Behavioral Interactions Research Articles

Structural Characterization of Appendages of Diverse Butterfly Species (Insecta: Lepidoptera) from Mohali, Chandigarh, India

Insects form a very important and integral part of any ecosystem. Their contributions include agriculture, biodiversity, human health as well as conservation of natural resources. Butterflies belonging to this category falls under suborder of Lepidoptera called Rhopalocera. They have large and vividly coloured wings, which are used for both defence and communication. Butterflies play important role in the ecosystem. Lives of plants and butterflies are interlinked. These insects enhance the aesthetic value of environment by their wonderful wing colours. At rest, their wings are held together upright, which sets them off from all other insects. Butterflies are extremely important in pollination as most of them are important pollinating agent for many plant species, contributing to the enhancement of genetic diversity and stability within the ecosystem. However, their fascinating complex sensory systems go beyond their obvious beauty and importance in ecology. For instance, their legs are more than just organs of locomotion; they are actually very fine devices with sensilla. These sensilla function as receptors so that butterflies would be able to sense various aspects of their surroundings. This review article deals with different species of butterflies and the different sensory adaptations of these sensilla. By looking at these sensory structures, one can gather information about different behavioural patterns, ecological interactions and evolved tactics of an organism. Studying butterfly appendages provides critical insights into their morphological adaptations, ecological roles, behavioural strategies, offering a deeper understanding of their evolutionary success. It highlights the structural and functional adaptations of butterfly leg sensilla across species, providing valuable insights into behavioural patterns and ecological interactions, thereby advancing our understanding of insect- environment relationships.

Mediating role of eWOM’s in green behavior interaction and corporate social responsibility: a stakeholder theory perspective

Purpose This research aims to explore how policymakers manage the information and communication of green behavior on social platforms to support their growth in corporate social responsibility (CSR). Social platforms play a strategic and interactive role through electronic word-of-mouth (eWOM), which brings unprecedented green purchase opportunities. Design/methodology/approach Based on stakeholder theory, a conceptual framework is designed to investigate the influence of green behavior interactions (GBIs) on CSR under the mediating effects of eWOM subfactors (eWC = eWOM communication, eWIA = eWOM information adoption and eWSC = eWOM source credibility). Data from 414 regular stakeholders of logistics firms were analyzed via structural equation modeling. Findings The results reveal positive influences of the GBI on eWC, eWIA, eWSC and CSR, with path coefficients of 0.329, 0.713, 0.809 and 0.316, respectively. The mediating effects of eWC and eWSC from the GBI to CSR were discovered with path coefficients of 0.105 and 0.226, respectively. Coincidentally, the mediating role of eWIA was positive but not supported. The outcomes of this study indicate that the administration of GBI and eWOM from a green purchase perspective is essential for a firm. The CSR practices of green logistics firms can be successfully supported by the administration of the GBI and eWOM indicators. Originality/value This study develops a novel multidimensional framework that illustrates the impact of eWOM on reducing information asymmetry, enhancing credibility, supporting informed decision-making and improving green consumer behavior. By amplifying positive reviews, increasing engagement and establishing a feedback loop, this framework aims to provide comprehensive insights into the efficacy of eWOM for firms’ products and services.

Wearable Collar Technologies for Dairy Cows: A Systematized Review of the Current Applications and Future Innovations in Precision Livestock Farming

Wearable collar technologies have become integral to the advancement of precision livestock farming, revolutionizing how dairy cattle are monitored in terms of their behaviour, health status, and productivity. These devices leverage cutting-edge sensors, including accelerometers, RFID tags, GPS receivers, microphones, gyroscopes, and magnetometers, to provide non-invasive, real-time insights that enhance animal welfare, optimize resource use, and support decision-making processes in livestock management. This systematized review focuses on analyzing the sensors integrated into collar-based systems, detailing their functionalities and applications. However, significant challenges remain, including the high energy consumption of some sensors, the need for frequent recharging, and limited parameter coverage by individual devices. Future developments must focus on integrating multiple sensor types into unified systems to provide comprehensive data on animal behaviour, health, and environmental interactions. Additionally, advancements in energy-efficient designs, longer battery life, and cost-reduction strategies are essential to enhance the practicality and accessibility of these technologies. By addressing these challenges, wearable collar systems can play a pivotal role in promoting sustainable, efficient, and responsible livestock farming, aligning with global goals for environmental and economic sustainability. This paper underscores the transformative potential of wearable collar technologies in reshaping the livestock industry and driving the adoption of innovative farming practices worldwide.

