Structural Elucidation and Total Synthesis for the Pair of Unprecedented Polypyridines with Anti-AChE and HIV-1 Protease Activities from Alangium chinense.

Unlike reported pyridine hybrids, 2S (1a) and 2R-alanginenmine A (1b) from Alangium chinense featuring an unprecedented piperidine-bridged polypyridine skeleton represented a pair of alkaloid subtypes with a unique multiple pyridine scaffold. Enlightened by the rare structural characteristics and possible biosynthetic pathway, (±)-alanginenmine A (1) have been achieved in ideal yield by gram-class total synthesis with four steps. In addition, both compounds 1a and 1b exhibited anti-acetylcholinesterase (AChE) and HIV-1 protease activities in the biological activity evaluation. Further, molecular docking was investigated for the mechanism of action between the isolated compounds and HIV-1 protease. The stronger Coulomb interactions and van der Waals interaction, as well as the hydrogen bond interactions of 1a, might be the main cause for its better anti-HIV-1 protease activity than 1b. This work provided a comprehensive research including natural product discovery, bioactivity evaluation, and total synthesis for the new type of leading anti-HIV-1 protease.

Developing air pollution concentration fields for health studies using multiple methods: Cross-comparison and evaluation.

Past air pollution epidemiological studies have used a wide range of methods to develop concentration fields for health analyses. The fields developed differ considerably among these methods. The reasons for these differences and comparisons of their strengths, as well as the limitations for estimating exposures, remains under-investigated. Here, we applied nine methods to develop fields of eight pollutants (carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), fine particulate matter (PM2.5), and three speciated PM2.5 constituents including elemental carbon (EC), organic carbon (OC), and sulfate (SO4)) for the metropolitan Atlanta region for five years. The nine methods are Central Monitor (CM), Site Average (SA), Inverse Distance Weighting (IDW), Kriging (KRIG), Land Use Regression (LUR), satellite Aerosol Optical Depth (AOD), CMAQ model, CMAQ with kriging adjustment (CMAQ-KRIG), and CMAQ based data fusion (CMAQ-DF). Additionally, we applied an increasingly popular method, Random Forest (RF), and compared its results for NO2 and PM2.5 with other methods. For statistical evaluation, we focused our discussion on the temporal coefficient of determination, although other metrics are also calculated. Raw output from the CMAQ model contains modeling biases and errors, which are partially mitigated by fusing observational data in the CMAQ-KRIG and CMAQ-DF methods. Based on analyses that simulated model responses to more limited input data, the RF model is more robust and outperforms LUR for PM2.5. These results suggest RF may have potential in air pollution health studies, especially when limited measurement data are available. The RF method has several important weaknesses, including a relatively poor performance for NO2, diagnostic challenges, and computational intensiveness. The results of this study will help to improve our understanding of the strengths and weaknesses of different methods for estimating air pollutant exposures in epidemiological studies.

New Monoterpenoid Indoles with Osteoclast Activities from Gelsemium elegans.

The well-known toxic medicine Gelsemium elegans is widely and historically used to treat bone fracture and skin ulcers by the folk people of China. Two new monoterpenoid indole alkaloids, gelselegandines D and E, together with the known analogue gelegamine A were isolated from G. elegans. Their structures were elucidated by means of spectroscopic techniques and quantum chemical calculations. All isolated compounds were tested for the effects on RANKL-induced osteoclast formation. Interestingly, gelselegandine E and gelegamine A, respectively, showed significant promoting and inhibitory activities on osteoclastogenesis, while gelselegandine D had no activity under the same concentration. This work suggested the different configurations for the carbons near the C-19/20 oxygen rings of the isolated compounds may be the key active groups on osteoclast formation and provided the evidence for the rationality as the traditional treatment for bone-related diseases of G. elegans.

Wip1 phosphatase deficiency impairs spatial learning and memory.

Spatial learning and memory are typically assessed to evaluate hippocampus-dependent cognitive and memory functions in vivo. Protein phosphorylation and dephosphorylation by kinases and phosphatases play critical roles in spatial learning and memory. Here we report that the Wip1 phosphatase is essential for spatial learning, with knockout mice lacking Wip1 phosphatase exhibiting dysfunctional spatial cognition. Aberrant phosphorylation of the Wip1 substrates p38, ATM, and p53 were observed in the hippocampi of Wip1-/- mice, but only p38 inhibition reversed impairments in long-term potentiation in Wip1-knockout mice. p38 inhibition consistently ameliorated the spatial learning dysfunction caused by Wip1 deficiency. Our results demonstrate that deletion of Wip1 phosphatase impairs hippocampus-dependent spatial learning and memory, with aberrant downstream p38 phosphorylation involved in this process and providing a potential therapeutic target.

