Nitrogen and sulfur co-doped porous carbon derived from polypyrrole-polythiophene for efficient peroxydisulfate activation towards degradation of aniline.

To enhance the catalytic activity of carbon materials and streamline their synthesis process, it is necessary to optimize the doping of heteroatoms and reduce the dependence on organic solvents. This can be achieved by utilizing carbonized Polypyrrole-Polythiophene (C(Ppy-Pth)), which is obtained through simultaneous and in-situ co-doping of N and S. This material can serve as an effective activator of peroxydisulfate (PDS) for the degradation of aniline (AN). The results showed that Ppy-Pth could be efficiently synthesized by using cetyltrimethyl ammonium bromide, pyrrole, thiophene, FeCl3, and H2O2 in water. Based on the price, self-decomposition and oxidation efficiency, the performance of PDS activated by C(Ppy-Pth) was superior to that of peroxymonosulfate (PMS) in degrading AN. The optimum conditions for catalyzing PDS and degrading 30 mg/L AN by C(Ppy-Pth) were 0.10 g/L C(Ppy-Pth)-1000-1/1, 2.10 mM PDS, and pH0 = 3.00, which resulted in 86.69% AN removal in 30 min. Carbonation temperature, N/S ratio and pyridine N content are the key factors affecting the catalytic activity of C(Ppy-Pth). Quenching, probe, and electrochemical experiment revealed that in the catalytic PDS system with C(Ppy-Pth)-1000-1/1 (pH0 = 3.00), the oxidation of AN mainly occurred through the generation of hydroxyl radical (·OH), superoxide anion (O2·-), and electron transfer on the C(Ppy-Pth)-1000-1/1 surface. The steady-state concentration of ·OH and O2·- were 2.65 × 10-14 M and 1.97 × 10-13 M, respectively, and the contribution rate of ·OH oxidation was 31.28%. The oxidation of AN by sulfate radical (SO4·-) and singlet oxygen (1O2) could be neglected. This study provides a promising strategy for the construction of PDS catalyst and wastewater treatment.

Impacts of delta 9-tetrahydrocannabinol against myocardial ischemia/reperfusion injury in diabetic rats: Role of PTEN/PI3K/Akt signaling pathway.

Despite the current optimal therapy, patients with myocardial ischemia/reperfusion (IR) injury still experience a high mortality rate, especially when diabetes mellitus is present as a comorbidity. Investigating potential treatments aimed at improving the outcomes of myocardial IR injury in diabetic patients is necessary. Our objective was to ascertain the cardioprotective effect of delta 9-tetrahydrocannabinol (THC) against myocardial IR injury in diabetic rats and examine the role of phosphatase and tensin homolog (PTEN)/phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt) signaling pathway in mediating this effect. Diabetes was induced in male Wistar rats (8-10 weeks old, 200-250 g; n = 60) by a single injection of streptozotocin. The duration of the diabetic period was 10 weeks. During the last 4 weeks of diabetic period, rats were treated with THC (1.5 mg/kg/day; intraperitoneally), either alone or in combination with LY294002, and then underwent IR intervention. After 24 h of reperfusion, infarct size, cardiac function, lactate dehydrogenase (LDH) and cardiac-specific isoform of troponin-I (cTn-I) levels, myocardial apoptosis, oxidative stress markers, and expression of PTEN, PI3K, and Akt proteins were evaluated. THC pretreatment resulted in significant improvements in infarct size and cardiac function and decreases in LDH and cTn-I levels (P < 0.05). It also reduced myocardial apoptosis and oxidative stress, accompanied by the downregulation of PTEN expression and activation of the PI3K/Akt signaling pathway (P < 0.05). LY294002 pretreatment abolished the cardioprotective action of THC. This study revealed the cardioprotective effects of THC against IR-induced myocardial injury in diabetic rats and also suggested that the mechanism may be associated with enhanced activity of the PI3K/Akt signaling pathway through the reduction of PTEN phosphorylation.

Mediating role of depression between workplace violence and job burnout among healthcare workers. / å·¥ä½œåœºæ‰€æš´åŠ›å¯¹åŒ»åŠ¡å·¥ä½œè€ èŒä¸šå€¦æ€ çš„å½±å“ï¼šæŠ‘éƒçš„ä¸­ä»‹ä½œç”¨.

