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

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

Gr-1+CD11b+ Myeloid-Derived Suppressor Cells: Formidable Partners in Tumor Metastasis

The growth and metastasis of solid tumors not only depends on their ability to escape from immune surveillance but also hinges on their ability to invade the vasculature system as well as to induce the formation of new blood vessels. Gr-1+CD11b+ myeloid-derived suppressor cells (MDSCs), overproduced in tumor-bearing hosts, contribute significantly to all these aspects. They also have a potential role in the osteolysis associated with bone metastases. They are formidable partners in tumor metastasis. © 2010 American Society for Bone and Mineral Research

Controlled epitaxial graphene growth within amorphous carbon corrals

Structured growth of high quality graphene is necessary for technological development of carbon based electronics. Specifically, control of the bunching and placement of surface steps under epitaxial graphene on SiC is an important consideration for graphene device production. We demonstrate lithographically patterned evaporated amorphous carbon corrals as a method to pin SiC surface steps. Evaporated amorphous carbon is an ideal step-flow barrier on SiC due to its chemical compatibility with graphene growth and its structural stability at high temperatures, as well as its patternability. The amorphous carbon is deposited in vacuum on SiC prior to graphene growth. In the graphene furnace at temperatures above 1200$^\circ$C, mobile SiC steps accumulate at these amorphous carbon barriers, forming an aligned step free region for graphene growth at temperatures above 1330$^\circ$C. AFM imaging and Raman spectroscopy support the formation of quality step-free graphene sheets grown on SiC with the step morphology aligned to the carbon grid