Using High-Temporal-Resolution Ambient Data to Investigate Gas-Particle Partitioning of Ammonium over Different Seasons.

Ammonium is one of the dominant inorganic water-soluble ions in fine particulate matter (PM2.5). In this study, source apportionment and thermodynamic equilibrium models were used to analyze the relationship between pH and the partitioning of ammonium (ε(NH4+)) using hourly ambient samples collected from Tianjin, China. We found a "Reversed-S curve" between pH and ε(NH4+) from the ambient hourly aerosol dataset when the theoretical ε(NO3-)* (an index identified in this work) was within specific ranges. A Boltzmann function was then used to fit the Reversed-S curve. For the summer data set, when ε(NO3-)* was between 0.7 and 0.8, the fitted R2 was 0.88. Through thermodynamic analysis, we found that the values of k[H+]2 (k = 3.08 × 104 L2 mol-2) and ε(NO3-)* can influence the pH-ε(NH4+) curve. Under certain situations, the values of k[H+]2 and ε(NO3-)* are similar to each other, and ε(NH4+) is sensitive to pH, suggesting that ε(NO3-)* plays an important role in affecting the ε(NH4+). During summer, winter, and spring seasons, when the relative humidity was greater than 0.36 and ε(NO3-)* was between 0.8 and 0.95, there was an obvious Reversed-S curve, with R2 = 0.60. The theoretical k[H+]2 and ε(NO3-)* developed in this work can be used to analyze the gas-particle partitioning of ammonia-ammonium and nitrate-nitric acid in the ambient atmosphere. Also, it is the first time that we created the joint source-NH3/HNO3 maps to integrate sources, aerosol pH and liquid water content, and ions (altogether in one map), which can provide useful information for designing effective strategies to control particulate matter pollution.

High-Resolution Data Sets Unravel the Effects of Sources and Meteorological Conditions on Nitrate and Its Gas-Particle Partitioning.

Nitrate is one of the most abundant inorganic water-soluble ions in fine particulate matter (PM2.5). However, the formation mechanism of nitrate in the ambient atmosphere, especially the impacts of its semivolatility and the various existing forms of nitrogen, remain under-investigated. In this study, hourly ambient observations of speciated PM2.5 components (NO3-, SO42-, etc.) were collected in Tianjin, China. Source contributions were analyzed by PMF/ME2 (Positive Matrix Factorization using the Multilinear Engine 2) program, and pH were estimated by ISORROPIA-II, to investigate the relationship between pH and nitrate. Five sources (factors) were resolved: secondary sulfate (SS), secondary nitrate (SN), dust, vehicle and coal combustion. SN and pH showed a triangle-shaped relationship. When SS was high, the fraction of nitrate partitioning into the aerosol phase exhibits a characteristic "S-curve" relationship with pH for different seasons. An index ( ITL) is developed and combined with pH to explore the sensitive regions of "S-curve". Controlling the emissions of anions (SO42-, Cl-), cations (Ca2+, Mg2+, etc.) and gases (NO x, NH3, SO2, etc.) will change pH, potentially reducing or increasing SN. The findings of this work provide an effective approach for exploring the formation mechanisms of nitrate under different influencing factors (sources, pH, and IRL).

Unprecedented sugar bridged bisindoles selective inhibiting glioma stem cells.

Unlike reported bisindoles linked by single bond directly, alstoniasidines A (1) and B (2), from Alstonia scholaris featuring unprecedented skeleton with two indole moieties bridged by a sugar, represented a novel bisindole type having strictosamide-glucopyranose-picraline scaffold. Both compounds exhibited selective cytotoxicity against human glioma stem cells (GSCs) and induced caspase-3 dependent extrinsic apoptosis by increasing the expression of interleukin 1 (IL-1), tumor necrosis factor (TNF-α), and the cleaved caspase-3, while damaged the unlimited proliferation and self-renewal capacity of GSCs. This finding might provide new type of leads for the selective killing of human glioma stem cells.

