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PDF file - 307K, lntrabursal injection of Adeno-Cre activates conditional alleles in OSE cells and induces histopathological changes of murine OSE post induction

PDF file - 53K, Tumor spectrum in Adeno-Cre injected mice

PDF file - 253K, Gene expression analysis

PDF file - 161K, Analysis of recombination efficiency of targeted alleles in mutant mice

PDF file - 325K, Nuclear p53 expression correlates positively with loss of wild type allele in serous epithelial ovarian carcinomas in p53m/+ mutant mice

PDF file - 267K, Widespread metabolomic alterations consistent with tumor development are found in blood of SEOC mice compared to wild type mice

PDF file - 255K, Immunohistochemical staining for CA125, WT1 and calretinin

PDF file - 192K

With urban expansion and traffic environment improvement, travel chains continue to grow, and the combination of travel purposes and modes becomes more complex. The promotion of mobility as a service (MaaS) has positive effects on facilitating the public transport traffic environment. However, public transport service optimization requires an accurate understanding of the travel environment, selection preferences, demand prediction, and systematic dispatch. Our study focused on the relationship between the trip-chain complexity environment and travel intention, combining the Theory of Planned Behavior (TPB) with travelers’ preferences to construct a bounded rationality theory. First, this study used K-means clustering to transform the characteristics of the travel trip chain into the complexity of the trip chain. Then, based on the partial least squares structural equation model (PLS-SEM) and the generalized ordered Logit model, a mixed-selection model was established. Finally, the travel intention of PLS-SEM was compared with the travel sharing rate of the generalized ordered Logit model to determine the trip-chain complexity effects for different public transport modes. The results showed that (1) the proposed model, which transformed travel-chain characteristics into travel-chain complexity using K-means clustering and adopted a bounded rationality perspective, had the best fit and was the most effective with comparison to the previous prediction approaches. (2) Compared with service quality, trip-chain complexity negatively affected the intention of using public transport in a wider range of indirect paths. Gender, vehicle ownership, and with children/without children had significant moderating effects on certain paths of the SEM. (3) The research results obtained by PLS-SEM indicated that when travelers were more willing to travel by subway, the subway travel sharing rate corresponding to the generalized ordered Logit model was only 21.25–43.49%. Similarly, the sharing rate of travel by bus was only 32–44% as travelers were more willing to travel by bus obtained from PLS-SEM. Therefore, it is necessary to combine the qualitative results of PLS-SEM with the quantitative results of generalized ordered Logit. Moreover, when service quality, preferences, and subjective norms were based on the mean value, with each increase in trip-chain complexity, the subway travel sharing rate was reduced by 3.89–8.30%, while the bus travel sharing rate was reduced by 4.63–6.03%.

The literature has offered much evidence regarding associations between the built environment (BE) and commuting behavior. However, most prior studies are conducted based on cross-sectional samples from developed countries, and little is known about the longitudinal link between BE and commuting behavior. Based on two rounds of survey data from China, this study examines relationships of BE with commuting mode choice from both cross-sectional and longitudinal perspectives. The effects of life-cycle events are considered within a unified framework. Results of the longitudinal examination of BE and commuting mode shift largely support the cross-sectional analysis. Specifically, promoting more balanced land use and improving residential density are important for car use reductions and active travel initiatives. Meanwhile, more balanced land use improves the probability of commuting by motorcycle and electric bike, but reduces the probability of commuting by public transit. This study also highlights the remarkable role played by life-cycle events in affecting commuting mode shifts.

The crucial role that the built environment plays in affecting commuting behavior has been widely examined with a primary focus on the residential built environment. Moreover, the spatial heterogen...

Public transport services are often improved to decrease auto-related mobility. However, it remains unclear how the built environment influences auto ownership and commuting mode choice near public...