OBJECTIVES: Health workers are at risk of workplace violence, which can seriously affects their mental health and work status. This study aims to explore the mediating role of depression between workplace violence and job burnout among healthcare workers. METHODS: From January 10 to February 5, 2019, a questionnaire was distributed to frontline healthcare workers through the wenjuanxing platform using convenient sampling (snowball sampling). The questionnaire included the Chinese version of the Workplace Violence Scale, Maslach Burnout Inventory, and Patient Health Questionnaires (PHQ-2). Descriptive statistics, correlation analysis, and mediation model tests were conducted on the cross-sectional data collection. RESULTS: The study included 3 684 participants, with (31.63±7.69) years old. Among them 2 079(56.43%) were experienced workplace violence, 687(18.65%) were screened positive for depression, and 2 247(60.99%) were experienced high levels of occupational burnout. Correlation analysis showed positive association between workplace violence and depression, workplace violence and occupational burnout, depression and occupational burnout (r=0.135, r=0.107, r=0.335, respectively, all P<0.001). After controlling for covariates, workplace violence had an indirect effect on occupational burnout through depression, with a standardized coefficient of 0.25 (SE=0.02, 95% CI 0.21 to 0.28), accounting for 13.87% of the total effect. CONCLUSIONS: The study highlights the close relationship between workplace violence, depression, and occupational burnout among healthcare workers, with depression acting as a mediator between workplace violence and occupational burnout. This study suggests that it is necessary to improve the communication skills of healthcare workers, increase the installation of security systems and emergency plans, use new media platforms to convey positive energy between doctors and patients, and open channels for medical consultation and complaints. It is also necessary to provide guidance for healthcare workers' depressive emotions. Addressing depression among health care workers will help reduce the harm caused by workplace violence, protect the physical and mental health of healthcare workers, and reduce work burnout.

Modeling and simulation of microblog-based public health emergency-associated public opinion communication.

With the advent of the era of "we media," many people's opinions have become easily accessible. Public health emergencies have always been an important aspect of public opinion exchange and emotional communication. In view of this sudden group panic, public opinion cannot be effectively monitored, controlled or guided. This makes it easy to amplify the beliefs and irrationality of social emotions, that threaten social security and stability. Considering the important role of opinion leaders in micro-blogs and users' interest in micro-blog information, a SIR model of public opinion propagation is constructed based on the novel coronavirus pneumonia model and micro-blog's public health emergencies information. The parameters of the model are calculated by combining the actual crawl data from the novel coronavirus pneumonia epidemic period, and the trends in the evolution of public opinion are simulated by MATLAB. The simulation results are consistent with the actual development of public opinion dissemination, which shows the effectiveness of the model. These research findings can help the government understand the principles that guide the propagation of public opinion and advise an appropriate time to control and correctly guide public opinion.

Jiedutongluotiaogan formula restores pancreatic function by suppressing excessive autophagy and endoplasmic reticulum stress.

CONTEXT: Jiedutongluotiaogan formula (JTTF), a traditional Chinese medicine (TCM), could promote islet function. However, the potential effect of JTTF on endoplasmic reticulum stress (ERS) and autophagy have not been reported. OBJECTIVE: This study explores the potential effect of JTTF on ERS and autophagy in the pancreas. MATERIALS AND METHODS: The Zucker diabetic fatty (ZDF) rats were randomised into five groups, control, model, JTTF (1, 3, 5 g/kg/day for 12 weeks). LPS induced pancreatic ß-cells were treated with JTTF (50, 100, 200 µg/mL). LPS was used to induce pancreatic ß-cell injury, with cell viability and insulin secretion evaluated using MTT, glucose-stimulated insulin secretion (GSIS) assays, and PCR. Intracellular Ca2+ concentration was measured using flow cytometry, while ERS and autophagy levels were monitored via Western blotting and/or immunostaining. RESULTS: Compared with the model group, body weight, FGB, HbA1c, IPGTT, FINs, and HOMA-IR in JTTF treatment groups were significantly reduced. In islets cells treated with JTTF, the pancreatic islet cells in the JTTF group were increased, lipid droplets were reduced, and there was a decrease in Ca2+ (16.67%). After JTTF intervention, PERK, p-PERK, IRE1α, p- IRE1α, ATF6, eIF2α, GRP78, p-ULK1, LC3 and p62 expression decreased, whereas Beclin1and p-mTOR expression increased. In addition, the expression of proteins related to apoptosis in the JTTF groups were lower than those in the control group. DISCUSSION AND CONCLUSIONS: JTTF may alleviate pancreatic ß-cell injury by inhibiting ER stress and excessive autophagy in diabetic rats. This provides a new direction for treating diabetes and restoring pancreatic dysfunction by TCM.

