妇科恶性肿瘤患者保留女性正常生理功能的思考

妇科医生需重视对妇科恶性肿瘤患者进行保留女性正常生理功能的治疗。对少女、育龄期妇女及早期患者治疗恶性肿瘤的同时,应尽量保留其正常的生理功能。需对患者进行全面评估,严格掌握实施保留生育功能手术的适应证;为预防放化疗对卵巢功能的损害,可以采取卵巢移位、卵巢组织冷冻移植,也可通过辅助生殖技术进行未成熟卵泡培养、卵子冷冻、卵母细胞冷冻及胚胎冷冻等。     

Prediction and classification in nonlinear data analysis: Something old,something new,something borrowed,something blue

Prediction and classification are two very active areas in modern data analysis. In this paper, prediction with nonlinear optimal scaling transformations of the variables is reviewed, and extended to the use of multiple additive components, much in the spirit of statistical learning techniques that are currently popular, among other areas, in data mining. Also, a classification/clustering method is described that is particularly suitable for analyzing attribute-value data from systems biology (genomics, proteomics, and metabolomics), and which is able to detect groups of objects that have similar values on small subsets of the attributes.This article is based on the Presidential Address Jacqueline Meulman gave on July 9, 2003 at the 68th Annual Meeting of the Psychometric Society held near Cagliari, Italy on the island of Sardinia.—Editor     

An efficient cervical disease diagnosis approach using segmented images and cytology reporting

Cervical cancer is the second most common cancer in women globally. A computer aided cervical disease diagnosis system that can relieve pressure on medical experts and save the cost is proposed. To implement our approach in the reality of cervical diseases diagnosis, a multi-modal framework is designed for three kinds of cervical diseases diagnosis that integrates uterine cervix images, Thinprep Cytology Test, human papillomavirus test, and patients’ age. However, too many features increase memory storage costs and computational costs, and it affects the spread of this system in poor areas. Feature selection not only eliminates redundant or irrelevant features but also finds the factors that influence the disease most first is performed in multi-modal frameworks for cervical diseases diagnosis. The detailed process of the method is as follows: first, according the representative color, an efficient image segmentation algorithm is developed; then from three different types of segmented images, we extract color features and texture features for interpreting uterine cervix images; next, Boruta algorithm is applied to feature selection; finally, the performance of Random Forests that utilizes selected features for cervical disease diagnosis is investigated. In the experiment, the proposed multi-modal diagnostic approach gives the final diagnosis for three different kinds of cervical diseases with 83.1% accuracy, which significantly outperforms methods using any single source of information alone. The validation cohort is applied to validate the efficiency of our method, and the performance of random forest obtained by using only 1.2% of features is like or even better than using 100% of features.     

Neural pathways mediating vaginal function: the vagus nerves and spinal cord oxytocin

The initial observations, made in our laboratory with Knut Larsson, of the ability of vaginocervical stimulation (VCS) to block withdrawal responses to foot pinch in rats has led to findings of multiple behavioral, autonomic, and neuroendocrine effects of this potent stimulus in rats and also in women. It has led to an understanding of: (1) the neuroanatomical and neurochemical basis of a novel and potent pain-blocking mechanism; (2) likely neuroanatomical pathways mediating both the Ferguson reflex and a specific autonomic response - the pupil-dilating effect of VCS; (3) a role for oxytocin as a putative central nervous system neurotransmitter that stimulates autonomic sympathetic preganglionic neurons within the spinal cord; and (4) a novel pathway that can convey sensory activity from the cervix, adequate to induce orgasm, via the vagus nerves. This latter pathway bypasses the spinal cord and projects directly to the medulla oblongata, and thus can convey genital afferent activity despite complete spinal cord injury at any level.