The effects of the built environment (BE) on modes of transport have been extensively evaluated in the literature with a primary focus on the neighborhood-level BE. Moreover, it has been revealed that transportation modes are associated with an individual’s life choices and the resulting quality of life (QoL). However, the effects of the BE on the transportation, which in turn affects the QoL, remain largely unknown. This is especially true considering that the BE can be evaluated at different spatial scales, which further involves both observed and unobserved clustering effects. Based on data from 8,862 respondents living in 97 Chinese cities (collected in 2014), this study builds a generalized structural equation model (GSEM) to explore the complex relationships between both neighborhood- and city-level BE attributes, active commuting, body mass index (BMI), and life satisfaction within a unified analysis framework. The results show that: (1) GSEM significantly outperforms the conventional structural equation model; (2) life satisfaction is related to both active commuting modes and BMI, while the active commuting time is related to BMI; and (3) the city-level BE has a much stronger relevance to active commuting time, BMI, and life satisfaction, but a weaker relevance to active commuting modes, than the neighborhood-level BE.

The links between built environments (BE) and commute durations have been extensively studied. However, relatively few studies have considered the effects of BEs at different spatial levels within a unified framework, or identified the gendered relationships between BEs and commute durations. Using survey data from 3209 household couples in 97 Chinese cities, this study investigates the effects of neighborhood- and city-level BEs on commute durations and the potential differences in these effects between the male and female members of the same household couple. A multi-group generalized multilevel structural equation model is applied to reveal the gendered relationships between neighborhood- and city-level BEs and commute durations. The findings suggest that the BE variables at two levels have significant effects on the commute duration. The mediating roles that the traffic congestion, car ownership, and commuting modes play in linking these BEs and commute durations are confirmed. Both levels of the BE variables are more influential factors for males’ commuting durations. These findings have policy implications for the design of gender-equal transportation systems.

Given the enormous traffic issues, such as congestion and crashes, resulting from the conflicts between trucks and passenger cars, an accurate and reliable prediction of truck traffic flow is needed to enhance the traffic flow efficiency and safety in the mixed traffic condition. Enabled by emerging sensing technologies, the GPS data become available and will reveal some insights to improve the understanding of truck traffic flow prediction. In the paper, a novel method of truck traffic flow prediction is proposed by using sampled GPS data in the roadway network. The proposed method consists of two phases, which are expansion and prediction. In the data expansion phase, a piece-wise constant coefficient method is designed to minimize errors between the sampled truck flow and the actual truck flow, where the coefficients are determined according to road grades and traffic flow size. In the prediction phase, Long Short Term Memory (LSTM) and Gated Recursive Unit (GRU) neural network methods are first time employed to improve the prediction accuracy. Considering that the sequence of the expansion and prediction could have different prediction performance, approaches using both ‘previous-prediction’, ‘post-expansion’ and ‘previous-expansion’, ‘post-prediction’ were used and the results compared with the survey data from traffic flows. The results demonstrate that LSTM and GRU have a superior performance compared to existing approaches using SRV and ARIMA for truck traffic flow prediction. For the whole prediction period, LSTM has better prediction results than GRU overall with an accuracy which is 4.10% better than that of GRU. Furthermore, the accuracy of the ‘previous-prediction’, ‘post-expansion’ is 8.26% greater than that of the ‘previous-expansion’, ‘post-prediction’.

Although the relationship between commuting time and residents’ happiness has been widely investigated, few studies have examined how the connection varies with urbanization levels. Using 7,774 individual samples across China, this study employs a multilevel ordered logit model to examine how commuting time is correlated with residents’ happiness. The effects of both the neighborhood and city-level built environment are revealed. Our findings show that commuting time is an essential factor correlated with residents’ happiness and the correlation varies across urbanization levels. People from cities with high urbanization rates (>70%) have a strong mental endurance of commuting time, whereas commuting time is more influential on residents’ happiness in cities with low urbanization rates (

Urban rail transit (URT) is often implemented in order to reduce car ownership and use. However, it is still unclear how the impacts of the built environment on car dependence differ in transit-ori...

