The role of ocelli in cockroach optomotor performance

Insect ocelli are relatively simple eyes that have been assigned various functions not related to pictorial vision. In some species they function as sensors of ambient light intensity, from which information is relayed to various parts of the nervous system, e.g., for the control of circadian rhythms. In this work we have investigated the possibility that the ocellar light stimulation changes the properties of the optomotor performance of the cockroach Periplaneta americana. We used a virtual reality environment where a panoramic moving image is presented to the cockroach while its movements are recorded with a trackball. Previously we have shown that the optomotor reaction of the cockroach persists down to the intensity of moonless night sky, equivalent to less than 0.1 photons/s being absorbed by each compound eye photoreceptor. By occluding the compound eyes, the ocelli, or both, we show that the ocellar stimulation can change the intensity dependence of the optomotor reaction, indicating involvement of the ocellar visual system in the information processing of movement. We also measured the cuticular transmission, which, although relatively large, is unlikely to contribute profoundly to ocellar function, but may be significant in determining the mean activity level of completely blinded cockroaches

WWOX protein expression varies among ovarian carcinoma histotypes and correlates with less favorable outcome

BACKGROUND: The putative tumor suppressor WWOX gene spans the common chromosomal fragile site 16D (FRA16D) at chromosome area 16q23.3-24.1. This region is a frequent target for loss of heterozygosity and chromosomal rearrangement in ovarian, breast, hepatocellular, prostate carcinomas and other neoplasias. The goal of these studies was to evaluate WWOX protein expression levels in ovarian carcinomas to determine if they correlated with clinico-pathological parameters, thus providing additional support for WWOX functioning as a tumor suppressor. METHODS: We performed WWOX protein expression analyses by means of immunobloting and immunohistochemistry on normal ovaries and specific human ovarian carcinoma Tissue Microarrays (n = 444). Univariate analysis of clinical-pathological parameters based on WWOX staining was determined by χ(2 )test with Yates' correction. The basic significance level was fixed at p < 0.05. RESULTS: Immunoblotting analysis from normal ovarian samples demonstrated consistently strong WWOX expression while 37% ovarian carcinomas showed reduced or undetectable WWOX protein expression levels. The immunohistochemistry of normal human ovarian tissue sections confirmed strong WWOX expression in ovarian surface epithelial cells and in epithelial inclusion cysts within the cortex. Out of 444 ovarian carcinoma samples analyzed 30% of tumors showed lack of or barely detectable WWOX expression. The remaining ovarian carcinomas (70%) stained moderately to strongly positive for this protein. The two histotypes showing significant loss of WWOX expression were of the Mucinous (70%) and Clear Cell (42%) types. Reduced WWOX expression demonstrated a significant association with clinical Stage IV (FIGO) (p = 0.007), negative Progesterone Receptor (PR) status (p = 0.008) and shorter overall survival (p = 0.03). CONCLUSION: These data indicate that WWOX protein expression is highly variable among ovarian carcinoma histotypes. It was also observed that subsets of ovarian tumors demonstrated loss of WWOX expression and is potentially associated with patient outcome

Snapshot navigation in the wavelet domain

Many animals rely on robust visual navigation which can be explained by snapshot models, where an agent is assumed to store egocentric panoramic images and subsequently use them to recover a heading by comparing current views to the stored snapshots. Long-range route navigation can also be explained by such models, by storing multiple snapshots along a training route and comparing the current image to these. For such models, memory capacity and comparison time increase dramatically with route length, rendering them unfeasible for small-brained insects and low-power robots where computation and storage are limited. One way to reduce the requirements is to use a compressed image representation. Inspired by the filter bank-like arrangement of the visual system, we here investigate how a frequency-based image representation influences the performance of a typical snapshot model. By decomposing views into wavelet coefficients at different levels and orientations, we achieve a compressed visual representation that remains robust when used for navigation. Our results indicate that route following based on wavelet coefficients is not only possible but gives increased performance over a range of other models