Validation of network communicability metrics for the analysis of brain structural networks.

Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

A regulatory network for the efficient control of transgene expression.

BACKGROUND: Expression of heterologous genes in mammalian cells or organisms for therapeutic or experimental purposes often requires tight control of transgene expression. Specifically, the following criteria should be met: no background gene activity in the off-state, high gene expression in the on-state, regulated expression over an extended period, and multiple switching between on- and off-states. METHODS: Here, we describe a genetic switch system for controlled transgene transcription using chimeric repressor and activator proteins functioning in a novel regulatory network. In the off-state, the target transgene is actively silenced by a chimeric protein consisting of multimerized eukaryotic transcriptional repression domains fused to the DNA-binding tetracycline repressor. In the on-state, the inducer drug doxycycline affects both the derepression of the target gene promoter and activation by the GAL4-VP16 transactivator, which in turn is under the control of an autoregulatory feedback loop. RESULTS: The hallmark of this new system is the efficient transgene silencing in the off-state, as demonstrated by the tightly controlled expression of the highly cytotoxic diphtheria toxin A gene. Addition of the inducer drug allows robust activation of transgene expression. In stably transfected cells, this control is still observed after months of repeated cycling between the repressed and activated states of the target genes. CONCLUSIONS: This system permits tight long-term regulation when stably introduced into cell lines. The underlying principles of this network system should have general applications in biotechnology and gene therapy.

Candida species distribution and antifungal susceptibility testing according to European Committee on Antimicrobial Susceptibility Testing and new vs. old Clinical and Laboratory Standards Institute clinical breakpoints: a 6-year prospective candidaemia survey from the fungal infection network of Switzerland.

We analyzed the species distribution of Candida blood isolates (CBIs), prospectively collected between 2004 and 2009 within FUNGINOS, and compared their antifungal susceptibility according to clinical breakpoints defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST) in 2013, and the Clinical and Laboratory Standards Institute (CLSI) in 2008 (old CLSI breakpoints) and 2012 (new CLSI breakpoints). CBIs were tested for susceptiblity to fluconazole, voriconazole and caspofungin by microtitre broth dilution (Sensititre(®) YeastOne? test panel). Of 1090 CBIs, 675 (61.9%) were C. albicans, 191 (17.5%) C. glabrata, 64 (5.9%) C. tropicalis, 59 (5.4%) C. parapsilosis, 33 (3%) C. dubliniensis, 22 (2%) C. krusei and 46 (4.2%) rare Candida species. Independently of the breakpoints applied, C. albicans was almost uniformly (>98%) susceptible to all three antifungal agents. In contrast, the proportions of fluconazole- and voriconazole-susceptible C. tropicalis and F-susceptible C. parapsilosis were lower according to EUCAST/new CLSI breakpoints than to the old CLSI breakpoints. For caspofungin, non-susceptibility occurred mainly in C. krusei (63.3%) and C. glabrata (9.4%). Nine isolates (five C. tropicalis, three C. albicans and one C. parapsilosis) were cross-resistant to azoles according to EUCAST breakpoints, compared with three isolates (two C. albicans and one C. tropicalis) according to new and two (2 C. albicans) according to old CLSI breakpoints. Four species (C. albicans, C. glabrata, C. tropicalis and C. parapsilosis) represented >90% of all CBIs. In vitro resistance to fluconazole, voriconazole and caspofungin was rare among C. albicans, but an increase of non-susceptibile isolates was observed among C. tropicalis/C. parapsilosis for the azoles and C. glabrata/C. krusei for caspofungin according to EUCAST and new CLSI breakpoints compared with old CLSI breakpoints.

Resting-brain functional connectivity predicted by analytic measures of network communication.