Background: Hypertrophic response to pathological stimuli is a complex biological process that involves transcriptional and epigenetic regulation of the cardiac transcriptome. Although previous studies have implicated transcriptional factors and signaling molecules in pathological hypertrophy, the role of RNA-binding protein in this process has received little attention. Methods: Here we used transverse aortic constriction and in vitro cardiac hypertrophy models to characterize the role of an evolutionary conserved RNA-binding protein Lin28a in pathological cardiac hypertrophy. Next-generation sequencing, RNA immunoprecipitation, and gene expression analyses were applied to identify the downstream targets of Lin28a. Epistatic analysis, metabolic assays, and flux analysis were further used to characterize the effects of Lin28a and its downstream mediator in cardiomyocyte hypertrophic growth and metabolic remodeling. Results: Cardiac-specific deletion of Lin28a attenuated pressure overload–induced hypertrophic growth, cardiac dysfunction, and alterations in cardiac transcriptome. Mechanistically, Lin28a directly bound to mitochondrial phosphoenolpyruvate carboxykinase 2 ( Pck2 ) mRNA and increased its transcript level. Increasing Pck2 was sufficient to promote hypertrophic growth similar to that caused by increasing Lin28a, whereas knocking down Pck2 attenuated norepinephrine-induced cardiac hypertrophy. Epistatic analysis demonstrated that Pck2 mediated, at least in part, the role of Lin28a in cardiac hypertrophic growth. Furthermore, metabolomic analyses highlighted the role for Lin28a and Pck2 in promoting cardiac biosynthesis required for cell growth. Conclusions: Our study demonstrates that Lin28a promotes pathological cardiac hypertrophy and glycolytic reprograming, at least in part, by binding to and stabilizing Pck2 mRNA.

With the development of information and communication technologies (ICTs), considerable attention is being paid to the relationship between ICT use and travel behavior. However, it is unclear whether the effects of ICT use on trip generation vary across travel modes. Based on the data of 1022 respondents collected by a web-based questionnaire survey in Beijing, this study used a zero-inflated Poisson model to investigate the effects of ICT use on trip generation in different travel modes, in which ICT use was measured by both the time spent online and the Internet use frequency. The results indicated that the effects of ICT use on trip generation vary across auto, transit, and active trips. Moreover, two measurements of ICT use play essential roles in influencing a trip generation. Specifically, only the frequency of ordering food online showed a positive association with the likelihood of generating any transit trips. These findings demonstrate the importance of considering the differences across travel modes when analyzing the relationship between ICT use and trip generation.

Visual Abstract, Highlights • Optimal treatment for patients with diabetes and myocardial infarction remains a challenge. • Hyperglycemia- and hyperinsulinemia-induced miR-24 reduction and O-GlcNAcylation in the diabetic heart contributes to poor survival in diabetic myocardial I/R and increased infarct size post-I/R. • Overexpression of miR-24 in murine hearts significantly reduces myocardial infarct size. • miR-24 targets multiple key proteins including O-GlcNac transferase, ATG4A (a key protein in autophagy), and BIM (a pro-apoptosis protein) to protect the myocardium from I/R injury. • miR-24 is a promising therapeutic candidate for diabetic I/R injury., Summary Management for patients with diabetes experiencing myocardial infarction remains a challenge. Here the authors show that hyperglycemia- and hyperinsulinemia-induced microRNA-24 (miR-24) reduction and O-GlcNAcylation in the diabetic heart contribute to poor survival and increased infarct size in diabetic myocardial ischemia/reperfusion (I/R). In a mouse model of myocardial I/R, pharmacological or genetic overexpression of miR-24 in hearts significantly reduced myocardial infarct size. Experimental validation revealed that miR-24 targets multiple key proteins, including O-GlcNac transferase, ATG4A, and BIM, to coordinately protect the myocardium from I/R injury. These results establish miR-24 as a promising therapeutic candidate for diabetic I/R injury.

