Context Effects Research Articles

Decoding motivation in English medium instruction: situated expectancy-value theory and student performance at a Chinese transnational university

ABSTRACT This study investigates English-medium instruction (EMI) academic motivation at a Chinese transnational university, aiming to bridge identified research gaps by employing the Situated Expectancy-Value Theory (SEVT). Specifically, it explores motivational predictors of EMI academic performance and the factors influencing these predictors. A longitudinal mixed-methods approach was adopted, utilising a validated Chinese EMI Student Academic Motivation Scale administered twice (n = 156) over a semester and semi-structured interviews with a subgroup of 15 participants. Results from multiple linear regression indicated that the combination of nine motivational variables had a moderate impact on EMI academic performance, and two of the predictor variables – expectations of success and emotional cost – were statistically significant predictors. Qualitative findings from the interviews revealed four key factors that influence the development of expectations of success: past learning experience, English language ability, learner autonomy, and socialisers’ influence; additionally, three main factors were identified as affecting the development of emotional cost: English language barriers, EMI curriculum, and peer pressure. The study concludes with practical pedagogical recommendations, drawn from both quantitative and qualitative data, aimed at enhancing EMI effectiveness in similar educational contexts.

Exploring the Longitudinal Links Popularity Goals and Adolescent Cyberbullying Perpetration: The Moderating Effects of Gender and Cultural Context

Background/Objectives: This longitudinal study aimed to examine how gender influences the relationship between popularity goals and cyberbullying perpetration among adolescents in China and the United States, controlling for peer-nominated popularity. Additionally, the study sought to identify potential cross-cultural differences in these dynamics. Methods: The research involved 1063 eighth and ninth graders (ages 12–16; 48.7% girls) who completed self-reported surveys in the fall of 2022 (Time 1) regarding cyberbullying behaviors and popularity goals. Peer nominations of popularity were also collected. Follow-up data on cyberbullying perpetration were obtained one year later in the fall of 2023 (Time 2). Results: Popularity goals were found to positively predict cyberbullying perpetration at Time 2 across all participants even after accounting for peer-nominated popularity. In China, this association was more pronounced among boys, whereas in the United States, the relationship was stronger for girls. Conclusions: Although cultural differences in the overall patterns were minimal, gender emerged as a significant moderating factor, revealing distinct cross-cultural variations. These findings underscore the need for culturally tailored approaches in interventions targeting adolescent cyberbullying.

What R Mandarin Chinese /ɹ/s? - acoustic and articulatory features of Mandarin Chinese rhotics.

Rhotic sounds are well known for their considerable phonetic variation within and across languages and their complexity in speech production. Although rhotics in many languages have been examined and documented, the phonetic features of Mandarin rhotics remain unclear, and debates about the prevocalic rhotic (the syllable-onset rhotic) persist. This paper extends the investigation of rhotic sounds by examining the articulatory and acoustic features of Mandarin Chinese rhotics in prevocalic, syllabic (the rhotacized vowel [ɚ]), and postvocalic (r-suffix) positions. Eighteen speakers from Northern China were recorded using ultrasound imaging. Results showed that Mandarin syllabic and postvocalic rhotics can be articulated with various tongue shapes, including tongue-tip-up retroflex and tongue-tip-down bunched shapes. Different tongue shapes have no significant acoustic differences in the first three formants, demonstrating a many-to-one articulation-acoustics relationship. The prevocalic rhotics in our data were found to be articulated only with bunched tongue shapes, and were sometimes produced with frication noise at the start. In general, rhotics in all syllable positions are characterized by a close F2 and F3, though the prevocalic rhotic has a higher F2 and F3 than the syllabic and postvocalic rhotics. The effects of syllable position and vowel context are also discussed.

