A review of system dynamics models applied in social and humanitarian researches

Over the past decades, the number of disasters has been on the rise, including earthquakes, war, flood and other incidents that cause destruction of society, such as education and health services. Forecasts show that over the next 50 years, natural and manmade disasters are expected to increase five-folds both in the number and impact. Therefore, there is a need for effective and efficient disaster support actions during emergencies. This compels humanitarian organizations to improve the effectiveness and efficiency of their approaches and facilitate decision making in resolving such complicated problems characterized by numerous parameters. Besides, humanitarian organizations face situations with multiple critical events, inadequate funding, limited time to plan and react, and operating in increasingly challenging circumstances. Useful approaches for tackling problems in such dynamic conditions require methods and tools that take into account uncertainty and enable managers to evaluate the dynamic complexity of such systems, to facilitate decision making. Among the large amount of decision-aid tools for humanitarian organizations, System Dynamic (SD) is a method used for the evaluation of complex system behavior and for presenting the effect of decisions over time in an easy-to-use model. This method has been applied in humanitarian problems, and this paper aims to present a review of the most relevant humanitarian publications associated with system dynamics. This literature review is a structured review of the papers published since 2003 onwards. The finding of this research can be used to facilitate further research in developing the system dynamic methodology for humanitarian organizations and to present the essential requirement of SD tools for modeling complex environments

Future perspectives in melanoma research. Meeting report from the "Melanoma Research: a bridge Naples-USA. Naples, December 6th-7 th2010"

Progress in understanding the molecular basis of melanoma has made possible the identification of molecular targets with important implications in clinical practice. In fact, new therapeutic approaches are emerging from basic science and it will be important to implement their rapid translation into clinical practice by active clinical investigation

Steel and bone: Mesoscale modeling and middle-out strategies in physics and biology

Mesoscale modeling is often considered merely as a practical strategy used when information on lower-scale details is lacking, or when there is a need to make models cognitively or computationally tractable. Without dismissing the importance of practical constraints for modeling choices, we argue that mesoscale models should not just be considered as abbreviations or placeholders for more “complete” models. Because many systems exhibit different behaviors at various spatial and temporal scales, bottom-up approaches are almost always doomed to fail. Mesoscale models capture aspects of multi-scale systems that cannot be parameterized by simple averaging of lower-scale details. To understand the behavior of multi-scale systems, it is essential to identify mesoscale parameters that “code for” lower-scale details in a way that relate phenomena intermediate between microscopic and macroscopic features. We illustrate this point using examples of modeling of multi-scale systems in materials science (steel) and biology (bone), where identification of material parameters such as stiffness or strain is a central step. The examples illustrate important aspects of a so-called “middle-out” modeling strategy. Rather than attempting to model the system bottom-up, one starts at intermediate (mesoscopic) scales where systems exhibit behaviors distinct from those at the atomic and continuum scales. One then seeks to upscale and downscale to gain a more complete understanding of the multi-scale systems. The cases highlight how parameterization of lower-scale details not only enables tractable modeling but is also central to understanding functional and organizational features of multi-scale systems

ProbFAST: Probabilistic Functional Analysis System Tool

<p>Abstract</p> <p>Background</p> <p>The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered on the meaning of differential gene regulation under distinct biological conditions and can be performed by analyzing the Multiple Differential Expression (MDE) of genes associated with normal and abnormal biological processes. Currently MDE analyses are limited to usual methods of differential expression initially designed for paired analysis.</p> <p>Results</p> <p>We proposed a web platform named ProbFAST for MDE analysis which uses Bayesian inference to identify key genes that are intuitively prioritized by means of probabilities. A simulated study revealed that our method gives a better performance when compared to other approaches and when applied to public expression data, we demonstrated its flexibility to obtain relevant genes biologically associated with normal and abnormal biological processes.</p> <p>Conclusions</p> <p>ProbFAST is a free accessible web-based application that enables MDE analysis on a global scale. It offers an efficient methodological approach for MDE analysis of a set of genes that are turned on and off related to functional information during the evolution of a tumor or tissue differentiation. ProbFAST server can be accessed at <url>http://gdm.fmrp.usp.br/probfast</url>.</p

Analysis of the cell surface layer ultrastructure of the oral pathogen Tannerella forsythia

