Faculty Bibliography

BACKGROUND: Simulation-based training provides a low-stress learning environment where real-life emergencies can be practiced. Simulation can improve surgical education and patient care in crisis situations through a team approach emphasizing interpersonal and communication skills. OBJECTIVE: This study assessed the effects of simulation-based training in the context of trauma resuscitation in teams of trainees. METHODS: In a New York State-certified level I trauma center, trauma alerts were assessed by a standardized video review process. Simulation training was provided in various trauma situations followed by a debriefing period. The outcomes measured included the number of healthcare workers involved in the resuscitation, the percentage of healthcare workers in role position, time to intubation, time to intubation from paralysis, time to obtain first imaging study, time to leave trauma bay for computed tomography scan or the operating room, presence of team leader, and presence of spinal stabilization. Thirty cases were video analyzed presimulation and postsimulation training. The two data sets were compared via a 1-sided t test for significance (p < 0.05). Nominal data were analyzed using the Fischer exact test. RESULTS: The data were compared presimulation and postsimulation. The number of healthcare workers involved in the resuscitation decreased from 8.5 to 5.7 postsimulation (p < 0.001). The percentage of people in role positions increased from 57.8% to 83.6% (p = 0.46). The time to intubation from paralysis decreased from 3.9 to 2.8 minutes (p < 0.05). The presence of a definitive team leader increased from 64% to 90% (p < 0.05). The rate of spine stabilization increased from 82% to 100% (p < 0.08). After simulation, training adherence to the advanced trauma life support algorithm improved from 56% to 83%. CONCLUSIONS: High-stress situations simulated in a low-stress environment can improve team interaction and educational competencies. Providing simulation training as a tool for surgical education may enhance patient care

Stem cell-based therapies offer tremendous potential for skin regeneration following injury and disease. Functional stem cell units have been described throughout all layers of human skin and the collective physical and chemical microenvironmental cues that enable this regenerative potential are known as the stem cell niche. Stem cells in the hair follicle bulge, interfollicular epidermis, dermal papillae, and perivascular space have been closely investigated as model systems for niche-driven regeneration. These studies suggest that stem cell strategies for skin engineering must consider the intricate molecular and biologic features of these niches. Innovative biomaterial systems that successfully recapitulate these microenvironments will facilitate progenitor cell-mediated skin repair and regeneration.

Neuropeptides play many important roles in cell-cell signaling and are involved in the control of anxiety, depression, pain, reward pathways, and many other processes that are relevant to psychiatric disorders. Mass spectrometry-based peptidomics techniques can identify the precise forms of peptides that are present in a given tissue. Utilizing this technique, peptides with any posttranslational modifications can be identified, and the exact sequence of the peptides can be determined. Unlike radioimmunoassays, which are limited by specific antibodies and often cannot discriminate between different lengths of peptides from the same precursor, peptidomics reveals the precise sequence and allows for the identification of both known and novel peptides. The use of isotopic labels allows for quantitative peptidomics, which results in the ability to compare peptide levels between differently treated samples. These tags can be synthesized in five different isotopic forms, permitting multivariate analysis of up to five different groups of tissue extracts in a single liquid chromatography/mass spectrometry run; this is ideal for measuring changes in neuropeptides in animals subjected to drug treatments, or in comparing animal models of psychiatric disorders.

In just the last decade, a multitude of bio-technologies and software pipelines have emerged to revolutionize genomics. To further their central goal, they aim to accelerate and improve the quality of de novo whole-genome assembly starting from short DNA sequences/reads. However, the performance of each of these tools is contingent on the length and quality of the sequencing data, the structure and complexity of the genome sequence, and the resolution and quality of long-range information. Furthermore, in the absence of any metric that captures the most fundamental "features" of a high-quality assembly, there is no obvious recipe for users to select the most desirable assembler/assembly. This situation has prompted the scientific community to rely on crowd-sourcing through international competitions, such as Assemblathons or GAGE, with the intention of identifying the best assembler(s) and their features. Somewhat circuitously, the only available approach to gauge de novo assemblies and assemblers relies solely on the availability of a high-quality fully assembled reference genome sequence. Still worse, reference-guided evaluations are often both difficult to analyze, leading to conclusions that are difficult to interpret. In this paper, we circumvent many of these issues by relying upon a tool, dubbed [Formula: see text], which is capable of evaluating de novo assemblies from the read-layouts even when no reference exists. We extend the FRCurve approach to cases where lay-out information may have been obscured, as is true in many deBruijn-graph-based algorithms. As a by-product, FRCurve now expands its applicability to a much wider class of assemblers - thus, identifying higher-quality members of this group, their inter-relations as well as sensitivity to carefully selected features, with or without the support of a reference sequence or layout for the reads. The paper concludes by reevaluating several recently conducted assembly competitions and the datasets that have resulted from them.

During the development of the spinal cord, proliferative neural progenitors differentiate into postmitotic neurons with distinct fates. How cells switch from progenitor states to differentiated fates is poorly understood. To address this question, we studied the differentiation of progenitors in the zebrafish spinal cord, focusing on the differentiation of Kolmer-Agduhr'' (KA'') interneurons from lateral floor plate (LFP) progenitors. In vivo cell tracking demonstrates that KA'' cells are generated from LFP progenitors by both symmetric and asymmetric cell divisions. A photoconvertible reporter of signaling history (PHRESH) reveals distinct temporal profiles of Hh response: LFP progenitors continuously respond to Hh, while KA'' cells lose Hh response upon differentiation. Hh signaling is required in LFP progenitors for KA'' fate specification, but prolonged Hh signaling interferes with KA'' differentiation. Notch signaling acts permissively to maintain LFP progenitor cells: activation of Notch signaling prevents differentiation, whereas inhibition of Notch signaling results in differentiation of ectopic KA'' cells. These results indicate that neural progenitors depend on Notch signaling to maintain Hh responsiveness and rely on Hh signaling to induce fate identity, whereas proper differentiation depends on the attenuation of both Notch and Hh signaling.

