On the use of cross-validation for the calibration of the adaptive lasso

Cross-validation is the standard method for hyperparameter tuning, or calibration, of machine learning algorithms. The adaptive lasso is a popular class of penalized approaches based on weighted L₁-norm penalties, with weights derived from an initial estimate of the model parameter. Although it violates the paramount principle of cross-validation, according to which no information from the hold-out test set should be used when constructing the model on the training set, a “naive” cross-validation scheme is often implemented for the calibration of the adaptive lasso. The unsuitability of this naive cross-validation scheme in this context has not been well documented in the literature. In this work, we recall why the naive scheme is theoretically unsuitable and how proper cross-validation should be implemented in this particular context. Using both synthetic and real-world examples and considering several versions of the adaptive lasso, we illustrate the flaws of the naive scheme in practice. In particular, we show that it can lead to the selection of adaptive lasso estimates that perform substantially worse than those selected via a proper scheme in terms of both support recovery and prediction error. In other words, our results show that the theoretical unsuitability of the naive scheme translates into suboptimality in practice, and call for abandoning it.     

TACE/ADAM-17 maturation and activation of sheddase activity require proprotein convertase activity

Proprotein convertases (PCs) have been proposed to play a role in tumor necrosis factor-alpha converting enzyme (TACE) processing/activation. Using the furin-deficient LoVo cells, as well as the furin-proficient synoviocytes and HT1080 cells expressing the furin inhibitor alpha(1)-PDX, we demonstrate that furin activity alone is not sufficient for effective maturation and activation of the TACE enzyme. Data from in vitro and in vivo cleavage assays indicate that PACE-4, PC5/PC6, PC1 and PC2 can directly cleave the TACE protein and/or peptide. PC inhibition in macrophages reduced the release of soluble TNF-alpha from transmembrane pro-TNF-alpha. We therefore conclude that furin, in addition to other candidate PCs, is involved in TACE maturation and activation.     

Dietary supplementation with Agaricus blazei murill extract prevents diet‐induced obesity and insulin resistance in rats

Objective:

Dietary supplement may potentially help to fight obesity and other metabolic disorders such as insulin‐resistance and low‐grade inflammation. The present study aimed to test whether supplementation with Agaricus blazei murill (ABM) extract could have an effect on diet‐induced obesity in rats.

Design and Methods:

Wistar rats were fed with control diet (CD) or high‐fat diet (HF) and either with or without supplemented ABM for 20 weeks.

Results:

HF diet‐induced body weight gain and increased fat mass compared to CD. In addition HF‐fed rats developed hyperleptinemia and insulinemia as well as insulin resistance and glucose intolerance. In HF‐fed rats, visceral adipose tissue also expressed biomarkers of inflammation. ABM supplementation in HF rats had a protective effect against body weight gain and all study related disorders. This was not due to decreased food intake which remained significantly higher in HF rats whether supplemented with ABM or not compared to control. There was also no change in gut microbiota composition in HF supplemented with ABM. Interestingly, ABM supplementation induced an increase in both energy expenditure and locomotor activity which could partially explain its protective effect against diet‐induced obesity. In addition a decrease in pancreatic lipase activity is also observed in jejunum of ABM‐treated rats suggesting a decrease in lipid absorption.

Conclusions:

Taken together these data highlight a role for ABM to prevent body weight gain and related disorders in peripheral targets independently of effect in food intake in central nervous system.     

BBGD: an online database for blueberry genomic data

Background  

Blueberry is a member of the Ericaceae family, which also includes closely related cranberry and more distantly related rhododendron, azalea, and mountain laurel. Blueberry is a major berry crop in the United States, and one that has great nutritional and economical value. Extreme low temperatures, however, reduce crop yield and cause major losses to US farmers. A better understanding of the genes and biochemical pathways that are up- or down-regulated during cold acclimation is needed to produce blueberry cultivars with enhanced cold hardiness. To that end, the blueberry genomics database (BBDG) was developed. Along with the analysis tools and web-based query interfaces, the database serves both the broader Ericaceae research community and the blueberry research community specifically by making available ESTs and gene expression data in searchable formats and in elucidating the underlying mechanisms of cold acclimation and freeze tolerance in blueberry.     

