Social Network Ties and Inflammation in U.S. Adults with Cancer

The growing evidence linking social connectedness and chronic diseases such as cancer calls for a better understanding of the underlying biophysiological mechanisms. This study assessed the associations between social network ties and multiple measures of inflammation in a nationally representative sample of adults with a history of cancer (N = 1,075) from the National Health and Nutrition Examination Survey III (1988–94). Individuals with lower social network index (SNI) scores showed significantly greater inflammation marked by C-reactive protein and fibrinogen, adjusting for age and sex. Compared to fully socially integrated individuals (SNI 4), those who were more socially isolated or had a SNI score of 3 or less exhibited = increasingly elevated inflammation burdens. Specifically, the age- and sex-adjusted odds ratios (95%CI) for SNIs of 3, 2, and 0–1 were 1.49 (1.08, 2.06), 1.69 (1.21, 2.36), and 2.35 (1.62, 3.40), respectively (p < .001). Adjusting for other covariates attenuated these associations. The SNI gradients in the risks of inflammation were particularly salient for the lower socioeconomic status groups and remained significant after adjusting for other social, health behavioral, and illness factors. This study provided initial insights into the immunological pathways by which social connections are related to morbidity and mortality outcomes of cancer in particular and aging-related diseases in general

Path integral formulation of stochastic optimal control with generalized costs

Path integral control solves a class of stochastic optimal control problems with a Monte Carlo (MC) method for an associated Hamilton-Jacobi-Bellman (HJB) equation. The MC approach avoids the need for a global grid of the domain of the HJB equation and, therefore, path integral control is in principle applicable to control problems of moderate to large dimension. The class of problems path integral control can solve, however, is defined by requirements on the cost function, the noise covariance matrix and the control input matrix. We relax the requirements on the cost function by introducing a new state that represents an augmented running cost. In our new formulation the cost function can contain stochastic integral terms and linear control costs, which are important in applications in engineering, economics and finance. We find an efficient numerical implementation of our grid-free MC approach and demonstrate its performance and usefulness in examples from hierarchical electric load management. The dimension of one of our examples is large enough to make classical grid-based HJB solvers impractical

The physiological impacts of wealth shocks in late life: Evidence from the Great Recession

Given documented links between individual socioeconomic status (SES) and health, it is likely that—in addition to its impacts on individuals’ wallets and bank accounts—the Great Recession also took a toll on individuals’ disease and mortality risk. Exploiting a quasi-natural experiment design, this study utilizes nationally representative, longitudinal data from the National Social Life, Health, and Aging Project (NSHAP) (2005-2011) (N=930) and individual fixed effects models to examine how household-level wealth shocks experienced during the Great Recession relate to changes in biophysiological functioning in older adults. Results indicate that wealth shocks significantly predicted changes in physiological functioning, such that losses in net worth from the pre- to the post-Recession period were associated with increases in systolic blood pressure and C-reactive protein over the six year period. Further, while the association between wealth shocks and changes in blood pressure was unattenuated with the inclusion of other indicators of SES, psychosocial well-being, and health behaviors in analytic models, we document some evidence of mediation in the association between changes in wealth and changes in C-reactive protein, which suggests specificity in the social and biophysiological mechanisms relating wealth shocks and health at older ages. Linking macro-level conditions, meso-level household environments, and micro-level biological processes, this study provides new insights into the mechanisms through which economic inequality contributes to disease and mortality risk in late life

Joint Microseismic Event Detection and Location with a Detection Transformer

Microseismic event detection and location are two primary components in microseismic monitoring, which offers us invaluable insights into the subsurface during reservoir stimulation and evolution. Conventional approaches for event detection and location often suffer from manual intervention and/or heavy computation, while current machine learning-assisted approaches typically address detection and location separately; such limitations hinder the potential for real-time microseismic monitoring. We propose an approach to unify event detection and source location into a single framework by adapting a Convolutional Neural Network backbone and an encoder-decoder Transformer with a set-based Hungarian loss, which is applied directly to recorded waveforms. The proposed network is trained on synthetic data simulating multiple microseismic events corresponding to random source locations in the area of suspected microseismic activities. A synthetic test on a 2D profile of the SEAM Time Lapse model illustrates the capability of the proposed method in detecting the events properly and locating them in the subsurface accurately; while, a field test using the Arkoma Basin data further proves its practicability, efficiency, and its potential in paving the way for real-time monitoring of microseismic events

Social Network Ties and Inflammation in U.S. Adults with Cancer

The growing evidence linking social connectedness and chronic diseases such as cancer calls for a better understanding of the underlying biophysiological mechanisms. This study assessed the associations between social network ties and multiple measures of inflammation in a nationally representative sample of adults with a history of cancer (N = 1,075) from the National Health and Nutrition Examinatio

Early-Life Socioeconomic Status and Adult Physiological Functioning: A Life Course Examination of Biosocial Mechanisms

A growing literature has demonstrated a link between early-life socioeconomic conditions and adult health at a singular point in life. No research exists, however, that specifies the life course patterns of socioeconomic status (SES) in relation to the underlying biological processes that determine health. Using an innovative life course research design consisting of four nationally representative longitudinal datasets that collectively cover the human life span from early adolescence to old age (Add Health, MIDUS, NSHAP, and HRS), we address this scientific gap and assess how SES pathways from childhood into adulthood are associated with biophysiological outcomes in different adult life stages. For each dataset, we constructed standardized, composite measures of early-life SES and adult SES and harmonized biophysiological measurements of immune and metabolic functioning. We found that the relative importance of early-life and adult SES varied across young-, mid-, and late-adulthood, such that early-life SES sets a life course trajectory of socioeconomic well-being and operates through adult SES to influence health as adults age. We also documented evidence of the detrimental health effects of downward mobility and persistent socioeconomic disadvantage. These findings are the first to specify the life course patterns of SES that matter for underlying biophysiological functioning in different stages of adulthood. The study thus contributes new knowledge critical for improving population health by identifying the particular points in the life course in which interventions might be most effective in preventing disease and premature mortality