A matter of measurement? Segregation and all-cause mortality in Sweden’s three metropolitan regions

Abstract Background Residential segregation can be operationalized and measured in many ways, along distinct dimensions. There are multiple mechanisms through which segregation and health mutually affect each other. Consequently, contextual health effects of segregation may vary depending on how segregation is measured. Methods We used longitudinal Swedish register data to compare associations between local measures of residential segregation (migrant density, migrant isolation, and the mutual information index) and all-cause mortality among the adult migrant and native-born populations in Sweden’s three largest metropolitan regions between 2004-2016. Results Among migrants, modest positive mortality gradients were observed across measures of migrant density and isolation, where a higher level of segregation was associated with higher risks of all-cause mortality (Q5 RR ranged from 1.08-1.20 across cities and measures). However, these effects were largely attenuated by individual-level socioeconomic factors, and reversed when further controlling for neighborhood economic deprivation (Q5 RR ranged from 0.74-0.87). Among the native-born, a positive gradient for mortality was found (Q5 RR ranged from 1.31-1.45), although this was reduced when accounting for neighborhood deprivation (Q5 RR ranged from 1.01 -1.11). For both migrants and the native-born, the mutual information index showed no clear association with mortality, although a mortality advantage is observed for migrants in the most segregated areas after individual and neighborhood level adjustments (Q5 RR ranged from 0.73-0.86). Conclusions Our findings show that the manner in which residential segregation is conceptualized and operationalized alters associations with health. However, individual and other contextual level confounders are important determinants which influences the patterns. Much of the negative health effects of residential segregation can be perceived through the lack of economic opportunities. Key messages • Associations between segregation and all-cause mortality depends on how segregation is conceptualized and measured. • The mortality disadvantage observed in local areas with high migrant density may be attributed to the lack of economic opportunities in the neighborhood.

Testing self-supportive strategies to regulate autonomy and motivation.

People regularly encounter situations in which they have to engage in tasks they find boring or irrelevant, in which case their autonomy-the need to act in ways that are meaningful for oneself-is impeded. When there is no motivational support available, individuals need to find ways to overcome their motivational barriers by themselves. Applying autonomy-regulation strategies may be effective for increasing autonomy and particularly the more adaptive types of motivation (i.e., intrinsic and internalized). Testing this idea, we investigated whether individuals apply self-supportive strategies to boost their feelings of autonomy and motivation in two studies via cross-sectional survey samples (overall N = 2,344). We analyzed how autonomy regulation strategies were associated with theoretically related variables via Structural Equation Modeling (SEM). In Study 1, the self-reported use of autonomy regulation strategies was strongly positively associated with intrinsic and internalized types of motivation, weakly positively correlated with introjected avoidance motivation, and not associated with external motivation. In Study 2, we introduced two dilemmas concerning motivational problems individuals face when engaging in tasks and being assigned a task, respectively. Results indicate that individuals report using general strategies of autonomy regulation to achieve fulfillment of autonomy and intrinsic motivation, next to more specific autonomy regulation strategies regarding specific dilemmas. Our results show that it would be worthwhile to investigate if stimulating individuals to use autonomy regulation strategies would positively affect their motivation (e.g., in job or study contexts), and that in doing so, it is important to consider both specific context effects on autonomy regulation as well as individual preferences for general strategies used to regulate one's autonomy.

Does Content-Focused Intervention Enhance Motivation in Physical Education? A Meta-Analysis

ABSTRACT Guided by the content specificity perspective of motivation, the purpose of the study was to identify the extent to which student motivation level is a function of content variations. Motivation intervention studies were reviewed and categorized into content-focused and motivation-only learning contexts for meta-analysis. Original and calculated effect sizes were used to determine the effects of each learning context on student motivation change. Two independent sample t-tests were conducted to compare effect sizes. The analyses showed that the content-focused learning context was effective in student motivation change (effect size g = 0.88). Within the content-focused learning context, intervention content was significantly more effective in student motivation change than the conventional curriculum (effect size g = 0.36). The findings suggest a possibility that motivation is content-specific and should be part of the curriculum.

Building Bridges in Diverse Societies: A Meta-Analysis of Field Experimental Cooperative Learning Studies on Intergroup Relations in Educational Settings

Cooperative learning has been widely utilized as an intervention to enhance intergroup relations in diverse societies, drawing on intergroup contact theory. Despite numerous field experiments testing its effectiveness in educational contexts, a comprehensive meta-analyses evaluating its overall efficacy has yet to be conducted. This meta-analysis aims to assess the magnitude of the effect of cooperative learning on promoting intergroup relations within experimental field studies conducted in educational settings. The article search was performed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, using predefined inclusion and exclusion criteria across ERIC, ScienceDirect, Scopus, and SpringerLink. Data analysis involved generating forest plots, conducting heterogeneity tests, calculating summary effects using a random effects model, and identifying publication bias. The meta-analysis of 18 field experimental intervention studies, involving 5265 participants, revealed that cooperative learning intervention programs positively impact intergroup relations, with a moderate effect size (ES = 0.33; 95% CI [0.25, 0.40]). Consequently, cooperative learning can be employed as an alternative strategy to bridge gaps, reduce prejudice, and improve relations among groups with diverse social identities in educational settings.

