Spatial Updating in the Lateral Intraparietal Cortex

Recent experiments in neurophysiology have begun to examine the active nature of our perceptual experience. One area of research focuses on the impact of eye movements on visual perception. With each eye movement, a new image is presented to the brain, yet our perception is that the world remains stable. This phenomenon, termed spatial constancy, depends on a convergence of information about our eye movements with sensory information from the visual system. Neurons in the lateral intraparietal cortex (LIP) contribute to the construction of an internal representation of space that is updated or "remapped" with each eye movement. Although the basic phenomenon of remapping has been described, many questions remain unanswered. Here we describe two experiments designed to gain a greater understanding of spatial updating in the primate brain. First, we hypothesized that spatial updating would be equally robust throughout the visual field. We tested this by monitoring the activity of neurons in LIP while varying the direction over which a stimulus trace must be updated. We found that individual neurons remap stimulus traces in multiple directions, though the strength of the remapped response is variable. Across the population of LIP neurons, remapping is effectively independent of saccade direction. These findings indicate that the activity of LIP neurons can contribute to the maintenance of spatial constancy throughout the visual field. Second, to begin to understand the circuitry underlying remapping, we studied a special case: when a stimulus must be updated from one visual hemifield to the other. We hypothesized that the forebrain commissures provide the primary route for this across-hemifield remapping. We tested this by comparing the signal related to within- and across-hemifield remapping. We predicted that in split-brain monkeys, across-hemifield remapping would be abolished while within-hemifield remapping would remain robust. Surprisingly, we found that in split-brain monkeys, LIP neurons can remap stimulus traces across hemifields, though this signal is weaker than that associated with within-hemifield remapping. This finding implies that while the forebrain commissures are likely to be the primary route for the interhemispheric transfer of visual information, they are not the only route available. This indicates that a distributed network of brain regions supports spatial updating

A robust prognostic signature for hormone-positive node-negative breast cancer

BACKGROUND: Systemic chemotherapy in the adjuvant setting can cure breast cancer in some patients that would otherwise recur with incurable, metastatic disease. However, since only a fraction of patients would have recurrence after surgery alone, the challenge is to stratify high-risk patients (who stand to benefit from systemic chemotherapy) from low-risk patients (who can safely be spared treatment related toxicities and costs). METHODS: We focus here on risk stratification in node-negative, ER-positive, HER2-negative breast cancer. We use a large database of publicly available microarray datasets to build a random forests classifier and develop a robust multi-gene mRNA transcription-based predictor of relapse free survival at 10 years, which we call the Random Forests Relapse Score (RFRS). Performance was assessed by internal cross-validation, multiple independent data sets, and comparison to existing algorithms using receiver-operating characteristic and Kaplan-Meier survival analysis. Internal redundancy of features was determined using k-means clustering to define optimal signatures with smaller numbers of primary genes, each with multiple alternates. RESULTS: Internal OOB cross-validation for the initial (full-gene-set) model on training data reported an ROC AUC of 0.704, which was comparable to or better than those reported previously or obtained by applying existing methods to our dataset. Three risk groups with probability cutoffs for low, intermediate, and high-risk were defined. Survival analysis determined a highly significant difference in relapse rate between these risk groups. Validation of the models against independent test datasets showed highly similar results. Smaller 17-gene and 8-gene optimized models were also developed with minimal reduction in performance. Furthermore, the signature was shown to be almost equally effective on both hormone-treated and untreated patients. CONCLUSIONS: RFRS allows flexibility in both the number and identity of genes utilized from thousands to as few as 17 or eight genes, each with multiple alternatives. The RFRS reports a probability score strongly correlated with risk of relapse. This score could therefore be used to assign systemic chemotherapy specifically to those high-risk patients most likely to benefit from further treatment

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

Pest management guide : corn, cotton, grain sorghum, rice, soybean, winter wheat

"2015 Missouri."includes statistics"This guide is intended to provide current recommendations for control of the most problematic weeds, insects and diseases encountered in Missouri corn, soybean and winter wheat cropping systems."--Page 2.Kevin W. Bradley (Extension Weed Scientist, Department of Agronomy), Laura E. Sweets, (Extension Plant Pathologist, Department of Plant Microbiology and Pathology, Commercial Agricultural Program), Wayne C. Bailey (Extension Entomologist, Department of Entomology), Moneen M. Jones (Assistant Research Professor, Fisher Delta Research Center), James W. Heiser (Research Associate - Weed Science, Fisher Delta Research Center)New 1/05, Revised 12/14/3C

