Marker-assisted optimization of an expert-based strategy for the acquisition of modern lettuce varieties to improve a genebank collection

To regularly improve the composition of the lettuce collection of the Centre for Genetic Resources, the Netherlands (CGN) with modern varieties, feedback from crop experts is used to select approximately 10% of the new material for incorporation in the collection. In the present study, assessments of six experts were compared to microsatellite data of 414 new varieties and 1408 existing accessions. Based on the microsatellite data, the extent to which the genetic diversity of the collection would be enriched (added value) was calculated for specific sets of new varieties. When individual assessments of experts were evaluated, the total added value of expert-based selections was not significantly higher compared to randomly chosen groups, except for a single expert. Unfamiliarity with new varieties was shown to be a crucial factor in the assessment of crop experts. According to the current acquisition protocol that seeks for consensus among experts, varieties are selected based on recommendations from at least three experts. This protocol also did not perform better than randomly chosen groups of new varieties. However, significantly better results were obtained with alternative protocols. It was concluded that breeding value was a more decisive criterion in the current acquisition protocol than maximal extension of the genetic diversity within the collection. A modified protocol addressing both commercial and diversity aspects was suggested in order to meet the demands of plant breeders as well as conservationist

Spatial clustering of array CGH features in combination with hierarchical multiple testing

We propose a new approach for clustering DNA features using array CGH data from multiple tumor samples. We distinguish data-collapsing: joining contiguous DNA clones or probes with extremely similar data into regions, from clustering: joining contiguous, correlated regions based on a maximum likelihood principle. The model-based clustering algorithm accounts for the apparent spatial patterns in the data. We evaluate the randomness of the clustering result by a cluster stability score in combination with cross-validation. Moreover, we argue that the clustering really captures spatial genomic dependency by showing that coincidental clustering of independent regions is very unlikely. Using the region and cluster information, we combine testing of these for association with a clinical variable in an hierarchical multiple testing approach. This allows for interpreting the significance of both regions and clusters while controlling the Family-Wise Error Rate simultaneously. We prove that in the context of permutation tests and permutation-invariant clusters it is allowed to perform clustering and testing on the same data set. Our procedures are illustrated on two cancer data sets

Disrupting the biological clock: Fertility benefits, egg freezing and proactive fertility management

In the last decade, the IVF sector has witnessed a shift from so-called reactive IVF to a new model of proactive fertility care. Whereas IVF was traditionally developed to treat people who found they were unable to conceive, the indication for IVF has broadened significantly to include a much wider group of potential patients through a new focus on proactive treatment of future (in)fertilities. This shift combines a number of new trends pertaining to preservation, prediction, private equity and platformisation, all of which have gained influence in contemporary assisted reproduction. This article focuses on the emergence of company-sponsored fertility benefits, which combines each of these trends. Whereas fertility benefits—especially egg freezing insurance—have primarily been discussed in terms of women’s empowerment or disenfranchisement, this article instead calls attention to the discursive, clinical and infrastructural shifts in contemporary assisted reproduction that have emerged with the rising popularity of these benefits. The analysis addresses these underdiscussed aspects of fertility benefits by focusing on the dynamics of demand, the shifts in the rationalisation of intensified treatment pathways in the face of new reimbursement practices, and the online, platform-based infrastructures that are built to provide these treatments. In doing so, it analyses how this remaking of fertility towards an ethos of proactive fertility management reflects broader capitalist tailwinds.The research on which this article was supported by the Wellcome Trust [grant number 209829/Z/17/Z], University of Cambridge, King’s College London and the Alan Turing Institute. I thank the two anonymous peer reviewers and the members of the Reproductive Sociology Research Group (ReproSoc) at the University of Cambridge for their valuable feedback

The Effect of Alcohol on Postprandial and Fasting Triglycerides

Alcohol has a significant additive effect on the postprandial triglyceride peak when it accompanies a meal containing fat, especially saturated fat. This results from a decrease in the breakdown of chylomicrons and VLDL remnants due to an acute inhibitory effect of alcohol on lipoprotein lipase activity. Furthermore, alcohol increases the synthesis of large VLDL particles in the liver, which is the main source of triglycerides in the hypertriglyceridemia associated with chronic excessive alcohol intake. In case of chronic consumption, lipoprotein lipase activity seems to adapt itself. The effect of alcohol on adipose tissues is less clear. Sometimes, a severe hypertriglyceridemia induced by alcohol (SHIBA) can be observed, especially in patients with type 2 diabetes mellitus and/or obesity increasing the risk of pancreatitis

Edgeworth expansions with exact cumulants for two-sample linear rank statistics

We show how to compute exact cumulants of two-sample linear rank statistics In order to approximate tail-probabilities of these statistics, we consider Edgeworth expansions using these exact cumulants instead of asymptotic cumulants. Finally, we use exact tail probabilities to show that in several cases Edgeworth expansions with exact cumulants provides a significantly better approximation than other existing methods

Exact distributions of two-sample rank statistics and block rank statistics using computer algebra

We derive generating functions for various rank statistics and we use computer algebra to compute the exact null distribution of these statistics. We present various techniques for reducing time and memory space used by the computations. We use the results to write Mathematica notebooks for computing exact tail-probabilities and to extend tables of critical values for some well-known rank statistics