T cell lymphoblastic leukemia (T-ALL) is known to be associated with chromosomal abnormalities that lead to aberrant expression of a number of transcription factors such as TAL1, which dimerizes with basic helix-loop-helix (bHLH) E proteins and inhibits their function. Activated Notch receptors also efficiently induce T cell leukemogenesis in mouse models. Interestingly, gain-of-function mutations or cryptic transcription initiation of the Notch1 gene have been frequently found in both human and mouse T-ALL. However, the correlations between these alterations and overall Notch activities or leukemogenesis have not been thoroughly evaluated. Therefore, we made use of our collection of T cell lymphomas developed in transgenic mice expressing Id1, which like TAL1, inhibits E protein function. By comparing expression levels of Notch target genes in Id1-expressing tumors to those in tumors induced by a constitutively active form of Notch1, N1C, we were able to assess the overall activities of Notch pathways and conclude that the majority of Id1-expressing tumors had elevated Notch function to a varying degree. However, 26% of the Id1-expressing tumors had no evidence of enhanced Notch activation, but that did not delay the onset of tumorigenesis. Furthermore, we examined the genetic or epigenetic alterations thought to contribute to ligand-independent activation or protein stabilization of Notch1 and found that some of the Id1-expressing tumors acquired these changes, but they are not uniformly associated with elevated Notch activities in Id1 tumor samples. In contrast, N1C-expressing tumors do not harbor any PEST domain mutations nor exhibit intragenic transcription initiation. Taken together, it appears that Notch activation provides Id1-expressing tumor cells with selective advantages in growth and survival. However, this may not be absolutely essential for lymphomagenesis in Id1 transgenic mice and additional factors could also cooperate with Id1 to induce T cell lymphoma. Therefore, a broad approach is necessary in designing T-ALL therapy.

The development of alternative empirical (testing) and non-empirical (non-testing) methods to traditional toxicological tests for complex human health effects is a tremendous task. Toxicants may potentially interfere with a vast number of physiological mechanisms thereby causing disturbances on various levels of complexity of human physiology. Only a limited number of mechanisms relevant for toxicity ('pathways' of toxicity) have been identified with certainty so far and, presumably, many more mechanisms by which toxicants cause adverse effects remain to be identified. Recapitulating in empirical model systems (i.e., in vitro test systems) all those relevant physiological mechanisms prone to be disturbed by toxicants and relevant for causing the toxicity effect in question poses an enormous challenge. First, the mechanism(s) of action of toxicants in relation to the most relevant adverse effects of a specific human health endpoint need to be identified. Subsequently, these mechanisms need to be modeled in reductionist test systems that allow assessing whether an unknown substance may operate via a specific (array of) mechanism(s). Ideally, such test systems should be relevant for the species of interest, i.e., based on human cells or modeling mechanisms present in humans. Since much of our understanding about toxicity mechanisms is based on studies using animal model systems (i.e., experimental animals or animal-derived cells), designing test systems that model mechanisms relevant for the human situation may be limited by the lack of relevant information from basic research. New technologies from molecular biology and cell biology, as well as progress in tissue engineering, imaging techniques and automated testing platforms hold the promise to alleviate some of the traditional difficulties associated with improving toxicity testing for complex endpoints. Such new technologies are expected (1) to accelerate the identification of toxicity pathways with human relevance that need to be modeled in test methods for toxicity testing (2) to enable the reconstruction of reductionist test systems modeling at a reduced level of complexity the target system/organ of interest (e.g., through tissue engineering, use of human-derived cell lines and stem cells etc.), (3) to allow the measurement of specific mechanisms relevant for a given health endpoint in such test methods (e.g., through gene and protein expression, changes in metabolites, receptor activation, changes in neural activity etc.), (4) to allow to measure toxicity mechanisms at higher throughput rates through the use of automated testing. In this chapter, we discuss the potential impact of new technologies on the development, optimization and use of empirical testing methods, grouped according to important toxicological endpoints. We highlight, from an ECVAM perspective, the areas of topical toxicity, skin absorption, reproductive and developmental toxicity, carcinogenicity/genotoxicity, sensitization, hematopoeisis and toxicokinetics and discuss strategic developments including ECVAM's database service on alternative methods. Neither the areas of toxicity discussed nor the highlighted new technologies represent comprehensive listings which would be an impossible endeavor in the context of a book chapter. However, we feel that these areas are of utmost importance and we predict that new technologies are likely to contribute significantly to test development in these fields. We summarize which new technologies are expected to contribute to the development of new alternative testing methods over the next few years and point out current and planned ECVAM projects for each of these areas.

Disruption of cellular cholesterol balance results in pathologic processes including atherosclerosis, metabolic syndrome, type II diabetes and Alzheimer's disease. Maintenance of cholesterol homeostasis requires constant metabolic adjustment, achieved partly through the fine regulation of the classical transcription factors (e.g., by SREBP and LXR), but also through members of a class of noncoding RNAs termed miRNAs. Some miRNAs have now been identified to be potent post-transcriptional regulators of lipid metabolism genes, including miR-122, miR-33, miR-758, and miR-106b. Different strategies have been developed to modulate miRNA effects for therapeutic purposes. The promise demonstrated by the use of anti-miRs in human preclinical studies, in the case of miR-122, raises the possibility that miR-33, miR-758, and miR-106b may become viable therapeutic targets in future. This review summarizes the evidence for a critical role of some miRNAs in regulating cholesterol metabolism and suggests novel ways to manage dyslipidemias and cardiovascular diseases.