20 research outputs found

    Regulator of G Protein Signaling Protein 12 (Rgs12) Controls Mouse Osteoblast Differentiation via Calcium Channel/Oscillation and Gαi-ERK Signaling

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    Bone homeostasis intimately relies on the balance between osteoblasts (OBs) and osteoclasts (OCs). Our previous studies have revealed that regulator of G protein signaling protein 12 (Rgs12), the largest protein in the Rgs super family, is essential for osteoclastogenesis from hematopoietic cells and OC precursors. However, how Rgs12 regulates OB differentiation and function is still unknown. To understand that, we generated an OB-targeted Rgs12 conditional knockout (CKO) mice model by crossing Rgs12 fl/fl mice with Osterix (Osx)-Cre transgenic mice. We found that Rgs12 was highly expressed in both OB precursor cells (OPCs) and OBs of wild-type (WT) mice, and gradually increased during OB differentiation, whereas Rgs12-CKO mice (Osx Cre/+ ; Rgs12 fl/fl ) exhibited a dramatic decrease in both trabecular and cortical bone mass, with reduced numbers of OBs and increased apoptotic cell population. Loss of Rgs12 in OPCs in vitro significantly inhibited OB differentiation and the expression of OB marker genes, resulting in suppression of OB maturation and mineralization. Further mechanism study showed that deletion of Rgs12 in OPCs significantly inhibited guanosine triphosphatase (GTPase) activity and cyclic adenosine monophosphate (cAMP) level, and impaired Calcium (Ca 2+ ) oscillations via restraints of major Ca 2+ entry sources (extracellular Ca 2+ influx and intracellular Ca 2+ release from endoplasmic reticulum), partially contributed by the blockage of L-type Ca 2+ channel mediated Ca 2+ influx. Downstream mediator extracellular signal-related protein kinase (ERK) was found inactive in OBs of Osx Cre/+ ; Rgs12 fl/fl mice and in OPCs after Rgs12 deletion, whereas application of pertussis toxin (PTX) or overexpression of Rgs12 could rescue the defective OB differentiation via restoration of ERK phosphorylation. Our findings reveal that Rgs12 is an important regulator during osteogenesis and highlight Rgs12 as a potential therapeutic target for bone disorders. © 2018 American Society for Bone and Mineral Research. © 2018 American Society for Bone and Mineral Researc

    Actively implementing an evidence-based feeding guideline for critically ill patients (NEED): a multicenter, cluster-randomized, controlled trial

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    Background: Previous cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes. Methods: We conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment. Results: Forty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference − 0.40 [95% CI − 0.71 to − 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference − 1.6% [95% CI − 4.3% to 1.2%]; P = 0.42) between groups. Conclusions: In this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness. Trial registration: ISRCTN, ISRCTN12233792. Registered November 20th, 2017

    Actively implementing an evidence-based feeding guideline for critically ill patients (NEED): a multicenter, cluster-randomized, controlled trial.

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    BackgroundPrevious cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes.MethodsWe conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment.ResultsForty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference - 0.40 [95% CI - 0.71 to - 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference - 1.6% [95% CI - 4.3% to 1.2%]; P = 0.42) between groups.ConclusionsIn this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness.Trial registrationISRCTN, ISRCTN12233792 . Registered November 20th, 2017

    Actively implementing an evidence-based feeding guideline for critically ill patients (NEED): a multicenter, cluster-randomized, controlled trial (vol 26, 46, 2022)

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    BackgroundPrevious cluster-randomized controlled trials evaluating the impact of implementing evidence-based guidelines for nutrition therapy in critical illness do not consistently demonstrate patient benefits. A large-scale, sufficiently powered study is therefore warranted to ascertain the effects of guideline implementation on patient-centered outcomes.MethodsWe conducted a multicenter, cluster-randomized, parallel-controlled trial in intensive care units (ICUs) across China. We developed an evidence-based feeding guideline. ICUs randomly allocated to the guideline group formed a local "intervention team", which actively implemented the guideline using standardized educational materials, a graphical feeding protocol, and live online education outreach meetings conducted by members of the study management committee. ICUs assigned to the control group remained unaware of the guideline content. All ICUs enrolled patients who were expected to stay in the ICU longer than seven days. The primary outcome was all-cause mortality within 28 days of enrollment.ResultsForty-eight ICUs were randomized to the guideline group and 49 to the control group. From March 2018 to July 2019, the guideline ICUs enrolled 1399 patients, and the control ICUs enrolled 1373 patients. Implementation of the guideline resulted in significantly earlier EN initiation (1.20 vs. 1.55 mean days to initiation of EN; difference - 0.40 [95% CI - 0.71 to - 0.09]; P = 0.01) and delayed PN initiation (1.29 vs. 0.80 mean days to start of PN; difference 1.06 [95% CI 0.44 to 1.67]; P = 0.001). There was no significant difference in 28-day mortality (14.2% vs. 15.2%; difference - 1.6% [95% CI - 4.3% to 1.2%]; P = 0.42) between groups.ConclusionsIn this large-scale, multicenter trial, active implementation of an evidence-based feeding guideline reduced the time to commencement of EN and overall PN use but did not translate to a reduction in mortality from critical illness.Trial registrationISRCTN, ISRCTN12233792 . Registered November 20th, 2017

    Investigating influence factors of traffic violations at signalized intersections using data gathered from traffic enforcement camera.

