Resources and Attitudes Influence Acculturation of Deaf Children with Cochlear Implants.

Early detection of hearing loss leads to early intervention-related decisions. Most children with cochlear implants (CIs) are born to hearing parents. Prior evidence suggests that this increased access to oral communication and the "hearing" world means oral communication is prioritized by hearing parents. Language plays a key role within culture and these communication decisions are likely to be associated with children's level of d/Deaf acculturation. This study was based on qualitative interviews. Thirty-two people associated with 14 children were interviewed; these were parents of children with CIs, four children over age 11 years, and teachers of 13 of the children. The study aimed to investigate parental communication decisions on child/family d/Deaf acculturation and the role of access to resources on children's d/Deaf acculturation development. Findings indicate two profiles of family acculturation-oral and bicultural and point to a possible relationship between access to resources and parents' decision-making process.

Weight variability, physical functioning and incident disability in older adults.

BACKGROUND: This study aimed to determine if greater variability in body mass index (BMI) is associated with declines in physical functioning and incident disability in older adults. METHODS: Included were participants from the Health, Aging and Body Composition Study who had semi-annual BMI data during the first 3 years of follow-up. Participants were categorized into quintiles of BMI variability, using two methods. The first method used average successive variability, whereas the second method adjusted these values to remove the variability due to net change in BMI over the 3-year period. Linear regression was used to assess the relationship between the two measures of BMI variability and net changes in BMI, fat mass index, appendicular lean mass index, and Health, Aging and Body Composition Physical Performance Score during the first 3 years of the study. Cox proportional hazard models were used to assess the relationship of BMI variability with the subsequent incidence of new disability, adjusting for confounding factors. RESULTS: Among 2121 participants, those in the highest BMI variability quintile were more likely to lose both body mass (ß: -0.086 [95% confidence interval, CI: -0.133, -0.040], P < 0.01) and fat mass (ß: -0.059 [95% CI: -0.117, -0.002], P = 0.04) and had greater declines in physical performance score (ß: -0.094 [95% CI: -0.162, -0.026], P < 0.01) compared to participants with the least variability in BMI. Participants with high BMI variability also had higher rates of incident disability (hazard ratio: 1.36 [95% CI: 1.07, 1.72], P = 0.01), independent of net BMI change. CONCLUSIONS: BMI variability in older adults is associated with decline in physical performance and incident disability. This relationship cannot be explained by net weight loss alone, supporting it as an independent feature of frailty.

Malaria parasite detection and cell counting for human and mouse using thin blood smear microscopy.

Despite the remarkable progress that has been made to reduce global malaria mortality by 29% in the past 5 years, malaria is still a serious global health problem. Inadequate diagnostics is one of the major obstacles in fighting the disease. An automated system for malaria diagnosis can help to make malaria screening faster and more reliable. We present an automated system to detect and segment red blood cells (RBCs) and identify infected cells in Wright-Giemsa stained thin blood smears. Specifically, using image analysis and machine learning techniques, we process digital images of thin blood smears to determine the parasitemia in each smear. We use a cell extraction method to segment RBCs, in particular overlapping cells. We show that a combination of RGB color and texture features outperforms other features. We evaluate our method on microscopic blood smear images from human and mouse and show that it outperforms other techniques. For human cells, we measure an absolute error of 1.18% between the true and the automatic parasite counts. For mouse cells, our automatic counts correlate well with expert and flow cytometry counts. This makes our system the first one to work for both human and mouse.