The Gram-negative oral pathogen Tannerella forsythia is decorated with a 2D crystalline surface (S-) layer, with two different S-layer glycoprotein species being present. Prompted by the predicted virulence potential of the S-layer, this study focused on the analysis of the arrangement of the individual S-layer glycoproteins by a combination of microscopic, genetic, and biochemical analyses. The two S-layer genes are transcribed into mRNA and expressed into protein in equal amounts. The S-layer was investigated on intact bacterial cells by transmission electron microscopy, by immune fluorescence microscopy, and by atomic force microscopy. The analyses of wild-type cells revealed a distinct square S-layer lattice with an overall lattice constant of 10.1 ± 0.7 nm. In contrast, a blurred lattice with a lattice constant of 9.0 nm was found on S-layer single-mutant cells. This together with in vitro self-assembly studies using purified (glyco)protein species indicated their increased structural flexibility after self-assembly and/or impaired self-assembly capability. In conjunction with TEM analyses of thin-sectioned cells, this study demonstrates the unusual case that two S-layer glycoproteins are co-assembled into a single S-layer. Additionally, flagella and pilus-like structures were observed on T. forsythia cells, which might impact the pathogenicity of this bacterium

Unique arbuscular mycorrhizal fungal communities uncovered in date palm plantations and surrounding desert habitats of Southern Arabia

The main objective of this study was to shed light on the previously unknown arbuscular mycorrhizal fungal (AMF) communities in Southern Arabia. We explored AMF communities in two date palm (Phoenix dactylifera) plantations and the natural vegetation of their surrounding arid habitats. The plantations were managed traditionally in an oasis and according to conventional guidelines at an experimental station. Based on spore morphotyping, the AMF communities under the date palms appeared to be quite diverse at both plantations and more similar to each other than to the communities under the ruderal plant, Polygala erioptera, growing at the experimental station on the dry strip between the palm trees, and to the communities uncovered under the native vegetation (Zygophyllum hamiense, Salvadora persica, Prosopis cineraria, inter-plant area) of adjacent undisturbed arid habitat. AMF spore abundance and species richness were higher under date palms than under the ruderal and native plants. Sampling in a remote sand dune area under Heliotropium kotschyi yielded only two AMF morphospecies and only after trap culturing. Overall, 25 AMF morphospecies were detected encompassing all study habitats. Eighteen belonged to the genus Glomus including four undescribed species. Glomus sinuosum, a species typically found in undisturbed habitats, was the most frequently occurring morphospecies under the date palms. Using molecular tools, it was also found as a phylogenetic taxon associated with date palm roots. These roots were associated with nine phylogenetic taxa, among them eight from Glomus group A, but the majority could not be assigned to known morphospecies or to environmental sequences in public databases. Some phylogenetic taxa seemed to be site specific. Despite the use of group-specific primers and efficient trapping systems with a bait plant consortium, surprisingly, two of the globally most frequently found species, Glomus intraradices and Glomus mosseae, were not detected neither as phylogenetic taxa in the date palm roots nor as spores under the date palms, the intermediate ruderal plant, or the surrounding natural vegetation. The results highlight the uniqueness of AMF communities inhabiting these diverse habitats exposed to the harsh climatic conditions of Southern Arabia

Saccade dysmetria indicates attenuated visual exploration in autism spectrum disorder

Background: Visual exploration in autism spectrum disorder (ASD) is characterized by attenuated social attention. The underlying oculomotor function during visual exploration is understudied, whereas oculomotor function during restricted viewing suggested saccade dysmetria in ASD by altered pontocerebellar motor modulation. Methods: Oculomotor function was recorded using remote eye tracking in 142 ASD participants and 142 matched neurotypical controls during free viewing of naturalistic videos with and without human content. The sample was heterogenous concerning age (6–30&nbsp;years), cognitive ability (60–140 IQ), and male/female ratio (3:1). Oculomotor function was defined as saccade, fixation, and pupil-dilation features that were compared between groups in linear mixed models. Oculomotor function was investigated as ASD classifier and features were correlated with clinical measures. Results: We observed decreased saccade duration (∆M&nbsp;=&nbsp;−0.50, CI [−0.21, −0.78]) and amplitude (∆M&nbsp;=&nbsp;−0.42, CI [−0.12, −0.72]), which was independent of human video content. We observed null findings concerning fixation and pupil-dilation features (POWER&nbsp;=.81). Oculomotor function is a valid ASD classifier comparable to social attention concerning discriminative power. Within ASD, saccade features correlated with measures of restricted and repetitive behavior. Conclusions: We conclude saccade dysmetria as ASD oculomotor phenotype relevant to visual exploration. Decreased saccade amplitude and duration indicate spatially clustered fixations that attenuate visual exploration and emphasize endogenous over exogenous attention. We propose altered pontocerebellar motor modulation as underlying mechanism that contributes to atypical (oculo-)motor coordination and attention function in ASD