The effect of congruent emotional context on semantic memory during discourse comprehension

ABSTRACT This study examined the effect of emotional context on the semantic memory of subsequent emotional words during discourse comprehension in two eye-tracking experiments. Four-sentence discourses were used as experimental materials. The first three sentences established an emotional or neutral context, while the fourth contained an emotional target word consistent with the preceding emotional context's valence. The discourses were presented twice using the text change paradigm, where the target words were replaced with strongly - or weakly-related words during the second presentation. Thus, four conditions were included in the present study: Emotional-strongly-related, Emotional-weakly-related, Neutral-strongly-related and Neutral-weakly-related. In Experiment 1, negative contexts and negative target words were used, whereas in Experiment 2, positive contexts and positive target words were used. The results revealed a semantic relatedness effect, whereby the strongly-related words have lower change detection accuracy, longer reading times and more fixations in both Experiments 1 and 2. Furthermore, across both experiments, the magnitude of the semantic relatedness effect was greater in the emotionally congruent contexts than in the neutral contexts. These results suggest that emotional context could increase efforts to change the discrimination of subsequent words and demonstrate an important role of emotional context on semantic memory during discourse processing.

No fences, good neighbors: measuring and explaining integration in European cross-border regions

ABSTRACT EU cross-border regions are defined as living laboratories of European integration by scholars and EU institutions. Nonetheless, on the research agenda of EU studies, the study of integration in cross-border regions is not central. Moreover, the dearth of explanatory research has hampered a comprehensive understanding of the determinants of cross-border integration. This article fills these gaps conceptually, theoretically, and empirically. It introduces a new conceptualization anchored in classic integration theories and a new measurement of integration in all 2014–2020 Interreg A programmes. Furthermore, by drawing on a post-functionalist framework and based on multiple linear regression analysis, the study shows that identity pressures, particularly linguistic proximity and a pro-European sentiment, and contextual effects, notably regional authority, are significantly positively correlated with cross-border integration, all other things being equal. The paper thus not only reveals to what extent cross-border regions are integrated but also which explanatory factors are associated with cross-border integration.

Writing performance and discourse organization in L2 Chinese: A longitudinal case study

The present study explored the development of writing performance and discourse organization in Chinese as a second language (L2) writing, focusing on the effects of genre and learning context. Tracking an L2 Chinese learner’s written production in two genres (i.e., narrative and argumentative) across four learning contexts (i.e., pre-study abroad, study abroad, post-study abroad, and delayed post-study abroad) longitudinally over four years, this study revealed that holistic ratings and discourse organizational devices showed distinct patterns in different genres and across learning contexts. Narrative essays generally received lower ratings than argumentative essays. Ratings of narrative essays remained relatively stable across four learning contexts, whereas those of argumentative essays displayed an omega-shaped pattern over the four-year period. Among six discourse organizational devices, subordinate clauses, textual connectives, and grammatical metaphors were used more in argumentative essays, but coordinate clauses and topic-prominent constructions were used more in narrative essays. The six discourse organizational devices exhibited discrete developmental trends throughout the four years of learning. This study provides a deeper understanding of writing performance and discourse organization in L2 Chinese development.

