Anesthetic management of a patient with a double inferior vena cava and pulmonary alveolar proteinosis who underwent bilateral living-donor lobar lung transplantation.

A 43-year-old woman with pulmonary fibrosis secondary to pulmonary alveolar proteinosis was scheduled to undergo lung transplantation. Before the lung transplantation, she had undergone multiple whole-lung lavage procedures on extracorporeal circulation (ECC), which had caused scarring of the right femoral subcutaneous tissues. Preoperative examination revealed a double inferior vena cava (IVC) with interiliac communication, and the left IVC ended at the left renal vein. Surgical exposure of the right femoral vessels was performed immediately after anesthetic induction for emergent vascular access to establish an ECC. Cardiopulmonary collapse did not occur and the ECC was not required until lung resection. The lung transplantation was completed uneventfully. Congenital IVC anomaly is rare, but may make cannulation through the femoral vein difficult. Scarring of the subcutaneous tissue could result in a difficult "percutaneous" approach to the vessels. Evaluation of the vascular anatomy related to the establishment of an ECC is important before lung transplantation

An updated radiocarbon-based ice margin chronology for the last deglaciation of the North American Ice Sheet Complex

The North American Ice Sheet Complex (NAISC; consisting of the Laurentide, Cordilleran and Innuitian ice sheets) was the largest ice mass to repeatedly grow and decay in the Northern Hemisphere during the Quaternary. Understanding its pattern of retreat following the Last Glacial Maximum is critical for studying many facets of the Late Quaternary, including ice sheet behaviour, the evolution of Holocene landscapes, sea level, atmospheric circulation, and the peopling of the Americas. Currently, the most up-to-date and authoritative margin chronology for the entire ice sheet complex is featured in two publications (Geological Survey of Canada Open File 1574 [Dyke et al., 2003]; ‘Quaternary Glaciations – Extent and Chronology, Part II’ [Dyke, 2004]). These often-cited datasets track ice margin recession in 36 time slices spanning 18 ka to 1 ka (all ages in uncalibrated radiocarbon years) using a combination of geomorphology, stratigraphy and radiocarbon dating. However, by virtue of being over 15 years old, the ice margin chronology requires updating to reflect new work and important revisions. This paper updates the aforementioned 36 ice margin maps to reflect new data from regional studies. We also update the original radiocarbon dataset from the 2003/2004 papers with 1541 new ages to reflect work up to and including 2018. A major revision is made to the 18 ka ice margin, where Banks and Eglinton islands (once considered to be glacial refugia) are now shown to be fully glaciated. Our updated 18 ka ice sheet increased in areal extent from 17.81 to 18.37 million km2, which is an increase of 3.1% in spatial coverage of the NAISC at that time. Elsewhere, we also summarize, region-by-region, significant changes to the deglaciation sequence. This paper integrates new information provided by regional experts and radiocarbon data into the deglaciation sequence while maintaining consistency with the original ice margin positions of Dyke et al. (2003) and Dyke (2004) where new information is lacking; this is a pragmatic solution to satisfy the needs of a Quaternary research community that requires up-to-date knowledge of the pattern of ice margin recession of what was once the world’s largest ice mass. The 36 updated isochrones are available in PDF and shapefile format, together with a spreadsheet of the expanded radiocarbon dataset (n = 5195 ages) and estimates of uncertainty for each interval

Fine-Scale Mapping of the 4q24 Locus Identifies Two Independent Loci Associated with Breast Cancer Risk

Background: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. Methods: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. Results: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10−4; OR, 1.04; 95% confidence interval (CI), 1.02–1.07] and rs77928427 (P = 1.86 × 10−4; OR, 1.04; 95% CI, 1.02–1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r2 ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor–binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. Conclusion: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. Impact: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk

New approach to risk determination: development of risk profile for new falls among community-dwelling older people by use of a genetic algorithm neural network (GANN)

Background. Falls risk in older people is multifactorial and complex. There is uncertainty about the importance of specific risk factors. Genetic algorithm neural networks (GANNs) can examine all available data and select the best nonlinear combination of variables for predicting falls. The aim of this work was to develop a risk profile for operationally defined new falls in a random sample of older people by use of a GANN approach. Methods. A random sample of 1042 community-dwelling people aged 65 and older, living in Nottingham, England, were interviewed at baseline (1985) and survivors reinterviewed at a 4-year follow-up (n = 690). The at-risk group (n = 435) was defined as those survivors who had not fallen in the year before the baseline interview. A GANN was used to examine all available attributes and, from these, to select the best nonlinear combination of variables that predicted those people who fell 4 years later. Results. The GANN selected a combination of 16 from a potential 253 variables and correctly predicted 35/114 new fallers (sensitivity = 31%; positive predictive value = 57%) and 295/321 nonfallers (specificity = 92%; negative predictive value = 79%); total correct = 76%. The variables selected by the GANN related to personal health, opportunity, and personal circumstances. Conclusions. This study demonstrates the capacity of GANNs to examine all available data and then to identify the best 16 variables for predicting falls. The risk profile complements risk factors in the current literature identified by use of standard and conventional statistical methods. Additional data about environmental factors might enhance the sensitivity of the GANN approach and help identify those older people who are at risk of falling