Temperature influences resource selection and predation risk tolerance in a climate generalist

ContextThermal conditions can influence animal behavior and predator–prey dynamics. Understanding the effects of temperature on animals and their interactions is of increasing importance given predictions for global warming.ObjectivesWe determined how temperature influenced avoidance of risky areas and habitat selection in a climate generalist, white-tailed deer (Odocoileus virginianus; hereafter “deer”), and how the effect varied between night and day in a system characterized by extreme heat and high predation risk from Florida panther (Puma concolor coryi).MethodsWe collected GPS locations of 224 (79 M, 145F) deer from June through September 2015–2018 in southwestern Florida, USA. We fit step-selection functions with interactions between ambient temperature and covariates including landcover and a spatial model of predation risk informed by panther kill sites.ResultsAvoidance of high-risk areas decreased with rising temperatures during night and day, indicating deer were less predation risk averse when balancing higher thermoregulatory costs. As temperatures increased during the day, deer increased avoidance of marshes and hardwood hammocks. However, temperature had weaker effects on habitat selection at night with only a moderate increase in selection of marshes with increasing temperatures.ConclusionsIn systems characterized by extreme heat, thermal conditions can have strong effects on animal behavior and species interactions. While climate generalists like deer have high tolerances to thermal stress, temperature still influenced predation risk tolerance and habitat selection of deer during both day and night periods. These responses are likely even stronger in species with narrower thermal tolerances (i.e., climate specialists). Thermal conditions are an important and potentially underappreciated driver of species interactions that is likely to become more significant with climate change.

Neuronal properties in the Lateral Habenula and adult-newborn interactions in virgin female and male mice.

The behavioral interactions between adults and newborns are decisive for the fitness and the survival of offsprings across the animal kingdom. In laboratory mice, while virgin females display caregiving behaviors, virgin males are rather neglectful or aggressive towards pups. Despite the importance of these behavioral variations, the underlying neural mechanisms remain poorly understood. Brain regions encoding these behaviors may exhibit sex-dependent functional differences at baseline. Additionally, these structures might undergo sex-specific plasticity after adults interact with the offspring.Emerging evidence suggests sex-based differences in input connectivity, genetics and receptor expression of the epithalamic Lateral Habenula (LHb). Moreover, LHb neuronal activity is instrumental for adult-newborn interactions. However, whether LHb neuronal function varies between sexes and/or undergoes adaptations following interactions with pups has not been fully investigated.In this study, we used in vivo and ex vivo single-cell electrophysiology to examine the basal LHb neuronal activity of virgin female and male mice. In a second set of experiments, we exposed mice to pups and recapitulated sex-based divergent behaviors. Recordings in acute slices showed no alterations in LHb firing properties, regardless of sex or pup exposure. These findings suggest that, although the LHb participates in adult behaviors towards pups, this is not mediated by sex-dependent functional differences or adaptations in the neuronal firing properties. Thus, this study provides new insights into the neural basis of sex-specific adult-newborn behaviors and the role of the LHb in these processes.Significance Statement Previous studies highlight the importance of the lateral habenula (LHb) in guiding parental behaviors. Virgin female and male mice differ in their behavior towards pups: while females are parental, males neglect or attack pups. We investigated whether LHb neuronal activity or its plasticity after pup exposure presented sex differences in virgin mice. Our findings reveal that LHb activity does not differ between naïve females and males, and it remains unchanged after pup exposure. This suggests a decoupling between sex-dimorphic behaviors towards newborns and activity of the LHb.

