Variable selection with P-splines in functional linear regression: Application in graft-versus-host disease

This paper focuses on the problems of estimation and variable selection in the functional linear regression model (FLM) with functional response and scalar covariates. To this end, two different types of regularization (L₁ and L₂) are considered in this paper. On the one hand, a sample approach for functional LASSO in terms of basis representation of the sample values of the response variable is proposed. On the other hand, we propose a penalized version of the FLM by introducing a P-spline penalty in the least squares fitting criterion. But our aim is to propose P-splines as a powerful tool simultaneously for variable selection and functional parameters estimation. In that sense, the importance of smoothing the response variable before fitting the model is also studied. In summary, penalized (L₁ and L₂) and nonpenalized regression are combined with a presmoothing of the response variable sample curves, based on regression splines or P-splines, providing a total of six approaches to be compared in two simulation schemes. Finally, the most competitive approach is applied to a real data set based on the graft-versus-host disease, which is one of the most frequent complications (30% –50%) in allogeneic hematopoietic stem-cell transplantation.     

Reference gene selection for quantitative real-time PCR normalization in tomato subjected to nitrogen, cold, and light stress

We examined eight putative consistently expressed genes—actin (ACT), β-tubulin, elongation factor 1α (EF1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), phosphoglycerate kinase (PGK), ribosomal protein L2 (RPL2), ubiquitin (UBI), and a catalytic subunit of protein phosphatase 2A (PP2Acs)—for their potential as references for the normalization of gene expression in tomato leaves. Expression stability of candidate reference genes was tested during growth conditions of nitrogen (N) starvation, low temperature, and suboptimal light. The geNorm algorithm, using reciprocal cross-validation among a larger group of candidate references, was applied for this purpose. The widely used reference genes GAPDH and PGK were top ranked during light stress but poorly ranked during N and cold stress. In contrast, EF1 was top ranked during N and cold stress but poorly ranked during light stress. The novel references RPL2 and PP2Acs, as well as the traditional references ACT and UBI, appeared to be stably expressed when looking at the data set as a whole. No gene was identified that exhibited such a constant level of expression as to outperform the other candidates under all experimental conditions. Thus, the results highlight the need for normalizing gene expression in tomato using the geometric average of multiple carefully selected reference genes.     

Effect of N2-He-O2 on decompression outcome in rats after variable time-at-depth dives

No study of decompression sickness has examined both variable gas mixtures and variable time at depth to the point of statistical significance. This investigation examined the effect of N2-He-O2 on decompression outcome in rats after variable time-at-depth dives. Unanesthetized male albino rats were subjected to one of two series of simulated dives: 1) N2-He-O2 dives (20.9% O2) at 175 feet of seawater fsw) and 2) N2-O2 dives (variable percentage of O2; depths from 141 to 207 fsw). Time at depth ranged from 10 to 120 min; rats were then decompressed within 10 s to surface pressure. The probability of decompression sickness (severe bends symptoms or death) was analyzed with a Hill equation model, with parameters for gas potency and equilibrium time for the three gases and weight of the animal. Relative potencies for the three gases were of similar magnitude for bends and statistically different for death in ascending order: O2 less than He less than N2. Estimated gas uptake rates were different. N2 took three to four times as long as He to reach full effect; the rate of O2 appeared to be considerably shorter than that of N2 or He. The large influence of O2 on decompression outcome questions the simplistic view that O2 cannot contribute to the decompression requirement.