Preference for biological motion is reduced in ASD: implications for clinical trials and the search for biomarkers

Background: The neurocognitive mechanisms underlying autism spectrum disorder (ASD) remain unclear. Progress has been largely hampered by small sample sizes, variable age ranges and resulting inconsistent findings. There is a pressing need for large definitive studies to delineate the nature and extent of key case/control differences to direct research towards fruitful areas for future investigation. Here we focus on perception of biological motion, a promising index of social brain function which may be altered in ASD. In a large sample ranging from childhood to adulthood, we assess whether biological motion preference differs in ASD compared to neurotypical participants (NT), how differences are modulated by age and sex and whether they are associated with dimensional variation in concurrent or later symptomatology. Methods: Eye-tracking data were collected from 486 6-to-30-year-old autistic (N = 282) and non-autistic control (N = 204) participants whilst they viewed 28 trials pairing biological (BM) and control (non-biological, CTRL) motion. Preference for the biological motion stimulus was calculated as (1) proportion looking time difference (BM-CTRL) and (2) peak look duration difference (BM-CTRL). Results: The ASD group showed a present but weaker preference for biological motion than the NT group. The nature of the control stimulus modulated preference for biological motion in both groups. Biological motion preference did not vary with age, gender, or concurrent or prospective social communicative skill within the ASD group, although a lack of clear preference for either stimulus was associated with higher social-communicative symptoms at baseline. Limitations: The paired visual preference we used may underestimate preference for a stimulus in younger and lower IQ individuals. Our ASD group had a lower average IQ by approximately seven points. 18% of our sample was not analysed for various technical and behavioural reasons. Conclusions: Biological motion preference elicits small-to-medium-sized case–control effects, but individual differences do not strongly relate to core social autism associated symptomatology. We interpret this as an autistic difference (as opposed to a deficit) likely manifest in social brain regions. The extent to which this is an innate difference present from birth and central to the autistic phenotype, or the consequence of a life lived with ASD, is unclear

Regulation of Signaling at Regions of Cell-Cell Contact by Endoplasmic Reticulum-Bound Protein-Tyrosine Phosphatase 1B

Protein-tyrosine phosphatase 1B (PTP1B) is a ubiquitously expressed PTP that is anchored to the endoplasmic reticulum (ER). PTP1B dephosphorylates activated receptor tyrosine kinases after endocytosis, as they transit past the ER. However, PTP1B also can access some plasma membrane (PM)-bound substrates at points of cell-cell contact. To explore how PTP1B interacts with such substrates, we utilized quantitative cellular imaging approaches and mathematical modeling of protein mobility. We find that the ER network comes in close proximity to the PM at apparently specialized regions of cell-cell contact, enabling PTP1B to engage substrate(s) at these sites. Studies using PTP1B mutants show that the ER anchor plays an important role in restricting its interactions with PM substrates mainly to regions of cell-cell contact. In addition, treatment with PTP1B inhibitor leads to increased tyrosine phosphorylation of EphA2, a PTP1B substrate, specifically at regions of cell-cell contact. Collectively, our results identify PM-proximal sub-regions of the ER as important sites of cellular signaling regulation by PTP1B

Identification of a gene signature for discriminating metastatic from primary melanoma using a molecular interaction network approach

Understanding the biological factors that are characteristic of metastasis in melanoma remains a key approach to improving treatment. In this study, we seek to identify a gene signature of metastatic melanoma. We configured a new network-based computational pipeline, combined with a machine learning method, to mine publicly available transcriptomic data from melanoma patient samples. Our method is unbiased and scans a genome-wide protein-protein interaction network using a novel formulation for network scoring. Using this, we identify the most influential, differentially expressed nodes in metastatic as compared to primary melanoma. We evaluated the shortlisted genes by a machine learning method to rank them by their discriminatory capacities. From this, we identified a panel of 6 genes, ALDH1A1, HSP90AB1, KIT, KRT16, SPRR3 and TMEM45B whose expression values discriminated metastatic from primary melanoma (87% classification accuracy). In an independent transcriptomic data set derived from 703 primary melanomas, we showed that all six genes were significant in predicting melanoma specific survival (MSS) in a univariate analysis, which was also consistent with AJCC staging. Further, 3 of these genes, HSP90AB1, SPRR3 and KRT16 remained significant predictors of MSS in a joint analysis (HR = 2.3, P = 0.03) although, HSP90AB1 (HR = 1.9, P = 2 × 10−4) alone remained predictive after adjusting for clinical predictors