An Automated Word Spelling Error Detection System

Accurate spelling has extensive consequences for written communication's clarity, credibility, and general effectiveness in several contexts, including academic and professional writing and personal communications. The frequency of spelling errors has increased significantly recently, mainly owing to the widespread use of digital media and society's dependence on written communication. Misspelled words can diminish the reliability of written correspondence and result in misinterpretations. Hence, there is an urgent requirement for an innovative and advanced solution to improve the identification of spelling errors. This research seeks to address these challenges and develop a system that significantly enhances the quality of written communication by improving the accuracy and relevance of spelling error detection and correction suggestions. According to this study, the implemented model is a promising technique to correct spelling problems in legal terminology, has been praised for its effectiveness and usability. Its recommendations include continuous research and development, improving its ability to use contextual cues and domain-specific information for error correction, emphasizing user-centric customization, implementing collaborative feedback systems, offering extensive training and support, prioritizing ethical and regulatory considerations, and fostering interdisciplinary collaboration. These suggestions aim to optimize the Spello model's performance, resilience, and scalability, and make it a fundamental technology in promoting accuracy, integrity, and accessibility in the legal profession and society. The model can become a fundamental technology in promoting accuracy, integrity, and accessibility in the legal profession and society through combined efforts and collaboration.

Sociohistorical context and post-prison life course

Life-course criminology has recently begun to focus on sociohistorical context, with the use of multi-cohort studies. However, those studies have mostly concentrated on aggregate crime rates. Desistance research, in turn, has largely overlooked the impact of the broader sociohistorical context. Based on recent work on the effect of sociohistorical context on crime rates, we propose that context may shape desistance and social reintegration in a nuanced way.We examined employment, housing, and marriages among Finnish first-time prisoners released between 1995 and 2014 (N = 23,350) until 2019. We quantified the link between selected macro-level indicators and these outcomes using age-period-cohort models.The results showed that the outcomes evolved in separate ways post-release. Employment and marriage became more common over time, but only employment showed distinct periodical changes. The probability of living in housing remained stable. A higher level of national unemployment was associated with all outcomes. The association between prisoner characteristics and the outcomes changed depending on release year.Post-prison societal integration should not be assessed by one measure alone. Desistance studies should address societal context when comparing different times or countries. Early studies may require replication if the associations between demographic factors and desistance outcomes are subject to change.

Longitudinal mediation analysis with multilevel and latent growth models: a separable effects causal approach

BackgroundCausal mediation analysis is widespread in applied medical research, especially in longitudinal settings. However, estimating natural mediational effects in such contexts is often difficult because of the presence of post-treatment confounding. Moreover, many models frequently used in applied research, like multilevel and latent growth models, present an additional difficulty, i.e. the presence of latent variables. In this paper, we propose a causal interpretation of these two classes of models based on a novel type of causal effects called separable, which overcome some of the issues of natural effects.MethodsWe formally derive conditions for the identifiability of separable mediational effects and their analytical expressions based on the g-formula. We carry out a simulation study to investigate how moderate and severe model misspecification, as well as violation of the identfiability assumptions, affect estimates. We also present an application to real data.ResultsThe results show how model misspecification impacts the estimates of mediational effects, particularly in the case of severe misspecification, and that the bias worsens over time. The violation of assumptions affects separable effect estimates in a very different way for the mixed effect and the latent growth models.ConclusionOur approach allows us to give multilevel and latent growth models an appealing causal interpretation based on separable effects. The simulation study shows that model misspecification can heavily impact effect estimates, highlighting the importance of careful model choice.

A theory of flexible multimodal synchrony.

Dominant theoretical accounts of interpersonal synchrony, the temporal coordination of biobehavioral processes between several individuals, have employed a linear approach, generally considering synchrony as a positive state, and utilizing aggregate scores. However, synchrony is known to take on a dynamical form with continuous shifts in its timeline. Acting as one continuously, is not always the optimal state, due to an intrinsic tension between individualistic and synergistic forms of action that exist in many social situations. We propose an alternative theory of flexible multimodal synchrony which highlights context as a key component that defines "pulls" toward synchrony and "pulls" toward segregation inherent to the social situation. Traitlike individual differences and relationship variables then sensitize individuals to these contextual "pulls." In this manner, context, individual differences, and relationship variables provide the backdrop to the emergence of flexible and dynamical synchrony patterns, which we consider adaptive, in several modalities-behavioral, physiological, and neural. We point to three consequences of synchrony patterns: social-, task, and self-oriented. We discuss multimodal associations that arise in different contexts considering the theory and delineate hypotheses that emanate from the theory. We then provide two empirical proofs-of-concept: First, we show how individual differences modulate the effect of context on synchrony's outcomes in a novel dyadic motor game. Second, we reanalyze previously reported data, to show how a "flexibility" approach to synchrony data analysis improves predictive ability when testing for synchrony's effects on social cohesion. We provide ways to standardize the characterization of context and guidelines for future synchrony research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Fragment of Interest: Personalized Video Fragment Recommendation with Inter-Fragment & Intra-Fragment Contextual Effect

