bluuebunny/crossref_metadata_2025 huggingface dataset:
Turbidity, velocity and interspecific interactions affect foraging behaviour of rosyside dace (Clinostomus funduloides) and yellowfin shiners (Notropis lutippinis)
Authors: Hazelton P. D. , Grossman G. D.
Published: March 2009

Abstract –  Fish diversity is strongly affected by habitat degradation (e.g., increased turbidity) and invasive species. We examined the effects of turbidity, velocity, length, dominance and intra‐ and interspecific competition on focal point depth, movement rate, dominance and aggression rate in native rosyside dace (Clinostomus funduloides) and invasive yellowfin shiners (Notropis lutipinnis) in a southern Appalachian stream (NC, USA). We compared results for intra‐ and interspecific groups of fishes at two densities (two and four fishes), three turbidity levels (10, 20 and 30 nephelometric turbidity units), and two velocities (12, 18 cm·s−1). Dominance was significantly correlated with length in intraspecific groups of both species, and dominant fish held more profitable foraging positions about 75% of the time. Yellowfin shiners were dominant more often than rosyside dace in interspecific trials. Akaike’s Information Criterion indicated that models containing turbidity, velocity, species and intraspecific competition, explained the greatest amount of information in focal point depth data. By contrast, movement and aggression rates were best explained by models based on dominance and velocity. Finally, aggression rate was best explained by models containing fish length and turbidity. These results indicate that habitat degradation, intra‐ and interspecific interactions influence the foraging behaviour and future success of these species in the Little Tennessee River drainage.
Influence of seasonal, diel, lunar, and other environmental factors on upstream fish passage in the Igarapava Fish Ladder, Brazil
Authors: Bizzotto P. M. , Godinho A. L. , Vono V. , Kynard B. , Godinho H. P.
Published: March 2009

Abstract –  Upstream fish passage was evaluated during 12 months in the vertical‐slot Igarapava Fish Ladder constructed around Igarapava Dam, in the heavily dammed Grande River, Southeast Brazil. A video monitoring system was used to observe 61,621 fish that passed the ladder, of which 93.5% were identified to 15 taxa. Among the migratory species, the most abundant were Pimelodus maculatus (33.6% of all fish), Leporinus octofasciatus (31.4%), Leporinus friderici (4.5%), and Prochilodus lineatus (3.1%). Seven taxa were classified as nonmigratory, and of these taxa, the small Bryconamericus stramineus was the most abundant (12.7%) of all fishes. Passage of the ‘nonmigratory’ taxa upstream in the ladder shows they are migratory in this system and have a strong behavioural drive to move to upstream habitat. Passage of most taxa had a strong seasonal pattern. While some species passed primarily during the day, others showed a distinct nocturnal pattern. Lunar phase and water temperature also strongly affected passage of some taxa. Rainfall and dam discharge had a small or null influence on most taxa; perhaps due to the fairly small catchment area of the reservoir and the highly regulated discharge at Igarapava Dam.
Spatial distributions of tree species in a subtropical forest of China
Authors: Li Lin , Huang Zhongliang , Ye Wanhui , Cao Honglin , Wei Shiguang , Wang Zhigao , Lian Juyu , Sun I‐Fang , Ma Keping , He Fangliang
Published: March 2009

The spatial dispersion of individuals in a species is an important pattern that is controlled by many mechanisms. In this study we analyzed spatial distributions of tree species in a large‐scale (20 ha) stem‐mapping plot in a species‐rich subtropical forest of China. O‐ring statistic was used to measure spatial patterns of species with abundance >10. Ω0–10, the mean conspecific density within 10 m of a tree, was used as a measure of the intensity of aggregation of a species. Our results showed: (1) aggregated distribution was the dominant pattern in the plot. The percentage of aggregated species decreased with increased spatial scale. (2) The percentages of significantly aggregated species decreased from abundant to intermediate and to rare species. Rare species was more strongly aggregated than common species. Aggregation was weaker in larger diameter classes. (3) Seed traits determined the spatial patterns of trees. Seed dispersal mode can influence spatial patterns of species, with species dispersed by both modes being less clumped than species dispersed by animal or wind, respectively. Considering these results, we concluded that seed dispersal limitation, self‐thinning and habitat heterogeneity primarily contributed to spatial patterns and species coexistence in the forest.
Plant species diversity and environmental heterogeneity: spatial scale and competing hypotheses
Authors: Lundholm Jeremy T.
Published: March 2009

Questions: What is the observed relationship between plant species diversity and spatial environmental heterogeneity? Does the relationship scale predictably with sample plot size? What are the relative contributions to diversity patterns of variables linked to productivity or available energy compared to those corresponding to spatial heterogeneity?