Numerous studies have identified the determinants of happiness. However, the literature provides scant evidence on the potential nonlinear relationships between built environment (BE) and commuting duration and happiness. Using survey data of 7837 respondents from 327 Chinese communities, this study applies a gradient boosting decision tree method to investigate the nonlinear relationships of BE and commuting duration with happiness, and how the nonlinear patterns of commuting duration vary across modes. The results suggest that compared with commuting duration (6.71%) and specific BE characteristics (ranging between 4.77% and 8.86%), household income has the largest relative contribution (14.57%). All BE characteristics show a nonlinear relationship with happiness. The commuting duration shows nonlinear relationships with happiness, and the nonlinear patterns vary across commuting modes. These findings identify effective the range of BE and commuting duration in affecting happiness. Therefore, transport practitioners and urban planners should deliberate on land use and transportation policies to promote happiness.

The relationships between the built environment (BE) and car dependence have been thoroughly evaluated, with a primary focus on the residential BE; however, the effects of the BE at workplaces have remained largely unexplored. Little is known about the potential nonlinear effects of the BE at both locations. Using data from a household travel survey in Changchun, China, we aimed to reveal the nonlinear effects of the residential and workplace BE on car dependence by building a gradient boosting decision trees model. The results show that the BE at both locations has strong explanatory power for car ownership and car purchasing intention. With relative contributions values of 17.90% and 18.13%, respectively, the BE at workplaces contributes less to explaining the two dependent variables than the BE at residences. All BE attributes show nonlinear effects on car ownership, and car purchasing intention and the effects differ between residential and workplace locations.

Direct reprogramming of fibroblasts to alternative cell fates by forced expression of transcription factors offers a platform to explore fundamental molecular events governing cell fate identity. The discovery and study of induced cardiomyocytes (iCMs) not only provides alternative therapeutic strategies for heart disease but also sheds lights on basic biology underlying CM fate determination. The iCM field has primarily focused on early transcriptome and epigenome repatterning, whereas little is known about how reprogramming iCMs remodel, erase, and exit the initial fibroblast lineage to acquire final cell identity. Here, we show that autophagy-related 5 (Atg5)-dependent autophagy, an evolutionarily conserved self-digestion process, was induced and required for iCM reprogramming. Unexpectedly, the autophagic factor Beclin1 (Becn1) was found to suppress iCM induction in an autophagy-independent manner. Depletion of Becn1 resulted in improved iCM induction from both murine and human fibroblasts. In a mouse genetic model, Becn1 haploinsufficiency further enhanced reprogramming factor-mediated heart function recovery and scar size reduction after myocardial infarction. Mechanistically, loss of Becn1 up-regulated Lef1 and down-regulated Wnt inhibitors, leading to activation of the canonical Wnt/β-catenin signaling pathway. In addition, Becn1 physically interacts with other classical class III phosphatidylinositol 3-kinase (PI3K III) complex components, the knockdown of which phenocopied Becn1 depletion in cardiac reprogramming. Collectively, our study revealed an inductive role of Atg5-dependent autophagy as well as a previously unrecognized autophagy-independent inhibitory function of Becn1 in iCM reprogramming.

This study proposes a short-term traffic flow prediction approach based on multiple traffic flow basic parameters, in which the chaos theory and support vector regression are utilized. First, a high-dimensional variable space can be obtained according to the traffic flow fundamental function. Then, a maximum conditional entropy method is proposed to determine the embedding dimension. And multiple time series are reconstructed based on the phase space reconstruction theory using the time delay obtained by mutual information method and the embedding dimension captured by the maximum conditional entropy method. Finally, the reconstructed phase space is used as the input and the support vector regression optimized by the genetic algorithm is utilized to predict the traffic flow. Numerical experiments are performed and the results show that the approach proposed has strong fitting capability and better prediction accuracy.