On the Security and Data Integrity of Low-Cost Sensor Networks for Air Quality Monitoring.

The emerging connected, low-cost, and easy-to-use air quality monitoring systems have enabled a paradigm shift in the field of air pollution monitoring. These systems are increasingly being used by local government and non-profit organizations to inform the public, and to support decision making related to air quality. However, data integrity and system security are rarely considered during the design and deployment of such monitoring systems, and such ignorance leaves tremendous room for undesired and damaging cyber intrusions. The collected measurement data, if polluted, could misinform the public and mislead policy makers. In this paper, we demonstrate such issues by using a.com, a popular low-cost air quality monitoring system that provides an affordable and continuous air quality monitoring capability to broad communities. To protect the air quality monitoring network under this investigation, we denote the company of interest as a.com. Through a series of probing, we are able to identify multiple security vulnerabilities in the system, including unencrypted message communication, incompetent authentication mechanisms, and lack of data integrity verification. By exploiting these vulnerabilities, we have the ability of "impersonating" any victim sensor in the a.com system and polluting its data using fabricated data. To the best of our knowledge, this is the first security analysis of low-cost and connected air quality monitoring systems. Our results highlight the urgent need in improving the security and data integrity design in these systems.

pH of Aerosols in a Polluted Atmosphere: Source Contributions to Highly Acidic Aerosol.

Acidity (pH) plays a key role in the physical and chemical behavior of PM2.5. However, understanding of how specific PM sources impact aerosol pH is rarely considered. Performing source apportionment of PM2.5 allows a unique link of sources pH of aerosol from the polluted city. Hourly water-soluble (WS) ions of PM2.5 were measured online from December 25th, 2014 to June 19th, 2015 in a northern city in China. Five sources were resolved including secondary nitrate (41%), secondary sulfate (26%), coal combustion (14%), mineral dust (11%), and vehicle exhaust (9%). The influence of source contributions to pH was estimated by ISORROPIA-II. The lowest aerosol pH levels were found at low WS-ion levels and then increased with increasing total ion levels, until high ion levels occur, at which point the aerosol becomes more acidic as both sulfate and nitrate increase. Ammonium levels increased nearly linearly with sulfate and nitrate until approximately 20 µg m-3, supporting that the ammonium in the aerosol was more limited by thermodynamics than source limitations, and aerosol pH responded more to the contributions of sources such as dust than levels of sulfate. Commonly used pH indicator ratios were not indicative of the pH estimated using the thermodynamic model.

Associations between exposure to ambient benzene and PM(2.5) during pregnancy and the risk of selected birth defects in offspring.

OBJECTIVE: A growing number of studies have investigated the association between air pollution and the risk of birth defects, but results are inconsistent. The objective of this study was to examine whether maternal exposure to ambient PM2.5 or benzene increases the risk of selected birth defects in Florida. METHODS: We conducted a retrospective cohort study of singleton infants born in Florida from 2000 to 2009. Isolated and non-isolated birth defect cases of critical congenital heart defects, orofacial clefts, and spina bifida were identified from the Florida Birth Defects Registry. Estimates of maternal exposures to PM2.5 and benzene for all case and non-case pregnancies were derived by aggregation of ambient measurement data, obtained from the US Environmental Protection Agency Air Quality System, during etiologically relevant time windows. Multivariable Poisson regression was used to estimate adjusted prevalence ratios (aPRs) and 95% confidence intervals (CIs) for each quartile of air pollutant exposure. RESULTS: Compared to the first quartile of PM2.5 exposure, higher levels of exposure were associated with an increased risk of non-isolated truncus arteriosus (aPR4th Quartile, 8.80; 95% CI, 1.11-69.50), total anomalous pulmonary venous return (aPR2nd Quartile, 5.00; 95% CI, 1.10-22.84), coarctation of the aorta (aPR4th Quartile, 1.72; 95% CI, 1.15-2.57; aPR3rd Quartile, 1.60; 95% CI, 1.07-2.41), interrupted aortic arch (aPR4th Quartile, 5.50; 95% CI, 1.22-24.82), and isolated and non-isolated any critical congenital heart defect (aPR3rd Quartile, 1.13; 95% CI, 1.02-1.25; aPR4th Quartile, 1.33; 95% CI, 1.07-1.65). Mothers with the highest level of exposure to benzene were more likely to deliver an infant with an isolated cleft palate (aPR4th Quartile, 1.52; 95% CI, 1.13-2.04) or any orofacial cleft (aPR4th Quartile, 1.29; 95% CI, 1.08-1.56). An inverse association was observed between exposure to benzene and non-isolated pulmonary atresia (aPR4th Quartile, 0.19; 95% CI, 0.04-0.84). CONCLUSION: Our results suggest a few associations between exposure to ambient PM2.5 or benzene and specific birth defects in Florida. However, many related comparisons showed no association. Hence, it remains unclear whether associations are clinically significant or can be causally related to air pollution exposures.

