THE EFFECT OF UNREPORTED DEMAND ON THE ​F/A-18’S SUPPLY CHAIN

This research investigates the causes of unreported demand associated with F/A-18 aircraft components during the execution of cannibalization and the issuance of repairable parts from the Stricken Aircraft Reclamation and Disposal Program (SARDIP). The current transition to the F-35 Joint Strike Fighter across the entire Marine Corps F/A-18 Type Model Series (TMS) platform provides an opportunity to research and analyze various aspects of the divestiture process. During the divestiture period of the F/A-18 platform, missing demand signals lead to inaccuracies in demand forecasting. This inaccurate demand capture increases stress on the supply system and future funding requirements within the organization. This study analyzes five years of demand data gathered from the Navy Enterprise Resource Planning (ERP) system in order to identify causes and sources of lost demand associated with cannibalization and SARDIP issues. In addition, this study presents an analysis of current Marine Corps aviation supply policies and cannibalization actions to identify shortfalls in demand reporting. The data gathered suggest that unreported demand leads to increases in demand variability and the ability to allocate funds for F/A-18 components. Although the impacts of unreported demand for the F/A-18 will disappear once the platform is no longer in service, unreported demand will continue to affect all aircraft remaining in service.Captain, United States Marine CorpsCaptain, United States Marine CorpsMajor, United States Marine CorpsApproved for public release. Distribution is unlimited

Iron and Cancer: More Ore To Be Mined

Iron is an essential nutrient that facilitates cell proliferation and growth. However, iron also has the capacity to engage in redox cycling and free radical formation. Therefore, iron can contribute to both tumour initiation and tumour growth; recent work has also shown that iron has a role in the tumour microenvironment and in metastasis. Pathways of iron acquisition, efflux, storage and regulation are all perturbed in cancer, suggesting that reprogramming of iron metabolism is a central aspect of tumour cell survival. Signalling through hypoxia-inducible factor (HIF) and WNT pathways may contribute to altered iron metabolism in cancer. Targeting iron metabolic pathways may provide new tools for cancer prognosis and therapy

Body mass index and breast cancer survival:a Mendelian randomization analysis

Abstract Background: There is increasing evidence that elevated body mass index (BMI) is associated with reduced survival for women with breast cancer. However, the underlying reasons remain unclear. We conducted a Mendelian randomization analysis to investigate a possible causal role of BMI in survival from breast cancer. Methods: We used individual-level data from six large breast cancer case-cohorts including a total of 36 210 individuals (2475 events) of European ancestry. We created a BMI genetic risk score (GRS) based on genotypes at 94 known BMI-associated genetic variants. Association between the BMI genetic score and breast cancer survival was analysed by Cox regression for each study separately. Study-specific hazard ratios were pooled using fixed-effect meta-analysis. Results: BMI genetic score was found to be associated with reduced breast cancer-specific survival for estrogen receptor (ER)-positive cases [hazard ratio (HR) = 1.11, per one-unit increment of GRS, 95% confidence interval (CI) 1.01–1.22, P = 0.03). We observed no association for ER-negative cases (HR = 1.00, per one-unit increment of GRS, 95% CI 0.89–1.13, P = 0.95). Conclusions: Our findings suggest a causal effect of increased BMI on reduced breast cancer survival for ER-positive breast cancer. There is no evidence of a causal effect of higher BMI on survival for ER-negative breast cancer cases

A transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer.

The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P < 5.82 × 10-6, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology

The (not so) controversial role of DNA methylation in epigenetic inheritance across generations.

It has been demonstrated originally in plants that phenotypic traits, such as floral symmetry, can be caused by changes of methylation patterns of specific genes. Such traits can be transgenerationally inherited for multiple generations and remain associated with cytosine methylation patterns. Whether genomic methylation may also contribute to epigenetic inheritance across generations in vertebrates and notably in mammals is still more controversial. One reason for this tentativeness is the dual occurrence of global genomic de-methylation first in pre-implantation embryos and subsequently in primordial germ cells (PGCs) of mammals. Although gene focused cases of epigenetic inheritance associated with genomic DNA methylation have been well studied mostly in rodents (such as imprinted genes and the Agouti viable yellow, Avy, allele), it is still a matter of debate whether genomic DNA methylation may provide a more general mechanism for the epigenetic inheritance of acquired traits across generations. We review the current literature on this topic with a focus on the potential role of DNA methylation for epigenetic inheritance across generations in mammals

A transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer

Abstract The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P &lt; 5.82 × 10−6, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology

Genome-wide association study of germline variants and breast cancer-specific mortality

Abstract Background: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry. Methods: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP). Results: We did not find any variant associated with breast cancer-specific mortality at P &lt; 5 × 10−8. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10−7, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84–0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10−7, HR = 1.27, 95% CI = 1.16–1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster. Conclusions: We uncovered germline variants on chromosome 7 at BFDP &lt; 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients