Factors influencing motivation to perform mental and physical tasks during the initial lockdown period of the COVID-19 pandemic

International Journal of Exercise Science 15(5): 1600-1615, 2022. Drastic changes to lifestyles have occurred during the COVID-19 pandemic. An unintended consequence of stay at home orders is increased isolation and less social interaction for many people. For overall wellbeing it is important to stay both physically and mentally active; however, for many individual’s motivation may be a barrier. There are non-modifiable (e.g. sex, age, personality, infection rates in the area) and modifiable factors (e.g. physical activity, diet, sleep) that may be associated with motivation to perform physical and mental tasks. We collected data from 794 subjects using an online survey between April 13th to May 3rd of 2020. Survey questionnaires included demographics, personality traits, diet, sleep, physical activity levels, mental workload and motivation to perform mental and physical tasks. Multiple linear regression analyses were used to assess the association between non-modifiable and modifiable variables on motivation to perform mental and physical tasks. The results of our analyses suggest that those who reported a higher quality of diet (REAP-S score), exercised vigorously, and reduced their sedentary time, reported higher motivation to perform both mental and physical tasks. Those who were employed and had higher grit were more motivated to perform physical tasks. Lower trait physical energy was associated with greater motivation to perform mental tasks. Our findings support that during challenging times, such as the COVID-19 pandemic, it is important for healthcare practitioners to emphasize the importance healthy lifestyle behaviors to prevent individuals from experiencing a lack of motivation to perform both mental and physical tasks. Future research should focus on trying to determine the directionality of the relationship between specific healthy lifestyle behaviors and motivation

Factors Influencing Motivation to Perform Mental and Physical Tasks during the Initial Lockdown Period of the COVID-19 Pandemic

Drastic changes to lifestyles have occurred during the COVID-19 pandemic. A consequence of non-pharmaceutical interventions (NPIs) used against this health crisis, such as stay-at-home orders, has been increased isolation and less social interaction for a majority of people. For overall wellbeing, it is important to stay both physically and mentally active. However, for many individuals motivation may be a barrier. There are non-modifiable (e.g., sex, age) and modifiable factors (e.g., physical activity, diet) that may be associated with motivation to perform physical/mental tasks. PURPOSE: To explore if there is an association between non-modifiable and modifiable variables on motivation to perform mental/physical tasks under COVID-19 NPIs. METHODS: We collected data from 794 subjects using Qualtrics and each subject completed our survey once each week during April 1st to May 3rd of 2020. This is an ongoing study that will terminate when the COVID-19 pandemic ends. Survey questionnaires included demographics, personality traits, diet, physical activity levels, and motivation to perform mental/physical tasks. Multiple linear regression analyses were used for statistical analysis. RESULTS: Significant results include: a) those who reported a higher quality of diet (REAP-S score) (β=.015, p\u3c0.05; β=0.000, p\u3c0.001), exercised vigorously (β=0.005, p\u3c0.01; β=0.000, p\u3c0.001), and reduced their sedentary time (β=.000, p\u3c0.01; β=.000, p\u3c0.001), reported higher motivation to perform both mental and physical tasks, respectively; b) those who were employed (β=.043, p\u3c0.05) and had higher grit (β=.041, p\u3c0.05) were more motivated to perform physical tasks; and c) lower trait physical energy was associated with greater motivation to perform mental tasks (β=.027, p\u3c0.05). CONCLUSION: Our findings indicate that living a healthy lifestyle is associated with motivation to perform both mental and physical tasks during the initial lockdown period of the COVID-19 pandemic. These preliminary results support the continuation of data collection. Future research should focus on trying to determine the directionality of the relationship between healthy lifestyle behaviors and motivation

Utilizing logistic regression to compare risk factors in disease modeling with imbalanced data: a case study in vitamin D and cancer incidence