In today’s fast-paced digital landscape, the attention span of users consuming video content is alarmingly brief, often as short as 15 seconds for music or entertainment videos and 6 minutes for lecture videos. This presents a significant challenge for video producers and platform providers as they seek to engage users with longer content. One promising solution involves recommending specific fragments within longer videos that align with individual user profiles. In this paper, we address this challenge by introducing a novel framework for video fragment recommendations, guided by three key insights. First, we implement a Self-Attention Block that captures the inter-fragment contextual effect, enhancing the relevance of recommendations. Second, we incorporate video-level preferences to ensure that the fragment recommendations are consistent with users’ overall interests. Third, we propose a Self-Attentive Herding Effect (SAHE) module to model the intra-fragment contextual effect, specifically the herding effect of time-sync comments within a fragment. To evaluate the effectiveness of our proposed method, we conduct extensive experiments comparing our model against the state-of-the-art approaches in terms of NDCG@K and Recall@K. Our results demonstrate that the model effectively leverages inter-fragment, intra-fragment contextual effects, and video-level preferences, outperforming existing methods. Additionally, we carry out empirical experiments to analyze the key components and parameters of the proposed model, providing further insights into its performance.

The impact of contextual effects in exercise therapy for low back pain: a systematic review and meta-analysis

BackgroundLow back pain is the leading cause of global disability for which exercise therapy is a widely recommended treatment. Research indicates that contextual factors may also influence treatment outcomes in low back pain. Examples include the patient-therapist relationship and other treatment-related circumstances that affect patient expectations. By focusing on the specific treatment effect, clinical trials often ignore the effect of contextual factors, thereby contributing to the so-called efficacy paradox. This means that treatment effects observed in clinical practice are often greater than those reported in clinical trials.This systematic review aims to investigate the proportion of improvement in pain and disability that can be attributed to contextual effects in the outcome of exercise therapy for patients with low back pain.MethodsA meta-analysis was conducted. PubMed, Embase, and the Cochrane database were searched for eligible articles reporting randomized controlled trials that compared exercise therapy to placebo interventions. Risk of bias was assessed with the Revised Cochrane Risk of Bias Tool. Outcomes of interest were pain and disability. Meta-analysis was carried out to calculate the proportion attributable to contextual effects for both pain and disability. The body of evidence was assessed using the GRADE methodology.ResultsEight studies met the inclusion criteria and were included in the meta-analysis. Five studies were rated as having a moderate risk of bias and two studies had a low risk of bias. Proportion attributable to contextual effects was 0.60 (95% CI 0.40–0.89) for pain and 0.69 (95% CI 0.48–1.00) for disability. Certainty of the evidence as assessed with the GRADE methodology was low.ConclusionsA large extent of pain and disability improvement after exercise therapy in low back pain is attributable to contextual effects although this conclusion is based on low certainty evidence.

Intrusion detection based on concept drift detection and online incremental learning