Methods: Observational and experimental studies that quantified relationships between plant species richness and within‐sample spatial environmental heterogeneity were reviewed. Effect size in experimental studies was quantified as the standardized mean difference between control (homogeneous) and heterogeneous treatments. For observational studies, effect sizes in individual studies were examined graphically across a gradient of plot size (focal scale). Relative contributions of variables representing spatial heterogeneity were compared to those representing available energy using a response ratio.

Results: Forty‐one observational and 11 experimental studies quantified plant species diversity and spatial environmental heterogeneity. Observational studies reported positive species diversity‐spatial heterogeneity correlations at all points across a plot size gradient from ∼1.0 × 10−1 to ∼1.0 × 1011 m2, although many studies reported spatial heterogeneity variables with no significant relationships to species diversity. The cross‐study effect size in experimental studies was not significantly different from zero. Available energy variables explained consistently more of the variance in species richness than spatial heterogeneity variables, especially at the smallest and largest plot sizes.

Main conclusions: Species diversity was not related to spatial heterogeneity in a way predictable by plot size. Positive heterogeneity‐diversity relationships were common, confirming the importance of niche differentiation in species diversity patterns, but future studies examining a range of spatial scales in the same system are required to determine the role of dispersal and available energy in these patterns.
Oral mucosal lesions and temporomandibular joint impairment of elderly people in the South East Local Government Area of Ibadan
Authors: Taiwo Juliana O. , Kolude Bamidele , Akinmoladun Victor
Published: March 2009

Objective: To determine the prevalence of oral mucosal lesions, temporomandibular joint (TMJ) impairment and oral health‐related habits in the elderly people in South East Local Government Area (SELGA) in Ibadan.

Background data: SELGA is one of the largest local government areas in Oyo State, Nigeria and has a population of 225 800.

Design: A cross‐sectional survey.

Methodology: A randomly selected sample of 690 elderly people from 23 wards in SELGA were examined by two trained and calibrated examiners using mirror, probe and natural light.

Results: One hundred and fifty‐five (22.46%) of the elderly examined had one or more oral pathology lesions, representing infection‐related swelling, non‐infection‐related swelling, pre‐malignant lesions, denture stomatitis, non‐denture based ulcers, angular cheilitis, geographic tongue, scrotal tongue, lichen planus, hyper‐pigmentation and TMJ impairment.

Fifty‐five (35.5%) of these pathologies were infection‐related swellings. Six (3.9%) of the pathologies were denture‐related stomatitis, 14(9.03%) were pre‐malignant lesions, 14(9.03%) were non‐infection‐related swelling, while 27 (17.4%) were TMJ impairment. The rest of the lesions constituted the remaining 25.1%. Only 15.9% of the participants had tobacco‐related habits, 10.7% drank alcohol, whilst 41.6% chewed kola nuts.

Conclusion: Oral pathoses prevalence (22.46%) was similar to findings in developed countries (29.9%) but with a reversal of causal factors, infection‐related swellings were more common, whereas pre‐malignant lesions were less common. The infections were mostly complications from periodontal disease, which culminated in abscess formation. Tobacco‐related habits were not highly prevalent among the elderly people in SELGA. However, oral pathoses resulting from nutritional deficiencies were the third most frequent lesions observed.
European College of Gerodontology: undergraduate curriculum guidelines in Gerodontology
Authors: Kossioni Anastassia , Vanobbergen Jacques , Newton James , Müller Frauke , Heath Robin
Published: March 2009

