The proteasome: a viable target in non-small cell lung cancer?

Giaccone, G. [Promotor

Learning causal models that make correct manipulation predictions with time series data

One of the fundamental purposes of causal models is using them to predict the effects of manipulating various components of a system. It has been argued by Dash (2005, 2003) that the Do operator will fail when applied to an equilibrium model, unless the underlying dynamic system obeys what he calls Equilibration-Manipulation Commutability. Unfortunately, this fact renders most existing causal discovery algorithms unreliable for reasoning about manipulations. Motivated by this caveat, in this paper we present a novel approach to causal discovery of dynamic models from time series. The approach uses a representation of dynamic causal models motivated by Iwasaki and Simon (1994), which asserts that all “causation across time" occurs because a variable’s derivative has been affected instantaneously. We present an algorithm that exploits this representation within a constraint-based learning framework by numerically calculating derivatives and learning instantaneous relationships. We argue that due to numerical errors in higher order derivatives, care must be taken when learning causal structure, but we show that the Iwasaki-Simon representation reduces the search space considerably, allowing us to forego calculating many high-order derivatives. In order for our algorithm to discover the dynamic model, it is necessary that the time-scale of the data is much finer than any temporal process of the system. Finally, we show that our approach can correctly recover the structure of a fairly complex dynamic system, and can predict the effect of manipulations accurately when a manipulation does not cause an instability. To our knowledge, this is the first causal discovery algorithm that has demonstrated that it can correctly predict the effects of manipulations for a system that does not obey the EMC condition

African Land Ecology: Opportunities and Constraints for Agricultural Development

Current agriculture in Sub-Sahara Africa is undeveloped and the Green Revolution has left the continent largely untouched. Poor performance is often related to a number of socio-economic factors. In this paper we argue that there are also some specifities of natural resources, namely local homogeneity and spatial diversity of the pre-dominant Basement Complex soils, that imply that simple fertilizer strategies may not produce the yield increases obtained elsewhere. Keywords: Sub-Sahara Africa, Agro-Ecology, Land use, Land resources, Basement Complex, Green Revolution, Micronutrients, Fertilizer Policy

Predictors of Gastrointestinal Transit Times in Colon Capsule Endoscopy

Optimizing the accuracy of colon capsule endoscopy (CCE) requires high completion rates. To prevent incomplete CCE, we aimed to identify predictors associated with slow CCE transit times. METHODS: In this population-based study, participants received CCE with a split-dose polyethylene glycol bowel preparation and booster regimen (0.5 L oral sulfate solution and 10 mg metoclopramide if capsule remained in stomach for > 1 hour). The following predictors were assessed: age, sex, body mass index (BMI), smoking, coffee and fiber intake, diet quality, physical activity, dyspeptic complaints, stool pattern, history of abdominal surgery, medication use, and CCE findings. Multivariable logistic and linear regressions with backward elimination were performed. RESULTS: We analyzed 451 CCE procedures with a completion rate of 51.9%. The completion rate was higher among older participants (odds ratio [OR] 1.54, 95% confidence interval [CI] 1.04–2.28, P = 0.03) and participants with a changed stool pattern (OR 2.27, 95% CI 1.20–4.30, P = 0.01). Participants with a history of abdominal surgery had a lower completion rate (OR 0.54, 95% CI 0.36–0.80, P = 0.003). Participants with higher BMI had faster stomach, small bowel, and total transit times (β = −0.10, P = 0.01; β = −0.14, P = 0.001; β = −0.12, P = 0.01). A faster small bowel transit was found in participants with a changed stool pattern (β = −0.08, P = 0.049) and the use of metoclopramide (β = −0.14, P = 0.001). Participants with high fiber intake had a slower colonic transit (β = 0.11, P = 0.03). DISCUSSION: Younger age, unchanged stool pattern, history of abdominal surgery, low BMI, and high fiber intake resulted in slower CCE transit times and lower completion rates. In future practice, these factors can be considered to adjust preparation protocols

Intra- and interobserver reliability in measuring aortic root rotation with cardiac magnetic resonance imaging

Background: The rotational position of the aortic root (AoR) is of substantial clinical interest as it has been associated with severe aortic complications, such as aortic dissections. We described a cardiac magnetic resonance (CMR)-based method for measuring AoR rotation and evaluated the reliability of measurements. Methods: CMR was used for measuring AoR rotation in 50 consecutive healthy subjects. Intra- and interobserver reliability were assessed by comparing repeated measurements by the same analyst and by three independent analysts. The angles of the non-coronary sinus (NCS), right coronary sinus (RCS), and left coronary sinus (LCS) were measured relative to the interatrial septum (IAS). The angle between IAS and posterior atrial wall was measured to examine the reliability of the IAS as a key anatomical landmark. Intra- and interobserver agreement were determined using intraclass correlation coefficients (ICCs). Results: Images of 47/50 (94%) subjects were analyzed; three were excluded due to insufficient image quality. The mean ± standard deviation (SD) AoR rotation angles of NCS, RCS, and LCS were 25.9°±12.9°, 37.5°±15.2°, and 97.0°±13.1°, respectively. For measurements of AoR rotation, both intraobserver [NCS: ICC =0.94, 95% confidence interval (CI): 0.88–0.96; RCS: ICC =0.93, 95% CI: 0.87–0.96; LCS: ICC =0.91, 95% CI: 0.84–0.95] and interobserver agreement (NCS: ICC =0.90, 95% CI: 0.84–0.94; RCS: ICC =0.86, 95% CI: 0.77–0.92; LCS: ICC =0.87, 95% CI: 0.80–0.92) were excellent. The IAS angle was 79.2°±8.9°; its intraobserver agreement was somewhat higher (ICC =0.94, 95% CI: 0.88–0.96) than the interobserver agreement (ICC =0.76, 95% CI: 0.63–0.85). Conclusions: The present study in healthy subjects reports a CMR-based approach for measuring AoR rotation. CMR allows to quantify AoR rotation with excellent intra- and interobserver agreement.</p

Reference values for white blood-cell-based inflammatory markers in the Rotterdam Study

Novel prognostic inflammatory markers of cancer survival and cardiovascular disease are; the neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR) and the systemic immune-