The Effect of Contraction–Expansion Nozzle on High-Temperature Shock Tube Flow

To achieve higher enthalpy and pressure, the technique of variable cross-section drive is effectively combined with the heating of light gas to enhance the intensity of the incident shock wave. A study was conducted to predict the impact of variable cross-sections on the performance of high-temperature shock tube flow using a shock tube with a 2.6:1 diameter ratio between the driver and driven sections. The driver section was filled with a helium–argon gas mixture (mass ratio of 1:9), while the driven section contained dry air. Under total pressure conditions of 14.5 MPa and total temperature of 3404 K, as well as total pressure of 45 MPa and total temperature of 4845 K in the driver section, corresponding to driven section pressures of 10 kPa and 80 kPa, the results of chemical non-equilibrium numerical simulations were compared to experimental measurements of the incident shock Mach number and total pressure. The results indicated the following: First, after adding the contraction–expansion nozzle, the incident shock accelerated through the contraction section and reflected within the contraction section. Strong oscillations occurred during the flow, with increasing intensity as the throat size decreased. Second, without the nozzle, the shock velocity increased and then decreased. However, with the nozzle, the Mach number was highest near the nozzle exit and gradually decreased thereafter. Third, the presence of the nozzle led to the formation of a distinct fan-shaped wavefront, accompanied by significant variations in flow variables such as pressure, temperature, and Mach number in the region. This phenomenon was attributed to the interaction between the shock wave and the nozzle geometry, which altered the flow dynamics. Finally, as the throat size decreased, the intensity of the incident shock also decreased. After reflecting at the end of the shock tube, the total pressure in the driven section also decreased. The numerical simulations employed a multi-component, multi-temperature chemical non-equilibrium model, validated against experimental data, to accurately capture the complex flow behavior and wave interactions within the shock tube.

Thermal Plasticity Changes Competitive Ability Across a Woodland Salamander Hybrid System

ABSTRACTTemperature mediates performance in ectotherms, affecting their ability to grow, survive, and reproduce. Aggression and evasion are key examples of thermally dependent behaviors that can impact fitness. However, we know relatively little about how the thermal plasticity of such behaviors varies among close relatives and impacts competitive outcomes. Woodland salamanders (Genus: Plethodon) from the Appalachian Mountains are distributed across wide thermal gradients in accordance with latitude or elevation. These plethodontid (lungless) salamanders compete for space and develop hybrid zones where territories overlap among species. Plethodontids tend to exhibit increased aggression at warmer temperatures, suggesting that as temperatures rise, behavioral interactions may be altered in ways that impact hybrid zone dynamics. It is thus far unclear, however, how salamander hybrids, which may encroach on their parent populations and drive competitive exclusion, respond behaviorally to warming. Here, we used staged bouts to examine the effects of temperature on aggression and evasion in the Plethodon shermani and Plethodon teyahalee hybrid system from the southern Appalachians. The behavior of salamanders from parent populations, particularly P. shermani, appears to be more sensitive to thermal changes than that of hybrid individuals. Additionally, evasive behavior was significantly more plastic than aggressive behavior in response to warming. Our results suggest that rising temperatures may increase competition for preferable microhabitats, but the effects on behavior among parental and hybrid salamanders will be asymmetric. Temperature may therefore alter the outcomes of competition, determining which populations can persist under rapid warming.

Leveraging natural language processing to enhance feedback-informed group therapy: A proof of concept.

