Kristin Melton

Interfering with Wnt signalling alters the periodicity of the segmentation clock.

Somites are embryonic precursors of the ribs, vertebrae and certain dermis tissue. Somite formation is a periodic process regulated by a molecular clock which drives cyclic expression of a number of clock genes in the presomitic mesoderm. To date the mechanism regulating the period of clock gene oscillations is unknown. Here we show that chick homologues of the Wnt pathway genes that oscillate in mouse do not cycle across the chick presomitic mesoderm. Strikingly we find that modifying Wnt signalling changes the period of Notch driven oscillations in both mouse and chick but these oscillations continue. We propose that the Wnt pathway is a conserved mechanism that is involved in regulating the period of cyclic gene oscillations in the presomitic mesoderm.

Gene expression and regulation of hindbrain and spinal cord development.

The formation of the central nervous system is one of the most fascinating processes in biology. Motor coordination, sensory perception and memory all depend on the complex cell connections that form with extraordinary precision between distinct nerve cell types within the central nervous system. The development of the central nervous system and its intricate connections occurs in several steps. During the first step known as neural induction, the neural plate forms as a uniform sheet of neuronal progenitors. Neural induction is followed by neurulation, the process in which the two halves of the neural plate are transformed into a hollow tube. Neurulation is accompanied by regionalisation of the neural tube anterior-posteriorly into the brain and spinal cord and dorso-ventrally into neural crest cells and numerous classes of sensory and motor neurons. The proper development of the vertebrate central nervous system requires the precise, finely balanced control of cell specification and proliferation, which is achieved through the complex interplay of multiple signaling systems. Bone morphogenetic proteins (BMPs), retinoic acid (RA) fibroblast growth factors (FGFs), Wnt and Hedgehog proteins are a few key factors that interact to pattern the developing central nervous system. In this review, we detail our current knowledge of the roles of these signaling factors in the development of the vertebrate nervous system in terms of the mechanisms underlying the formation and specification of the hindbrain and spinal cord.

Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care

Background Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection within the neonatal intensive care unit (NICU) environment. Objective This paper presents two phenotyping AE and ME detection algorithms (ie, IV infiltrations, narcotic medication oversedation and dosing errors) and describes manual annotation of airway management and medication/fluid AEs from NICU EHRs. Methods From 753 NICU patient EHRs from 2011, we developed two automatic AE/ME detection algorithms, and manually annotated 11 classes of AEs in 3263 clinical notes. Performance of the automatic AE/ME detection algorithms was compared to trigger tool and voluntary incident reporting results. AEs in clinical notes were double annotated and consensus achieved under neonatologist supervision. Sensitivity, positive predictive value (PPV), and specificity are reported. Results Twelve severe IV infiltrates were detected. The algorithm identified one more infiltrate than the trigger tool and eight more than incident reporting. One narcotic oversedation was detected demonstrating 100% agreement with the trigger tool. Additionally, 17 narcotic medication MEs were detected, an increase of 16 cases over voluntary incident reporting. Conclusions Automated AE/ME detection algorithms provide higher sensitivity and PPV than currently used trigger tools or voluntary incident-reporting systems, including identification of potential dosing and frequency errors that current methods are unequipped to detect.

A phenotype-driven ENU mutagenesis screen identifies novel alleles with functional roles in early mouse craniofacial development.