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    To effectively reduce traffic violations that often cause severe crashes at signalized intersections, exploring their contributing factors seems hugely urgent and essential. This study attempted to investigate the influence factors of wrong-way driving (WWD), red-light-running (RLR), violating traffic markings (VTM), and driving in the inaccurate oriented lane (DIOL) at signalized intersections by using data collected from traffic enforcement camera in Hohhot, China. To this end, an ordinary multinomial logit model was developed. By considering the unobserved heterogeneity between observations, a random effects multinomial logit model was proposed as well. After that, the marginal effects of explanatory variables were computed. The outcomes showed that non-local vehicles were more likely to commit WWD and VTM than local vehicles. WWD and RLR frequently occurred in the daytime and evening (6:00-23:59), and on most days within a week. RLR and DIOL mainly happened in June and July. The left-turn lane ratio significantly increased RLR and DIOL. The cloudy, partly cloudy, and rainy days obviously increased WWD and VTM. The temperature from 21 to 30 degrees centigrade was apparently associated with the higher likelihoods of RLR and DIOL. According to the findings of this study, some intervention measures, targeting different vehicle types and considering temporal factors, road, and weather conditions, were recommended to reduce WWD, RLR, VTM, and DIOL at signalized intersections

    Investigating crash injury severity at unsignalized intersections in Heilongjiang Province, China

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    Many studies suggest that more crashes occur due to mixed traffic flow at unsignalized intersections. However, very little is known about the injury severity of these crashes. The objective of this study is therefore to investigate how contributory factors affect crash injury severity at unsignalized intersections. The dataset used for this analysis derived from police crash reports from Dec. 2006 to Apr. 2009 in Heilongjiang Province, China. An ordered probit model was developed to predict the probability that the injury severity of a crash will be one of four levels : no injury, slight injury, severe injury, and fatal injury. The injury severity of a crash was evaluated in terms of the most severe injury sustained by any person involved in the crash. Results from the present study showed that different factors had varying effects on crash injury severity. Factors found to resuit in the increased probability of serious injuries include adverse weather, sideswiping with pedestrians on poor surface, the interaction of rear-ends and the third-class highway, winter night without illumination, and the interaction between traffic signs or markings and the third-class highway. Although there are some limitations in the current study, this study provides more insights into crash injury severity at unsignalized intersections

    Optimizing the Deployment of Automated Speed Camera at the Intersections Using GPS Trajectories

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    The economical and rational deployment of automated speed camera is a critical issue for traffic police department to implement speed management efficiently. Based on taxi GPS trajectories collected from Chengdu, 2016, this study optimizes the deployment interval and number of ASCs at the intersections by using K-means clustering and kernel density estimation according to the critical mixed distance halo effect and the delta speed distribution, respectively. Results illustrate that speeding is more likely to happen within the speed limit of 40\ua0km/h rather than 60\ua0km/h. From the whole perspective, with the growing deployment number of ASCs, the upstream distance halo effects gradually increase, while the downstream distance halo effects gradually decrease within the range of about 4500\ua0m. Given that the interaction between two adjacent ASCs, the critical mixed distance halo effect of ASCs is about 215\ua0m and 529\ua0m corresponding to the smaller and larger values of critical delta speed in the northeast direction respectively, and about 315\ua0m and 585\ua0m in the southwest direction. Generally, one ASC should be deployed every 500\ua0m and 600\ua0m within the speed limit of 60\ua0km/h, and every 200\ua0m and 300\ua0m within the speed limit of 40\ua0km/h in the northeast and southwest directions, respectively

    Modeling duration of overtaking between non-motorized vehicles: A nonparametric survival analysis based approach.

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    The use of non-motorized vehicles in urban city has improved the convenience of short-distance travel and reduced traffic pollution. However, the overtaking behaviour of non-motorized vehicles impacts traffic safety and efficiency significantly. The objective of this study is to model the durations of overtaking behaviour in the non-motorized vehicle exclusive lane. A total of 3010 overtaking events of non-motorized vehicles were extracted from two locations in Chengdu, China. The nonparametric survival analysis was conducted to model the overtaking duration of non-motorized vehicles. The categorical variables that significantly influence the overtaking duration were examined by the Log-rank test. The results show that the overtaking durations of female riders is longer than that of male riders. It takes longer for electrical bikes to complete overtaking than conventional bikes. When the non-motorized vehicle is under the load state (i.e. passengers or goods on the non-motorized vehicle), the overtaking behaviour takes more time than the un-load state. Moreover, it takes less time to overtake the non-motorized vehicle with load than to overtake the one without load. When there is a wrong-way driving phenomenon or under higher traffic volume, the duration is longer compared to the normal traffic and lower traffic volume conditions. The findings of this study attempt to provide a more profound understanding of non-motorized vehicles overtaking behaviour under different traffic conditions and give insights to the safety research of non-motorized vehicles

    Exploring Driver Injury Severity at Intersection: An Ordered Probit Analysis

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    It is well known that intersections are the most hazardous locations; however, only little is known about driver injury severity in intersection crashes. Hence, the main goal of this study was to further examine the different factors contributing to driver injury severity involved in fatal crashes at intersections. Data used for the present analysis was from the US DOT-Fatality Analysis Reporting System (FARS) crash database from the year 2011. An ordered probit model was employed to fit the fatal crash data and analyze the factors impacting each injury severity level. The analysis results displayed that driver injury severity is significantly affected by many factors. They include driver age and gender, driver ethnicity, vehicle type and age (years of use), crash type, driving drunk, speeding, violating stop sign, cognitively distracted driving, and seat belt usage. These findings from the current study are beneficial to form a solid basis for adopting corresponding measures to effectively drop injury severity suffering from intersection crash. More insights into the effects of risk factors on driver injury severity could be acquired using more advanced statistical models
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