Ageing and chronic disease-related changes in the morphometric characteristics of ovarian follicles in cynomolgus monkeys (Macaca fascicularis)

Quantification of follicles in human ovarian tissue using image processing software and trained artificial intelligence†

Cancer survival rates in prepubertal girls and young women have risen in recent decades due to increasingly efficient treatments. However, many such treatments are gonadotoxic, causing premature ovarian insufficiency, loss of fertility, and ovarian endocrine function. Implantation of donor ovarian tissue encapsulated in immune-isolating capsules is a promising method to restore physiological endocrine function without immunosuppression or risk of reintroducing cancer cells harbored by the tissue. The success of this approach is largely determined by follicle density in the implanted ovarian tissue, which is analyzed manually from histologic sections and necessitates specialized, time-consuming labor. To address this limitation, we developed a fully automated method to quantify follicle density that does not require additional coding. We first analyzed ovarian tissue from 12 human donors between 16 and 37 years old using semi-automated image processing with manual follicle annotation and then trained artificial intelligence program based on follicle identification and object classification. One operator manually analyzed 102 whole slide images from serial histologic sections. Of those, 77 images were assessed by a second manual operator, followed with an automated method utilizing artificial intelligence. Of the 1181 follicles the control operator counted, the comparison operator counted 1178, and the artificial intelligence counted 927 follicles with 80% of those being correctly identified as follicles. The three-stage artificial intelligence pipeline finished 33% faster than manual annotation. Collectively, this report supports the use of artificial intelligence and automation to select tissue donors and grafts with the greatest follicle density to ensure graft longevity for premature ovarian insufficiency treatment.

Effects of Hochuekkito, a traditional Japanese medicine (Kampo), on reproduction of aging female mice

Purpose

To determine the potentials of Hochuekkito (HET) treatment for aging infertility.

Methods

Mice at 36 weeks of age were fed without (control, n = 40) or with low (100 mg/kg/day, n = 24) and high (1000 mg/kg/day, n = 38) doses of HET for 12 weeks. Aging animals at 48 weeks of age were used for in vitro fertilization-embryo transfer (IVF-ET), and their ovaries were subjected to histological and quantitative inflammation analyses.

Results

HET administration decreased transcript levels of ovarian inflammatory markers, interleukin 6 (IL-6), IL-1β, tumor necrosis factor (TNF)-α, and interferon-gamma (IFN-γ) but suppressed ovulation rates and the number of ovulated oocytes in aging mice. Furthermore, HET treatment decreased the rates of oocytes maturation and fertilization and the cumulus-cell expression of TNF-α-induced protein 6 and epidermal growth factor receptor. After IVF-ET, no improvement of declined live offspring rate by aging was achieved by HET administration, although there were no adverse effects on embryo development and implantation as well as gross morphology and bodyweight of pups.

Conclusion

Present study indicated HET treatment interfered with ovulation and fertilization in aging mice without affecting ovarian follicle development. No improvement on the age-associated decline of live offspring rate and follicle development was achieved after HET treatment.