The effects of air pollution and commuting behavior on life satisfaction have received increasing research interests. However, the literature pays scant attention to haze pollution and its moderating effects on the relationship between commuting behavior and life satisfaction. Using two-round of cross-sectional survey data across 92 Chinese cities, this paper analyzes the impacts of haze pollution and commuting behavior on life satisfaction, and the moderating effects of haze pollution on the link between commuting behavior and life satisfaction. The findings suggest that haze pollution and its changes are important triggers of life satisfaction. Moreover, the effects of changes in haze pollution correlate with basic haze pollution levels. Active commuters report higher life satisfaction, while transit commuters report lower life satisfaction. Longer commutes cause losses in life satisfaction. Additionally, haze pollution mitigates the losses in life satisfaction for commuters using public transit, but strengthens the negative effect of commuting time.

Background Health-related lifestyle is widely believed to play an essential role in the prevalence of overweight and obesity. However, it is unclear how urbanization moderates the effect of health-related lifestyle on overweight and obesity. Methods Based on survey data of 8266 individuals across China, we applied several multilevel logit models to examine whether the effect of health-related lifestyle on overweight and obesity differ between urban and rural areas and how the effect varies with urbanization level. Results We found differences in people's health-related lifestyle between urban and rural areas and variations with urbanization levels. The estimated results showed that most health-related lifestyle variables influence individual’ risks of overweight and obesity in urban areas, whereas only car ownership, exercise time and smoking show effects on being overweight and obese in rural areas. Except for active commuting time, and exercise time, all other health-related lifestyle variables showed different effects on overweight and obesity in areas with different urbanization levels. Conclusions These findings provide a better understanding of the role played by urbanization in moderating the effects of health-related lifestyle on overweight and obesity. It suggests that, to mitigate the overweight epidemic, policy makers should pay more attention to local characteristics when promoting related strategies.

One common goal of urban planning is to promote health, where the built environment (BE) is believed to play an essential role. This study provides new evidence for the links between body mass index (BMI) and the BE at different geographic scales in a unified framework. Based on a sample of 10,962 individuals across 95 cities in China, this study explores the collective effects of the BE attributes at neighborhood and city levels on BMI using a gradient boosting decision tree (GBDT) approach. Moreover, whether the relationships between the city-level BE attributes and BMI vary across social groups is revealed. The results indicate that the city-level BE attributes have larger collective effects on BMI than the neighborhood-level BE attributes. Specifically, population size is the greatest contributor to predicting BMI, with a relative importance of 13.92% among all influential factors. Moreover, it is found that the effects of city-level BE attributes vary across different social groups. These findings suggest it is of vital importance for urban planners to coordinate both neighborhood- and city-level BE planning to deter the risks of obesity, and urban planning can be more effective if it is implemented considering local socio-demographic characteristics.

Short-term traffic flow forecasting is a key component of intelligent transportation system, yet difficult to be forecasted reliably, and accurately. A novel hybrid forecasting model is proposed by combining three predictors, namely, the autoregressive integrated moving average (ARIMA), back propagation neural network (BPNN) and support vector regression (SVR). First, it is assumed that all previous intervals can have influence on the predicted interval and then the entropy-based gray relation analysis method is applied to analyze the correlation and determine the length of time constrain window. Second, an improved Euclidean distance is employed to identify the similarity. Furthermore, the rank-exponent method is utilized to rank the results according to the similarity and fuse the predicted values of the predictors. Finally, a numerical experiment is implemented, which indicates that the performance of forecasting results is superior to the conventional ones.

Considerable attention has been paid to the determinants of commuting mode shift patterns. However, the literature provides little evidence on the impacts of changes in the built environment (BE) on commuting mode shift, and few studies shed light on the gender differences in the impacts of influential factors. Based on longitudinal data from China, this study explores how life events and changes in the BE influence commuting mode shift and whether the impacts differ between household couples. The results identify significant differences in the impacts of the influential factors between household couples. Most life events show significant impacts on the spouses’ commuting mode shift, whereas changes in the BE characteristics are more influential on the wife’s modal shift behavior. These findings suggest that urban planners and policy makers should better understand the gender differences to develop gender-equal transportation systems when implementing urban planning and transportation strategies.