Imbalanced data, a common challenge encountered in statistical analyses of clinical trial datasets and disease modeling, refers to the scenario where one class significantly outnumbers the other in a binary classification problem. This imbalance can lead to biased model performance, favoring the majority class, and affecting the understanding of the relative importance of predictive variables. Despite its prevalence, the existing literature lacks comprehensive studies that elucidate methodologies to handle imbalanced data effectively. In this study, we discuss the binary logistic model and its limitations when dealing with imbalanced data, as model performance tends to be biased towards the majority class. We propose a novel approach to addressing imbalanced data and apply it to publicly available data from the VITAL trial, a large-scale clinical trial that examines the effects of vitamin D and Omega-3 fatty acid to investigate the relationship between vitamin D and cancer incidence in sub-populations based on race/ethnicity and demographic factors such as body mass index (BMI), age, and sex. Our results demonstrate a significant improvement in model performance after our undersampling method is applied to the data set with respect to cancer incidence prediction. Both epidemiological and laboratory studies have suggested that vitamin D may lower the occurrence and death rate of cancer, but inconsistent and conflicting findings have been reported due to the difficulty of conducting large-scale clinical trials. We also utilize logistic regression within each ethnic sub-population to determine the impact of demographic factors on cancer incidence, with a particular focus on the role of vitamin D. This study provides a framework for using classification models to understand relative variable importance when dealing with imbalanced data

Interrelation between Stress Management and Secretion Systems of <em>Ralstonia solanacearum</em>: An In Silico Assessment

Ralstonia solanacearum (Rs), the causative agent of devastating wilt disease in several major and minor economic crops, is considered one of the most destructive bacterial plant pathogens. However, the mechanism(s) by which Rs counteracts host-associated environmental stress is still not clearly elucidated. To investigate possible stress management mechanisms, orthologs of stress-responsive genes in the Rs genome were searched using a reference set of known genes. The genome BLAST approach was used to find the distributions of these orthologs within different Rs strains. BLAST results were first confirmed from the KEGG Genome database and then reconfirmed at the protein level from the UniProt database. The distribution pattern of these stress-responsive factors was explored through multivariate analysis and STRING analysis. STRING analysis of stress-responsive genes in connection with different secretion systems of Rs was also performed. Initially, a total of 28 stress-responsive genes of Rs were confirmed in this study. STRING analysis revealed an additional 7 stress-responsive factors of Rs, leading to the discovery of a total of 35 stress-responsive genes. The segregation pattern of these 35 genes across 110 Rs genomes was found to be almost homogeneous. Increasing interactions of Rs stress factors were observed in six distinct clusters, suggesting six different types of stress responses: membrane stress response (MSR), osmotic stress response (OSR), oxidative stress response (OxSR), nitrosative stress response (NxSR), and DNA damage stress response (DdSR). Moreover, a strong network of these stress responses was observed with type 3 secretion system (T3SS), general secretory proteins (GSPs), and different types of pili (T4P, Tad, and Tat). To the best of our knowledge, this is the first report on overall stress response management by Rs and the potential connection with secretion systems

Understanding the source components captured by the Purple Air Network

PM2.5 has been linked to numerous pollution-mediated adverse health effects and their monitoring is key for taking preventative and mitigative measures. Accurate measurements of PM2.5 concentrations are available at EPA sites, but such data lacks spatial resolution due to a limited number of monitoring locations. In recent years the deployment of low-cost sensor networks has opened up the possibility of acquiring air quality data at a high spatiotemporal resolution. However, the sensitivity, noise, and accuracy of data acquired by low-cost sensors remain a concern. Here, we studied PM2.5 measurements made from EPA and Purple Air (PA) sensor networks in the Chicago area to understand the parameters influencing the performance characteristics of the low-cost sensor network. Using time series decomposition of PM2.5 data into short-term and baseline components using Kolmogorov–Zurbenko (KZ) filter and analysis of the extracted frequency signals, we determine that PA sensor data is more sensitive to meteorological conditions than anthropogenic activities in both short-term, and baseline components. We hypothesize that the low-cost sensor networks may have different sensitivity to aerosol from different sources and hence care must be taken in their calibrations and in their use for evaluating the impact of air quality mitigation policies

