American Indian elders, aged 55 years and older, represent a neglected segment of the United States (U.S.) health care system. This group is more likely to be uninsured and to suffer from greater morbidities, poorer health outcomes and quality of life, and lower life expectancies compared to all other aging populations in the country. Despite the U.S. government's federal trust responsibility to meet American Indians' health-related needs through the Indian Health Service (IHS), elders are negatively affected by provider shortages, limited availability of health care services, and gaps in insurance. This qualitative study examines the perspectives of professional stakeholders involved in planning, delivery of, and advocating for services for this population to identify and analyze macro- and meso-level factors affecting access to and use of health care and insurance among American Indian elders at the micro level.

Between June 2016 and March 2017, we undertook in-depth qualitative interviews with 47 profe and insurance needs. Policies and practices must target meso and macro levels of contextual influence. Although Medicaid expansion under the ACA enables providers of essential services to elders, including the IHS, to enhance care through increased reimbursements, future policy efforts must improve upon this funding situation and fulfill the federal trust responsibility.
Findings point to recommendations to improve the prevention and treatment of illness among American Indian elders by meeting their unique health care and insurance needs. Policies and practices must target meso and macro levels of contextual influence. Although Medicaid expansion under the ACA enables providers of essential services to elders, including the IHS, to enhance care through increased reimbursements, future policy efforts must improve upon this funding situation and fulfill the federal trust responsibility.
The survival rate after childhood cancer has improved to 80%. selleck kinase inhibitor The majority of childhood cancer survivors (CCS) will experience late complications which require follow up care, including access to their individual cancer treatment summary. The need to understand CCS needs and preferences in terms of ways to receive information e.g. digitally, becomes important. This study aims to through a mixed methods approach a) examine how CCS' health awareness was impacted by viewing their personalized digital treatment summary and follow-up recommendations, b) explore E health literacy, and c) determine self-reported survivorship experiences and health care usage.

Survivors with a recent visit to the Late effects clinic were eligible for the study (n = 70). A representative sample of primary diagnoses were invited (n = 28). 16 CCS were enrolled. Recent medical visits, e health literacy and impressions of the digital treatment summary were assessed by a survey in conjunction with viewing their digital treatment summarsituation and consequently aided empowerment. A digital treatment summary, provided by knowledgeable health care professionals, may increase the self-managed care and adherence to follow-up recommendations. Further insights into e health literacy in larger samples of CCS may determine to what extent health-related information can be communicated via digital resources to this at risk population.
Reading the treatment summaries furthered the survivors understanding of their health situation and consequently aided empowerment. A digital treatment summary, provided by knowledgeable health care professionals, may increase the self-managed care and adherence to follow-up recommendations. Further insights into e health literacy in larger samples of CCS may determine to what extent health-related information can be communicated via digital resources to this at risk population.
The essence of energy metabolism has spread to the field of esophageal cancer (ESC) cells. Herein, we tried to develop a prognostic prediction model for patients with ESC based on the expression profiles of energy metabolism associated genes.

The overall survival (OS) predictive gene signature was developed, internally and externally validated based on ESC datasets including The Cancer Genome Atlas (TCGA), GSE54993 and GSE19417 datasets. Hub genes were identified in each energy metabolism related molecular subtypes by weighted gene correlation network analysis, and then enrolled for determination of prognostic genes. Univariate, LASSO and multivariate Cox regression analysis were applied to assess prognostic genes and build the prognostic gene signature. Kaplan-Meier curve, time-dependent receiver operating characteristic (ROC) curve, nomogram, decision curve analysis (DCA), and restricted mean survival time (EMST) were used to assess the performance of the gene signature.

A novel energy metabolism based eight-gene signature (including UBE2Z, AMTN, AK1, CDCA4, TLE1, FXN, ZBTB6 and APLN) was established, which could dichotomize patients with significantly different OS in ESC. The eight-gene signature demonstrated independent prognostication potential in patient with ESC. The prognostic nomogram constructed based on the gene signature showed excellent predictive performance, whose robustness and clinical usability were higher than three previous reported prognostic gene signatures.

Our study established a novel energy metabolism based eight-gene signature and nomogram to predict the OS of ESC, which may help in precise clinical management.
Our study established a novel energy metabolism based eight-gene signature and nomogram to predict the OS of ESC, which may help in precise clinical management.
Angiogenesis assessment is important for personalized therapeutic intervention in patients with non-small-cell lung cancer (NSCLC). This study investigated whether radiologic parameters obtained by dynamic contrast-enhanced (DCE)-integrated magnetic resonance-positron emission tomography (MR-PET) could be used to quantitatively assess tumor angiogenesis in NSCLC.

This prospective cohort study included 75 patients with NSCLC who underwent DCE-integrated MR-PET at diagnosis. The following parameters were analyzed metabolic tumor volume (MTV), maximum standardized uptake value (SUV
), reverse reflux rate constant (k
), volume transfer constant (K
), blood plasma volume fraction (v
), extracellular extravascular volume fraction (v
), apparent diffusion coefficient (ADC), and initial area under the time-to-signal intensity curve at 60 s post enhancement (iAUC
). Serum biomarkers of tumor angiogenesis, including vascular endothelial growth factor-A (VEGF-A), angiogenin, and angiopoietin-1, were measured by enzyme-linked immunosorbent assays simultaneously.selleck kinase inhibitor