Predicting language diversity with complex network

Evolution and propagation of the world's languages is a complex phenomenon, driven, to a large extent, by social interactions. Multilingual society can be seen as a system of interacting agents, where the interaction leads to a modification of the language spoken by the individuals. Two people can reach the state of full linguistic compatibility due to the positive interactions, like transfer of loanwords. But, on the other hand, if they speak entirely different languages, they will separate from each other. These simple observations make the network science the most suitable framework to describe and analyze dynamics of language change. Although many mechanisms have been explained, we lack a qualitative description of the scaling behavior for different sizes of a population. Here we address the issue of the language diversity in societies of different sizes, and we show that local interactions are crucial to capture characteristics of the empirical data. We propose a model of social interactions, extending the idea from, that explains the growth of the language diversity with the size of a population of country or society. We argue that high clustering and network disintegration are the most important characteristics of models properly describing empirical data. Furthermore, we cancel the contradiction between previous models and the Solomon Islands case. Our results demonstrate the importance of the topology of the network, and the rewiring mechanism in the process of language change

Climate Dynamics: A Network-Based Approach for the Analysis of Global Precipitation

Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010). The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that extreme events can enhance high precipitation gradients, leading to a systematic absence of long-range patterns

Practical Issues in Imputation-Based Association Mapping

Imputation-based association methods provide a powerful framework for testing untyped variants for association with phenotypes and for combining results from multiple studies that use different genotyping platforms. Here, we consider several issues that arise when applying these methods in practice, including: (i) factors affecting imputation accuracy, including choice of reference panel; (ii) the effects of imputation accuracy on power to detect associations; (iii) the relative merits of Bayesian and frequentist approaches to testing imputed genotypes for association with phenotype; and (iv) how to quickly and accurately compute Bayes factors for testing imputed SNPs. We find that imputation-based methods can be robust to imputation accuracy and can improve power to detect associations, even when average imputation accuracy is poor. We explain how ranking SNPs for association by a standard likelihood ratio test gives the same results as a Bayesian procedure that uses an unnatural prior assumption—specifically, that difficult-to-impute SNPs tend to have larger effects—and assess the power gained from using a Bayesian approach that does not make this assumption. Within the Bayesian framework, we find that good approximations to a full analysis can be achieved by simply replacing unknown genotypes with a point estimate—their posterior mean. This approximation considerably reduces computational expense compared with published sampling-based approaches, and the methods we present are practical on a genome-wide scale with very modest computational resources (e.g., a single desktop computer). The approximation also facilitates combining information across studies, using only summary data for each SNP. Methods discussed here are implemented in the software package BIMBAM, which is available from http://stephenslab.uchicago.edu/software.html

A viscoelastic deadly fluid in carnivorous pitcher plants

Background : The carnivorous plants of the genus Nepenthes, widely distributed in the Asian tropics, rely mostly on nutrients derived from arthropods trapped in their pitcher-shaped leaves and digested by their enzymatic fluid. The genus exhibits a great diversity of prey and pitcher forms and its mechanism of trapping has long intrigued scientists. The slippery inner surfaces of the pitchers, which can be waxy or highly wettable, have so far been considered as the key trapping devices. However, the occurrence of species lacking such epidermal specializations but still effective at trapping insects suggests the possible implication of other mechanisms. Methodology/Principal Findings : Using a combination of insect bioassays, high-speed video and rheological measurements, we show that the digestive fluid of Nepenthes rafflesiana is highly viscoelastic and that this physical property is crucial for the retention of insects in its traps. Trapping efficiency is shown to remain strong even when the fluid is highly diluted by water, as long as the elastic relaxation time of the fluid is higher than the typical time scale of insect movements. Conclusions/Significance : This finding challenges the common classification of Nepenthes pitchers as simple passive traps and is of great adaptive significance for these tropical plants, which are often submitted to high rainfalls and variations in fluid concentration. The viscoelastic trap constitutes a cryptic but potentially widespread adaptation of Nepenthes species and could be a homologous trait shared through common ancestry with the sundew (Drosera) flypaper plants. Such large production of a highly viscoelastic biopolymer fluid in permanent pools is nevertheless unique in the plant kingdom and suggests novel applications for pest control

Computer-aided diagnosis for (123I)FP-CIT imaging: impact on clinical reporting

BACKGROUND: For (123I)FP-CIT imaging, a number of algorithms have shown high performance in distinguishing normal patient images from those with disease, but none have yet been tested as part of reporting workflows. This study aims to evaluate the impact on reporters' performance of a computer-aided diagnosis (CADx) tool developed from established machine learning technology. Three experienced (123I)FP-CIT reporters (two radiologists and one clinical scientist) were asked to visually score 155 reconstructed clinical and research images on a 5-point diagnostic confidence scale (read 1). Once completed, the process was then repeated (read 2). Immediately after submitting each image score for a second time, the CADx system output was displayed to reporters alongside the image data. With this information available, the reporters submitted a score for the third time (read 3). Comparisons between reads 1 and 2 provided evidence of intra-operator reliability, and differences between reads 2 and 3 showed the impact of the CADx. RESULTS: The performance of all reporters demonstrated a degree of variability when analysing images through visual analysis alone. However, inclusion of CADx improved consistency between reporters, for both clinical and research data. The introduction of CADx increased the accuracy of the radiologists when reporting (unfamiliar) research images but had less impact on the clinical scientist and caused no significant change in accuracy for the clinical data. CONCLUSIONS: The outcomes for this study indicate the value of CADx as a diagnostic aid in the clinic and encourage future development for more refined incorporation into clinical practice