Theophylline Acetaldehyde as the Initial Product in Doxophylline Metabolism in Human Liver.

Doxophylline (DOXO) and theophylline are widely used as bronchodilators for treating asthma and chronic obstructive pulmonary disease, and DOXO has a better safety profile than theophylline. How DOXO's metabolism and disposition affect its antiasthmatic efficacy and safety remains to be explored. In this study, the metabolites of DOXO were characterized. A total of nine metabolites of DOXO were identified in vitro using liver microsomes from human and four other animal species. Among them, six metabolites were reported for the first time. The top three metabolites were theophylline acetaldehyde (M1), theophylline-7-acetic acid (M2), and etophylline (M4). A comparative analysis of DOXO metabolism in human using liver microsomes, S9 fraction, and plasma samples demonstrated the following: 1) The metabolism of DOXO began with a cytochrome P450 (P450)-mediated, rate-limiting step at the C ring and produced M1, the most abundant metabolite in human liver microsomes. However, in human plasma, the M1 production was rather low. 2) M1 was further converted to M2 and M4, the end products of DOXO metabolism in vivo, by non-P450 dismutase in the cytosol. This dismutation process also relied on the ratio of NADP+/NADPH in the cell. These findings for the first time elucidated the metabolic sites and routes of DOXO metabolism in human. SIGNIFICANCE STATEMENT: We systematically characterized doxophylline metabolism using in vitro and in vivo assays. Our findings evolved the understandings of metabolic sites and pathways for methylxanthine derivatives with the aldehyde functional group.

Reversible and Irreversible Inhibition of Cytochrome P450 Enzymes by Methylophiopogonanone A.

Methylophiopogonanone A (MOA), an abundant homoisoflavonoid bearing a methylenedioxyphenyl moiety, is one of the major constituents in the Chinese herb Ophiopogon japonicas This work aims to assess the inhibitory potentials of MOA against cytochrome P450 enzymes and to decipher the molecular mechanisms for P450 inhibition by MOA. The results showed that MOA concentration-dependently inhibited CYP1A, 2C8, 2C9, 2C19, and 3A in human liver microsomes (HLMs) in a reversible way, with IC50 values varying from 1.06 to 3.43 µM. By contrast, MOA time-, concentration-, and NADPH-dependently inhibited CYP2D6 and CYP2E1, along with KI and kinact values of 207 µM and 0.07 minute-1 for CYP2D6, as well as 20.9 µM and 0.03 minutes-1 for CYP2E1. Further investigations demonstrated that a quinone metabolite of MOA could be trapped by glutathione in an HLM incubation system, and CYP2D6, 1A2, and 2E1 were the major contributors to catalyze the metabolic activation of MOA to the corresponding O-quinone intermediate. Additionally, the potential risks of herb-drug interactions triggered by MOA or MOA-related products were also predicted. Collectively, our findings verify that MOA is a reversible inhibitor of CYP1A, 2C8, 2C9, 2C19, and 3A but acts as an inactivator of CYP2D6 and CYP2E1. SIGNIFICANCE STATEMENT: Methylophiopogonanone A (MOA), an abundant homoisoflavonoid isolated from the Chinese herb Ophiopogon japonicas, is a reversible inhibitor of CYP1A, 2C8, 2C9, 2C19, and 3A but acts as an inactivator of CYP2D6 and CYP2E1. Further investigations demonstrated that a quinone metabolite of MOA could be trapped by glutathione in a human liver microsome incubation system, and CYP2D6, 1A2, and 2E1 were the major contributors to catalyze the metabolic activation of MOA to the corresponding O-quinone intermediate.

Catalytic esterification performance of protease in micro-aqueous system.

OBJECTIVE: To evaluate the catalytic esterification performance of proteases in micro-aqueous systems and to study the suitable conditions for maintaining protease activity. RESULTS: It was found that the protease showed better enzyme catalytic activity in the micro-aqueous phase containing 4% boric acid-borax buffer than that of the pure organic phase. The protease activity was easily activated by 0.20 M boric acid-borax buffer, and the enzyme activity was still high for a long time in alkaline environment (pH 8.40-9.60) and under the temperature of 40-55 °C. Experiments using protease and Candida lipase to synthesize sucrose-6-ethyl ester showed that protease had better esterification activity than Candida lipase in the micro-aqueous phase.

Effect of selective serotonin reuptake inhibitor on prefrontal-striatal connectivity is dependent on the level of TNF-α in patients with major depressive disorder.