Spatiotemporal distributions of ambient oxides of nitrogen, with implications for exposure inequality and urban design.

UNLABELLED: Intra-urban differences in concentrations of oxides of nitrogen (NO(x)) and exposure disparities in the Tampa area were investigated across temporal scales through emissions estimation, dispersion modeling, and analysis of residential subpopulation exposures. A hybrid estimation method was applied to provide link-level hourly on-road mobile source emissions. Ambient concentrations in 2002 at 1 km resolution were estimated using the CALPUFF dispersion model. Results were combined with residential demographic data at the block-group level, to investigate exposures and inequality for select racioethnic, age, and income population subgroups. Results indicate that on-road mobile sources contributed disproportionately to ground-level concentrations and dominated the spatial footprint across temporal scales (annual average to maximum hour). The black, lower income (less than $40K annually), and Hispanic subgroups had higher estimated exposures than the county average; the white and higher income (greater than $60K) subgroups had lower than average exposures. As annual average concentration increased, the disparity between groups generally increased. However for the highest 1-hr concentrations, reverse disparities were also found. IMPLICATIONS: Current studies of air pollution exposure inequality have not fully considered differences by time scale and are often limited in spatial resolution. The modeling methods and the results presented here can be used to improve understanding of potential impacts of urban growth form on health and to improve urban sustainability. Results suggest focusing urban design interventions on reducing on-road mobile source emissions in areas with high densities of minority and low income groups.

Privacy and security concerns with passively collected location data for digital contact tracing among U.S. college students.

People continue to use technology in new ways, and how governments harness digital information should consider privacy and security concerns. During COVID19, numerous countries deployed digital contact tracing that collect location data from user's smartphones. However, these apps had low adoption rates and faced opposition. We launched an interdisciplinary study to evaluate smartphone location data concerns among college students in the US. Using interviews and a large survey, we find that college students have higher concerns regarding privacy, and place greater trust in local government with their location data. We discuss policy recommendations for implementing improved contact tracing efforts.

Research on the integral forming process of thin walled and thick mouth seamless gas cylinders.

There is a considerable difference in wall thickness between the mouth and the cavity of thin-walled and thick-mouthed seamless gas cylinders, and the existing manufacturing processes are unable to effectively meet product requirements. To overcome such issue, a step-by-step boring-necking-spinning solution for gas cylinders was proposed, in which sufficient wall thickness is reserved for the mouth area of the cylinder blank, followed by necking-spinning to realize the overall forming of thin-walled, thick-mouthed seamless gas cylinders. The stress-strain distribution and geometric dimensional changes of gas cylinders during the spinning process were investigated by means of finite element simulation, and the effects of different process parameters on the stress and wall thickness of the bottle mouth were analyzed. Further, multi-objective optimization of the response surface model was performed using the NSGA-II algorithm to derive a set of optimal process parameters. Finally, the correctness of the simulation and optimization results was verified experimentally, and the expected geometry and optimal strain state of the gas cylinder were obtained. The newly developed processing solution represents a groundbreaking advancement in the manufacturing of thin-walled and thick-mouthed gas cylinders.

Monitoring vs. modeled exposure data in time-series studies of ambient air pollution and acute health outcomes.