During pathological hypertrophy, the heart undergoes extensive metabolic changes prior to the onset of structural remodeling, yet, it remains unknown whether and how this metabolic remodeling could contribute to cardiac hypertrophic growth. Here, we identified the RNA-binding protein Lin28a as a critical regulator of pathological cardiac hypertrophy and metabolic re-patterning. Cardiac specific deletion of Lin28a attenuated pressure overload-induced hypertrophy and cardiac dysfunction. Transcriptomics and metabolomic analysis highlighted roles for Lin28a in promoting cardiac glycolysis and anabolic biosynthesis. Mechanistically, Lin28a directly bound to mitochondrial phosphoenolpyruvate carboxykinase 2 ( Pck2 ) mRNA and positively modulated its transcript level. By utilizing the neonatal rat cardiomyocytes (NRCMs) hypertrophy model, we found that manipulation of Pck2 expression phenocopied the metabolic and hypertrophic phenotypes of manipulating Lin28a expression. Furthermore, epistatic analyses demonstrated that overexpression of Pck2 reversed the attenuation of norepinephrine-induced enhancement of cardiac glycolysis and cardiac hypertrophy by loss of Lin28a function, and knockdown of Pck2 suppressed Lin28a-induced increase in cardiac glycolysis and cardiomyocyte hypertrophic growth. Thus, our study revealed a critical role of Lin28a in the regulation of pathological cardiac hypertrophic growth through Pck2-mediated regulation of cardiac metabolism.

Although the impacts of built environment on car ownership and use have been extensively studied, limited evidence has been offered for the role of spatial effects in influencing the interaction between built environment and travel behavior. Ignoring the spatial effects may lead to misunderstanding the role of the built environment and providing inconsistent transportation policies. In response to this, we try to employ a two-step modeling approach to investigate the impacts of built environment on car ownership and use by combining multilevel Bayesian model and conditional autocorrelation (CAR) model to control for spatial autocorrelation. In the two-step model, the predicting car ownership status in the first-step model is used as a mediating variable in the second-step car use model. Taking Changchun as a case study, this paper identifies the presence of spatial effects in influencing the effects of built environment on car ownership and use. Meanwhile, the direct and cascading effects of built environment on car ownership and use are revealed. The results show that the spatial autocorrelation exists in influencing the interaction between built environment and car dependency. The results suggest that it is necessary for urban planners to pay attention to the spatial effects and make targeted policy according to local land use characteristics.

Along with urbanization and economic development, the number of private cars has increased rapidly in recent years in China, which contributes to concerns about traffic congestion, hard parking, energy consumption, and emissions. This study aims to investigate the joint effect of built environment and parking availability on car ownership and use based on a household travel survey conducted in Changchun, China. The binary logistic model was first employed to investigate the determinants of the car ownership in Changchun. Next, this study examined the potential impacts of the built environment and parking availability on car use for the journey to work. The result shows that built environment and parking availability can be both significantly associated with car ownership and use after controlling for the socio-economic characteristics. Moreover, in contrast with the model ignoring the parking availability, the model for car use considering the joint effect fit the data better. The results indicate that car dependency depends on the joint effect of the built environment and parking availability. These results suggest that transit-oriented urban expansion and compact land use can contribute to reducing car commuting. Meanwhile, parking restrictions at both trip start and end would be effective for sustainable transport because parking oversupply could encourage more car dependency.

