Comparison of Naso-temporal Asymmetry During Monocular Smooth Pursuit, Optokinetic Nystagmus, and Ocular Following Response in Strabismic Monkeys

Purpose: Under monocular viewing conditions, humans and monkeys with infantile strabismus exhibit asymmetric naso-temporal (N-T) responses to motion stimuli. The goal of this study was to compare and contrast these N-T asymmetries during 3 visually mediated eye tracking tasks-optokinetic nystagmus (OKN), smooth pursuit (SP) response, and ocular following responses (OFR). Methods: Two adult strabismic monkeys were tested under monocular viewing conditions during OKN, SP, or OFR stimulation. OKN stimulus was unidirectional motion of a 30°x30° random dot pattern at 20°, 40°, or 80°/s for 1 minute. OFR stimulus was brief (200 ms) unidirectional motion of a 38°x28°whitenoise at 20°, 40°, or 80°/s. SP stimulus consisted of foveal step-ramp target motion at 10°, 20°, or 40°/s. Results: Mean nasalward steady state gain (0.87±0.16) was larger than temporalward gain (0.67±0.19) during monocular OKN (P<0.001). In monocular OFR, the asymmetry is manifested as a difference in OFR velocity gain (nasalward: 0.33±0.19, temporalward: 0.22±0.12; P=0.007). During monocular SP, mean nasal gain (0.97±0.2) was larger than temporal gain (0.66±0.14; P<0.001) and the mean nasalward acceleration during pursuit initiation (156±61°/s2) was larger than temporalward acceleration (118±77°/s2; P=0.04). Comparison of N-T asymmetry ratio across the 3 conditions using ANOVA showed no significant difference. Conclusion: N-T asymmetries are identified in all 3 visual tracking paradigms in both monkeys with either eye viewing. Our data are consistent with the current hypothesis for the mechanism for N-T asymmetry that invokes an imbalance in cortical drive to brainstem circuits

The reference frame for encoding and retention of motion depends on stimulus set size

YesThe goal of this study was to investigate the reference frames used in perceptual encoding and storage of visual motion information. In our experiments, observers viewed multiple moving objects and reported the direction of motion of a randomly selected item. Using a vector-decomposition technique, we computed performance during smooth pursuit with respect to a spatiotopic (nonretinotopic) and to a retinotopic component and compared them with performance during fixation, which served as the baseline. For the stimulus encoding stage, which precedes memory, we found that the reference frame depends on the stimulus set size. For a single moving target, the spatiotopic reference frame had the most significant contribution with some additional contribution from the retinotopic reference frame. When the number of items increased (Set Sizes 3 to 7), the spatiotopic reference frame was able to account for the performance. Finally, when the number of items became larger than 7, the distinction between reference frames vanished. We interpret this finding as a switch to a more abstract nonmetric encoding of motion direction. We found that the retinotopic reference frame was not used in memory. Taken together with other studies, our results suggest that, whereas a retinotopic reference frame may be employed for controlling eye movements, perception and memory use primarily nonretinotopic reference frames. Furthermore, the use of nonretinotopic reference frames appears to be capacity limited. In the case of complex stimuli, the visual system may use perceptual grouping in order to simplify the complexity of stimuli or resort to a nonmetric abstract coding of motion information

Predictive model of biliocystic communication in liver hydatid cysts using classification and regression tree analysis

<p>Abstract</p> <p>Background</p> <p>Incidence of liver hydatid cyst (LHC) rupture ranged 15%-40% of all cases and most of them concern the bile duct tree. Patients with biliocystic communication (BCC) had specific clinic and therapeutic aspect. The purpose of this study was to determine witch patients with LHC may develop BCC using classification and regression tree (CART) analysis</p> <p>Methods</p> <p>A retrospective study of 672 patients with liver hydatid cyst treated at the surgery department "A" at Ibn Sina University Hospital, Rabat Morocco. Four-teen risk factors for BCC occurrence were entered into CART analysis to build an algorithm that can predict at the best way the occurrence of BCC.</p> <p>Results</p> <p><b>I</b>ncidence of BCC was 24.5%. Subgroups with high risk were patients with jaundice and thick pericyst risk at 73.2% and patients with thick pericyst, with no jaundice 36.5 years and younger with no past history of LHC risk at 40.5%. Our developed CART model has sensitivity at 39.6%, specificity at 93.3%, positive predictive value at 65.6%, a negative predictive value at 82.6% and accuracy of good classification at 80.1%. Discriminating ability of the model was good 82%.</p> <p>Conclusion</p> <p>we developed a simple classification tool to identify LHC patients with high risk BCC during a routine clinic visit (only on clinical history and examination followed by an ultrasonography). Predictive factors were based on pericyst aspect, jaundice, age, past history of liver hydatidosis and morphological Gharbi cyst aspect. We think that this classification can be useful with efficacy to direct patients at appropriated medical struct's.</p

Micro-RNAs as diagnostic or prognostic markers in human epithelial malignancies

Micro-RNAs (miRs) are important regulators of mRNA and protein expression; the ability of miR expression profilings to distinguish different cancer types and classify their sub-types has been well-described. They also represent a novel biological entity with potential value as tumour biomarkers, which can improve diagnosis, prognosis, and monitoring of treatment response for human cancers. This endeavour has been greatly facilitated by the stability of miRs in formalin-fixed paraffin-embedded (FFPE) tissues, and their detection in circulation. This review will summarize some of the key dysregulated miRs described to date in human epithelial malignancies, and their potential value as molecular bio-markers in FFPE tissues and blood samples. There remain many challenges in this domain, however, with the evolution of different platforms, the complexities of normalizing miR profiling data, and the importance of evaluating sufficiently-powered training and validation cohorts. Nonetheless, well-conducted miR profiling studies should contribute important insights into the molecular aberrations driving human cancer development and progression