The survival rate of cancer patients was improved due to the development of cancer treatment techniques, and thus the fertility protection for young female cancer patients has attracted increasing attention. Radiotherapy, as one of the comprehensive cancer treatment, could cause ovarian damage in adolescent and child-bearing women, which leads to fertility decline and a series of side effects. Radiation can cause ovarian damage not only by acting on biological macromolecules directly, but also by increasing oxidative stress between oocytes and ovarian granulosa cells indirectly. At present, the fertility preservation of female cancer patients undergoing radiotherapy mainly includes physical protection, drug protection and biological protection. Recently, the development of new technologies for the preservation of fertility in female cancer patients has also brought new hope, including factors such as protective effects, patient age, and the selection of specific cancer treatment measures, which are the main considerations in the selection process of fertility preservation measures. This article reviews the research progress on radiation-induced ovarian damage, with a focus on the introduction of the fertility preservation measures and new technologies for young female tumor patients receiving radiotherapy.

Although attention plays an important role in cognitive and perception, there is no simple way to measure one's attention abilities. We identified that the strength of brain functional network in sustained attention task can be used as the physiological indicator to predict behavioral performance. Behavioral and electroencephalogram (EEG) data from 14 subjects during three force control tasks were collected in this paper. The reciprocal of the product of force tolerance and variance were used to calculate the score of behavioral performance. EEG data were used to construct brain network connectivity by wavelet coherence method and then correlation analysis between each edge in connectivity matrices and behavioral score was performed. The linear regression model combined those with significantly correlated network connections into physiological indicator to predict participant's performance on three force control tasks, all of which had correlation coefficients greater than 0.7. These results indicate that brain functional network strength can provide a widely applicable biomarker for sustained attention tasks.