BACKGROUND: We hypothesize that the tumor necrosis factor-α (TNF-α) may play a role in disturbing the effect of selective serotonin reuptake inhibitor (SSRI) on the striatal connectivity in patients with major depressive disorder (MDD). METHODS: We performed a longitudinal observation by combining resting-state functional magnetic resonance imaging (rs-fMRI) and biochemical analyses to identify the abnormal striatal connectivity in MDD patients, and to evaluate the effect of TNF-α level on these abnormal connectivities during SSRI treatment. Eighty-five rs-fMRI scans were collected from 25 MDD patients and 35 healthy controls, and the scans were repeated for all the patients before and after a 6-week SSRI treatment. Whole-brain voxel-wise functional connectivity (FC) was calculated by correlating the rs-fMRI time courses between each voxel and the striatal seeds (i.e. spherical regions placed at the striatums). The level of TNF-α in serum was evaluated by Milliplex assay. Factorial analysis was performed to assess the interaction effects of 'TNF-α × treatment' in the regions with between-group FC difference. RESULTS: Compared with controls, MDD patients showed significantly higher striatal FC in the medial prefrontal cortex (MPFC) and bilateral middle/superior temporal cortices before SSRI treatment (p < 0.001, uncorrected). Moreover, a significant interaction effect of 'TNF-α × treatment' was found in MPFC-striatum FC in MDD patients (p = 0.002), and the significance remained after adjusted for age, gender, head motion, and episode of disease. CONCLUSION: These findings provide evidence that treatment-related brain connectivity change is dependent on the TNF-α level in MDD patients, and the MPFC-striatum connectivities possibly serve as an important target in the brain.

Effects of Different Alcohol Dosages on Steering Behavior in Curve Driving.

OBJECTIVE: The aim of this article is to explore the detailed characteristics of steering behavior in curve driving at different alcohol dosages. BACKGROUND: Improper operation of the steering wheel is a contributing factor to increased crash risks on curves. METHOD: The experiments were conducted using a driving simulator. Twenty-five licensed drivers were recruited to perform the experiments at the four different breath alcohol concentration (BrAC) levels. The steering angle (SA), steering speed (SS), steering reversal rate (SRR), and peak-to-peak value of the steering angle (PP) were used to characterize the steering behavior. The vehicle's speed and the number of lane exceedances per kilometer were also used to examine the driving performance. RESULTS: The SSs on the 200 m (χ2(3) = 20.67, p < .001), 500 m (χ2(3) = 22.42, p < .001), and 800 m (χ2(3) = 22.86, p < .001) radius curves were significantly faster for drivers under the influence of alcohol compared with those given a placebo. There were significant effects of alcohol on the SRR and PP on the 200 m, 500 m, and 800 m radius curves. CONCLUSION: For all of the curves, the SS, SRR, and PP had a tendency to increase as the BrAC increased. The large PP at a high BrAC, accompanied by the high speed, SS, and SRR, resulted in a high probability of lane exceedance. The use of measures of SS, SRR, and PP aided in the improvement of the accuracy of the intoxication detection for the different types of curves. APPLICATION: The most important application is to provide guidance for detecting alcohol-impaired-driving.

[Inhibitory effect of flavonoids from Scutellariae Radix on human cytochrome P450 1A].

This study investigated the inhibitory effect of eight natural flavonoids in Chinese herb Scutellariae Radix on huamn cytochrome P450 1 A(CYP1 A), a key cancer chemo-preventive target. In this study, phenacetin was used as a probe substrate for CYP1 A, while human liver microsomes and recombinant human CYP1 A enzymes were used as enzyme sources. Liquid chromatography-tandem mass spectrometry was used to monitor the formation rates of acetaminophen, the O-deethylated metabolite of phenacetin. The dose-dependent inhibition curves were depicted based on the changes of the formation rates of acetaminophen, while the IC_(50) were determined. Inhibition kinetic analyses and docking simulations were used to investigate the inhibition modes and mechanism of wogonin(the most potent CYP1 A inhibitor in this herb), while the inhibition constants(K_i) of wogonin against both CYP1 A1 and CYP1 A2 were determined. Among all tested flavonoids, wogonin, 7-methoxyflavanone and oroxylin A displayed a strong inhibitory effect on CYP1 A(IC_(50)<1 µmol·L~(-1)), baicalein exhibited a moderate inhibitory effect on CYP1 A(IC_(50) between 1-10 µmol·L~(-1)), and baicalin, scutellarein and wogonoside displayed a very weak inhibitory effect on CYP1 A(IC_(50) between 10-25 µmol·L~(-1)), but scutellarin displayed a negligible inhibitory effect on CYP1 A(IC_(50)>100 µmol·L~(-1)). Further investigations demonstrated that wogonin had a weak inhibitory effect on other human CYP enzymes, suggesting that it could be used as a lead compound for the development of specific inhibitors of CYP1 A. Furthermore, the inhibition kinetic analyses clearly demonstrated that wogonin could strongly inhibit phenacetin O-deethylation in both CYP1 A1 and CYP1 A2 in a competitive manner, with K_i values at 0.118 and 0.262 µmol·L~(-1), respectively. Molecular docking demonstrated that wogonin could strongly interact with CYP1 A1 and CYP1 A2 via hydrophobic and π-π interactions, as well as Ser120 and Ser116 in CYP1 A1 via hydrogen-bonding. In conclusion, this study found that some flavonoids in Scutellariae Radix displayed a strong inhibitory effect on CYP1 A, while wogonin is the most potent CYP1 A inhibitor with a relatively high selectivity towards CYP1 A over other human CYPs.