Group therapy has evolved as a powerful therapeutic approach, facilitating mutual support, interpersonal learning, and personal growth among members. However, the complexity of studying communication dynamics, emotional expressions, and group interactions between multiple members and often coleaders is a frequent barrier to advancing group therapy research and practice. Fortunately, advances in machine learning technologies, for example, natural language processing (NLP), make it possible to study these complex verbal and behavioral interactions within a small group. Additionally, these technologies may serve to provide leaders and members with important and actionable feedback about group therapy sessions, possibly enhancing the utility of feedback-informed care in group therapy. As such, this study sought to provide a proof of concept for applying NLP technologies to automatically assess alliance ratings from participant utterances in two community-based online support groups for weight stigma. We compared traditional machine learning approaches with advanced transformer-based language models, including variants pretrained on mental health and psychotherapy data. Results indicated that several models detected relationships between participant utterances and alliance, with the best performing model achieving an area under the receiver operating characteristic curve of 0.654. Logistic regression analysis identified specific utterances associated with high and low alliance ratings, providing interpretable insights into group dynamics. While acknowledging limitations such as small sample size and the specific context of weight stigma groups, this study provides insights into the potential of NLP in augmenting feedback-informed group therapy. Implications for real-time process monitoring and future directions for enhancing model performance in diverse group therapy settings are discussed. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

ABIET: An explainable transformer for identifying functional groups in biological active molecules.

Recent advancements in deep learning have revolutionized the field of drug discovery, with Transformer-based models emerging as powerful tools for molecular design and property prediction. However, the lack of explainability in such models remains a significant challenge. In this study, we introduce ABIET (Attention-Based Importance Estimation Tool), an explainable Transformer model designed to identify the most critical regions for drug-target interactions - functional groups (FGs) - in biologically active molecules. Functional groups play a pivotal role in determining chemical behavior and biological interactions. Our approach leverages attention weights from Transformer-encoder architectures trained on SMILES representations to assess the relative importance of molecular subregions. By processing attention scores using a specific strategy - considering bidirectional interactions, layer-based extraction, and activation transformations - we effectively distinguish FGs from non-FG atoms. Experimental validation on diverse datasets targeting pharmacological receptors, including VEGFR2, AA2A, GSK3, JNK3, and DRD2, demonstrates the model's robustness and interpretability. Comparative analysis with state-of-the-art gradient-based and perturbation-based methods confirms ABIET's superior performance, with functional groups receiving statistically higher importance scores. This work enhances the transparency of Transformer predictions, providing critical insights for molecular design, structure-activity analysis, and targeted drug development.

Value reciprocity mechanism in hotels: testing customer participation behaviour and value co-creation as mediators and previous experience as a moderator

PurposeThis study investigates the reciprocity mechanism in value co-creation and clarifies how service providers may effectively trigger customer participation behaviour and boost value co-creation to enhance customer citizenship behaviour, which brings extra benefits for service providers.Design/methodology/approachBy combining equity theory, social exchange theory and co-creation theory, this research proposes a model for the reciprocity mechanism in value co-creation incorporating customer co-creation perception (CCCP) conducting hotel dialogue, access, risk assessment and transparency (DART) activities; customer participation behaviour (CPB – information seeking, information sharing, responsible behaviour and personal interaction); customer citizenship behaviour (CCB – feedback, advocacy, helping and tolerance) and value co-creation in hotels. It also applies script theory to explore how customers’ previous experiences with the hotel may impact the value reciprocity mechanism. The collected data from tourists are analysed using partial least squares structural equation modelling (PLS-SEM).FindingsThe results confirm that CCCP drives CPB, value co-creation and CCB. CPB also enhances value co-creation, consequently boosting CCB. Moreover, CPB and value co-creation are the reciprocity mechanisms that mediate CCCP to CCB. Findings also reveal that CPB has a greater impact on value co-creation for first-time customers. In contrast, CCCP has a higher effect on value co-creation for repeat customers.Practical implicationsThe proposed model is a managerial tool that assists practitioners in effectively driving customer participation behaviour and improving value co-creation for first-time customers and repeat customers.Originality/valueThis study uncovers the significance of the hospitality service provider’s DART actions in forming customer perceptions and leading customer behaviour towards value co-creation.

Anchoring Ru single-atoms on MXene achieves dual-enzyme activities for mild photothermal augmented nanocatalytic therapy.