A Barley Efflux Transporter Operates in a Na+-Dependent Manner,as Revealed by a Multidisciplinary Platform

Plant growth and survival depend upon the activity of membrane transporters that control the movement and distribution of solutes into, around, and out of plants. Although many plant transporters are known, their intrinsic properties make them difficult to study. In barley (Hordeum vulgare), the root anion-permeable transporter Bot1 plays a key role in tolerance to high soil boron, facilitating the efflux of borate from cells. However, its three-dimensional structure is unavailable and the molecular basis of its permeation function is unknown. Using an integrative platform of computational, biophysical, and biochemical tools as well as molecular biology, electrophysiology, and bioinformatics, we provide insight into the origin of transport function of Bot1. An atomistic model, supported by atomic force microscopy measurements, reveals that the protein folds into 13 transmembrane-spanning and five cytoplasmic α-helices. We predict a trimeric assembly of Bot1 and the presence of a Na⁺ ion binding site, located in the proximity of a pore that conducts anions. Patch-clamp electrophysiology of Bot1 detects Na⁺-dependent polyvalent anion transport in a Nernstian manner with channel-like characteristics. Using alanine scanning, molecular dynamics simulations, and transport measurements, we show that conductance by Bot1 is abolished by removal of the Na⁺ ion binding site. Our data enhance the understanding of the permeation functions of Bot1.     

Predicting the activity phase of a follower neuron with A-current in an inhibitory network

The transient potassium A-current is present in most neurons and plays an important role in determining the timing of action potentials. We examine the role of the A-current in the activity phase of a follower neuron in a rhythmic feed-forward inhibitory network with a reduced three-variable model and conduct experiments to verify the usefulness of our model. Using geometric analysis of dynamical systems, we explore the factors that determine the onset of activity in a follower neuron following release from inhibition. We first analyze the behavior of the follower neuron in a single cycle and find that the phase plane structure of the model can be used to predict the potential behaviors of the follower neuron following release from inhibition. We show that, depending on the relative scales of the inactivation time constant of the A-current and the time constant of the recovery variable, the follower neuron may or may not reach its active state following inhibition. Our simple model is used to derive a recursive set of equations to predict the contribution of the A-current parameters in determining the activity phase of a follower neuron as a function of the duration and frequency of the inhibitory input it receives. These equations can be used to demonstrate the dependence of activity phase on the period and duty cycle of the periodic inhibition, as seen by comparing the predictions of the model with the activity of the pyloric constrictor (PY) neurons in the crustacean pyloric network.     

SCNProDB: A database for the identification of soybean cyst nematode proteins

Soybean cyst nematode (Heterodera glycines, SCN) is the most destructive pathogen of soybean around the world. Crop rotation and resistant cultivars are used to mitigate the damage of SCN, but these approaches are not completely successful because of the varied SCN populations. Thus, the limitations of these practices with soybean dictate investigation of other avenues of protection of soybean against SCN, perhaps through genetically engineering of broad resistance to SCN. For better understanding of the consequences of genetic manipulation, elucidation of SCN protein composition at the subunit level is necessary. We have conducted studies to determine the composition of SCN proteins using a proteomics approach in our laboratory using twodimensional polyacrylamide gel electrophoresis (2D-PAGE) to separate SCN proteins and to characterize the proteins further using mass spectrometry. Our analysis resulted in the identification of several hundred proteins. In this investigation, we developed a web based database (SCNProDB) containing protein information obtained from our previous published studies. This database will be useful to scientists who wish to develop SCN resistant soybean varieties through genetic manipulation and breeding efforts. The database is freely accessible from: http://bioinformatics.towson.edu/Soybean_SCN_proteins_2D_Gel_DB/Gel1.aspx