To evaluate the effect of a cyclooxygenase-1 (COX-1) inhibitor, SC-560, on the growth inhibition of s.c. human ovarian SKOV-3 carcinoma and on angiogenesis. Human ovarian SKOV-3 carcinoma cells xenograft-bearing mice were treated with SC-560, a COX-1-selective inhibitor, 6 mg/kg alone i.g. daily, and i.p. injections of cisplatin 3 mg/kg every other day for 21 days. Prostaglandin E 2 (PGE 2 ) levels were determined by ELISA. Microvessel density (MVD) of ovarian carcinoma was determined with anti-CD 34 as the label by immunohistochemistry. In addition, the expression of COX-1 at protein levels in the control group was detected by immunohistochemistry. SC-560 reduced the growth of tumors when SKOV-3 cells were xenografted in nude female mice. The inhibitory rates in SC-560 group and cisplatin group were 47.1% and 51.7%, respectively, which is significant statistically compared to that of control group (all, P \ 0.05). In treatment groups, SC-560 significantly reduced intratumor PGE 2 levels (P \ 0.01). MVDs in SC-560 group were 35.73 ± 9.87, which are significant statistically compared to that of control group (74.33 ± 9.50) (P \ 0.01). COX-1, not COX-2, protein levels are elevated in tumor tissues. These findings may implicate COX-1 as a suitable target for the treatment of ovarian cancer and that antiangiogenic therapy can be used to inhibit ovarian cancer growth.
This study was aimed at investigating the ultrasound based on deep learning algorithm to evaluate the rehabilitation effect of transumbilical laparoscopic single-site total hysterectomy on pelvic floor function in patients. The bilinear convolutional neural network (BCNN) structure was constructed in the ultrasound imaging system. The spatial transformer network (STN) was used to preserve image information. Two algorithms, BCNN-R and BCNN-S, were proposed to remove sensitive information after ultrasonic image processing, and then, subtle features of the image were identified and classified. 80 patients undergoing transumbilical laparoscopic single-site total hysterectomy in hospital were randomly divided into a control group and a treatment group, with 40 cases in each group. In the control group, conventional ultrasound was used to assess the image of pelvic floor function in patients undergoing laparoendoscopic single-site surgery (LESS); in the observation group, ultrasound based on deep learning algorithm was used. The postoperative incision pain score, average postoperative anus exhaust time, average hospital stay, and postoperative satisfaction of the two groups were evaluated, respectively. The highest accuracy of constructed network BCNN-S was 88.98%; the highest recall rate of BCNN-R was 88.51%; the highest accuracy rate of BCNN-R was 97.34%. The operation time, intraoperative blood loss, and exhaust time were similar between the two groups, and the difference had no statistical significance (
P
>
0.05
). The numerical rating scale (NRS) scores were compared, the observation group had less pain, the difference between the two groups had statistical significance (
P
<
0.05
), and the postoperative recovery was good. The BCNN based on deep learning can realize the imaging of the uterus by ultrasound and realize the evaluation of pelvic floor function, and the probability of pelvic floor dysfunction is small, which is worthy of clinical promotion.
Scars are often considered to be skin problems that affect beauty. The tension acting on the edge of the wound is the main factor causing the scar hyperplasia. At present, the clinical use of botulinum toxin A (BTX-A) around the wound to cause transient muscle paralysis reduce the muscle movement around the wound and wound tension to prevent scar hyperplasia during wound healing. But the use of BTX-A to prevent scarring requires the use of a syringe. The syringe can cause trauma and pain when How to cite this article: Sun P, Ji Z, Li Z, Pan B. Prevention of scar hyperplasia in the skin by conotoxin: A prospective review.
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