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Search Results: 1 - 10 of 26467 matches for " Jennifer Kim "
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Neurocritical Care Training for the Neurosurgery Resident  [PDF]
Paul EKaloostian, Jennifer Kim, Howard Yonas
Open Journal of Modern Neurosurgery (OJMN) , 2013, DOI: 10.4236/ojmn.2013.32003

Introduction: Recent data has associated favorable outcomes in patients who were treated in a “semi-closed” intensive care unit and attended to by a devoted team of neurointensivists as opposed to the neurosurgeons. This has led many to question the need for dedicated critical care education in the neurosurgical residency training program. Our aim was to determine what current neurosurgery residents and program directors/chairman thoughts were on NCC education in neurosurgical resident training, and to discuss possible methods to allow for collaboration between the NCC team and the neurosurgeons. Methods: Surveys were sent out electronically to all residency programs. Thirty-nine responses from junior residents, 36 responses from senior/chief residents, and eight responses from program directors/chairman were obtained. Results: No statistical difference between the majority responses of the different level residents, and between program directors/chairman and combined resident responses. Conclusions: Clearly, neurosurgery residents of all levels and program directors/chairman value NCC education and see a valuable role for this knowledge in their future. Most residents however do not want to spend an additional year of fellowship training to become certified neurointensivists. We discuss the role of NCC education in residency training and possible solutions to allow collaboration between the NCC team and the neurosurgical team.

RELATCH: relative optimality in metabolic networks explains robust metabolic and regulatory responses to perturbations
Joonhoon Kim, Jennifer L Reed
Genome Biology , 2012, DOI: 10.1186/gb-2012-13-9-r78
Abstract: Computational modeling of metabolic networks has been useful in studying microbial metabolism and developing tools for many applications. Among different computational approaches, constraint-based models utilize genome-scale metabolic networks to predict metabolic flux distributions in microbial cells, and they have been used to guide metabolic engineering [1], drug discovery [2], and adaptive evolution [3] studies. For example, flux balance analysis (FBA) predicts metabolic flux distributions in optimally growing microbes, by maximizing biomass yields [4,5]. FBA can also predict the effects of gene deletions on metabolic behaviors by removing the associated reactions from the network, and its predictions are shown to be consistent with experimental observations for parental and gene knockout strains of Escherichia coli that have undergone adaptive evolution [6,7]. Recently, FBA has been used to discover drug targets by identifying essential metabolic functions in different growth conditions representing the host environment [8,9]. Incorporation of additional molecular crowding constraints, which restrict total enzyme levels and thus flux capacities, into FBA improves growth rate predictions of parental and mutant E. coli strains in different environmental conditions [10]. Genomics-driven constraints, such as grouping reaction constraints [11] have also been incorporated to improve flux and growth rate predictions in genetically or environmentally perturbed strains.Several constraint-based approaches for integrating omics data (for example, transcriptomics, proteomics, or metabolomics) with metabolic models have been developed to predict metabolic flux distributions in different environmental or genetic conditions [12-16]. For example, E-Flux uses relative gene expression levels to place upper and lower bounds on individual fluxes in the models [12], while another approach, gene inactivity moderated by metabolism and expression (GIMME), instead uses expression data
OptORF: Optimal metabolic and regulatory perturbations for metabolic engineering of microbial strains
Joonhoon Kim, Jennifer L Reed
BMC Systems Biology , 2010, DOI: 10.1186/1752-0509-4-53
Abstract: Here we propose an effective method to systematically integrate transcriptional regulatory networks and metabolic networks. This allows for the formulation of linear optimization problems that search for metabolic and/or regulatory perturbations that couple biomass and biochemical production, thus proposing adaptive evolutionary strain designs. Using genome-scale models of Escherichia coli, we have implemented the OptORF algorithm (which considers gene deletions and transcriptional regulation) and compared its metabolic engineering strategies for ethanol production to those found using OptKnock (which considers reaction deletions). Our results found that the reaction-based strategies often require more gene deletions to remove the identified reactions (2 more genes than reactions), and result in lethal growth phenotypes when transcriptional regulation is considered (162 out of 200 cases). Finally, we present metabolic engineering strategies for producing ethanol and higher alcohols (e.g. isobutanol) in E. coli using our OptORF approach. We have found common genetic modifications such as deletion of pgi and overexpression of edd, as well as chemical specific strategies for producing different alcohols.By taking regulatory effects into account, OptORF can propose changes such as the overexpression of metabolic genes or deletion of transcriptional factors, in addition to the deletion of metabolic genes, that may lead to faster evolutionary trajectories. While biofuel production in E. coli is evaluated here, the developed OptORF approach is general and can be applied to optimize the production of different compounds in other biological systems.Metabolic engineering has emerged as an important field aimed to improve cellular production of valuable biochemicals and biofuels. Conventional approaches in metabolic engineering for identifying targets for manipulation focus on metabolic branch points, where undesired reactions are eliminated from competing branches to enhance
An Automated Phenotype-Driven Approach (GeneForce) for Refining Metabolic and Regulatory Models
Dipak Barua ,Joonhoon Kim ,Jennifer L. Reed
PLOS Computational Biology , 2010, DOI: 10.1371/journal.pcbi.1000970
Abstract: Integrated constraint-based metabolic and regulatory models can accurately predict cellular growth phenotypes arising from genetic and environmental perturbations. Challenges in constructing such models involve the limited availability of information about transcription factor—gene target interactions and computational methods to quickly refine models based on additional datasets. In this study, we developed an algorithm, GeneForce, to identify incorrect regulatory rules and gene-protein-reaction associations in integrated metabolic and regulatory models. We applied the algorithm to refine integrated models of Escherichia coli and Salmonella typhimurium, and experimentally validated some of the algorithm's suggested refinements. The adjusted E. coli model showed improved accuracy (~80.0%) for predicting growth phenotypes for 50,557 cases (knockout mutants tested for growth in different environmental conditions). In addition to identifying needed model corrections, the algorithm was used to identify native E. coli genes that, if over-expressed, would allow E. coli to grow in new environments. We envision that this approach will enable the rapid development and assessment of genome-scale metabolic and regulatory network models for less characterized organisms, as such models can be constructed from genome annotations and cis-regulatory network predictions.
