Auditory Brainstem Evoked Response Patterns in the Neonatal Intensive Care Unit.

OBJECTIVE: Delayed maturation of auditory brainstem pathway in neonates admitted to the neonatal intensive care unit (NICU) may lead to misdiagnosis of children with normal peripheral hearing and inappropriate use of amplification devices. The aim of this study is to determine the pattern of auditory brain stem response in neonates admitted to the NICU for proper hearing assessment in this high-risk population. STUDY DESIGN: This prospective study was conducted on 1,469 infants who were admitted to the NICU, of which 1,423 had one or more risk factors for permanent congenital hearing loss and were screened with automated auditory brain stem response (AABR). A total of 60 infants were referred for diagnostic ABR analysis after failure on AABR screening. The control group comprised 60 well-baby nursery neonates with no risk factors for PCHL. RESULTS: Mean values of absolute latencies of waves III and V; interpeak latencies I-III, III-V, and I-V; amplitude of waves I, and V; and I/V amplitude ratio at 90 dBnHL measured for the right and left ears at 1 and 3 months of age show significant difference in NICU neonates compared with controls (p < 0.05). All the diagnostic ABR measurements significantly improved at the age of 3 months (p < 0.001) except wave I absolute latency of both groups (p > 0.05). Significant correlations were found between ABR readings at the age of 1 and 3 months and the gestational age of the NICU neonates (p < 0.05). CONCLUSION: Diagnostic ABR findings in NICU neonates suggested delayed maturation of the auditory brainstem pathway with a great impact of gestational age on this maturation. Auditory maturational changes were observed at 3 months of age of patient and control groups.

Development of Bioinformatics Infrastructure for Genomics Research.

BACKGROUND: Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet's role has evolved in response to changing needs from the consortium and the African bioinformatics community. OBJECTIVES: H3ABioNet set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage, and analysis. METHODS AND RESULTS: Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrollment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Because H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System, and eBiokits. A set of reproducible, portable, and cloud-scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for downstream interpretation of prioritized variants. To provide support for these and other bioinformatics queries, an online bioinformatics helpdesk backed by broad consortium expertise has been established. Further support is provided by means of various modes of bioinformatics training. CONCLUSIONS: For the past 4 years, the development of infrastructure support and human capacity through H3ABioNet, have significantly contributed to the establishment of African scientific networks, data analysis facilities, and training programs. Here, we describe the infrastructure and how it has affected genomics and bioinformatics research in Africa.