Post-partum testosterone administration partially reverses the effects of perinatal cadmium exposure on sexual behavior in rats

This study investigated the effects of perinatal cadmium exposure on sexual behavior, organ weight, and testosterone levels in adult rats. We examined whether immediate postpartum testosterone administration is able to reverse the toxic effects of the metal. Forty pregnant Wistar rats were divided into three groups: 1) control, 2) 10 mg kg-1 cadmium chloride per day, and 3) 20 mg kg-1 cadmium chloride per day. These dams were treated on gestational days 18 and 21 and from lactation 1 to 7. Immediately after birth, half of the offspring from the experimental and control groups received 50 μl (i.p.) of 0.2% testosterone. Male sexual behavior, histological analysis and weight of organs as well as serum testosterone levels were assessed. Results showed that both cadmium doses disrupted sexual behavior in male rats, and postnatal treatment with testosterone reversed the toxic effects of 10 mg kg-1 cadmium and attenuated the effects of 20 mg kg-1 cadmium. Body weight and absolute testis, epididymis, and seminal vesicle weight were decreased by the higher cadmium dose, and testosterone supplementation did not reverse these effects. Serum testosterone levels were unaffected by both cadmium doses. No histological changes were detected in all organs analyzed. Maternal cadmium exposure effects in sexual parameters of male rat offspring were explained by the altered masculinization of the hypothalamus. We suggest that cadmium damaged cerebral sexual differentiation by its actions as an endocrine disruptor and supported by the changes discretely observed from early life during sexual development to adult life, reflected by sexual behavior. Testosterone supplementation after birth reversed some crucial parameters directly related to sexual behavior.

Dynamic texture segmentation based on deterministic partially self-avoiding walks

Recently there has been a considerable interest in dynamic textures due to the explosive growth of multimedia databases. In addition, dynamic texture appears in a wide range of videos, which makes it very important in applications concerning to model physical phenomena. Thus, dynamic textures have emerged as a new field of investigation that extends the static or spatial textures to the spatio-temporal domain. In this paper, we propose a novel approach for dynamic texture segmentation based on automata theory and k-means algorithm. In this approach, a feature vector is extracted for each pixel by applying deterministic partially self-avoiding walks on three orthogonal planes of the video. Then, these feature vectors are clustered by the well-known k-means algorithm. Although the k-means algorithm has shown interesting results, it only ensures its convergence to a local minimum, which affects the final result of segmentation. In order to overcome this drawback, we compare six methods of initialization of the k-means. The experimental results have demonstrated the effectiveness of our proposed approach compared to the state-of-the-art segmentation methods.

Dynamic texture analysis and segmentation using deterministic partially self-avoiding walks

Dynamic texture is a recent field of investigation that has received growing attention from computer vision community in the last years. These patterns are moving texture in which the concept of selfsimilarity for static textures is extended to the spatiotemporal domain. In this paper, we propose a novel approach for dynamic texture representation, that can be used for both texture analysis and segmentation. In this method, deterministic partially self-avoiding walks are performed in three orthogonal planes of the video in order to combine appearance and motion features. We validate our method on three applications of dynamic texture that present interesting challenges: recognition, clustering and segmentation. Experimental results on these applications indicate that the proposed method improves the dynamic texture representation compared to the state of the art.