Confound-leakage: confound removal in machine learning leads to leakage

BACKGROUND: Machine learning (ML) approaches are a crucial component of modern data analysis in many fields, including epidemiology and medicine. Nonlinear ML methods often achieve accurate predictions, for instance, in personalized medicine, as they are capable of modeling complex relationships between features and the target. Problematically, ML models and their predictions can be biased by confounding information present in the features. To remove this spurious signal, researchers often employ featurewise linear confound regression (CR). While this is considered a standard approach for dealing with confounding, possible pitfalls of using CR in ML pipelines are not fully understood. RESULTS: We provide new evidence that, contrary to general expectations, linear confound regression can increase the risk of confounding when combined with nonlinear ML approaches. Using a simple framework that uses the target as a confound, we show that information leaked via CR can increase null or moderate effects to near-perfect prediction. By shuffling the features, we provide evidence that this increase is indeed due to confound-leakage and not due to revealing of information. We then demonstrate the danger of confound-leakage in a real-world clinical application where the accuracy of predicting attention-deficit/hyperactivity disorder is overestimated using speech-derived features when using depression as a confound. CONCLUSIONS: Mishandling or even amplifying confounding effects when building ML models due to confound-leakage, as shown, can lead to untrustworthy, biased, and unfair predictions. Our expose of the confound-leakage pitfall and provided guidelines for dealing with it can help create more robust and trustworthy ML models

Weak Glycolipid Binding of a Microdomain-Tracer Peptide Correlates with Aggregation and Slow Diffusion on Cell Membranes

10.1371/journal.pone.0051222PLoS ONE712

Ice loss from the East Antarctic Ice Sheet during late Pleistocene interglacials

Understanding ice sheet behaviour in the geological past is essential for evaluating the role of the cryosphere in the climate system and for projecting rates and magnitudes of sea level rise in future warming scenarios1,2,3,4. Although both geological data5,6,7 and ice sheet models3,8 indicate that marine-based sectors of the East Antarctic Ice Sheet were unstable during Pliocene warm intervals, the ice sheet dynamics during late Pleistocene interglacial intervals are highly uncertain3,9,10. Here we provide evidence from marine sedimentological and geochemical records for ice margin retreat or thinning in the vicinity of the Wilkes Subglacial Basin of East Antarctica during warm late Pleistocene interglacial intervals. The most extreme changes in sediment provenance, recording changes in the locus of glacial erosion, occurred during marine isotope stages 5, 9, and 11, when Antarctic air temperatures11 were at least two degrees Celsius warmer than pre-industrial temperatures for 2,500 years or more. Hence, our study indicates a close link between extended Antarctic warmth and ice loss from the Wilkes Subglacial Basin, providing ice-proximal data to support a contribution to sea level from a reduced East Antarctic Ice Sheet during warm interglacial intervals. While the behaviour of other regions of the East Antarctic Ice Sheet remains to be assessed, it appears that modest future warming may be sufficient to cause ice loss from the Wilkes Subglacial Basin

Using viral vectors as gene transfer tools (Cell Biology and Toxicology Special Issue: ETCS-UK 1 day meeting on genetic manipulation of cells)

In recent years, the development of powerful viral gene transfer techniques has greatly facilitated the study of gene function. This review summarises some of the viral delivery systems routinely used to mediate gene transfer into cell lines, primary cell cultures and in whole animal models. The systems described were originally discussed at a 1-day European Tissue Culture Society (ETCS-UK) workshop that was held at University College London on 1st April 2009. Recombinant-deficient viral vectors (viruses that are no longer able to replicate) are used to transduce dividing and post-mitotic cells, and they have been optimised to mediate regulatable, powerful, long-term and cell-specific expression. Hence, viral systems have become very widely used, especially in the field of neurobiology. This review introduces the main categories of viral vectors, focusing on their initial development and highlighting modifications and improvements made since their introduction. In particular, the use of specific promoters to restrict expression, translational enhancers and regulatory elements to boost expression from a single virion and the development of regulatable systems is described

Significance of vascular endothelial growth factor in growth and peritoneal dissemination of ovarian cancer

Vascular endothelial growth factor (VEGF) is a key regulator of angiogenesis which drives endothelial cell survival, proliferation, and migration while increasing vascular permeability. Playing an important role in the physiology of normal ovaries, VEGF has also been implicated in the pathogenesis of ovarian cancer. Essentially by promoting tumor angiogenesis and enhancing vascular permeability, VEGF contributes to the development of peritoneal carcinomatosis associated with malignant ascites formation, the characteristic feature of advanced ovarian cancer at diagnosis. In both experimental and clinical studies, VEGF levels have been inversely correlated with survival. Moreover, VEGF inhibition has been shown to inhibit tumor growth and ascites production and to suppress tumor invasion and metastasis. These findings have laid the basis for the clinical evaluation of agents targeting VEGF signaling pathway in patients with ovarian cancer. In this review, we will focus on VEGF involvement in the pathophysiology of ovarian cancer and its contribution to the disease progression and dissemination

Spin coherence and 14N ESEEM effects of nitrogen-vacancy centers in diamond with X-band pulsed ESR

Pulsed ESR experiments are reported for ensembles of negatively-charged nitrogen-vacancy centers (NV ) in diamonds at X-band magnetic fields (280–400 mT) and low temperatures (2–70 K). The NV centers in synthetic type IIa diamonds (nitrogen impurity concentration  <1 ppm) are prepared with bulk concentrations of 2 ⋅ 10 cm to 4 ⋅ 10 cm by high-energy electron irradiation and subsequent annealing. We find that a proper post-radiation anneal (1000°C for 60 min) is critically important to repair the radiation damage and to recover long electron spin coherence times for NV s. After the annealing, spin coherence times of T  = 0.74ms at 5 K are achieved, being only limited by C nuclear spectral diffusion in natural abundance diamonds. By measuring the temperature dependence of T in the under-annealed diamonds (900°C) we directly extract the density (10 cm ) and activation energy (2.5 meV) of unannealed defects responsible for the faster NV decoherence. At X-band magnetic fields, strong electron spin echo envelope modulation (ESEEM) is observed originating from the central N nucleus, and we extract accurate N nuclear hypefine and quadrupole tensors. In addition, the ESEEM effects from two proximal C sites (second-nearest neighbor and fourth-nearest neighbor) are resolved and the respective C hyperfine coupling constants are extracted.  −  − 13  −3 14  −3  − 13 14 −16  −3  − 14 14 13 13 2