An Examination of Dynamic Gene Expression Changes in the Mouse Brain During Pregnancy and the Postpartum Period.

The developmental transition to motherhood requires gene expression changes that alter the brain to drive the female to perform maternal behaviors. We broadly examined the global transcriptional response in the mouse maternal brain, by examining four brain regions: hypothalamus, hippocampus, neocortex, and cerebellum, in virgin females, two pregnancy time points, and three postpartum time points. We find that overall there are hundreds of differentially expressed genes, but each brain region and time point shows a unique molecular signature, with only 49 genes differentially expressed in all four regions. Interestingly, a set of "early-response genes" is repressed in all brain regions during pregnancy and postpartum stages. Several genes previously implicated in underlying postpartum depression change expression. This study serves as an atlas of gene expression changes in the maternal brain, with the results demonstrating that pregnancy, parturition, and postpartum maternal experience substantially impact diverse brain regions.

DNA-Encoded Chromatin Structural Intron Boundary Signals Identify Conserved Genes with Common Function.

The regulation of metazoan gene expression occurs in part by pre-mRNA splicing into mature RNAs. Signals affecting the efficiency and specificity with which introns are removed have not been completely elucidated. Splicing likely occurs cotranscriptionally, with chromatin structure playing a key regulatory role. We calculated DNA encoded nucleosome occupancy likelihood (NOL) scores at the boundaries between introns and exons across five metazoan species. We found that (i) NOL scores reveal a sequence-based feature at the introns on both sides of the intron-exon boundary; (ii) this feature is not part of any recognizable consensus sequence; (iii) this feature is conserved throughout metazoa; (iv) this feature is enriched in genes sharing similar functions: ATPase activity, ATP binding, helicase activity, and motor activity; (v) genes with these functions exhibit different genomic characteristics; (vi) in vivo nucleosome positioning data confirm ontological enrichment at this feature; and (vii) genes with this feature exhibit unique dinucleotide distributions at the intron-exon boundary. The NOL scores point toward a physical property of DNA that may play a role in the mechanism of pre-mRNA splicing. These results provide a foundation for identification of a new set of regulatory DNA elements involved in splicing regulation.

ContextProvider: Context awareness for medical monitoring applications.

Smartphones are sensor-rich and Internet-enabled. With their on-board sensors, web services, social media, and external biosensors, smartphones can provide contextual information about the device, user, and environment, thereby enabling the creation of rich, biologically driven applications. We introduce ContextProvider, a framework that offers a unified, query-able interface to contextual data on the device. Unlike other context-based frameworks, ContextProvider offers interactive user feedback, self-adaptive sensor polling, and minimal reliance on third-party infrastructure. ContextProvider also allows for rapid development of new context and bio-aware applications. Evaluation of ContextProvider shows the incorporation of an additional monitoring sensor into the framework with fewer than 100 lines of Java code. With adaptive sensor monitoring, power consumption per sensor can be reduced down to 1% overhead. Finally, through the use of context, accuracy of data interpretation can be improved by up to 80%.

iWander: An Android application for dementia patients.

Non-pharmacological management of dementia puts a burden on those who are taking care of a patient that suffer from this chronic condition. Caregivers frequently need to assist their patients with activities of daily living. However, they are also encouraged to promote functional independence. With the use of a discrete monitoring device, functional independence is increased among dementia patients while decreasing the stress put on caregivers. This paper describes a tool which improves the quality of treatment for dementia patients using mobile applications. Our application, iWander, runs on several Android based devices with GPS and communication capabilities. This allows for caregivers to cost effectively monitor their patients remotely. The data uncollected from the device is evaluated using Bayesian network techniques which estimate the probability of wandering behavior. Upon evaluation several courses of action can be taken based on the situation's severity, dynamic settings and probability. These actions include issuing audible prompts to the patient, offering directions to navigate them home, sending notifications to the caregiver containing the location of the patient, establishing a line of communication between the patient-caregiver and performing a party call between the caregiver-patient and patient's local 911. As patients use this monitoring system more, it will better learn and identify normal behavioral patterns which increases the accuracy of the Bayesian network for all patients. Normal behavior classifications are also used to alert the caregiver or help patients navigate home if they begin to wander while driving allowing for functional independence.

iFall: an Android application for fall monitoring and response.

Injuries due to falls are among the leading causes of hospitalization in elderly persons, often resulting in a rapid decline in quality of life or death. Rapid response can improve the patients outcome, but this is often lacking when the injured person lives alone and the nature of the injury complicates calling for help. This paper presents an alert system for fall detection using common commercially available electronic devices to both detect the fall and alert authorities. We use an Android-based smart phone with an integrated tri-axial accelerometer. Data from the accelerometer is evaluated with several threshold based algorithms and position data to determine a fall. The threshold is adaptive based on user provided parameters such as: height, weight, and level of activity. The algorithm adapts to unique movements that a phone experiences as opposed to similar systems which require users to mount accelerometers to their chest or trunk. If a fall is suspected a notification is raised requiring the user's response. If the user does not respond, the system alerts pre-specified social contacts with an informational message via SMS. If a contact responds the system commits an audible notification, automatically connects, and enables the speakerphone. If a social contact confirms a fall, an appropriate emergency service is alerted. Our system provides a realizable, cost effective solution to fall detection using a simple graphical interface while not overwhelming the user with uncomfortable sensors.