Artificial Neural Network Inference (ANNI): A Study on Gene-Gene Interaction for Biomarkers in Childhood Sarcomas

Objective: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI). Method: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs) dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model. Results: Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS); FCGRT and OLFM1 in Ewing’s sarcoma (EWS)) suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen. Conclusions: The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas

Adherence Support Workers: A Way to Address Human Resource Constraints in Antiretroviral Treatment Programs in the Public Health Setting in Zambia

BACKGROUND: In order to address staff shortages and improve adherence counseling for people on antiretroviral therapy (ART), the Zambia Prevention, Care and Treatment Partnership (ZPCT) developed an innovative strategy of training community volunteers to provide adherence support at the health facility and community levels. The objective of this study was to assess the effectiveness of these 'adherence support workers' (ASWs) in adherence counseling, treatment retention and addressing inadequate human resources at health facilities.METHODOLOGY/PRINCIPAL FINDINGS: The study used quantitative and qualitative research techniques at five selected ART sites in four provinces in Zambia. Five hundred patients on ART were interviewed using a structured questionnaire to compare the quality of adherence counseling before and after the ASW scheme was introduced at the selected sites and between ASWs and HCWs after the introduction of ASWs. In addition, 3,903 and 4,972 electronic records of all new patients accessing antiretroviral therapy for the time period of 12 months before and 12 months after the introduction of ASWs respectively, were analyzed to assess loss to follow-up rates. Two focus group discussions with ASWs and health care workers (HCWs) were conducted in each clinic. Key informant interviews in the ART clinics were also conducted. There was a marked shift of workload from HCWs to ASWs without any compromise in the quality of counseling. Quality of adherence counseling by ASWs was comparable to HCWs after their introduction. The findings suggest that the deployment of ASWs helped reduce waiting times for adherence counseling. Loss to follow-up rates of new clients declined from 15% to 0% after the deployment of ASWs.CONCLUSION: Adherence counseling tasks can be shifted to lay cadres like ASWs without compromising the quality of counseling. Follow-up of clients by ASWs within the community is necessary to improve retention of clients on ART

Metabolomic and lipidomic plasma profile changes in human participants ascending to Everest Base Camp.

At high altitude oxygen delivery to the tissues is impaired leading to oxygen insufficiency (hypoxia). Acclimatisation requires adjustment to tissue metabolism, the details of which remain incompletely understood. Here, metabolic responses to progressive environmental hypoxia were assessed through metabolomic and lipidomic profiling of human plasma taken from 198 human participants before and during an ascent to Everest Base Camp (5,300 m). Aqueous and lipid fractions of plasma were separated and analysed using proton (1H)-nuclear magnetic resonance spectroscopy and direct infusion mass spectrometry, respectively. Bayesian robust hierarchical regression revealed decreasing isoleucine with ascent alongside increasing lactate and decreasing glucose, which may point towards increased glycolytic rate. Changes in the lipid profile with ascent included a decrease in triglycerides (48-50 carbons) associated with de novo lipogenesis, alongside increases in circulating levels of the most abundant free fatty acids (palmitic, linoleic and oleic acids). Together, this may be indicative of fat store mobilisation. This study provides the first broad metabolomic account of progressive exposure to environmental hypobaric hypoxia in healthy humans. Decreased isoleucine is of particular interest as a potential contributor to muscle catabolism observed with exposure to hypoxia at altitude. Substantial changes in lipid metabolism may represent important metabolic responses to sub-acute exposure to environmental hypoxia.King's College London, National Institute of Health Researc

Proteomic Analysis of Rat Hypothalamus Revealed the Role of Ubiquitin–Proteasome System in the Genesis of DR or DIO

Obesity has become a global epidemic, contributing to the increasing burdens of cardiovascular disease and type 2 diabetes. However, the precise molecular mechanisms of obesity remain poorly elucidated. The hypothalamus plays a major part in regulating energy homeostasis by integrating all kinds of nutritional signals. This study investigated the hypothalamus protein profile in diet-induced obese (DIO) and diet-resistant (DR) rats using two dimensional gel electrophoresis (2-DE) combined with MALDI-TOF/TOF–MS analysis. Twenty-two proteins were identified in the hypothalamus of DIO or DR rats. These include metabolic enzymes, antioxidant proteins, proteasome related proteins, and signaling proteins, some of which are related to AMP-activated protein kinase (AMPK) signaling or mitochondrial respiration. Among these proteins, in comparison with the normal-diet group, Ubiquitin was significantly decreased in DR rats but not changed in DIO rats, while Ubiquitin carboxyl-terminal esterase L1 (UCHL-1) was decreased in DIO rats but not changed in DR rats. The expression level of Ubiquitin and UCHL-1 were further validated using Western blot analysis. Our study reveals that Ubiquitin and UCHL-1 are obesity-related factors in the hypothalamus that may play an important role in the genesis of DR or DIO by interfering with the integrated signaling network that control energy balance and feeding