Caveolin-1 is essential for protecting against binge drinking-induced liver damage through inhibiting reactive nitrogen species.

UNLABELLED: Caveolin-1 (Cav-1) is known to participate in many diseases, but its roles in alcoholic liver injury remain unknown. In the present study, we aimed to explore the roles of Cav-1 in protecting hepatocytes from ethanol-mediated nitrosative injury. We hypothesized that Cav-1 could attenuate ethanol-mediated nitrosative stress and liver damage through regulating epidermal growth factor receptor/signal transducer and activator of transcription 3/inducible nitric oxide synthase (EGFR/STAT3/iNOS)-signaling cascades. Ethanol-fed mice had time- and dose-dependent increases of Cav-1 in serum and liver with peak increase at 12 hours. Compared to wild-type mice, Cav-1 deficiency mice revealed higher expression of iNOS, higher levels of nitrate/nitrite and peroxynitrite, and had more serious liver damage, accompanied with higher levels of cleaved caspase-3 and apoptotic cell death in liver, and higher levels of alanine aminotransferase and aspartate aminotransferase in serum. Furthermore, the results revealed that the ethanol-mediated Cav-1 increase was in an extracellular signal-regulated kinase-dependent manner, and Cav-1 protected hepatocytes from ethanol-mediated apoptosis by inhibiting iNOS activity and regulating EGFR- and STAT3-signaling cascades. In agreement with these findings, clinical trials in human subjects revealed that serum Cav-1 level was time dependently elevated and peak concentration was observed 12 hours after binge drinking. Alcohol-induced liver lesions were negatively correlated with Cav-1 level, but positively correlated with nitrate/nitrite level, in serum of binge drinkers. CONCLUSIONS: Cav-1 could be a cellular defense protein against alcoholic hepatic injury through inhibiting reactive nitrogen species and regulating EGFR/STAT3/iNOS-signaling cascades.

[Distribution laws of Chinese medical syndrome types and analyses of risk factors in senile hypertension patients: a clinical study].

OBJECTIVE: To explore the distribution laws of TCM syndrome types and to analyze the distribution of dynamic blood pressure curve, atherosclerosis, and age in senile hypertension patients. METHODS: Totally 1 131 senile hypertension patients were recruited from 7 provinces and municipal cities. Features of TCM syndromes, classification and distribution curves, and syndrome distribution laws were observed. The distribution curves of dynamic blood pressure, carotid atherosclerosis, and age were compared in each TCM syndrome types. RESULTS: There were four main syndrome types in 736 cases (56.15%), i.e., excessive accumulation of phlegm-dampness syndrome (210 cases, 16.02%), yin deficiency and hyperactivity of yang syndrome (177 cases, 13.50%), Gan-Shen yin deficiency syndrome (79 cases, 6.03%), and deficiency of qi and yin syndrome (252 cases, 19.22%). Besides, there were two more sub-types, i.e., collateral obstruction by blood stasis syndrome and collateral obstruction by phlegm and stasis. Circadian blood pressure monitor was completed in 211 cases. Of them, abnormal circadian blood pressure occurred in 152 cases (accounting for 72. 38%); yin deficiency and hyperactivity of yang syndrome, excessive accumulation of phlegm-dampness syndrome, deficiency of qi and yin syndrome plus collateral obstruction by blood stasis syndrome were most often seen. Color ultrasound of carotid artery was performed in 660 patients of main syndromes. The incidence was quite higher in those of excessive accumulation of phlegm-dampness syndrome (182 cases, 27. 58%), deficiency of qi and yin syndrome plus collateral obstruction by blood stasis syndrome or collateral obstruction by phlegm and stasis (322 cases, 48.79%). Yin deficiency and hyperactivity of yang syndrome was dominant in patients 60 -79 years old, while deficiency of qi and yin syndrome and Gan-Shen yin deficiency syndrome were dominant in patients older than 80 years. CONCLUSIONS: Excessive accumulation of phlegm-dampness syndrome, yin deficiency and hyperactivity of yang syndrome, Gan-Shen yin deficiency syndrome, and deficiency of qi and yin syndrome were main syndrome types in senile hypertension patients. There was statistical difference in the distribution curves of blood pressure, atherosclerosis, and age of various TCM syndrome types.

