main reasons being pharmacists’ advice (21.4%) and having an old prescription (13.1%), whereas 37.1% did not report their reasons for self-medication. Most participants (60.4%) engaged in self-medication despite not having any symptoms and 62.9% had taken antibiotics in the last three months. Most participants were aware that no medication has been approved for COVID-19 (81.1%), the negative effects of self-medication (66.6%), and the transmission routes of the virus. Meanwhile, more than 40% of the participants have not worn a mask while outside their homes, and do not follow the international COVID-19 guidelines. The most prevalent drug used by participants for self-medication against COVID-19 was paracetamol (81.1%) and antibiotics (78%). The factors associated with awareness of COVID-19 and self-medication practices included age, gender, educational qualification, and occupation. This study revealed considerable high self-medication practices among Mogadishu residents, thus highlighting the need to promote awareness regarding the adverse effects of self-medication and sanitisation guidelines in addressing COVID-19 at the community level.

PMID:37379300 | DOI:10.1371/journal.pone.0284854