Photodynamic Control of Bioactivity in a Nanofiber Matrix

Self-assembling peptide materials have been used extensively to mimic natural extracellular matrices (ECMs) by presenting bioactive epitopes on a synthetic matrix. Although this approach can facilitate a desired response from cells grown in the matrix, it lacks the capacity for spatial or temporal regulation of the presented signals. We describe here a photoresponsive, synthetic ECM using a supramolecular platform composed of peptide amphiphiles (PAs) that self-assemble into cylindrical nanofibers. A photocleavable nitrobenzyl ester group was included in the peptide backbone using a novel Fmoc-amino acid that is compatible with microwave-assisted solid-phase peptide synthesis. The placement of the photolabile group on the peptide backbone enabled efficient removal of the ECM-derived cell adhesion epitope RGDS from PA molecules upon exposure to light (half-life of photolysis ∼1.9 min) without affecting the nanofiber assembly. Fibroblasts cultured on RGDS-presenting PA nanofiber substrates demonstrated increased cell spreading and more mature focal adhesions compared with unfunctionalized and control (RGES-presenting) surfaces, as determined by immunostaining and cell morphological analysis. Furthermore, we observed an arrest in fibroblast spreading on substrates containing a cleavable RGDS epitope when the culture was exposed to light; in contrast, this dynamic shift in cell response was absent when the RGDS epitope was attached to the PA molecule by a light-insensitive control linker. Light-responsive bioactive materials can contribute to the development of synthetic systems that more closely mimic the dynamic nature of native ECM

Post-Assembly Functionalization of Supramolecular Nanostructures with Bioactive Peptides and Fluorescent Proteins by Native Chemical Ligation

Post-assembly functionalization of supramolecular nanostructures has the potential to expand the range of their applications. We report here the use of the chemoselective native chemical ligation (NCL) reaction to functionalize self-assembled peptide amphiphile (PA) nanofibers. This strategy can be used to incorporate specific bioactivity on the nanofibers, and as a model, we demonstrate functionalization with the RGDS peptide following self-assembly. Incorporation of bioactivity is verified by the observation of characteristic changes in fibroblast morphology following NCL-mediated attachment of the signal to PA nanofibers. The NCL reaction does not alter the PA nanofiber morphology, and biotinylated RGDS peptide was found to be accessible on the nanofiber surface after ligation for binding with streptavidin-conjugated gold nanoparticles. In order to show that this strategy is not limited to short peptides, we utilized NCL to conjugate yellow fluorescent protein and/or cyan fluorescent protein to self-assembled PA nanofibers. Förster resonance energy transfer and fluorescence anisotropy measurements are consistent with the immobilization of the protein on the PA nanofibers. The change in electrophoretic mobility of the protein upon conjugation with PA molecules confirmed the formation of a covalent linkage. NCL-mediated attachment of bioactive peptides and proteins to self-assembled PA nanofibers allows the independent control of self-assembly and bioactivity while retaining the biodegradable peptide structure of the PA molecule and thus can be useful in tailoring design of biomaterials

Supramolecular Nanofibers Enhance Growth Factor Signaling by Increasing Lipid Raft Mobility

The nanostructures of self-assembling biomaterials have been previously designed to tune the release of growth factors in order to optimize biological repair and regeneration. We report here on the discovery that weakly cohesive peptide nanostructures in terms of intermolecular hydrogen bonding, when combined with low concentrations of osteogenic growth factor, enhance both BMP-2 and Wnt mediated signaling in myoblasts and bone marrow stromal cells, respectively. Conversely, analogous nanostructures with enhanced levels of internal hydrogen bonding and cohesion lead to an overall reduction in BMP-2 signaling. We propose that the mechanism for enhanced growth factor signaling by the nanostructures is related to their ability to increase diffusion within membrane lipid rafts. The phenomenon reported here could lead to new nanomedicine strategies to mediate growth factor signaling for translational targets