Neutrophil function in cured cancer patients

Spontaneous and endotoxin-stimulated nitroblue tetrazolium (NBT) dye reduction was evaluated in 86 individuals cured of various types of solid malignancies and in 55 healthy adults. Oxygen consumption tests, at rest and during phagocytosis, were performed with polymorphonuclear leukocytes of 22 patients and 10 controls, chosen at random. The results revealed an impaired capacity of patients' neutrophils to reduce NBT. The decrease in the stimulated reduction values was more pronounced (p less than 0.0005) than in spontaneous values (p less than 0.01), and was also noticed in patients who had been treated by surgery alone and in those with a disease-free interval of 10 years or more. Oxygen consumption by patients' leukocytes was similar to that of controls. The present results, especially those of the endotoxin-stimulated NBT test, might reflect a neutrophil dysfunction in cured cancer patients. The nature of such an abnormality and its possible clinical implication are still obscure.     

Work measurement for estimating food preparation time of a bioregenerative diet

During space missions, such as the prospective Mars mission, crew labor time is a strictly limited resource. The diet for such a mission (based on crops grown in a bioregenerative life support system) will require astronauts to prepare their meals essentially from raw ingredients. Time spent on food processing and preparation is time lost for other purposes. Recipe design and diet planning for a space mission should therefore incorporate the time required to prepare the recipes as a critical factor. In this study, videotape analysis of an experienced chef was used to develop a database of recipe preparation time. The measurements were highly consistent among different measurement teams. Data analysis revealed a wide variation between the active times of different recipes, underscoring the need for optimization of diet planning. Potential uses of the database developed in this study are discussed and illustrated in this work.     

Learning and generalization with the information bottleneck

The Information Bottleneck is an information theoretic framework that finds concise representations for an ‘input’ random variable that are as relevant as possible for an ‘output’ random variable. This framework has been used successfully in various supervised and unsupervised applications. However, its learning theoretic properties and justification remained unclear as it differs from standard learning models in several crucial aspects, primarily its explicit reliance on the joint input–output distribution. In practice, an empirical plug-in estimate of the underlying distribution has been used, so far without any finite sample performance guarantees. In this paper we present several formal results that address these difficulties. We prove several finite sample bounds, which show that the information bottleneck can provide concise representations with good generalization, based on smaller sample sizes than needed to estimate the underlying distribution. The bounds are non-uniform and adaptive to the complexity of the specific model chosen. Based on these results, we also present a preliminary analysis on the possibility of analyzing the information bottleneck method as a learning algorithm in the familiar performance-complexity tradeoff framework. In addition, we formally describe the connection between the information bottleneck and minimal sufficient statistics.     

Unsupervised natural image patch learning

Computational Visual Media - A metric for natural image patches is an important tool for analyzing images. An efficient means of learning one is to train a deep network to map an image patch to a...     

Adaptive Application of SAT Solving Techniques

New heuristics and strategies have enabled major advancements in SAT solving in recent years. However, experimentation has shown that there is no winning solution that works in all cases. A degradation of orders of magnitude can be observed if the wrong heuristic is chosen. The problem is that it is impossible to know, in advance, which heuristics are best for a given problem. Consequently, many ideas - those that turn out to be useful for a small subset of the cases, but significantly increase run times on most others - are discarded.We propose the notion of Adaptive Solving as a possible solution to this problem. In our framework, the SAT solver monitors the effectiveness of the search on-the-fly using a Performance Metric. The metric gives a score according to its assessment of the search progress. Based on this score, one or more heuristics are turned on or off. The goal is to use a specific heuristic or strategy when it is advantageous, and turn it off when it is not, before it does too much damage. We suggest several possible metrics, and compare their effectiveness. Our adaptive solver achieves significant speedups on a large set of examples. We also show that applying different heuristics on different parts of the search space can improve run times even beyond what can be achieved by the best heuristic on its own.     

Nectar Minerals as Regulators of Flower Visitation in Stingless Bees and Nectar Hoarding Wasps

Various nectar components have a repellent effect on flower visitors, and their adaptive advantages for the plant are not well understood. Persea americana (avocado) is an example of a plant that secretes nectar with repellent components. It was demonstrated that the mineral constituents of this nectar, mainly potassium and phosphate, are concentrated enough to repel honey bees, Apis mellifera, a pollinator often used for commercial avocado pollination. Honey bees, however, are not the natural pollinator of P. americana, a plant native to Central America. In order to understand the role of nectar minerals in plant—pollinator relationships, it is important to focus on the plant’s interactions with its natural pollinators. Two species of stingless bees and one species of social wasp, all native to the Yucatan Peninsula, Mexico, part of the natural range of P. americana, were tested for their sensitivity to sugar solutions enriched with potassium and phosphate, and compared with the sensitivity of honey bees. In choice tests between control and mineral-enriched solutions, all three native species were indifferent for mineral concentrations lower than those naturally occurring in P. americana nectar. Repellence was expressed at concentrations near or exceeding natural concentrations. The threshold point at which native pollinators showed repellence to increasing levels of minerals was higher than that detected for honey bees. The results do not support the hypothesis that high mineral content is attractive for native Hymenopteran pollinators; nevertheless, nectar mineral composition may still have a role in regulating flower visitors through different levels of repellency.     

Novel m1 muscarinic agonists in treatment and delaying the progression of Alzheimer's disease: an unifying hypothesis

M1 selective agonists from the AF series (e.g. AF102B, AF150(S)), via m1 muscarinic receptors, activate distinct signal transductions, enhance amyloid precursors proteins secretion from transfected cells and primary cell cultures, show neurotrophic effects and are beneficial in a variety of animal models for Alzheimer's disease. Such m1 agonists may be effective in the treatment and therapy of Alzheimer's disease.     

Proton-Conductive Melanin-Like Fibers through Enzymatic Oxidation of a Self-Assembling Peptide

Melanin pigments have various properties that are of technological interest including photo- and radiation protection, rich coloration, and electronic functions. Nevertheless, laboratory-based synthesis of melanin and melanin-like materials with morphologies and chemical structures that are specifically optimized for these applications, is currently not possible. Here, melanin-like materials that are produced by enzymatic oxidation of a supramolecular tripeptide structures that are rich in tyrosine and have a 1D morphology are demonstrated, that are retained during the oxidation process while conducting tracks form through oxidative tyrosine crosslinking. Specifically, a minimalistic self-assembling peptide, Lys–Tyr–Tyr (KYY) with strong propensity to form supramolecular fibers, is utilized. Analysis by Raman spectroscopy shows that the tyrosines are pre-organized inside these fibers and, upon enzymatic oxidation, result in connected catechols. These form 1D conducting tracks along the length of the fiber, which gives rise to a level of internal disorder, but retention of the fiber morphology. This results in highly conductive structures demonstrated to be dominated by proton conduction. This work demonstrates the ability to control oxidation but retain a well-defined fibrous morphology that does not have a known equivalent in biology, and demonstrate exceptional conductivity that is enhanced by enzymatic oxidation.