Single-atom catalysts with abnormally high catalytic activity have garnered extensive attention and interest for their application in tumor therapy. Despite the advancements made with current nanotherapeutic agents, developing efficient systems for cancer treatment remains challenging due to low activity, uncontrollable behavior, and nonselective interactions. Herein, we have constructed Ru single-atom-anchored MXene nanozymes (Ru-Ti3C2Tx-PEG) with a mild photothermal effect and multi-enzyme catalytic activity for synergistic tumor therapy. Ru single atoms anchored on the surface of MXene nanosheets not only facilitate multi-enzyme catalytic activity but also amplify the photothermal performance owing to the localized surface plasmon resonance effect. The Ru single atoms could decompose H2O2 into toxic hydroxyl radicals (•OH) in response to the tumor microenvironment (TME) for enzyme catalytic therapy, and the heat produced by the nanozyme under near-infrared laser excitation enhanced the •OH generation yield. Moreover, the nanozyme exhibited oxygen formation and glutathione depletion capability in cancer cells, thereby regulating the TME and accelerating the •OH levels. The in vitro and in vivo studies in this work confirm that the two-dimensional Ru single-atom-anchored MXene nanozyme has an extraordinary tumor growth inhibition effect, thus presenting a rational therapeutic strategy for tumor ablation through the synergistic effect of photothermal activity and heat-promoted enzymatic catalysis.

Instructional Strategy for Teaching Children with Autism in the Classroom

This research looks at a number of persons who have communication problems due to various diseases. Children with autism are one of them. Because children with autism have three basic disorders: communication, social interaction, and behavior, their communication and social interaction will undoubtedly differ from those of typical children. This research will look into instructional communication for children with autism in the classroom at Rumah Autis Depok. Rumah Autis is a social institution created to fill the gap between the demand for therapeutic locations and schools for children with autism and special needs who come from low-income households. The ethnography of communication approach was used in this research because ethnography of communication focuses on communication processes that involve language and culture. The findings of this research indicated that the communication utilized by children with autism, particularly instructional communication in the classroom, is quite unique and distinct. Teachers must speak firmly but not loudly or repeatedly. Therefore, the students easily understand. Children with autism are easily distracted, and thus, the teacher does not allow wearing eye-catching clothing and headscarves in class. The research encourages communication ethnographers to reflect on fieldwork issues and gives a framework for doing so, particularly when it comes to teaching children with autism

A Qualitative Analysis of Unintentional Injuries in Autism Spectrum Disorder.

Prior research demonstrates that children with autism are more likely to experience unintentional injuries than the general population. Limited research exists on the symptoms or traits directly related to autism and this elevated injury rate, especially from the perspective of families with children with autism. This study used qualitative methodology to elucidate risk factors that may contribute to unintentional injuries in children with autism from the perspective of mothers raising children with autism. Participants included 15 mothers reporting on their children with autism. The mothers engaged in a semi-structured qualitative interview consisting of questions related to child characteristics, injury concerns and experiences, injury prevention strategies and resources, and safety behaviors. Interviews were transcribed and coded in NVivo following a systematic, deductive approach. Injury risk and concern among mothers was generally related to both the diagnostic and associated features of ASD as well as commonly co-occurring behaviors or disorders. Mothers reported that deficits in social communication and social interaction, plus restricted or repetitive patterns of behavior, contributed to increased unintentional injury risk. Additionally, mothers reported that general developmental differences and behavior during play or exploration increased risk of injury. By considering the lived experiences of families of children with autism, this study reveals that specific diagnostic features, associated features, and other behaviors often co-occurring with autism underlie parental perceptions of increased risk of and concern for unintentional injury in children with autism. These findings guide where intervention is needed and inform development of evidence-based, practical safety interventions.

The clockwork of insect activity: Advancing ecological understanding through automation.

