To investigate the role of ovarian membrane receptors for LH, FSH and prolactin of patients with developing Polycystic ovary (PCO) syndrome, seven patients were selected and the receptor function was studied in relation to changes of several serum hormone levels. The results were compared with those from individuals with regular menstrual cycles in the late follicular (LF; n=6) and midluteal (ML; n = 6) phases. LH receptor binding in the normal cycle remained low (1.73+0.14 fmole/mg homogenate protein) in the LF phase and elevated 3 fold in the ML phase. LH receptors in the PCO patients maintained a higher binding level than that in the LF phase, being close to the ML level. FSH receptors were at a high level in the LF phase (4.09+0.40 fmole/mg homogenate protein), but decreased by 23% in the ML phase. In the PCO group the ovarian FSH receptor showed a high level, near to that in the LF phase. Prolactin receptors showed no significant changes among the two controls and PCO group. PCO patients showed increased levels of serum LH and testosterone and a raised ratio of estrone to estradiol, although there was no change in the serum FSH level. These data suggested that the LH receptor binding in PCO was not so low as to the LF level. A lack of the down-regulation mechanism of LH receptors, in spite of the high level of serum LH in PCO, might be one of the clues to elucidate the pathophysiological mechanism in developing P00 syndrome. Elevated levels of the gonadotropin receptors, especially FSH receptors, seem to be involved in the high incidence of ovarian hyperstimulation during hormone treatment.polycystic ovary (PCO) ;
Although the Hough transformation is a powerful method to detect segments in an image, it requires not only a vast amount of memory but also a long processing time when a highly accurate detection is demanded. This paper proposes a new method of detecting segments with high accuracy using the Hough transformation without increasing the amount of memory. Unlike the conventional segment detection method in which the detection process is based on the parameter plane, this new method feeds the process back to the image plane from the parameter plane. Another feature of the method is the elimination in the parameter plane of Hough curves which are derived from pixels in the image plane constituting already detected segments. Experiments show that this method detects segments with a high accuracy from “noisy” images including many long and short segments.
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