Purpose The primary purpose of this paper is to introduce the drift detection method-online random forest (DDM-ORF) model for intrusion detection, combining DDM for detecting concept drift and ORF for incremental learning. The paper addresses the challenges of dynamic and nonstationary data, offering a solution that continuously adapts to changes in the data distribution. The goal is to provide effective intrusion detection in real-world scenarios, demonstrated through comprehensive experiments and evaluations using Apache Spark. Design/methodology/approach The paper uses an experimental approach to evaluate the DDM-ORF model. The design involves assessing classification performance metrics, including accuracy, precision, recall and F-measure. The methodology integrates Apache Spark for distributed computing, using metrics such as processed records per second and input rows per second. The evaluation extends to the analysis of IP addresses, ports and taxonomies in the MAWILab data set. This comprehensive design and methodology showcase the model’s effectiveness in detecting intrusions through concept drift detection and online incremental learning on large-scale, heterogeneous data. Findings The paper’s findings reveal that the DDM-ORF model achieves outstanding classification results with 99.96% accuracy, demonstrating its efficacy in intrusion detection. Comparative analysis against a convolutional neural network-based model indicates superior performance in anomalous and suspicious detection rates. The exploration of IP addresses, ports and taxonomies uncovers valuable insights into attack patterns. Apache Spark evaluation attests to the system’s high processing rates. The study emphasizes the scalability, availability and fault tolerance of DDM-ORF, making it suitable for real-world scenarios. Overall, the paper establishes the model’s proficiency in handling dynamic, nonstationary data for intrusion detection. Research limitations/implications The research acknowledges certain limitations, including the potential challenge of DDM detecting only frequency changes in class labels and not complex concept drifts. The incremental random forest’s reliance on memory may pose constraints as the forest size increases, potentially leading to overfitting. Addressing these limitations could involve exploring alternative concept drift detection algorithms and implementing ensemble pruning techniques for memory efficiency. Further research avenues may investigate algorithms balancing accuracy and memory usage, such as compressed random forests, to enhance the model’s effectiveness in evolving data environments. Practical implications The study’s practical implications are noteworthy. The proposed DDM-ORF model, designed for intrusion detection through concept drift detection and online incremental learning, offers a scalable, available and fault-tolerant solution. Leveraging Apache Spark and Microsoft Azure Cloud enhances processing capabilities for large data sets in dynamic, nonstationary scenarios. The model’s applicability to heterogeneous data sets and its achievement of high-accuracy multi-class classification make it suitable for real-world intrusion detection. Moreover, the auto-scaling features of Microsoft Azure Cloud contribute to adaptability, ensuring efficient resource utilization without downtime. These practical implications underscore the model’s relevance and effectiveness in diverse operational contexts. Social implications The DDM-ORF model’s social implications are significant, contributing to enhanced cybersecurity measures. By providing an effective intrusion detection system, it helps safeguard digital ecosystems, preserving user privacy and securing sensitive information. The model’s accuracy in identifying and classifying various intrusion attempts aids in mitigating potential cyber threats, thereby fostering a safer online environment for individuals and organizations. As cybersecurity is paramount in the digital age, the social impact lies in fortifying the resilience of networks, systems and data against malicious activities, ultimately promoting trust and reliability in online interactions. Originality/value The DDM-ORF model introduces a novel approach to intrusion detection by combining drift detection and online incremental learning. This originality lies in its utilization of the DDM-ORF algorithm, offering a dynamic and adaptive system for evolving data. The model’s contribution extends to its scalability, fault-tolerance and suitability for heterogeneous data sets, addressing challenges in dynamic, nonstationary environments. Its application on a large-scale data set and multi-class classification, along with integration with Apache Spark and Microsoft Azure Cloud, enhances the field’s understanding and application of intrusion detection, providing valuable insights for securing digital infrastructures.

Porphyrin-engineered nanoscale metal-organic frameworks: enhancing photodynamic therapy and ferroptosis in oncology.

Photodynamic therapy and ferroptosis induction have risen as vanguard oncological interventions, distinguished by their precision and ability to target vulnerabilities in cancer cells. Photodynamic therapy's non-invasive profile and selective cytotoxicity complement ferroptosis' unique mode of action, which exploits iron-dependent lipid peroxidation, offering a pathway to overcome chemoresistance with lower systemic impact. The synergism between photodynamic therapy and ferroptosis is underscored by the depletion of glutathione and glutathione peroxidase four inhibitions by photodynamic therapy-induced reactive oxygen species, amplifying lipid peroxidation and enhancing ferroptotic cell death. This synergy presents an opportunity to refine cancer treatment by modulating redox homeostasis. Porphyrin-based nanoscale metal-organic frameworks have unique hybrid structures and exceptional properties. These frameworks can serve as a platform for integrating photodynamic therapy and ferroptosis through carefully designed structures and functions. These nanostructures can be engineered to deliver multiple therapeutic modalities simultaneously, marking a pivotal advance in multimodal cancer therapy. This review synthesizes recent progress in porphyrin-modified nanoscale metal-organic frameworks for combined photodynamic therapy and ferroptosis, delineating the mechanisms that underlie their synergistic effects in a multimodal context. It underscores the potential of porphyrin-based nanoscale metal-organic frameworks as advanced nanocarriers in oncology, propelling the field toward more efficacious and tailored cancer treatments.