Understanding insect behaviour and its underlying drivers is vital for interpreting changes in local biodiversity and predicting future trends. Conventional insect traps are typically limited to assess the composition of local insect communities over longer time periods and provide only limited insights into the effects of abiotic factors, such as light on species activity. Achieving finer temporal resolution is labour-intensive or only possible under laboratory conditions. Here, we demonstrate that time-controlled insect sampling using an automated Malaise trap in combination with metabarcoding allows for the observation and documentation of taxon-specific activity patterns. Furthermore, these recorded activity patterns can provide valuable insights into the underlying ecological processes. Insect activity curves, derived from predicted detection numbers using generalised linear latent variable models, reveal distinct differences in activity patterns at higher and lower taxonomic level. While our findings align with existing literature, they also reveal that the activity patterns of some species are more complex than previously known. Additionally, a comparison of the assessed activity patterns across taxa suggest potential, previously undescribed parasitoid-host relationships. Within taxonomic groups, we observe variations in both the timing and duration of activity patterns, which can be linked to differences in mating strategies among closely related species. By capturing circadian rhythms of insect activity through time-controlled bulk sampling, we can expand our knowledge on species behaviour, ecology and temporal interactions. This contributes significantly to the advancement of chronoecology, allowing for further exploration of the roles of species and benefits in natural and anthropogenic ecosystems, alongside their potentially significant threat.

The impact of online customer service and store features on consumer experience and willingness to revisit their preferred online store

From aspects scarcely studied, such as the online store ambiance and display of the product in the online store, to more prevalent issues related to purchasing behaviour, such as online customer service, the ethics of online stores, and online technologies, this article develops and tests a conceptual model of the factors that significantly impact consumer interactions, experience, behaviour and their willingness to revisit online stores. Data collected from 272 Romanian online shoppers during 2021–2022 is analysed by structural equation modelling with SmartPLS. The results highlight a positive link between online customer service, consumer behaviour, and store ambiance. Ethics of online sales positively influence consumer behaviour within the online store. Online store technology is significantly associated with consumer behaviour and online store interaction. The paper extends the theory of Planned Behaviour, highlighting significant links between online consumer service and other factors and their implications on online purchasing behaviour and on the willingness to return to the online store.

Public health: a critical nexus of social, environmental, and behavioral interactions

Public health: a critical nexus of social, environmental, and behavioral interactions

Vapor-Liquid Equilibrium Data for The Binary Systems of Methacrylic Acid, Methyl Methacrylate, and Water at 26 kPa and 50 kPa

Methyl methacrylate (MMA) is a significant organic compound utilized across diverse industrial sectors. This research study aims to examine the separation of azeotropic systems containing MMA derived from the C4 route. The primary focus of this examination is on vapor-liquid equilibrium (VLE) data for binary systems of methacrylic acid (MAA) and water, as well as methacrylic acid and MMA. The study will be conducted under vacuum pressures of 26 kPa and 50 kPa. The objective of this study is to generate and analyze VLE data, thereby facilitating a comprehensive understanding of the azeotropic behavior and non-ideal interactions in these systems. The VLE data were obtained using a modified Rose-Williams type recirculation still. The azeotropic composition of the methacrylic acid and water system was confirmed, and the data were validated through Herrington and van Ness methods to ensure thermodynamic consistency. The findings indicate that the excess of the calculated Gibbs free energy and activity coefficient substantiates the non-ideal behavior. In conclusion, this study provides valuable insights into the design and optimization of the MMA by-product separation process. To further refine the model and enhance its predictive capabilities, additional research is recommended, focusing on exploring the impact of diverse experimental conditions and evaluating the efficacy of alternative predictive models.

Identification of Components of the Sex Pheromone of the kōwhai Moth, Uresiphita Polygonalis Maorialis, a New Zealand Native Crambid