BACKGROUND: Population-based short-term air pollution health studies often have limited spatiotemporally representative exposure data, leading to concerns of exposure measurement error. OBJECTIVE: To compare the use of monitoring and modeled exposure metrics in time-series analyses of air pollution and cardiorespiratory emergency department (ED) visits. METHODS: We obtained daily counts of ED visits for Atlanta, GA during 2009-2013. We leveraged daily ZIP code level concentration estimates for eight pollutants from nine exposure metrics. Metrics included central monitor (CM), monitor-based (inverse distance weighting, kriging), model-based [community multiscale air quality (CMAQ), land use regression (LUR)], and satellite-based measures. We used Poisson models to estimate air pollution health associations using the different exposure metrics. The approach involved: (1) assessing CM-based associations, (2) determining if non-CM metrics can reproduce CM-based associations, and (3) identifying potential value added of incorporating full spatiotemporal information provided by non-CM metrics. RESULTS: Using CM exposures, we observed associations between cardiovascular ED visits and carbon monoxide, nitrogen dioxide, fine particulate matter, elemental and organic carbon, and between respiratory ED visits and ozone. Non-CM metrics were largely able to reproduce CM-based associations, although some unexpected results using CMAQ- and LUR-based metrics reduced confidence in these data for some spatiotemporally-variable pollutants. Associations with nitrogen dioxide and sulfur dioxide were only detected, or were stronger, when using metrics that incorporate all available monitoring data (i.e., inverse distance weighting and kriging). SIGNIFICANCE: The use of routinely-collected ambient monitoring data for exposure assignment in time-series studies of large metropolitan areas is a sound approach, particularly when data from multiple monitors are available. More sophisticated approaches derived from CMAQ, LUR, or satellites may add value when monitoring data are inadequate and if paired with thorough data characterization. These results are useful for interpretation of existing literature and for improving exposure assessment in future studies. IMPACT STATEMENT: This study compared and interpreted the use of monitoring and modeled exposure metrics in a daily time-series analysis of air pollution and cardiorespiratory emergency department visits. The results suggest that the use of routinely-collected ambient monitoring data in population-based short-term air pollution and health studies is a sound approach for exposure assignment in large metropolitan regions. CMAQ-, LUR-, and satellite-based metrics may allow for health effects estimation when monitoring data are sparse, if paired with thorough data characterization. These results are useful for interpretation of existing health effects literature and for improving exposure assessment in future air pollution epidemiology studies.

Exploring influential factors of CO2 emissions in China's cities using machine learning techniques.

The precise and exhaustive discernment of factors influencing CO2 emissions underpins the advancement toward sustainable, low-carbon development. Although numerous studies have probed the correlation between predetermined proxy variables and carbon emissions, methodological constraints have often led to an inability to effectively discern carbon emission determinants among numerous potential variables or unravel complex, non-linear relationships, and interaction effects. To redress these research gaps, this research utilized machine learning models to correlate urban CO2 emissions with socioeconomic indicators. The model outputs were then visualized and interpreted using explainable methods. The findings indicated that the model successfully identified a comprehensive array of dominant influences on urban CO2 emissions, principally associated with local fiscal policies, land use, energy consumption, industrial development, and urban transportation. The findings further revealed a complex non-linear association between these factors and urban CO2 emissions; however, the majority of these variables displayed a prevalent propensity to intensify carbon emissions in correspondence with an increase in sample value. Additionally, these factors exhibited a complex interactive influence on urban CO2 emissions, with distinct pairings producing a suppressive effect exclusively at specific combination of sample values. Consequently, this research posited that a robust correlation between urban socioeconomic development and CO2 emissions in China remains to be established. Given the varied impacts of these influencing factors across different cities, a differentiated approach to development should be adopted when charting low-carbon trajectories.

Unexpected Performance Improvements of Nitrogen Dioxide and Ozone Sensors by Including Carbon Monoxide Sensor Signal.

Low-cost air quality (LCAQ) sensors are increasingly being used for community air quality monitoring. However, data collected by low-cost sensors contain significant noise, and proper calibration of these sensors remains a widely discussed, but not yet fully addressed, area of concern. In this study, several LCAQ sensors measuring nitrogen dioxide (NO2) and ozone (O3) were deployed in six cities in the United States (Atlanta, GA; New York City, NY; Sacramento, CA; Riverside, CA; Portland, OR; Phoenix, AZ) to evaluate the impacts of different climatic and geographical conditions on their performance and calibration. Three calibration methods were applied, including regression via linear and polynomial models and random forest methods. When signals from carbon monoxide (CO) sensors were included in the calibration models for NO2 and O3 sensors, model performance generally increased, with pronounced improvements in selected cities such as Riverside and New York City. Such improvements may be due to (1) temporal co-variation between concentrations of CO and NO2 and/or between CO and O3; (2) different performance levels of low-cost CO, NO2, and O3 sensors; and (3) different impacts of environmental conditions on sensor performance. The results showed an innovative approach for improving the calibration of NO2 and O3 sensors by including CO sensor signals into the calibration models. Community users of LCAQ sensors may be able to apply these findings further to enhance the data quality of their deployed NO2 and O3 monitors.