Optimizing crash risk models for freeway segments: A focus on the heterogeneous effects of road geometric design features, traffic operation status, and crash units.

Traffic crash risk prediction models have been developed to investigate crash occurrence mechanisms and analyze the effects of various traffic operation factors, data on which are collected by densely deployed detectors, on crash risk. However, in China, freeway detectors are widely spaced (the spacing is usually more than 2 km) and the road geometries vary frequently, especially in mountainous areas. Moreover, many freeway sections are located in urban areas and serve commuting functions. Due to the different mechanisms of crash occurrence on road segments with different geometric design features and traffic operation status, it is necessary to consider these heterogeneities in crash risk prediction. In addition to considering observable heterogeneous effects, it is equally important to consider the existence of unobserved heterogeneities among crash units. This study focuses on the effects of different types of heterogeneities on crash risk for segments of the Yongtaiwen Freeway in Zhejiang Province, China, using crash, traffic flow, and road geometric design data. Latent class analysis (LCA), latent profile analysis (LPA), and a combination of both methods are respectively used to classify road segments into subgroups based on road geometric design features, the traffic operation status, and a combination of both. The results reveal that the binary logit model considering the heterogeneous effects of the combination of road geometric design features and the traffic operation status achieves the best performance. Furthermore, binary conditional logit models and grouped random parameter logit models are developed to analyze the unobserved heterogeneity among crash units, and the results show that the latter has a better goodness of fit. Finally, a paradigm of the crash risk prediction for freeway segments with widely-spaced traffic detectors and frequently-changing geometric features is provided for traffic safety management departments.

A study on the visual recognition patterns of multi-information guide signs based on eye movement data analysis.

A two-factor experiment was devised to assess the appropriateness of the quantity and arrangement of information on multi-information guide signs at unique, spacious exits on elevated expressway sections. This experiment investigated 77 signs containing varying amounts of road name information and different placements of destination road names. The research entailed an indoor experiment that incorporated eye-tracking technology and involved the analysis of a total of twenty-eight indicators. A comprehensive index system was developed, identifying three key aspects: visual recognition efficiency, visual recognition difficulty, and visual fatigue. Utilizing repeated measure analysis of variances, the impact of these two factors was examined to identify significant indicators and establish a comprehensive assessment indicator system. The Technique for Order of Preference by Similarity to Ideal Solution method, in conjunction with the coefficient of entropy weight, was employed to assess the effectiveness of these two factors. The findings demonstrated that the 28 eye-movement indicators utilized in this study effectively constitute a valuable indicator system for evaluating drivers' visual recognition characteristics. These indicators capture the subtle psychophysical traits inherent in the process of recognizing signs, including visual recognition efficiency, difficulty, and fatigue. Regarding the first experimental factor, the number of sign road names significantly influences drivers' visual recognition characteristics (Sig < 0.05). Specifically, an increase in the number of sign road names leads to diminished visual recognition efficiency and heightened visual recognition difficulty and fatigue. Consequently, it is advisable to restrict the number of sign road names to a maximum of six per sign under typical circumstances, with nine being the limit under special conditions. As for the second experimental factor, the placement of the destination road name within the sign layout exerts a significant impact on visual recognition characteristics (Sig < 0.05). Each type of multi-information sign exhibits a distinct visual recognition pattern. Generally, the upper portion of the sign is more easily recognized, while the lower part poses greater recognition challenges. Therefore, to mitigate visual recognition risks, it is recommended that road information placement be prioritized based on actual usage conditions.

Exploring the associations of demographics and scale measures with cognitive driving behavior among older drivers in China.