The identification of sex pheromones in native New Zealand moths has been limited, largely due to their minimal pest impact on agricultural ecosystems. The kōwhai moth, Uresiphita polygonalis maorialis, a native crambid, is known for its herbivory on Sophora spp. and Lupinus arboreus leaves. Understanding the chemical ecology of this species is essential for studying its behavior, population dynamics, and ecological interactions. In this study, the female sex pheromone of U. polygonalis maorialis was analyzed using coupled gas chromatography-electroantennogram detection (GC-EAD). This approach identified four antennally active compounds in the female gland extracts. Subsequent gas chromatography-mass spectrometry (GC-MS) and chemical derivatization revealed these compounds to be tetradecyl acetate (14:Ac), (E)-11-tetradecenyl acetate (E11-14:Ac), (Z)-11-tetradecenyl acetate (Z11-14:Ac), and (Z)-11-hexadecenyl acetate (Z11-16:Ac). Field trapping experiments evaluated various combinations of these four EAD-active compounds and (E)-11-hexadecenyl acetate (E11-16:Ac). Results indicated that traps baited with blends containing E11-14:Ac, Z11-14:Ac, and Z11-16:Ac captured significantly more males compared to unbaited delta traps. A blend ratio of 144:84:72 µg (E11-14:Ac: Z11-14:Ac: Z11-16:Ac) proved the most effective, capturing the highest number of males. Male captures were recorded from late November to late February, peaking in late December, suggesting a univoltine population in Canterbury. Among the three tested doses, the 300 µg and 1000 µg doses of the three-component blend were the most effective. The identification of the sex pheromone components of U. polygonalis maorialis provides a valuable tool for monitoring this species, contributing to a deeper understanding of its population densities and distribution within its native range. It also offers insights into the evolutionary development of pheromone communication within the genus, shedding light on species divergence and adaptation.

Physical behaviours during pregnancy may alter the association of maternal insulin sensitivity with neonatal adiposity: a prospective pre-birth cohort of mother-child pairs

BackgroundLower maternal insulin sensitivity during pregnancy is associated with greater fetal adiposity. Physical activity can improve insulin sensitivity, but it is not known if physical behaviours influence the known association of maternal insulin sensitivity with offspring adiposity. This study aimed to investigate the moderating impact of physical behaviours on this association.MethodsPregnant women (n = 812) from the Gen3G cohort were recruited during the first trimester of pregnancy and followed until delivery. At the first (V1) and second trimester (V2) hospital visits, Gen3G staff measured anthropometry, and participants reported sleep duration as well as leisure physical activity and sedentary behaviour via lifestyle questionnaires. We used plasma glucose and insulin values from the 75 g oral glucose tolerance test at V2 to calculate insulin sensitivity using the Matsuda index. We recorded birthweight from electronic medical records. Among a subset of neonates (n = 265), trained research staff measured skinfold thickness using a calibrated skinfold caliper following standardized protocols to estimate neonatal adiposity. Linear regression analyses assessed the association of insulin sensitivity with birthweight z-score and sum of neonatal skinfold thickness, adjusting for maternal age, race/ethnicity, gravidity, smoking, with and without adjustment for maternal body mass index at V1. We evaluated moderation by physical activity, sedentary behaviour, or nighttime sleep duration using interaction terms and stratified analyses for the association of maternal insulin sensitivity with offspring birthweight and with offspring adiposity.ResultsLower Matsuda index was associated with higher birthweight z-score (ß±SE= -0.180 ± 0.056, p = 0.001) and with higher sum of skinfold thickness (neonatal adiposity) (ß±SE=-0.877 ± 0.383, p = 0.02) in fully adjusted models. The association between Matsuda index and sum of skinfold thickness was weaker in women with higher levels of physical activity at V2 ([high ≥ 1.26 kcal/kg/day] ß±SE=-0.15 ± 0.65) compared to women with lower levels [low < 1.26 kcal/kg/day] ß±SE=-1.36 ± 0.51, P-interaction = 0.01). We also observed potential interactions of sleep and sedentary behaviour at V2 with Matsuda index for the association with birthweight z-score. We did not observe effect modification by levels of physical behaviours assessed at V1.ConclusionThe association between lower insulin sensitivity and higher neonatal adiposity was attenuated in women with higher physical activity levels in the second trimester, independent of maternal body mass index.

Insights to unusual antiferromagnetic behavior and exchange coupling interactions in Mn23C6

Insights to unusual antiferromagnetic behavior and exchange coupling interactions in Mn₂₃C₆