Proper craniofacial development begins during gastrulation and requires the coordinated integration of each germ layer tissue (ectoderm, mesoderm, and endoderm) and its derivatives in concert with the precise regulation of cell proliferation, migration, and differentiation. Neural crest cells, which are derived from ectoderm, are a migratory progenitor cell population that generates most of the cartilage, bone, and connective tissue of the head and face. Neural crest cell development is regulated by a combination of intrinsic cell autonomous signals acquired during their formation, balanced with extrinsic signals from tissues with which the neural crest cells interact during their migration and differentiation. Although craniofacial anomalies are typically attributed to defects in neural crest cell development, the cause may be intrinsic or extrinsic. Therefore, we performed a phenotype‐driven ENU mutagenesis screen in mice with the aim of identifying novel alleles in an unbiased manner, that are critically required for early craniofacial development. Here we describe 10 new mutant lines, which exhibit phenotypes affecting frontonasal and pharyngeal arch patterning, neural and vascular development as well as sensory organ morphogenesis. Interestingly, our data imply that neural crest cells and endothelial cells may employ similar developmental programs and be interdependent during early embryogenesis, which collectively is critical for normal craniofacial morphogenesis. Furthermore our novel mutants that model human conditions such as exencephaly, craniorachischisis, DiGeorge, and Velocardiofacial sydnromes could be very useful in furthering our understanding of the complexities of specific human diseases. genesis 49:342–359, 2011.

Somitogenesis: Breaking New Boundaries

Segmentation is a fundamental process in vertebrate embryogenesis, and one of the earliest manifestations of segmental patterning is the generation of transient, serially repeated blocks of mesodermal cells known as somites. Disruption of the normal segmentation process in humans leads to vertebral abnormalities such as spondylocostal dysostosis. In this minireview, we discuss recent advances in the dynamic molecular and cellular mechanisms governing segmentation.

Automated detection of medication administration errors in neonatal intensive care

OBJECTIVE To improve neonatal patient safety through automated detection of medication administration errors (MAEs) in high alert medications including narcotics, vasoactive medication, intravenous fluids, parenteral nutrition, and insulin using the electronic health record (EHR); to evaluate rates of MAEs in neonatal care; and to compare the performance of computerized algorithms to traditional incident reporting for error detection. METHODS We developed novel computerized algorithms to identify MAEs within the EHR of all neonatal patients treated in a level four neonatal intensive care unit (NICU) in 2011 and 2012. We evaluated the rates and types of MAEs identified by the automated algorithms and compared their performance to incident reporting. Performance was evaluated by physician chart review. RESULTS In the combined 2011 and 2012 NICU data sets, the automated algorithms identified MAEs at the following rates: fentanyl, 0.4% (4 errors/1005 fentanyl administration records); morphine, 0.3% (11/4009); dobutamine, 0 (0/10); and milrinone, 0.3% (5/1925). We found higher MAE rates for other vasoactive medications including: dopamine, 11.6% (5/43); epinephrine, 10.0% (289/2890); and vasopressin, 12.8% (54/421). Fluid administration error rates were similar: intravenous fluids, 3.2% (273/8567); parenteral nutrition, 3.2% (649/20124); and lipid administration, 1.3% (203/15227). We also found 13 insulin administration errors with a resulting rate of 2.9% (13/456). MAE rates were higher for medications that were adjusted frequently and fluids administered concurrently. The algorithms identified many previously unidentified errors, demonstrating significantly better sensitivity (82% vs. 5%) and precision (70% vs. 50%) than incident reporting for error recognition. CONCLUSIONS Automated detection of medication administration errors through the EHR is feasible and performs better than currently used incident reporting systems. Automated algorithms may be useful for real-time error identification and mitigation.

