An application of the 2-nitrobenzenesulfenyl method to proteomic profiling of human colorectal carcinoma: A novel approach for biomarker discovery

In the development of novel biomarkers, the proteomic approach is advantageous because using it the cancer-associated proteins can be directly identified. We previously developed a 2-nitrobenzenesulfenyl (NBS) method to improve quantitative proteome analysis. Here, we applied this method to proteomic profiling of colorectal carcinoma (CRC) to identify novel proteins with altered expression in CRC. Each pair of tumor and normal tissue specimens from 12 CRC patients was analyzed, and approximately 5000 NBS-labeled paired peaks were quantified. Peaks with altered signal intensities (>1.5-fold) and occurring frequently in the samples (>70%) were selected, and 128 proteins were identified by MS/MS analyses as differentially expressed proteins in CRC tissues. Many proteins were newly revealed to be CRC related; 30 were reported in earlier studies of CRC. Six proteins that were up-regulated in CRC (ZYX, RAN, RCN1, AHCY, LGALS1, and VIM) were further characterized and validated by Western blot and immunohistochemistry. All six were found to be CRC-localized, either in cancer cells or in stroma cells near the cancer cells. These results indicate that the proteins identified in this study are novel candidates for CRC markers, and that the NBS method is useful in proteome mining to discover novel biomarkers.     

Accumulation of triosephosphate isomerase, with sequence homology to Beta amyloid peptides, in vessel walls of the newborn piglet hippocampus

We investigated whether beta-amyloid (Abeta)-like immunoreactivity was seen in the brains of newborn piglets. The immunoreactivity for Abeta(1-42) and Abeta(1-40) proteins, but not Abeta precursor protein, was present in CD68-positive perivascular cells of the hippocampus and in parts of the meninges. It was colocalized with immunoreactivity for receptor for advanced glycation end product and tumor necrosis factor-alpha. The protein with a molecular mass of 27 kDa, which was recognized by the Abeta antibodies, was identified as triosephosphate isomerase (TPI) with sequence homology to Abeta peptides by N-terminal amino acid sequencing, mass fingerprint analysis using matrix-associated laser desorption/ionization mass spectrometry, and Western blotting. Western blotting assay also revealed that detectable expression of Abeta proteins were not seen in the piglet brains. These findings indicate that TPI with sequence homology to Abeta peptides accumulates in perivascular cells of the microglia/macrophage lineage located around arterial vessels of the newborn piglet hippocampus.     

Cooperation of categorical and behavioral learning in a practical solution to the abstraction problem

Real robots should be able to adapt autonomously to various environments in order to go on executing their tasks without breaking down. They achieve this by learning how to abstract only useful information from a huge amount of information in the environment while executing their tasks. This paper proposes a new architecture which performs categorical learning and behavioral learning in parallel with task execution. We call the architectureSituation Transition Network System (STNS). In categorical learning, it makes a flexible state representation and modifies it according to the results of behaviors. Behavioral learning is reinforcement learning on the state representation. Simulation results have shown that this architecture is able to learn efficiently and adapt to unexpected changes of the environment autonomously. Atsushi Ueno, Ph.D.: He is a research associate in the Artificial Intelligence Laboratory at the Graduate School of Information Science at the Nara Institute of Science and Technology (NAIST). He received the B.E., the M.E., and the Ph.D. degrees in aeronautics and astronautics from the University of Tokyo in 1991, 1993, and 1997 respectively. His research interest is robot learning and autonomous systems. He is a member of Japan Association for Artificial Intelligence (JSAI). Hideaki Takeda, Ph.D.: He is an associate professor in the Artificial Intelligence Laboratory at the Graduate School of Information Science at the Nara Institute of Science and Technology (NAIST). He received his Ph.D. in precision machinery engineering from the University of Tokyo in 1991. He has conducted research on a theory of intelligent computer-aided design systems, in particular experimental study and logical formalization of engineering design. He is also interested in multiagent architectures and ontologies for knowledge base systems.     

Spatiotemporal conversion of auditory information for cochleotopic mapping

Auditory communication signals such as monkey calls are complex FM vocal sounds and in general induce action potentials in different timing in the primary auditory cortex. Delay line scheme is one of the effective ways for detecting such neuronal timing. However, the scheme is not straightforwardly applicable if the time intervals of signals are beyond the latency time of delay lines. In fact, monkey calls are often expressed in longer time intervals (hundreds of milliseconds to seconds) and are beyond the latency times observed in the brain (less than several hundreds of milliseconds). Here, we propose a cochleotopic map similar to that in vision known as a retinotopic map. We show that information about monkey calls could be mapped on a cochleotopic cortical network as spatiotemporal firing patterns of neurons, which can then be decomposed into simple (linearly sweeping) FM components and integrated into unified percepts by higher cortical networks. We suggest that the spatiotemporal conversion of auditory information may be essential for developing the cochleotopic map, which could serve as the foundation for later processing, or monkey call identification by higher cortical areas.     

