Exploring neighborhood environments and active communting in Chennai, India

Few studies assess built environment correlates of active commuting in low-and-middle-income countries (LMICs), but the different context could yield distinct findings. Policies and investments to promote active commuting remain under-developed in LMICs like India, which grapples with traffic congestion, lack of activity-supportive infrastructure, poor enforcement of traffic rules and regulations, air pollution, and overcrowding. This cross-sectional study investigated associations between home neighborhood environment characteristics and active commuting in Chennai, India. Adults (N = 370, 47.2% female, mean age = 37.9 years) were recruited from 155 wards in the metropolitan area of Chennai in southern India between January and June 2015. Participants self-reported their usual mode of commute to work, with responses recoded into three categories: (1) multi-modal or active commuting (walking and bicycling; n = 56); (2) public transit (n = 52); and (3) private transport (n = 111). Environmental attributes around participants’ homes were assessed using the Neighborhood Environment Walkability Scale for India (NEWS-India). Associations between environmental characteristics and likelihood of active commuting and public transit use were modeled using logistic regression with private transport (driving alone or carpool) as the reference category, adjusting for age, gender, and household car ownership. Consistent with other international studies, participants living in neighborhoods with a mix of land uses and a transit stop within a 10-minute walk from home were more likely to use active commuting (both p < 0.01). Land-use mix was significantly associated with the use of public transit compared to private transport (adjusted odds ratio (aOR) = 5.2, p = 0.002). Contrary to findings in high-income countries, the odds of active commuting were reduced with improved safety from crime (aOR = 0.2, p = 0.003), aesthetics (aOR = 0.2, p = 0.05), and street connectivity (aOR = 0.2, p = 0.003). Different environmental attributes were associated with active commuting, suggesting that these relationships are complex and may distinctly differ from those in high-income countries. Unexpected inverse associations of perceived safety from crime and aesthetics with active commuting emphasize the need for high-quality epidemiologic studies with greater context specificity in the study of physical activity in LMICs. Findings have public health implications for India and suggest that caution should be taken when translating evidence across countries

Automated Ecological Assessment of Physical Activity: Advancing Direct Observation.

Technological advances provide opportunities for automating direct observations of physical activity, which allow for continuous monitoring and feedback. This pilot study evaluated the initial validity of computer vision algorithms for ecological assessment of physical activity. The sample comprised 6630 seconds per camera (three cameras in total) of video capturing up to nine participants engaged in sitting, standing, walking, and jogging in an open outdoor space while wearing accelerometers. Computer vision algorithms were developed to assess the number and proportion of people in sedentary, light, moderate, and vigorous activity, and group-based metabolic equivalents of tasks (MET)-minutes. Means and standard deviations (SD) of bias/difference values, and intraclass correlation coefficients (ICC) assessed the criterion validity compared to accelerometry separately for each camera. The number and proportion of participants sedentary and in moderate-to-vigorous physical activity (MVPA) had small biases (within 20% of the criterion mean) and the ICCs were excellent (0.82-0.98). Total MET-minutes were slightly underestimated by 9.3-17.1% and the ICCs were good (0.68-0.79). The standard deviations of the bias estimates were moderate-to-large relative to the means. The computer vision algorithms appeared to have acceptable sample-level validity (i.e., across a sample of time intervals) and are promising for automated ecological assessment of activity in open outdoor settings, but further development and testing is needed before such tools can be used in a diverse range of settings

The nucleolus functions as a phase-separated protein quality control compartment

The nuclear proteome is rich in stress-sensitive proteins, which suggests that effective protein quality control mechanisms are in place to ensure conformational maintenance. We investigated the role of the nucleolus in this process. In mammalian tissue culture cells under stress conditions, misfolded proteins entered the granular component (GC) phase of the nucleolus. Transient associations with nucleolar proteins such as NPM1 conferred low mobility to misfolded proteins within the liquid-like GC phase, avoiding irreversible aggregation. Refolding and extraction of proteins from the nucleolus during recovery from stress was Hsp70-dependent. The capacity of the nucleolus to store misfolded proteins was limited, and prolonged stress led to a transition of the nucleolar matrix from liquid-like to solid, with loss of reversibility and dysfunction in quality control. Thus, we suggest that the nucleolus has chaperone-like properties and can promote nuclear protein maintenance under stress.We acknowledge support by the MPIB Imaging facility and G. Cardone for providing the algorithm for image quantification