Direct conversion of fibroblasts into induced cardiomyocytes (iCMs) offers an alternative strategy for cardiac disease modeling and regeneration. During iCM reprogramming, the starting fibroblasts must overcome existing epigenetic barriers to acquire the CM-like chromatin pattern. However, epigenetic dynamics along this reprogramming process have not been studied. Here, we took advantage of our recently generated polycistronic system and determined the dynamics of two critical histone marks, H3K27me3 and H3K4me3, in parallel with gene expression at a set of carefully selected cardiac and fibroblast loci during iCM reprogramming. We observed reduced H3K27me3 and increased H3K4me3 at cardiac promoters as early as day 3, paralleled by a rapid significant increase in their mRNA expression. In contrast, H3K27me3 at loci encoding fibroblast marker genes did not increase until day 10 and H3K4me3 progressively decreased along the reprogramming process; these changes were accompanied by a gradual decrease in the mRNA expression of fibroblast marker genes. Further analyses of fibroblast-enriched transcription factors revealed a similarly late deposition of H3K27me3 and decreased mRNA expression of Sox9, Twist1 and Twist2, three important players in epithelial−mesenchymal transition. Our data suggest early rapid activation of the cardiac program and later progressive suppression of fibroblast fate at both epigenetic and transcriptional levels. Additionally, we determined the DNA methylation states of representative cardiac promoters and found that not every single CpG was equally demethylated during early stages of iCM reprogramming. Rather, there are specific CpGs, whose demethylation states correlated tightly with transcription activation, that we propose are the major contributing CpGs. Our work thus reveals a differential re-patterning of H3K27me3, H3K4me3 at cardiac and fibroblast loci during iCM reprogramming and could provide future genome-wide epigenetic studies with important guidance such as the appropriate time window and loci to be utilized as positive and negative controls.

Concerns about transportation energy consumption and emissions force urban planners and policy makers to pay more attention to the effects of car ownership and use on the environment in China. However, few studies have investigated the relationship between the built environment and car ownership and use in China, especially in mid-sized and small cities. This study uses Changchun, China as a case study and examines the potential impacts of the built environment and socio-demographics on car ownership and use for commuting simultaneously using Bayesian multilevel binary logistic models. Furthermore, the spatial autocorrelation of car ownership and use is recognized across traffic analysis zones (TAZs), which are specifically represented by the conditional autoregressive (CAR) model. The estimated results indicate that socio-demographic characteristics have significant effects on car ownership and use. Moreover, the built environment measured at the TAZ level still shows a significant association with other factors controlled. Specifically, it suggests that denser residential density, compact land use, better transit services and street connectivity can reduce car dependency more effectively. This study provides new insights into how the built environment influences the car ownership and use, which can be useful for urban planners and policy makers to develop strategies for reducing car dependency.

Direct cardiac reprogramming holds great promise for cardiac regeneration and disease modelling.1–15 We recently reported that stoichiometry of Gata4 (G), Mef2c (M), and Tbx5 (T) influences the efficiency and quality of induced cardiomyocyte (iCM) reprogramming.16 We generated a full set of polycistronic vectors to manipulate the relative levels of G, M, and T protein expression. Among the six combinations, MGT that expresses a relative high expression of M and low expressions of G and T resulted in the most efficient in vitro iCM reprogramming.16 Here, we performed genetic lineage tracing in a murine myocardial infarction (MI) model to determine whether MGT could improve in vivo iCM reprogramming efficiency and result in a further improvement in ventricular contractile function compared with the traditional separate G, M, and T (G/M/T) delivery. We took advantage of the unique feature that retrovirus infects only dividing cells to deliver MGT, G/M/T, or dsRed into actively dividing cardiac fibroblasts, but not CMs, in MI hearts.3 We prepared retrovirus encoding the single-triplet MGT as well as G/M/T and dsRed control viruses. These viruses were subjected to ultracentrifugation and were concentrated at 1 × 1010 p.f.a./mL. According to the previously established protocol,3 8–12 week old male mice were treated with 10 μL of ultra-high-titre retrovirus (∼1010 p.f.a./mL) by injection into the myocardial wall immediately following coronary artery ligation. To determine whether MGT enhances reprogramming of non-myocytes into iCMs in vivo , we performed genetic lineage tracing experiments using Periostin-Cre; R26R-lacZ mice3 to quantify the number of iCMs that had a fibroblast origin. Consistent with previous reports,3 we did not detect any β-galactosidase activity in the CMs of control …