The complex relationship between structural and functional connectivity, as measured by noninvasive imaging of the human brain, poses many unresolved challenges and open questions. Here, we apply analytic measures of network communication to the structural connectivity of the human brain and explore the capacity of these measures to predict resting-state functional connectivity across three independently acquired datasets. We focus on the layout of shortest paths across the network and on two communication measures-search information and path transitivity-which account for how these paths are embedded in the rest of the network. Search information is an existing measure of information needed to access or trace shortest paths; we introduce path transitivity to measure the density of local detours along the shortest path. We find that both search information and path transitivity predict the strength of functional connectivity among both connected and unconnected node pairs. They do so at levels that match or significantly exceed path length measures, Euclidean distance, as well as computational models of neural dynamics. This capacity suggests that dynamic couplings due to interactions among neural elements in brain networks are substantially influenced by the broader network context adjacent to the shortest communication pathways.

Iowa Department of Transportation Fiscal Year 2011 Report of Savings by Using Video Conferencing Through Iowa Communications Network to the Iowa General Assembly

Iowa Code section 8D.10 requires certain state agencies prepare an annual report to the General Assembly certifying the identified savings associated with that state agency’s use of the Iowa Communications Network (ICN). This report covers estimated cost savings related to video conferencing via ICN for the Iowa Department of Transportation (Iowa DOT). In fiscal year 2011, the Iowa DOT did not conduct any sessions utilizing ICN’s video conferencing system, therefore, no cost savings were calculated for this report.

Iowa Commercial and Industrial Network, January 1, 2011

Map produced by Iowa Department of Transportation about Iowa Commercial and Industrial Network.

Agency Fact Sheet, Department of Iowa Communications Network, FY2007

This document produced by the Iowa Department of Administrative Services has been developed to provide a multitude of information about executive branch agencies/department on a single sheet of paper. The facts provides general information, contact information, workforce data, leave and benefits information and affirmative action data.

Soil infiltration based on bp neural network and grey relational analysis

Soil infiltration is a key link of the natural water cycle process. Studies on soil permeability are conducive for water resources assessment and estimation, runoff regulation and management, soil erosion modeling, nonpoint and point source pollution of farmland, among other aspects. The unequal influence of rainfall duration, rainfall intensity, antecedent soil moisture, vegetation cover, vegetation type, and slope gradient on soil cumulative infiltration was studied under simulated rainfall and different underlying surfaces. We established a six factor-model of soil cumulative infiltration by the improved back propagation (BP)-based artificial neural network algorithm with a momentum term and self-adjusting learning rate. Compared to the multiple nonlinear regression method, the stability and accuracy of the improved BP algorithm was better. Based on the improved BP model, the sensitive index of these six factors on soil cumulative infiltration was investigated. Secondly, the grey relational analysis method was used to individually study grey correlations among these six factors and soil cumulative infiltration. The results of the two methods were very similar. Rainfall duration was the most influential factor, followed by vegetation cover, vegetation type, rainfall intensity and antecedent soil moisture. The effect of slope gradient on soil cumulative infiltration was not significant.

Citrus fruit and cancer risk in a network of case-control studies.

BACKGROUND: Citrus fruit has shown a favorable effect against various cancers. To better understand their role in cancer risk, we analyzed data from a series of case-control studies conducted in Italy and Switzerland. PATIENTS AND METHODS: The studies included 955 patients with oral and pharyngeal cancer, 395 with esophageal, 999 with stomach, 3,634 with large bowel, 527 with laryngeal, 2,900 with breast, 454 with endometrial, 1,031 with ovarian, 1,294 with prostate, and 767 with renal cell cancer. All cancers were incident and histologically confirmed. Controls were admitted to the same network of hospitals for acute, nonneoplastic conditions. Odds ratios (OR) were estimated by multiple logistic regression models, including terms for major identified confounding factors for each cancer site, and energy intake. RESULTS: The ORs for the highest versus lowest category of citrus fruit consumption were 0.47 (95% confidence interval, CI, 0.36-0.61) for oral and pharyngeal, 0.42 (95% CI, 0.25-0.70) for esophageal, 0.69 (95% CI, 0.52-0.92) for stomach, 0.82 (95% CI, 0.72-0.93) for colorectal, and 0.55 (95% CI, 0.37-0.83) for laryngeal cancer. No consistent association was found with breast, endometrial, ovarian, prostate, and renal cell cancer. CONCLUSIONS: Our findings indicate that citrus fruit has a protective role against cancers of the digestive and upper respiratory tract.