Establishing, versus Maintaining, Brain Function: A Neuro-computational Model of Cortical Reorganization after Injury to the Immature Brain

The effect of age at injury on outcome after acquired brain injury (ABI) has been the subject of much debate. Many argue that young brains are relatively tolerant of injury. A contrasting viewpoint due to Hebb argues that greater system integrity may be required for the initial establishment of a function than for preservation of an already-established function. A neuro-computational model of cortical map formation was adapted to examine effects of focal and distributed injury at various stages of development. This neural network model requires a period of training during which it self-organizes to establish cortical maps. Injuries were simulated by lesioning the model at various stages of this process and network function was monitored as "development" progressed to completion. Lesion effects are greater for larger, earlier, and distributed (multifocal) lesions. The mature system is relatively robust, particularly to focal injury. Activities in recovering systems injured at an early stage show changes that emerge after an asymptomatic interval. Early injuries cause qualitative changes in system behavior that emerge after a delay during which the effects of the injury are latent. Functions that are incompletely established at the time of injury may be vulnerable particularly to multifocal injury

Out of Sync: New Temporary Worker Proposals Unlikely to Meet U.S. Labor Needs

A key component of the immigration reform bill now being debated in Congress is a new temporary worker program that, ostensibly, would replace the current stream of undocumented migration with a regulated flow of less-skilled immigrant workers. However, growing long-term labor shortages in key industries dependent on less-skilled labor require the recruitment and training of permanent entry-level workers, both native-born and foreign-born, to fill a wide range of occupations. Yet the larger immigration reform bill provides for only a small increase in the overall level of permanent immigration, and the vast majority of this increase is not geared to the growing demand for less-skilled labor. In addition, the temporary worker provisions of the legislation, as they now stand, do not provide a path to permanent residence for any new temporary workers, and set a cap on the admission of temporary workers that falls well below current labor demand. As a result, neither industry nor workers have incentives to invest in each other to maximize the economic benefits of a temporary worker program. An alternative program that allows workers to apply for permanent status would better address industry's need for a larger and more settled less-skilled workforce and would more likely discourage undocumented immigration in the future

Alternate wiring of a KNOXI genetic network underlies differences in leaf development of A. thaliana and C. hirsuta

Two interrelated problems in biology are understanding the regulatory logic and predictability of morphological evolution. Here, we studied these problems by comparing Arabidopsis thaliana, which has simple leaves, and its relative, Cardamine hirsuta, which has dissected leaves comprising leaflets. By transferring genes between the two species, we provide evidence for an inverse relationship between the pleiotropy of SHOOTMERISTEMLESS (STM) and BREVIPEDICELLUS (BP) homeobox genes and their ability to modify leaf form. We further show that cis-regulatory divergence of BP results in two alternative configurations of the genetic networks controlling leaf development. In C. hirsuta, ChBP is repressed by the microRNA164A (MIR164A)/ChCUP-SHAPED COTYLEDON (ChCUC) module and ChASYMMETRIC LEAVES1 (ChAS1), thus creating cross-talk between MIR164A/CUC and AS1 that does not occur in A. thaliana. These different genetic architectures lead to divergent interactions of network components and growth regulation in each species. We suggest that certain regulatory genes with low pleiotropy are predisposed to readily integrate into or disengage from conserved genetic networks influencing organ geometry, thus rapidly altering their properties and contributing to morphological divergence

Urinary Protein Profiles in a Rat Model for Diabetic Complications

Diabetes mellitus is estimated to affect ∼24 million people in the United States and more than 150 million people worldwide. There are numerous end organ complications of diabetes, the onset of which can be delayed by early diagnosis and treatment. Although assays for diabetes are well founded, tests for its complications lack sufficient specificity and sensitivity to adequately guide these treatment options. In our study, we employed a streptozotocin- induced rat model of diabetes to determine changes in urinary protein profiles that occur during the initial response to the attendant hyperglycemia (e.g. the first two months) with the goal of developing a reliable and reproducible method of analyzing multiple urine samples as well as providing clues to early markers of disease progression. After filtration and buffer exchange, urinary proteins were digested with a specific protease, and the relative amounts of several thousand peptides were compared across rat urine samples representing various times after administration of drug or sham control. Extensive data analysis, including imputation of missing values and normalization of all data was followed by ANOVA analysis to discover peptides that were significantly changing as a function of time, treatment and interaction of the two variables. The data demonstrated significant differences in protein abundance in urine before observable pathophysiological changes occur in this animal model and as function of the measured variables. These included decreases in relative abundance of major urinary protein precursor and increases in pro-alpha collagen, the expression of which is known to be regulated by circulating levels of insulin and/or glucose. Peptides from these proteins represent potential biomarkers, which can be used to stage urogenital complications from diabetes. The expression changes of a pro-alpha 1 collagen peptide was also confirmed via selected reaction monitoring

Human Biomarker Discovery and Predictive Models for Disease Progression for Idiopathic Pneumonia Syndrome Following Allogeneic Stem Cell Transplantation

