BackgroundDespite numerous medical advances in the care of at-risk preterm neonates, oral feeding still represents one of the first and most advanced neurological challenges facing this delicate population. Objective, quantitative, and noninvasive assessment tools, as well as neurotherapeutic strategies, are greatly needed in order to improve feeding and developmental outcomes. Pulsed pneumatic orocutaneous stimulation has been shown to improve nonnutritive sucking (NNS) skills in preterm infants who exhibit delayed or disordered nipple feeding behaviors. Separately, the study of the salivary transcriptome in neonates has helped identify biomarkers directly linked to successful neonatal oral feeding behavior. The combination of noninvasive treatment strategies and transcriptomic analysis represents an integrative approach to oral feeding in which rapid technological advances and personalized transcriptomics can safely and noninvasively be brought to the bedside to inform medical care decisions and improve care and outcomes.ObjectiveThe study aimed to conduct a multicenter randomized control trial (RCT) to combine molecular and behavioral methods in an experimental conceptualization approach to map the effects of PULSED somatosensory stimulation on salivary gene expression in the context of the acquisition of oral feeding habits in high-risk human neonates. The aims of this study represent the first attempt to combine noninvasive treatment strategies and transcriptomic assessments of high-risk extremely preterm infants (EPI) to (1) improve oral feeding behavior and skills, (2) further our understanding of the gene ontology of biologically diverse pathways related to oral feeding, (3) use gene expression data to personalize neonatal care and individualize treatment strategies and timing interventions, and (4) improve long-term developmental outcomes.MethodsA total of 180 extremely preterm infants from three neonatal intensive care units (NICUs) will be randomized to receive either PULSED or SHAM (non-pulsing) orocutaneous intervention simultaneous with tube feedings 3 times per day for 4 weeks, beginning at 30 weeks postconceptional age. Infants will also be assessed 3 times per week for NNS performance, and multiple saliva samples will be obtained each week for transcriptomic analysis, until infants have achieved full oral feeding status. At 18 months corrected age (CA), infants will undergo neurodevelopmental follow-up testing, the results of which will be correlated with feeding outcomes in the neo-and post-natal period and with gene expression data and intervention status.ResultsThe ongoing National Institutes of Health funded randomized controlled trial R01HD086088 is actively recruiting participants. The expected completion date of the study is 2021.ConclusionsDifferential salivary gene expression profiles in response to orosensory entrainment intervention are expected to lead to the development of individualized interventions for the diagnosis and management of oral feeding in preterm infants.Trial Registrat...
We performed a functional near-infrared spectroscopy (fNIRS) study of the evoked hemodynamic responses seen in hand and face sensorimotor cortical representations during (1) active motor tasks and (2) pulsed pneumotactile stimulation. Contralateral fNIRS measurements were performed on 22 healthy adult participants using a block paradigm that consisted of repetitive right hand and right oral angle somatosensory stimulation using a pulsed pneumotactile array stimulator, and repetitive right-hand grip compression and bilabial compressions on strain gages. Results revealed significant oxyhemoglobin (HbO) modulation across stimulus conditions in corresponding somatotopic cortical regions. Of the 22 participants, 86% exhibited a decreased HbO response during at least one of the stimulus conditions, which may be indicative of cortical steal, or hypo-oxygenation occurring in channels adjacent to the primary areas of activation. Across all conditions, 56% of participants' HbO responses were positive and 44% were negative. Hemodynamic responses most likely differed across hand and face motor and somatosensory cortical regions due to differences in regional arterial/venous anatomy, cortical vascular beds, extent and orientation of somatotopy, task dynamics, and mechanoreceptor typing in hand and face. The combination of optical imaging and task conditions allowed for non-invasive examination of hemodynamic changes in somatosensory and motor cortices using natural, pneumatic stimulation of glabrous hand and hairy skin of the lower face and functionally relevant and measurable motor tasks involving the same structures.
Background and Objective: The emergence of the nonnutritive suck (NNS) pattern in preterm infants reflects the integrity of the brain and is used by clinicians in the neonatal intensive care unit (NICU) to assess feeding readiness and oromotor development. A critical need exists for an integrated software platform that provides NNS signal preprocessing, adaptive waveform discrimination, feature detection, and batch processing of big data sets across multiple NICU sites. Thus, the goal was to develop and describe a cross-platform graphical user interface (GUI) and terminal application known as NeoNNS for single and batch file time series and frequency-domain analyses of NNS compression pressure waveforms using analysis parameters derived from previous research on NNS dynamics. Methods. NeoNNS was implemented with Python and the Tkinter GUI package. The NNS signal-processing pipeline included a low-pass filter, asymmetric regression baseline correction, NNS peak detection, and NNS burst classification. Data visualizations and parametric analyses included time- and frequency-domain view, NNS spatiotemporal index view, and feature cluster analysis to model oral feeding readiness. Results. 568 suck assessment files sampled from 30 extremely preterm infants were processed in the batch mode (<50 minutes) to generate time- and frequency-domain analyses of infant NNS pressure waveform data. NNS cycle discrimination and NNS burst classification yield quantification of NNS waveform features as a function of postmenstrual age. Hierarchical cluster analysis (based on the Tsfresh python package and NeoNNS) revealed the capability to label NNS records for feeding readiness. Conclusions. NeoNNS provides a versatile software platform to rapidly quantify the dynamics of NNS development in time and frequency domains at cribside over repeated sessions for an individual baby or among large numbers of preterm infants at multiple hospital sites to support big data analytics. The hierarchical cluster feature analysis facilitates modeling of feeding readiness based on quantitative features of the NNS compression pressure waveform.
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