Effective undergraduate teaching of gerodontology to present and future dental students is important if good oral health care of older people is to be assured. A review of the undergraduate curriculum for gerodontology is presented and indicates the need for a knowledge base from which new graduates can develop a special interest in care of older patients. The aim is improved care of older patients, satisfaction for teaching staff involved and improved professional standing for Dentistry. Motivation of students could also be achieved by the positive match between rising patient awareness and ethical responsibility of the profession for those older patients. As it stands, the undergraduate curriculum should include topics on specific care for the elderly and other patient groups, which extend the competences already agreed by the Association for Dental Education in Europe (ADEE). The logistics of teaching these topics will need co‐ordination of those staff with appropriate skill and interest, preferably as a development of existing curriculum content.
Contribution of small insects to pollination of common buckwheat, a distylous crop
Authors: Taki Hisatomo , Okabe Kimiko , Makino Shun’ichi , Yamaura Yuichi , Sueyoshi Masahiro
Published: March 2009

Crop pollination by animals is an essential ecosystem service. Among animal‐pollinated crops, distylous plants strongly depend on animal pollination. In distylous pollination systems, pollinator species are usually limited, although flowers of some distylous plants are visited by diverse animals. We studied the pollination biology of common buckwheat (Fagopyrum esculentum), a distylous crop mainly pollinated by honeybees and visited by many insect species, to evaluate the effects of non‐honeybee species on pollination services. We focused on insects smaller than honeybees to determine their contribution to pollination. We applied pollination treatments with bags of coarse mesh to exclude flower visits by honeybees and larger insects and compared the seed set of bagged plants with that of untreated plants for pin and thrum flower morphs. We found a great reduction of seed set only in bagged pin flowers. We also confirmed that small insects, including ants, bees, wasps and flies, carried pin‐morph pollen. These small insects transfer pollen from the short anthers of pin flowers to the short styles of thrum flowers, leading to sufficient seed set in thrum flowers. Consequently, small, non‐honeybee insects have the potential to maintain at least half of the yield of this honeybee‐dependent distylous crop.
Inferring Heterogeneity in Aquitards Using High‐Resolution δD and δ18O Profiles
Authors: Hendry M. Jim , Wassenaar L.I.
Published: March 2009

Vertical depth profiles of pore water isotopes (δD and δ18O) in clay‐rich aquitards have been used to show that solute transport is dominated by molecular diffusion, to define the timing of geologic events, and to estimate vertical hydraulic conductivity. The interpretation of the isotopic profiles in these studies was based on pore water samples collected from piezometers installed in nests (typically 4 to 15 piezometers) over depths of 10 to 80 m. Data from piezometer nests generally have poor vertical resolution (meters), raising questions about their capacity to reveal the impact of finer scale heterogeneities such as permeable sand bodies or fractured till zones on solute transport. Here, we used high‐resolution (30‐cm) depth profiles of δD and δ18O from two continuously cored boreholes in a till aquitard to provide new insights into the effects of sand bodies on solute transport. High‐resolution core‐derived profiles indicate that such heterogeneities can cause major deviations from one‐dimensional diffusion profiles. Further, comparison of piezometer‐measured values with best‐fit diffusion trends shows subtle deviations, suggesting the presence of heterogeneities that should not be ignored. High‐resolution profiles also more clearly defined the contact between the highly fractured oxidized zone and the underlying unoxidized zone than the piezometers.
Perspectives on Rural Health Workforce Issues: Illinois‐Arkansas Comparison
Authors: MacDowell Martin , Glasser Michael , Fitts Michael , Fratzke Mel , Peters Karen
Published: March 2009

ABSTRACT: 
Context: Past research has documented rural physician and health care professional shortages. Purpose: Rural hospital chief executive officers’ (CEOs’) reported shortages of health professionals and perceptions about recruiting and retention are compared in Illinois and Arkansas. Methods: A survey, previously developed and sent to 28 CEOs in Illinois, was mailed to 110 CEOs in Arkansas. Only responses from rural CEOs are presented (Arkansas n = 39 and Illinois n = 22). Findings: Physician shortages were reported by 51 CEOs (83.6%). Most reported physician shortages in Arkansas were for family medicine, internal medicine, cardiology, obstetrics‐gynecology, general surgery, and psychiatry. Most reported physician shortages in Illinois were for family medicine, obstetrics‐gynecology, orthopedic surgery, internal medicine, cardiology, and general surgery. Additionally, registered nurses and pharmacists were the top 2 allied health professions shortages. Multivariate analysis (factor and discriminant analyses) examined community attributes associated with ease of recruiting physicians. Six factors were identified and assessed as to their importance in influencing ease of recruitment, with the state included in the model. Three factors were identified as discriminating whether or not physician recruitment was easy: community supportive for family, community cooperates and perceives a good future, and community attractiveness. Conclusions: Similarities in shortages and attributes influencing recruitment in both states suggest that efforts and policies in health professions workforce development can be generalized between regions. This study further reinforces some important known issues concerning retention and recruitment, such as the importance of identifying providers whose preferences are matched to the characteristics and lifestyle of a given area.
A Rural Perspective on Perinatal Depression: Prevalence, Correlates, and Implications for Help‐Seeking Among Low‐Income Women
Authors: Price Sarah Kye , Proctor Enola K.
Published: March 2009