Context Effects on Human Milk Oligosaccharide Linkage Conformation and Dynamics Revealed by MA'AT Analysis.

An emerging NMR method, MA'AT analysis, has been applied to investigate context effects on the conformational properties of several human milk oligosaccharides (HMOs). The MA'AT model of the β-(1→4) linkage in the disaccharide, methyl β-lactoside (MeL), was compared to those obtained for the same linkage in the HMO trisaccharides, methyl 2'-fucosyllactoside (Me2'FL) and methyl 3-fucosyllactoside (Me3FL), and in the tetrasaccharide, methyl 2',3-difucosyllactoside (Me2',3DFL). MA'AT analysis revealed significant context effects on the mean values and circular standard deviations (CSDs) of the psi (ψ) torsion angles in these linkages. α-Fucosylation at both O2'Gal and O3Glc of MeL to give Me2',3DFL significantly constrained librational motion about ψ (70% reduction in the CSD) and shifted its mean value by ∼18°. α-Fucosylation at the O3Glc of MeL to give Me3FL constrained ψ more than α-fucosylation at the O2Gal to give Me2'FL. These effects can be explained by the expected solution conformation of Me3FL, which closely resembles the Lewisx trisaccharide. Comparisons of MA'AT models of ψ to those obtained by 1 μs aqueous molecular dynamics simulation (GLYCAM06) revealed identical trends, that is, MA'AT analysis was able to recapitulate molecular behavior in solution that was heretofore only available from MD simulation. The results highlight the capabilities of MA'AT analysis to determine probability distributions of molecular torsion angles in solution as well as degrees of librational averaging of these angles.

Examining differences in the effects and contexts of naturalistic psilocybin use for White participants vs. Participants of Color: A longitudinal online survey study

BackgroundPsilocybin (a psychoactive compound found in “magic mushrooms” or “shrooms”) has been gaining increased attention in research and popular culture as a number of clinical and observational studies have demonstrated that it may have potential for improving mental wellbeing. Relatedly, there has been a substantial uptick in naturalistic (e.g., real-world, non-clinical) psilocybin use in the United States. While a number of longitudinal studies have demonstrated that naturalistic psilocybin use is linked to positive mental health outcomes on average, few studies have examined how the effects of psilocybin and contexts for psilocybin use may differ for White populations compared to Populations of Color. ObjectiveTo examine differences in health outcomes, subjective effects, and contexts of naturalistic psilocybin use in White participants compared to Participants of Color. MethodsThis study used data from a large, online longitudinal study of individuals who planned to engage in naturalistic psilocybin use (N = 2833). We used mixed-effects models to assess whether race/ethnicity (White vs. Participant of Color) moderated associations between time (Time 2 [initial assessment point for longitudinal measures], Time 5 [2–4 weeks post-psilocybin experience, and Time 6 [2–3 months post-experience]) and outcomes related to mental health (depression, anxiety, spiritual wellbeing, cognitive flexibility, emotion regulation [expressive suppression + cognitive reappraisal]). We also used exploratory chi-squared tests to examine differences in contexts for psilocybin use as well as differences in subjective effects related to the psilocybin experience. ResultsRace/ethnicity moderated the associations between time for predicting spiritual wellbeing (beta = −1.8; 95 % CI [−3.4, −0.17]; p < 0.05), cognitive flexibility (beta = −1.5 [−2.7, −0.26]; p < 0.05), and emotion regulation – expressive suppression (beta = 0.25 [0.06, 0.44]; p < 0.05) at Time 6 (but not Time 5). Additionally, Participants of Color reported minor differences in subjective effects and context for use compared to White participants (e.g., more likely to have set an intention prior to use, report time speeding up during the experience, etc.). We found reductions in anxiety and depression for both Participants of Color and White participants, and our moderation tests for these outcomes were not significant. ConclusionRace/ethnicity impacts the associations between psilocybin use and various markers of mental wellbeing. Future longitudinal studies and experimental studies with larger samples of color can further elucidate the preliminary findings from this study.