Hydrocarbons with a homoconjugated polyene system and their monoepoxy derivatives: Sex attractants of geometrid and noctuid moths distributed in Japan

Although several sex pheromones of the family Geometridae have been characterized, investigations on Japanese species are limited. In order to obtain more information, screening using known sex pheromones and their analogs was carried out. The (Z,Z,Z)-3,6,9-triunsaturated and (Z,Z)-6,9-diunsaturated hydrocarbons with straight C¹⁹-C²¹ chains were synthesized by the Grignard coupling reaction as a key step starting from linolenic and linoleic acids, respectively. Oxidation of the homoconjugated trienes withm-chloroperoxybenzoic acid yielded a 111 mixture of three monoepoxy derivatives that could be separated by silica gel chromatography. The chemical structure of each positional isomer was confirmed using two-dimensional NMR techniques and MS measurements, which enabled characteristic fragment ions from the isomers to be identified. Field tests using lures incorporating only one of the above six hydrocarbons or nine epoxides were carried out in a forest in Tokyo. Consequently, attraction of male moths of 14 geometrid species in addition to four species in another family, the Noctuidae, was observed. It was concluded that hydrocarbons with a homoconjugated polyene system and the monoepoxy derivatives are important components of sex pheromones produced by Japanese lepidopterous insects, particularly the geometrid moths.     

Superconductivity in dilute Cu-Nb-Sn alloys containing Nb3Sn precipitates

The dilute Cu-Nb-Sn alloys containing small amounts of Nb and Sn less than 1 at % exhibited superconductivity after quenching from the liquid state and ageing. The best superconducting properties ( andJ _c=130 A cm^–2) in a Cu-0.30 at % Nb 0.15 at % Sn alloy were obtained when the sample was aged at 550° C for 384 h. This sample exhibited a structure of fine Nb₃Sn precipitates of 200 to 500Å diameter distributed homogeneously in the Cu matrix, and therefore it was concluded that superconductivity in these alloys resulted from the proximity effect of Nb₃Sn particles. In spite of the similar structure obtained by ageing at 800° C, the Cu-Nb-Sn alloys showed inferior superconducting properties compared to the Cu-0.4 at % Nb alloy and this would be explained qualitatively by the difference in the mean free path in the two alloys.     

Interdiffusion in Co-Mn alloys

Interdiffusion coefficient in cobalt-manganese alloys has been determined by Matano's method in the temperature range between 1133 and 1423 K on (pure Co)-(Co-30.28 at. pct Mn alloy) and (pure Co)-(Co-51.76 at. pct Mn alloy) couples. This, ∼D, has been found to increase with the increase of manganese content. However, the activation energy (∼Q) and frequency factor ( ₀) show a maximum at about 10 at. pct Mn. The concentration dependence of and has been discussed taking into account the thermodynamic properties of the alloy. The difference in between the ferro- and paramagnetic phases in Co-5 at. pct Mn alloy has been found to be 24 kJ/mol, which is larger, than that for the diffusion of Mn⁵⁴ in this alloy. Further it has been found that the Kirkendall marker moves toward manganese-rich side, showing that manganese atoms diffuse faster than cobalt atoms. From the marker shift, the intrinsic diffusion coefficients,D _Co andD _Mn, at 33 at. pct Mn have been determined as follows:D _Co=0.22×10⁻⁴ exp(−263 kJ mol⁻¹/RT) m²/s, andD _Mn=0.98×10⁻⁴ exp(−229 kJ mol⁻¹/RT) m²/s.     

On intractability of the classUP

The classUP [V] is the class of sets accepted by polynomial-time nondeterministic Turing machines which have at most one accepting path for every input. The complexity of this class closely relates to that of computing inverses ofone-way functions, where a one-way function is a one-to-one, length-increasing, and polynomial-time computable function whose inverse cannot be computed within polynomial time. It is known [GS], [K] that there exists a one-way function if and only ifP UP. In this paper the intractability of sets inUP is investigated in terms of polynomial-time reducibility to a sparse set. It is shown thatUP has a set that is _m ^P -reducible to no sparse set ifP UP. We interpret this structural property in the relation with approximation algorithms: it is shown that ifP UP, thenUP has a set with no 1-APT approximation and, furthermore,UP has a set that is not _m ^P -reducible to any set with a 1-APT approximation. The implication of this result in the study of one-way functions is also discussed. In order to prove the main theorem, we introduce a variation of tree-pruning methods.This paper was written while the author visited the Department of Mathematics, University of California, Santa Barbara. This research was supported in part by the National Science Foundation under Grant CCR-8611980.     

An Extension of the Receiver Operating Characteristic Curve and AUC-Optimal Classification

While most proposed methods for solving classification problems focus on minimization of the classification error rate, we are interested in the receiver operating characteristic (ROC) curve, which provides more information about classification performance than the error rate does. The area under the ROC curve (AUC) is a natural measure for overall assessment of a classifier based on the ROC curve. We discuss a class of concave functions for AUC maximization in which a boosting-type algorithm including RankBoost is considered, and the Bayesian risk consistency and the lower bound of the optimum function are discussed. A procedure derived by maximizing a specific optimum function has high robustness, based on gross error sensitivity. Additionally, we focus on the partial AUC, which is the partial area under the ROC curve. For example, in medical screening, a high true-positive rate to the fixed lower false-positive rate is preferable and thus the partial AUC corresponding to lower false-positive rates is much more important than the remaining AUC. We extend the class of concave optimum functions for partial AUC optimality with the boosting algorithm. We investigated the validity of the proposed method through several experiments with data sets in the UCI repository.