Endothelial cells are not required for specification of respiratory progenitors

Crosstalk between mesenchymal and epithelial cells influences organogenesis in multiple tissues, such as lung, pancreas, liver, and the nervous system. Lung mesenchyme comprises multiple cell types, however, and precise identification of the mesenchymal cell type(s) that drives early events in lung development remains unknown. Endothelial cells have been shown to be required for some aspects of lung epithelial patterning, lung stem cell differentiation, and regeneration after injury. Furthermore, endothelial cells are involved in early liver and pancreas development. From these observations we hypothesized that endothelial cells might also be required for early specification of the respiratory field and subsequent lung bud initiation. We first blocked VEGF signaling in E8.5 cultured foreguts with small molecule VEGFR inhibitors and found that lung specification and bud formation were unaltered. However, when we examined E9.5 mouse embryos carrying a mutation in the VEGFR Flk-1, which do not develop endothelial cells, we found that respiratory progenitor specification was impeded. Because the E9.5 embryos were substantially smaller than control littermates, suggesting the possibility of developmental delay, we isolated and cultured foreguts from mutant and control embryos on E8.5, when no size differences were apparent. We found that both specification of the respiratory field and lung bud formation occurred in mutant and control explants. These observations were unaffected by the presence or absence of serum. We also observed that hepatic specification and initiation occurred in the absence of endothelial cells, and that expansion of the liver epithelium in culture did not differ between mutant and control explants. Consistent with previously published results, we also found that pancreatic buds were not maintained in cultured foreguts when endothelial cells were absent. Our observations support the conclusion that endothelial cells are not required for early specification of lung progenitors and bud initiation, and that the diminished lung specification seen in E9.5 Flk−/− embryos is likely due to developmental delay resulting from the insufficient delivery of oxygen, nutrients, and other factors in the absence of a vasculature.

Using Health Information Technology to Improve Safety in Neonatal Care: A Systematic Review of the Literature

Health information technology (HIT) interventions may improve neonatal patient safety but may also introduce new errors. The objective of this review was to evaluate the evidence for use of HIT interventions to improve safety in neonatal care. Evidence for improvement exists for interventions like computerized provider order entry in the neonatal population, but is lacking for several other interventions. Many unique applications of HIT are emerging as technology and use of the electronic health record expands. Future research should focus on the impact of these interventions in the neonatal population.

Phenotyping for patient safety

Background Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection within the neonatal intensive care unit (NICU) environment. Objective This paper presents two phenotyping AE and ME detection algorithms (ie, IV infiltrations, narcotic medication oversedation and dosing errors) and describes manual annotation of airway management and medication/fluid AEs from NICU EHRs. Methods From 753 NICU patient EHRs from 2011, we developed two automatic AE/ME detection algorithms, and manually annotated 11 classes of AEs in 3263 clinical notes. Performance of the automatic AE/ME detection algorithms was compared to trigger tool and voluntary incident reporting results. AEs in clinical notes were double annotated and consensus achieved under neonatologist supervision. Sensitivity, positive predictive value (PPV), and specificity are reported. Results Twelve severe IV infiltrates were detected. The algorithm identified one more infiltrate than the trigger tool and eight more than incident reporting. One narcotic oversedation was detected demonstrating 100% agreement with the trigger tool. Additionally, 17 narcotic medication MEs were detected, an increase of 16 cases over voluntary incident reporting. Conclusions Automated AE/ME detection algorithms provide higher sensitivity and PPV than currently used trigger tools or voluntary incident-reporting systems, including identification of potential dosing and frequency errors that current methods are unequipped to detect.

Research and applications: Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care

Background Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection within the neonatal intensive care unit (NICU) environment. Objective This paper presents two phenotyping AE and ME detection algorithms (ie, IV infiltrations, narcotic medication oversedation and dosing errors) and describes manual annotation of airway management and medication/fluid AEs from NICU EHRs. Methods From 753 NICU patient EHRs from 2011, we developed two automatic AE/ME detection algorithms, and manually annotated 11 classes of AEs in 3263 clinical notes. Performance of the automatic AE/ME detection algorithms was compared to trigger tool and voluntary incident reporting results. AEs in clinical notes were double annotated and consensus achieved under neonatologist supervision. Sensitivity, positive predictive value (PPV), and specificity are reported. Results Twelve severe IV infiltrates were detected. The algorithm identified one more infiltrate than the trigger tool and eight more than incident reporting. One narcotic oversedation was detected demonstrating 100% agreement with the trigger tool. Additionally, 17 narcotic medication MEs were detected, an increase of 16 cases over voluntary incident reporting. Conclusions Automated AE/ME detection algorithms provide higher sensitivity and PPV than currently used trigger tools or voluntary incident-reporting systems, including identification of potential dosing and frequency errors that current methods are unequipped to detect.