[Perceived morbidity and community burden of chikungunya in La Reunion]. / Morbidité perçue et impact communautaire du chikungunya a l'île de La Réunion: enquête de cohorte en population TELECHIK.

BACKGROUND: Persistence of clinical manifestations, especially polyarthralgia and fatigue, is a characteristic feature of chikungunya virus (CHIK-v) infection. The purpose of this study was to measure the impact of prolonged or late-onset manifestations of CHIK-v infection on the self-perceived health of people on Reunion Island. METHODS: This retrospective cohort survey, dubbed TELECHIK survey, was conducted eighteen months after the end of the chikungunya outbreak on a representative random sample from the SEROCHIK population-based survey conducted on Reunion Island. A total of 1094 subjects whose CHIK-v specific IgG antibody status had been documented were interviewed about current symptoms. RESULTS: Analysis of data showed 45% of CHIK+ vs 14% of CHIK- subjects reporting musculoskeletal pain (P < 0.001), 56% vs. 44% reporting fatigue (P = 0.003), 77% vs. 53% reporting cerebral manifestations (P < 0.001), 51% vs. 34% reporting sensorineural impairments (P < 0.001), 18% vs. 13% reporting digestive complaints (P = 0.06), and 38% vs. 32% reporting skin involvement (P = 0.13). The mean delay between infection and interview was two years (range, 15-34 months). Analysis of data after correction for age, gender, body mass index and comorbidity indicated that rheumatic pain, fatigue, cerebral manifestations and sensorineural impairments were more likely in CHIK+ than CHIK- subjects but the likelihood of digestive and skin manifestations was the same. CONCLUSION: With a mean delay of two years after infection, 45% to 77% of CHIK+ subjects reported prolonged or late-onset symptoms attributable to CHIK-v. These results indicate that persistent manifestations of chikungunya infection have a heavy impact on rheumatologic, neurological and sensorineural health.

Automatic detection of follicular regions in H&E images using iterative shape index.

Follicular Lymphoma (FL) accounts for 20-25% of non-Hodgkin lymphomas in the United States. The first step in grading FL is identifying follicles. Our paper discusses a novel technique to segment follicular regions in H&E stained images. The method is based on three successive steps: (1) region-based segmentation, (2) iterative shape index (concavity index) calculation, (3) and recursive watershed. A novel aspect of this method is the use of iterative Concavity Index (CI) to control the follicular splitting process in recursive watershed. CI takes into consideration the convex hull of the object and the closest area surrounding it. The mean Zijbendos similarity index (ZSI) final segmentation score on fifteen cases was 78.33%, with a standard deviation of 2.83.

Using Bayes' rule to model multisensory enhancement in the superior colliculus.

The deep layers of the superior colliculus (SC) integrate multisensory inputs and initiate an orienting response toward the source of stimulation (target). Multisensory enhancement, which occurs in the deep SC, is the augmentation of a neural response to sensory input of one modality by input of another modality. Multisensory enhancement appears to underlie the behavioral observation that an animal is more likely to orient toward weak stimuli if a stimulus of one modality is paired with a stimulus of another modality. Yet not all deep SC neurons are multisensory. Those that are exhibit the property of inverse effectiveness: combinations of weaker unimodal responses produce larger amounts of enhancement. We show that these neurophysiological findings support the hypothesis that deep SC neurons use their sensory inputs to compute the probability that a target is present. We model multimodal sensory inputs to the deep SC as random variables and cast the computation function in terms of Bayes' rule. Our analysis suggests that multisensory deep SC neurons are those that combine unimodal inputs that would be more uncertain by themselves. It also suggests that inverse effectiveness results because the increase in target probability due to the integration of multisensory inputs is larger when the unimodal responses are weaker.

A new image smoothing method based on a simple model of spatial processing in the early stages of human vision.

The difficulty of preserving edges is central to the problem of smoothing images. The main problem is that of distinguishing between meaningful contours and noise, so that the image can be smoothed without loss of details. Substantial efforts have been devoted to solving this difficult problem, and a plethora of filtering methods have been proposed in the literature. Non-linear filters have proved to be more efficient than their linear counterparts. Here, a new nonlinear filter for noise smoothing is introduced. This filter is based on the psychophysical phenomenon of human visual contrast sensitivity. Results on real images are presented to demonstrate the validity of our approach compared to other known filtering methods.