Cellular Scale Anisotropic Topography Guides Schwann Cell Motility
Jennifer A. Mitchel, Diane Hoffman-Kim
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0024316
Abstract: Directed migration of Schwann cells (SC) is critical for development and repair of the peripheral nervous system. Understanding aspects of motility specific to SC, along with SC response to engineered biomaterials, may inform strategies to enhance nerve regeneration. Rat SC were cultured on laminin-coated microgrooved poly(dimethyl siloxane) platforms that were flat or presented repeating cellular scale anisotropic topographical cues, 30 or 60 μm in width, and observed with timelapse microscopy. SC motion was directed parallel to the long axis of the topography on both the groove floor and the plateau, with accompanying differences in velocity and directional persistence in comparison to SC motion on flat substrates. In addition, feature dimension affected SC morphology, alignment, and directional persistence. Plateaus and groove floors presented distinct cues which promoted differential motility and variable interaction with the topographical features. SC on the plateau surfaces tended to have persistent interactions with the edge topography, while SC on the groove floors tended to have infrequent contact with the corners and walls. Our observations suggest the capacity of SC to be guided without continuous contact with a topographical cue. SC exhibited a range of distinct motile morphologies, characterized by their symmetry and number of extensions. Across all conditions, SC with a single extension traveled significantly faster than cells with more or no extensions. We conclude that SC motility is complex, where persistent motion requires cellular asymmetry, and that anisotropic topography with cellular scale features can direct SC motility.
Predictors of outcome in neck pain patients undergoing chiropractic care: comparison of acute and chronic patients
Cynthia Peterson, Jennifer Bolton, B Kim Humphreys
Chiropractic & Manual Therapies , 2012, DOI: 10.1186/2045-709x-20-27
Abstract: Acute (< 4 weeks) (n?=?274) and chronic (> 3 months) (n?=?255) neck pain patients with no chiropractic or manual therapy in the prior 3 months were included. Patients completed the numerical pain rating scale (NRS) and Bournemouth questionnaire (BQ) at baseline prior to treatment. At 1 week, 1 month and 3 months after start of treatment the NRS and BQ were completed along with the Patient Global Impression of Change (PGIC) scale. Demographic information was provided by the clinician. Improvement at each of the follow up points was categorized using the PGIC. Multivariate regression analyses were done to determine significant independent predictors of improvement.Baseline mean neck pain and total disability scores were significantly (p?<?0.001and p?<?0.008 respectively) higher in acute patients. Both groups reported significant improvement at all data collection time points, but was significantly larger for acute patients. The PGIC score at 1 week (OR?=?3.35, 95% CI?=?1.13-9.92) and the baseline to 1 month BQ total change score (OR?=?1.07, 95% CI?=?1.03-1.11) were identified as independent predictors of improvement at 3 months for acute patients. Chronic patients who reported improvement on the PGIC at 1 month were more likely to be improved at 3 months (OR?=?6.04, 95% CI?=?2.76-13.69). The presence of cervical radiculopathy or dizziness was not predictive of a negative outcome in these patients.The most consistent predictor of clinically relevant improvement at both 1 and 3 months after the start of chiropractic treatment for both acute and chronic patients is if they report improvement early in the course of treatment. The co-existence of either radiculopathy or dizziness however do not imply poorer prognosis in these patients.Patients suffering from neck pain are second only to low back pain patients in terms of the frequency of presentation for chiropractic treatment [1-4]. For many of these patients the precise diagnosis is difficult to ascertain and thus become
Socioeconomic disparities in behavioral risk factors and health outcomes by gender in the Republic of Korea
Hak-Ju Kim, Jennifer Ruger
BMC Public Health , 2010, DOI: 10.1186/1471-2458-10-195
Abstract: We examined data from a nationally representative stratified random sample of 4213 men and 4618 women from the 1998 Korea National Health and Nutrition Examination Survey, and 8289 men and 8827 women from the 2005 Korea National Health and Nutrition Examination Survey using General Linear Modeling and multiple logistic regression methods.Controlling for behavioral risk factors (smoking, drinking, obesity, exercise, and sleep), those in lower socioeconomic positions had poorer health outcomes in both self-reported acute and chronic disease and subjective measures; differences were especially pronounced among women. A socioeconomic gradient for education and income was found for both men and women for morbidity and self-reported health status, but the gradient was more pronounced in women. In 1998, the odds ratios (ORs) of higher morbidity