Propuesta de virtualización de servidores con Hyper-V en el centro de datos de la Facultad de Ciencias Médicas de la UNAN-Managua

La importancia del crecimiento en la potencia de cómputo y la existencia de problemas relacionados con el uso del hardware, ha hecho de la virtualización la solución más idónea para resolver tales dificultades, dentro de sus propósitos se encuentran hacer uso eficiente de los recursos y disminuir el costo total asociado a los mismos. Este trabajo de investigación fue realizado con la finalidad de proponer una solución para la virtualización servidores. La virtualización es una tecnología que permite la creación de equipos, basados en software, que reproducen el ambiente de una máquina física en sus aspectos de CPU, memoria, almacenamiento y entrada y salida de dispositivos. Se limita a trabajar básicamente con Hyper-V con el fin de acotar y definir la solución de virtualización , debido a la numerosa cantidad de soluciones que existen actualmente, como lo son VMware, Cytrix, entre otros. El enfoque principal se encontrará relacionado principalmente a la virtualización de servidores, a la disposición de Hyper-V para trabajar en cluster y al tipo de cluster que se puede implementar. El objetivo general de este trabajo es entonces, proponer una solución para efectuar la virtualización ya manera explicativa se describe como trabaja un cluster de alta disponibilidad con Hyper-V para efectuar tareas de migración de maquinas virtuales, empleando técnicas propias que vienen incorporadas en el software, como Live Migration ó Quick Migration que facilitan de gran forma la gestión y administración del entorno virtual. También se describirá brevemente los detalles técnicos para la implementación del centro de datos, la disposición de las áreas funcionales, el diagrama de distribución y otros parámetros importantes a tenerse en cuenta para disponer de un centro de datos confiable

Integrated analysis of breast cancer cell lines reveals unique signaling pathways

Mapping of sub-networks in the EGFR-MAPK pathway in different breast cancer cell lines reveals that PAK1 may be a marker for sensitivity to MEK inhibitors

Modeling precision treatment of breast cancer

Background: First-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets. Results: We used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples. Conclusions: These results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified

Genome co-amplification upregulates a mitotic gene network activity that predicts outcome and response to mitotic protein inhibitors in breast cancer.

BACKGROUND: High mitotic activity is associated with the genesis and progression of many cancers. Small molecule inhibitors of mitotic apparatus proteins are now being developed and evaluated clinically as anticancer agents. With clinical trials of several of these experimental compounds underway, it is important to understand the molecular mechanisms that determine high mitotic activity, identify tumor subtypes that carry molecular aberrations that confer high mitotic activity, and to develop molecular markers that distinguish which tumors will be most responsive to mitotic apparatus inhibitors. METHODS: We identified a coordinately regulated mitotic apparatus network by analyzing gene expression profiles for 53 malignant and non-malignant human breast cancer cell lines and two separate primary breast tumor datasets. We defined the mitotic network activity index (MNAI) as the sum of the transcriptional levels of the 54 coordinately regulated mitotic apparatus genes. The effect of those genes on cell growth was evaluated by small interfering RNA (siRNA). RESULTS: High MNAI was enriched in basal-like breast tumors and was associated with reduced survival duration and preferential sensitivity to inhibitors of the mitotic apparatus proteins, polo-like kinase, centromere associated protein E and aurora kinase designated GSK462364, GSK923295 and GSK1070916, respectively. Co-amplification of regions of chromosomes 8q24, 10p15-p12, 12p13, and 17q24-q25 was associated with the transcriptional upregulation of this network of 54 mitotic apparatus genes, and we identify transcription factors that localize to these regions and putatively regulate mitotic activity. Knockdown of the mitotic network by siRNA identified 22 genes that might be considered as additional therapeutic targets for this clinically relevant patient subgroup. CONCLUSIONS: We define a molecular signature which may guide therapeutic approaches for tumors with high mitotic network activity