Antimicrobial indole alkaloids from Tabernaemontana corymbosa.

Four unreported monoterpene indole alkaloids, tabernaecorymines B-E (1-4), together with twenty-one known indole alkaloids (5-25) were obtained from the stem bark of Tabernaemontana corymbosa. Their structures and absolute configurations were elucidated by extensive spectroscopy, quantum chemical calculations, DP4+ probability analyses and Mo2(OAc)4-induced electronic circular dichroism experiment. The antibacterial and antifungal activities of these compounds were evaluated and some of them showed significant activity against Staphylococcus aureus,Bacillus subtilis, Streptococcus dysgalactiae and Candida albicans.

11,12-Diacetyl-carnosol Protects SH-SY5Y Cells from Hydrogen Peroxide Damage through the Nrf2/HO-1 Pathway.

Background: Oxidative stress-induced neurotoxicity plays a key role in Alzheimer's disease (AD). 11,12-Diacetyl-carnosol (NO.20), an acetylated derivative of carnosol extracted from rosemary, displays a high antioxidative effect in vitro. Purpose: We investigated the neuroprotective effect of NO.20 on H2O2-induced neurotoxicity in human neuroblastoma SH-SY5Y cells and its possible mechanism. Results: We found that NO.20 pretreatment (1 µM for 1 h) had cytoprotective effects and weakened H2O2-induced damage in SH-SY5Y cells by reducing viability loss, apoptotic rate, and reactive oxygen species production. In addition, NO.20 inhibited H2O2-induced mitochondrial dysfunctions: it alleviated mitochondrial membrane potential loss and cytochrome c release, decreased the Bax/Bcl-2 ratio, and reduced caspase-3 expression. NO.20 also downregulated malondialdehyde and upregulated glutathione. Furthermore, NO.20 pretreatment caused the nuclear translocation of the transcription factor NF-E2-related factor 2 (Nrf2), increasing heme oxygenase-1 (HO-1) expression in SH-SY5Y cells. Notably, we found that silencing Nrf2 using small interfering RNA (siRNA) suppressed the NO.20-induced HO-1 expression and abolished the neuroprotective effect of NO.20. Conclusion: These results demonstrate that NO.20 protects SH-SY5Y cells from H2O2-induced neurotoxicity by activating the Nrf2/HO-1 pathway. Thus, the neuroprotective and antioxidative stress effects of NO.20 may make it a promising neuroprotective compound for AD treatment.

The influence of sports on proactive personality and academic achievement of college students: The role of self-efficacy.

Objective: To explore the mediating effect of self-efficacy on the relationship between the proactive personality and academic performance of college students in different sports groups. Methods: A questionnaire survey is used to study 552 college students. The research tools include the proactive personality scale, the self-efficacy scale table (general, academic, and self-regulation efficacy scale tables), and the academic performance self-report scale table. This research employs SPSS 11.0 statistical software to carry out correlation analysis, regression analysis, and t-tests on the data collected, while the test of mediating effect is carried out by AMOS 22.0. Results: (1) The degree of self-efficacy and academic performance of college students participating in physical activities is significantly greater than that of the non-sports group; (2) the proactive personality level of the sports group is significantly higher than the non-sports group in the dimension of "conscientiousness"; (3) a confirmatory factor analysis of the mediating effect hypothesis model, using the structural equation model, found that self-efficacy plays a full mediating role in the relationship between proactive personality and academic performance; the direct effect of self-efficacy on the proactive personality and academic performance of college students in different sports groups is not significant. Conclusion: College students involved in sports exercise have higher scores on some items about proactive personality than non-sports groups; girls' self-efficacy level is higher than that of boys; self-efficacy plays a full mediating role in the relationship between proactive personality and academic performance; self-efficacy had no significant effect on proactive personality and gender in different sports groups.