Age-related changes and frailty are reasons for the high proportion of older drivers in certain types of crashes, such as giving right of way at intersections and turning left. The identified crash causes include the driver's demographics, driving style, cognitive function, and mental workload. This study aimed to explore the associations of demographics and scale measures with cognitive driving behavior. Thirty-nine drivers, consisting of twenty younger drivers (18-60 years old) and nineteen older drivers (above 60 years old), participated in driving simulation experiments after completing scale tests. The selected scale measures included the demographic questionnaire, Multidimensional Driving Style Inventory (MDSI-C), Mini-Mental State Examination (MMSE), Trail Making Test Part A (TMT-A) and Part B (TMT-B), and the National Aeronautics and Space Administration Task Load Index (NASA-TLX) for obtaining subjective information from drivers. Driving scenarios were developed based on the driving characteristics of older adults to investigate age-related driving ability. The driving behavior parameters included reaction time, lateral stability, and driving speed, corresponding to reaction, perception, and execution. Three stepwise regression models showed that NASA-TLX, the interaction between age and driving experience, and the interaction between age and TMT-A significantly explained 53.3 % of reaction time variance; TMT-A, risk driving style, anxiety driving style, and gender significantly explained 53.5 % of lateral stability variance; TMT-A, NASA-TLX, and MMSE significantly explained 60.6 % of driving speed variance. Subsequently, the impact of four age-related predictor variables on driving behavior was further discussed. It is worth noting that a rich driving experience may compensate for driving performance. However cognitive impairment impairs this compensation. Driving behavior is influenced by a combination of various factors. Age, as a physiological indicator, is not sufficient to be a strong predictive factor for lateral stability and driving speed. The results provide a reference for traffic safety management departments to streamline driving suitability test procedures and propose targeted training methods for older drivers.

Predicting driver's takeover time based on individual characteristics, external environment, and situation awareness.

The driver's takeover time is crucial to ensure a safe takeover transition in conditional automated driving. The study aimed to construct a prediction model of driver's takeover time based on individual characteristics, external environment, and situation awareness variables. A total of 18 takeover events were designed with scenarios, non-driving-related tasks, takeover request time, and traffic flow as variables. High-fidelity driving simulation experiments were carried out, through which the driver's takeover data was obtained. Fifteen basic factors and three dynamic factors were extracted from individual characteristics, external environment, and situation awareness. In this experiment, these 18 factors were selected as input variables, and XGBoost and Shapely were used as prediction methods. A takeover time prediction model (BM + SA model) was then constructed. Moreover, we analyzed the main effect of input variables on takeover time, and the interactive contribution made by the variables. And in this experiment, the 15 basic factors were selected as input variables, and the basic takeover time prediction model (BM model) was constructed. In addition, this study compared the performance of the two models and analyzed the contribution of input variables to takeover time. The results showed that the goodness of fit of the BM + SA model (Adjusted_R2) was 0.7746. The XGBoost model performs better than other models (support vector machine, random forest, CatBoost, and LightBoost models). The relative importance degree of situation awareness variables, individual characteristic variables, and external environment variables to takeover time gradually reduced. Takeover time increased with the scan and gaze durations and decreased with pupil area and self-reported situation awareness scores. There was also an interaction effect between the variables to affect takeover time. Overall, the performance of the BM + SA model was better than that of the BM model. This study can provide support for predicting driver's takeover time and analyzing the mechanism of influence on takeover time. This study can provide support for the development of real-time driver's takeover ability prediction systems and optimization of human-machine interaction design in automated vehicles, as well as for the management department to evaluate and improve the driver's takeover performance in a targeted manner.

A review of truck driver persona construction for safety management.

The trucking industry urgently requires comprehensive methods to evaluate driver safety, given the high incidence of serious traffic accidents involving trucks. The concept of a "truck driver persona" emerges as a crucial tool in enhancing driver safety and enabling precise management of road transportation safety. Currently, the road transport sector is only beginning to adopt the user persona approach, and thus the development of such personas for road transport remains an exploratory endeavor. This paper delves into three key aspects: identifying safety risk characteristic parameters, exploring methods for constructing personas and designing safety management interventions. Initially, bibliometric methods are employed to analyze safety risk factors across five domains: truck drivers, vehicles, roads, the environment, and management. This analysis provides the variables necessary to develop personas for road transportation drivers. Existing methods for constructing user personas are then reviewed, with a particular focus on their application in the context of road transportation. Integrating contemporary ideas in persona creation, we propose a framework for developing safety risk personas specific to road transportation drivers. These personas are intended to inform and guide safety management interventions. Moreover, the four stages of driver post-evaluation are integrated into the persona development process, outlining tailored safety management interventions for each stage: pre-post, pre-transit, in-transit, and on-post. These interventions are designed to be orderly and finely tuned. Lastly, we offer optimization recommendations and suggest future research directions based on safety risk factors, persona construction, and safety management interventions. Overall, this paper presents a safety management-oriented research technology system for constructing safety risk personas for truck drivers. We argue that improving the design of the persona index system, driven by big data, and encompassing the entire driver duty cycle-from pre-post to on-post-will significantly enhance truck driver safety. This represents a vital direction for future development in the field.

