Analysis of the structure and expression of the c-myc oncogene in cervical tumor and in cervical tumor-derived cell lines

The structure of the c-myc oncogene in 17 cervical tumors and patient-matched nontumor tissues from Chinese patients residing in Taiwan was analysed. In contrast to recent reports on Mexican patients, none of the samples showed rearrangements and sequence amplification in the c-myc gene. The discrepancy may be explained by different carcinogenesis mechanisms being in operation in different geographic regions. Although no structural alterations in the c-myc gene were found in seven cervical carcinoma cell lines analysed, Northern blot analysis indicated different levels of c-myc gene expression which may be related to the presence of human papillomavirus (HPV) sequence in the cell and suggests a possible c-myc-hpv interaction in some stages of the transformation process.     

The effect of sodium chlorate and nitrapyrin on the nitrification mediated nitrosation process in soils

Summary The influence of total nitrification to nitrate or partial nitrification to nitrite on the soil organic nitrogen status was examined. NH ₄ ⁺ –¹⁵N was added to the soil in the absence and the presence of NaClO₃, respectively nitrapyrin. The first chemical inhibits only nitrate formation, the second inhibits total nitrification. The accumulation of nitrite nitrogen in the soil at levels up to 5 mg kg^–1 increased the loss of nitrogen. Yet, it did not increase the binding of mineral nitrogen into soil organic matter, relative to the control soil. The data suggest that the biochemistry of the nitrite formation process, rather than the levels of nitrite ions formed, are of primary importance in the role of nitrification mediated nitrosation of soil organic matter.     

A nuclear yeast gene (GCY) encodes a polypeptide with high homology to a vertebrate eye lens protein

We describe here the nuclear gene for a yeast protein showing unexpectedly high homology with mammalian aldo/keto reductases as well as with p-crystallin, one of the prominent proteins of the frog eye lens. Although it could be proven that the gene occurs as a single copy in the haploid yeast genome, replacement of the intact by a disrupted, nonfunctional allele led to no obvious phenotype, indicating that the gene is dispensable. The gene was assigned to chromosome XV. It is transcribed in vivo into an mRNA of about 1300 bases with a coding capacity for a protein of 312 amino acids (estimated Mr 35,000).     

Coordinates transformation and learning control for visually-guided voluntary movement with iteration: A Newton-like method in a function space

In order to control visually-guided voluntary movements, the central nervous system (CNS) must solve the following three computational problems at different levels: (1) determination of a desired trajectory in the visual coordinates, (2) transformation of the coordinates of the desired trajectory to the body coordinates and (3) generation of motor command. In this paper, the second and the third problems are treated at computational, representational and hardware levels of Marr. We first study the problems at the computational level, and then propose an iterative learning scheme as a possible algorithm. This is a trial and error type learning such as repetitive training of golf swing. The amount of motor command needed to coordinate activities of many muscles is not determined at once, but in a step-wise, trial and error fashion in the course of a set of repetitions. Actually, the motor command in the (n+1)-th iteration is a sum of the motor command in then-th iteration plus two modification terms which are, respectively, proportional to acceleration and speed errors between the desired trajectory and the realized trajectory in then-th iteration. We mathematically formulate this iterative learning control as a Newton-like method in functional spaces and prove its convergence under appropriate mathematical conditions with use of dynamical system theory and functional analysis. Computer simulations of this iterative learning control of a robotic manipulator in the body or visual coordinates are shown. Finally, we propose that areas 2, 5, and 7 of the sensory association cortex are possible sites of this learning control. Further we propose neural network model which acquires transformation matrices from acceleration or velocity to motor command, which are used in these schemes.