Goodwinsheridan9191

To provide a potential biological, mechanistic link for the well-established association between primary care access and reduced mortality, this study sought to measure the impact of having a usual source of health care on leukocyte telomere length (LTL).

Our study population included 3202 participants aged 50 to 84 years from National Health and Nutrition Examination Survey 1999 to 2001.

Cross-sectional Study. LTLs between people with and without a usual source of care were compared using unadjusted and adjusted linear regression models. Fully adjusted models accounted for demographic characteristics, health conditions, and health behaviors.

After controlling for individual factors, health conditions, and health behaviors, people who had a usual source of health care had significantly longer LTL (β = 89.8 base pairs,

-value = .005) compared with those without a usual source of care; corresponding to approximately 7 years of life.

Having a usual source of health care is associated with longer LTL among older adults. This study provides a potential biologic link for the noted association between primary care access and reduced mortality that has been observed at the individual and population level.

Having a usual source of health care is associated with longer LTL among older adults. This study provides a potential biologic link for the noted association between primary care access and reduced mortality that has been observed at the individual and population level.Using data from 2014 to 2018, we found that the proportion of family physicians caring for children under age 5 years and between ages 5 and 18 years has significantly declined. This has implications for the pediatric primary care workforce and may exacerbate inequities in access to care for pediatric patients in all geographies, particularly those in areas with a shortage of pediatricians.This issue of the Journal contains some exceptional research articles. A few are truly "must-reads," including a fascinating look at the relationship between having a usual source of care and telomere length. Glucosamine/chrondroitin supplementation seems to be helpful for more than just arthritis pain. There is a very practical advice on keeping patients discharged from the emergency department out of the hospital and on reducing patient requests for inappropriate antibiotics. This issue also features 5 articles addressing how family physicians can combat the opioid epidemic. Three articles highlight research on diabetes and another 3 on breast cancer. Payment reform, dermoscopy, and telemedicine are among many other topics covered.

There is a need for improved selection of patients for adjuvant chemotherapy after resection of non-metastatic colorectal cancer (CRC). Regulator of chromosome condensation 2 (RCC2) is a potential prognostic biomarker. We report on the establishment of a robust protocol for RCC2 expression analysis and prognostic tumour biomarker evaluation in patients who did and did not receive adjuvant chemotherapy.

RCC2 was analysed in 2916 primary CRCs from the QUASAR2 randomised trial and two single-hospital Norwegian series. A new protocol using fluorescent antibody staining and digital image analysis was optimised. Biomarker value for 5-year relapse-free survival was analysed in relation to tumour stage, adjuvant chemotherapy and the molecular markers microsatellite instability,

/



/

mutations and

expression.

Low RCC2 expression was scored in 41% of 2696 evaluable samples. Among patients with stage I-III CRC who had not received adjuvant chemotherapy, low RCC2 expression was an independent marker of inferior 5-year relapse-free survival in multivariable Cox models including clinicopathological factors and molecular markers (HR 1.45, 95% CI 1.09 to 1.94, p=0.012, N=521). RCC2 was not prognostic in patients who had received adjuvant chemotherapy, neither in QUASAR2 nor the pooled Norwegian series. The interaction between RCC2 and adjuvant chemotherapy for prediction of patient outcome was significant in stage III, and strongest among patients with microsatellite stable tumours (p

=0.028).

Low expression of RCC2 is a biomarker for poor prognosis in patients with stage I-III CRC and seems to be a predictive biomarker for effect of adjuvant chemotherapy.

Low expression of RCC2 is a biomarker for poor prognosis in patients with stage I-III CRC and seems to be a predictive biomarker for effect of adjuvant chemotherapy.The molecular process of transcription by RNA Polymerase II is highly conserved among eukaryotes ("classic model"). A distinct way of locating transcription start sites (TSSs) has been identified in a budding yeast Saccharomyces cerevisiae ("scanning model"). Herein, we applied genomic approaches to elucidate the origin of the scanning model and its underlying genetic mechanisms. We first identified TSSs at single-nucleotide resolution for 12 yeast species using the nAnT-iCAGE technique, which significantly improved the annotations of these genomes by providing accurate 5' boundaries for protein-coding genes. We then inferred the initiation mechanism of each species based on its TSS maps and genome sequences. We discovered that the scanning model likely originated after the split of Yarrowia lipolytica and the other budding yeasts. AMG510 molecular weight Species that use the scanning model showed an adenine-rich region immediately upstream of the TSS that might facilitate TSS selection. Both initiation mechanisms share a strong preference for pyrimidine-purine dinucleotides surrounding the TSS. Our results suggest that the purine is required to accurately recruit the first nucleotide, thereby increasing the chances of a messenger RNA of being capped during mRNA maturation, which is critical for efficient translation initiation during protein biosynthesis. Based on our findings, we propose a model for TSS selection in the scanning-model species, as well as a model for the stepwise process responsible for the origin and evolution of the scanning model.Single-cell DNA methylation data has become increasingly abundant and has uncovered many genes with a positive correlation between expression and promoter methylation, challenging the common dogma based on bulk data. However, computational tools for analyzing single-cell methylome data are lagging far behind. A number of tasks, including cell type calling and integration with transcriptome data, requires the construction of a robust gene activity matrix as the prerequisite but challenging task. The advent of multi-omics data enables measurement of both DNA methylation and gene expression for the same single cells. Although such data is rather sparse, they are sufficient to train supervised models that capture the complex relationship between DNA methylation and gene expression and predict gene activities at single-cell level. Here, we present methylome association by predictive linkage to expression (MAPLE), a computational framework that learns the association between DNA methylation and expression using both gene- and cell-dependent statistical features.