Interactive effects analysis of road, traffic, and weather characteristics on shared e-bike speeding risk: A data-driven approach.

As electric bikes (e-bikes) rapidly develop in China, their traffic safety issues are becoming increasingly prominent. Accurately detecting risky riding behaviors and conducting mechanism analysis on the multiple risk factors are crucial in formulating and implementing precise management policies. The emergence of shared e-bikes and the advancements in interpretable machine learning present new opportunities for accurately analyzing the determinants of risky riding behaviors. The primary objective of this study is to examine and analyze the risk factors related to speeding behavior to aid urban management agencies in crafting necessary management policies. This study utilizes a large-scale dataset of shared e-bike trajectory data to establish a framework for detecting speeding behavior. Subsequently, the extreme gradient boosting (XGBoost) model is employed to identify the level of speeding risk by leveraging its excellent identification ability. Moreover, based on measuring the degree of interaction among road, traffic, and weather characteristics, the investigation of the complex interactive effects of these risk factors on high-risk speeding is conducted using bivariate partial dependence plots (PDP) by its superior parsing ability. Feature importance analysis results indicate that the top five ranked variables that significantly affect the identified results of speed risk levels are land use density, rainfall, road level, curbside parking density, and bike lane width. The interaction analysis results indicate that higher levels of road and bike lane width correspond to an increased possibility of high-risk speeding among riders. Land use density, curbside parking density, and rainfall display a nonlinear effect on high-risk speeding. Introducing road level, bike lane width, and time interval could change the patterns of nonlinear effects in land use density, curbside parking density, and rainfall. Finally, several policy recommendations are proposed to improve e-bike traffic safety by utilizing the extracted feature values associated with a higher probability of high-risk speeding.

Inhibition of endoplasmic reticulum stress and excessive autophagy by Jiedu Tongluo Tiaogan Formula via a CaMKKß/AMPK pathway contributes to protect pancreatic ß-cells.

ETHNOPHARMACOLOGICAL RELEVANCE: Jiedu Tongluo Tiaogan Formula (JTTF), a traditional Chinese herbal decoction, exhibits the potential to treat type 2 diabetes mellitus (T2DM) by inhibiting endoplasmic reticulum stress (ERS) and excessive autophagy, which are the risk factors for the abnormal development and progression of ß cells. AIM OF THE STUDY: We aimed to assess the effect of JTTF on pancreatic glucotoxicity by inhibiting ERS and excessive autophagy, for which db/db mice and INS-1 insulinoma cells were used. MATERIALS AND METHODS: The chemical composition of the JTTF was analyzed by UPLC-Q/TOF-MS. Diabetic (db/db) mice were treated with distilled water or JTTF (2.4 and 7.2 g/kg/day) for 8 weeks. Furthermore, INS-1 cells induced by high glucose (HG) levels were treated with or without JTTF (50, 100, and 200 µg/mL) for 48 h to elucidate the protective mechanism of JTTF on glucose toxicity. The experimental methods included an oral glucose tolerance test, hematoxylin-eosin staining, immunohistochemistry, western blotting, RT-qPCR, and acridine orange staining. RESULT: 28 chemical components of JTTF were identified. Additionally, treatment with JTTF significantly decreased the severity of glycemic symptoms in the db/db mice. Moreover, the treatment partially restored glucose homeostasis in the db/db mice and protected the pancreatic ß-cell function. JTTF protected INS-1 cells from HG injury by upregulating GSIS and PDX1, MafA mRNA expression. Further, treatment with JTTF downregulated GRP78 and ATF6 expression, whereas it inhibited Beclin-1 and LC3 activation. The treatment protected the cells from HG-induced ERS and excessive autophagy by downregulating the CaMKKß/AMPK pathway. CONCLUSIONS: The present study findings show that JTTF may protects ß-cells by inhibiting the CaMKKß/AMPK pathway, which deepens our understanding of the effectiveness of JTTF as a treatment strategy against T2DM.