Effects of Crime Type and Location on Park Use Behavior

Crime and the fear of crime can be a barrier to park use, and locations of crimes can have varied effects. Unsafe areas in or around the park, around the residence, or along the route to the park can alter park use behavior. Our study aimed to examine associations between objective measures of types and location of crimes and park use behaviors. In 2013 we surveyed a sample (N = 230) of residents in Greensboro, North Carolina, about park use, with responses matched to objective crime and spatial measures. We measured all crimes and violent crimes near home, near the closest park, and along the shortest route between home and park. By using ordered and binary logistic modeling, we examined the relationships between the locations of crime and park use and duration of park visit, park rating, and never visiting parks. Additional models included distance to the closest park. Increased crime in parks and near home was associated with fewer park visits. Greater violent crime in all locations was related to fewer park visits. Park ratings were lower for parks with high violent crime rates. Given the importance of parks as settings for outdoor recreation and physical activity, crime may have a detrimental effect on physical activity and, therefore, public health

An inventory of interactors of the human HSP60/HSP10 chaperonin in the mitochondrial matrix space

The HSP60/HSP10 chaperonin assists folding of proteins in the mitochondrial matrix space by enclosing them in its central cavity. The chaperonin forms part of the mitochondrial protein quality control system. It is essential for cellular survival and mutations in its subunits are associated with rare neurological disorders. Here we present the first survey of interactors of the human mitochondrial HSP60/HSP10 chaperonin. Using a protocol involving metabolic labeling of HEK293 cells, cross-linking, and immunoprecipitation of HSP60, we identified 323 interacting proteins. As expected, the vast majority of these proteins are localized to the mitochondrial matrix space. We find that approximately half of the proteins annotated as mitochondrial matrix proteins interact with the HSP60/HSP10 chaperonin. They cover a broad spectrum of functions and metabolic pathways including the mitochondrial protein synthesis apparatus, the respiratory chain, and mitochondrial protein quality control. Many of the genes encoding HSP60 interactors are annotated as disease genes. There is a correlation between relative cellular abundance and relative abundance in the HSP60 immunoprecipitates. Nineteen abundant matrix proteins occupy more than 60% of the HSP60/HSP10 chaperonin capacity. The reported inventory of interactors can form the basis for interrogating which proteins are especially dependent on the chaperonin

Learning Interpretable Rules for Multi-label Classification

Multi-label classification (MLC) is a supervised learning problem in which, contrary to standard multiclass classification, an instance can be associated with several class labels simultaneously. In this chapter, we advocate a rule-based approach to multi-label classification. Rule learning algorithms are often employed when one is not only interested in accurate predictions, but also requires an interpretable theory that can be understood, analyzed, and qualitatively evaluated by domain experts. Ideally, by revealing patterns and regularities contained in the data, a rule-based theory yields new insights in the application domain. Recently, several authors have started to investigate how rule-based models can be used for modeling multi-label data. Discussing this task in detail, we highlight some of the problems that make rule learning considerably more challenging for MLC than for conventional classification. While mainly focusing on our own previous work, we also provide a short overview of related work in this area.Comment: Preprint version. To appear in: Explainable and Interpretable Models in Computer Vision and Machine Learning. The Springer Series on Challenges in Machine Learning. Springer (2018). See http://www.ke.tu-darmstadt.de/bibtex/publications/show/3077 for further informatio

Cerebral blood flow predicts differential neurotransmitter activity

Application of metabolic magnetic resonance imaging measures such as cerebral blood flow in translational medicine is limited by the unknown link of observed alterations to specific neurophysiological processes. In particular, the sensitivity of cerebral blood flow to activity changes in specific neurotransmitter systems remains unclear. We address this question by probing cerebral blood flow in healthy volunteers using seven established drugs with known dopaminergic, serotonergic, glutamatergic and GABAergic mechanisms of action. We use a novel framework aimed at disentangling the observed effects to contribution from underlying neurotransmitter systems. We find for all evaluated compounds a reliable spatial link of respective cerebral blood flow changes with underlying neurotransmitter receptor densities corresponding to their primary mechanisms of action. The strength of these associations with receptor density is mediated by respective drug affinities. These findings suggest that cerebral blood flow is a sensitive brain-wide in-vivo assay of metabolic demands across a variety of neurotransmitter systems in humans