for illiterate vs. college educated females was 5.4:1 and 1.9:1 for females in the lowest income quintile vs. the highest. The OR for education decreased in 2005 to 2.9:1 and that for income quintiles remained the same at 1.9:1. The OR of lower self-reported health status for illiterate vs. college educated females was 2.9:1 and 1.6:1 for females in the lowest income quintile vs. the highest in 1998, and 3.3:1 and 2.3:1 in 2005.Among Korean adults, men and women in lower socioeconomic position, as denoted by education, income, and somewhat less by occupation, experience significantly higher levels of morbidity and lower self-reported health status, even after controlling for standard behavioral risk factors. Disparities were more pronounced for women than for men. Efforts to reduce health disparities in South Korea require attention to the root causes of socioeconomic inequality and gender differences in the impact of socioeconomic position on health.Health disparities research has documented the significant relationship between social and economic inequalities and health status, although the role of specific types of social and eco
Reproductive Toxic Effects of Cisplatin and Its Modulation by the Antioxidant Sodium 2-Mercaptoethanesulfonate (Mesna) in Female Rats
John Yeh, Beom Su Kim and Jennifer Peresie
Reproductive Biology Insights , 2012, DOI: 10.4137/RBI.S7663
Abstract: Study Objective: Chemical protection against cisplatin, which is a commonly used cancer chemotherapeutic agent, is not well defined. We tested the hypothesis that the antioxidant mesna might protect against the cisplatin-induced repoductive effects in female rats. Design & Setting: Adult female rats were injected with saline, cisplatin alone, or mesna + cisplatin, mated with males, and euthanized on gestational day 17. Patients: Animal Model. Interventions: The administration of either cisplatin or mesna + cisplatin (two injections one week apart, mesna 30 minute pretreatment) followed by mating one week after treatment. Main Outcomes Measured: The number corpora lutea, implantation and resorptions sites, viable and non-viable fetuses, fetal weights, and the level of progesterone per corpus luteum. Results: The administration of cisplatin caused an increase in pre- and post- implantation loss, an increase in the number of resorptions and a decrease in the number of viable fetuses. Mesna administered prior to cisplatin resulted in a decrease in the rate of the pre- and post implantation loss, along with a decrease in the number of resorptions and an increase in the number of live fetuses. Conclusions: Prior exposure to cisplatin caused significant adverse effects on fertility as evidenced by the decreased implantation due to increased fetal loss. The administration of mesna appeared to temper cisplatin damage by lessening the cisplatin effects on fetal resorption.
High temperatures alter physiological properties of pyramidal cells and inhibitory interneurons in hippocampus
Jennifer A. Kim,Barry W. Connors
Frontiers in Cellular Neuroscience , 2012, DOI: 10.3389/fncel.2012.00027
Abstract: Temperature has multiple effects on neurons, yet little is known about the effects of high temperature on the physiology of mammalian central neurons. Hyperthermia can influence behavior and cause febrile seizures. We studied the effects of acute hyperthermia on the immature hippocampus in vitro by recording from pyramidal neurons and inhibitory oriens-lacunosum moleculare (O-LM) interneurons (identified by green fluorescent protein (GFP) expression in the GIN mouse line). Warming to 41°C caused depolarization, spontaneous action potentials, reduced input resistance and membrane time constant, and increased spontaneous synaptic activity of most pyramidal cells and O-LM interneurons. Pyramidal neurons of area CA3 were more strongly excited by hyperthermia than those of area CA1. About 90% of O-LM interneurons in both CA1 and CA3 increased their firing rates at hyperthermic temperatures; interneurons in CA3 fired faster than those in CA1 on average. Blockade of fast synaptic transmission did not abolish the effect of hyperthermia on neuronal excitability. Our results suggest that hyperthermia increases hippocampal excitability, particularly in seizure-prone area CA3, by altering the intrinsic membrane properties of pyramidal cells and interneurons.
Majorana Zero Modes in Semiconductor Nanowires in Contact with Higher-$T_c$ Superconductors
Younghyun Kim,Jennifer Cano,Chetan Nayak
Physics , 2012, DOI: 10.1103/PhysRevB.86.235429
Abstract: We analyze the prospects for stabilizing Majorana zero modes in semiconductor nanowires that are proximity-coupled to higher-temperature superconductors. We begin with the case of iron pnictides which, though they are s-wave superconductors, are believed to have superconducting gaps that change sign. We then consider the case of cuprate superconudctors. We show that a nanowire on a step-like surface, especially in an orthorhombic material such as YBCO, can support Majorana zero modes at an elevated temperature.
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