Allogeneic hematopoietic stem cell transplantation (SCT) is the only curative therapy for many malignant and non-malignant conditions. Idiopathic pneumonia syndrome (IPS) is a frequently fatal complication that limits successful outcomes. Preclinical models suggest that IPS represents an immune mediated attack on the lung involving elements of both the adaptive and the innate immune system. However, the etiology of IPS in humans is less well understood. To explore the disease pathway and uncover potential biomarkers of disease, we performed two separate label-free, proteomics experiments defining the plasma protein profiles of allogeneic SCT patients with IPS. Samples obtained from SCT recipients without complications served as controls. The initial discovery study, intended to explore the disease pathway in humans, identified a set of 81 IPS-associated proteins. These data revealed similarities between the known IPS pathways in mice and the condition in humans, in particular in the acute phase response. In addition, pattern recognition pathways were judged to be significant as a function of development of IPS, and from this pathway we chose the lipopolysaccaharide-binding protein (LBP) protein as a candidate molecular diagnostic for IPS, and verified its increase as a function of disease using an ELISA assay. In a separately designed study, we identified protein-based classifiers that could predict, at day 0 of SCT, patients who: 1) progress to IPS and 2) respond to cytokine neutralization therapy. Using cross-validation strategies, we built highly predictive classifier models of both disease progression and therapeutic response. In sum, data generated in this report confirm previous clinical and experimental findings, provide new insights into the pathophysiology of IPS, identify potential molecular classifiers of the condition, and uncover a set of markers potentially of interest for patient stratification as a basis for individualized therapy. © 2012 by The American Society for Biochemistry and Molecular Biology, Inc

Aquilegia, Vol. 40 No. 1 - Winter 2015-2016, Newsletter of the Colorado Native Plant Society

https://epublications.regis.edu/aquilegia/1188/thumbnail.jp

Performance Assessments of Nuclear Waste Repositories: A Dialogue on Their Value and Limitations

Performance Assessment (PA) is the use of mathematical models to simulate the long-term behavior of engineered and geologic barriers in a nuclear waste repository; methods of uncertainty analysis are used to assess effects of parametric and conceptual uncertainties associated with the model system upon the uncertainty in outcomes of the simulation. PA is required by the U.S. Environmental Protection Agency as part of its certification process for geologic repositories for nuclear waste. This paper is a dialogue to explore the value and limitations of PA. Two “skeptics” acknowledge the utility of PA in organizing the scientific investigations that are necessary for confident siting and licensing of a repository; however, they maintain that the PA process, at least as it is currently implemented, is an essentially unscientific process with shortcomings that may provide results of limited use in evaluating actual effects on public health and safety. Conceptual uncertainties in a PA analysis can be so great that results can be confidently applied only over short time ranges, the antithesis of the purpose behind long-term, geologic disposal. Two “proponents” of PA agree that performance assessment is unscientific, but only in the sense that PA is an engineering analysis that uses existing scientific knowledge to support public policy decisions, rather than an investigation intended to increase fundamental knowledge of nature; PA has different goals and constraints than a typical scientific study. The “proponents” describe an ideal, six-step process for conducting generalized PA, here called probabilistic systems analysis (PSA); they note that virtually all scientific content of a PA is introduced during the model-building steps of a PSA; they contend that a PA based on simple but scientifically acceptable mathematical models can provide useful and objective input to regulatory decision makers. The value of the results of any PA must lie between these two views and will depend on the level of knowledge of the site, the degree to which models capture actual physical and chemical processes, the time over which extrapolations are made, and the proper evaluation of health risks attending implementation of the repository. The challenge is in evaluating whether the quality of the PA matches the needs of decision makers charged with protecting the health and safety of the public.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45530/1/11161_2004_Article_220844.pd

Aquilegia, Vol. 37 No. 6, Winter 2013, Newsletter of the Colorado Native Plant Society

https://epublications.regis.edu/aquilegia/1146/thumbnail.jp

Integrated re-analysis of transcriptomic and proteomic datasets reveals potential mechanisms for Zika viral-based oncolytic therapy in neuroblastoma [version 3; peer review: 1 approved, 2 approved with reservations, 1 not approved]

Background Paediatric neuroblastoma and brain tumours account for a third of all childhood cancer-related mortality. High-risk neuroblastoma is highly aggressive and survival is poor despite intensive multi-modal therapies with significant toxicity. Novel therapies are desperately needed. The Zika virus (ZIKV) can access the nervous system and there is growing interest in employing ZIKV as a potential therapy against paediatric nervous system tumours, including neuroblastoma. Methods Here, we perform extensive data mining, integration and re-analysis of ZIKV infection datasets to highlight molecular mechanisms that may govern the oncolytic response in neuroblastoma cells. We collate infection data of multiple neuroblastoma cell lines by different ZIKV strains from a body of published literature to inform the susceptibility of neuroblastoma to the ZIKV oncolytic response. Integrating published transcriptomics, interaction proteomics, dependency factor and compound datasets we propose the involvement of multiple host systems during ZIKV infection. Results Through data mining of published literature, we observed most paediatric neuroblastoma cell lines to be highly susceptible to ZIKV infection and propose the PRVABC59 ZIKV strain to be the most promising candidate for neuroblastoma oncolytic virotherapy. ZIKV induces TNF signalling, lipid metabolism, the Unfolded Protein Response (UPR), and downregulates cell cycle and DNA replication processes. ZIKV infection is dependent on sterol regulatory element binding protein (SREBP)-regulated lipid metabolism and three protein complexes; V-ATPase, ER Membrane Protein Complex (EMC) and mammalian translocon. We propose ZIKV non-structural protein 4B (NS4B) as a likely mediator of ZIKVs interaction with IRE1-mediated UPR, lipid metabolism and mammalian translocon. Conclusions Our work provides a significant understanding of ZIKV infection in neuroblastoma cells, which will facilitate the progression of ZIKV-based oncolytic virotherapy through pre-clinical research and clinical trials