ABSTRACT: 
Context/Purpose: To examine a low‐income sample of women in the rural Midwest (N = 1,086) who were screened for perinatal depression through the outreach and education activities within a Healthy Start Initiative project. Specifically, we describe the frequency and severity of depressive symptoms, explore social and demographic correlates of depression, and examine help‐seeking through patterns of self‐referral to a Healthy Start perinatal depression project in a rural, medically underserved community. Methods: Depression screening data using the Primary Care Evaluation of Mental Disorders (PRIME‐MD) as well as intake records from the project were analyzed in a retrospective analysis to identify important demographic and psychosocial characteristics associated with elevated levels of depressive symptoms and help‐seeking patterns. Findings: Thirty‐six percent of screened women met criteria for major, minor, or subthreshold depression, with 13% meeting diagnostic criteria for major depression alone. Less than 8% were currently receiving any type of mental health services or treatment at screening. The most significant correlate of self‐referral to the Healthy Start project was meeting symptom criteria for major depression, although minor depression, subthreshold depression, and status as low‐income/Temporary Aid to Needy Families (TANF)‐eligible were all significantly associated with self‐referral. Conclusions: The findings from this study highlight the potential significance of identifying and addressing the unmet mental health needs of low‐income rural women during and around pregnancy. In addition, the study illustrates that low income, in addition to depressive symptoms, impacts mental health service delivery in this rural community with a fragmented mental health service infrastructure.
The Condition‐Dependent Transcriptional Network inEscherichia coli
Authors: Lemmens Karen , De Bie Tijl , Dhollander Thomas , Monsieurs Pieter , De Moor Bart , Collado‐Vides Julio , Engelen Kristof , Marchal Kathleen
Published: March 2009

Thanks to the availability of high‐throughput omics data, bioinformatics approaches are able to hypothesize thus‐far undocumented genetic interactions. However, due to the amount of noise in these data, inferences based on a single data source are often unreliable. A popular approach to overcome this problem is to integrate different data sources. In this study, we describe DISTILLER, a novel framework for data integration that simultaneously analyzes microarray and motif information to find modules that consist of genes that are co‐expressed in a subset of conditions, and their corresponding regulators. By applying our method on publicly available data, we evaluated the condition‐specific transcriptional network ofEscherichia coli. DISTILLER confirmed 62% of 736 interactions described in RegulonDB, and 278 novel interactions were predicted.
Ranking Genes by Their Co‐expression to Subsets of Pathway Members
Authors: Adler Priit , Peterson Hedi , Agius Phaedra , Reimand Jüri , Vilo Jaak
Published: March 2009

Cellular processes are often carried out by intricate systems of interacting genes and proteins. Some of these systems are rather well studied and described in pathway databases, while the roles and functions of the majority of genes are poorly understood. A large compendium of public microarray data is available that covers a variety of conditions, samples, and tissues and provides a rich source for genome‐scale information. We focus our study on the analysis of 35 curated biological pathways in the context of gene co‐expression over a large variety of biological conditions. By defining a global co‐expression similarity rank for each gene and pathway, we perform exhaustive leave‐one‐out computations to describe existing pathway memberships using other members of the corresponding pathway as reference. We demonstrate that while successful in recovering biological base processes such as metabolism and translation, the global correlation measure fails to detect gene memberships in signaling pathways where co‐expression is less evident. Our results also show that pathway membership detection is more effective when using only a subset of corresponding pathway members as reference, supporting the existence of more tightly co‐expressed subsets of genes within pathways. Our study assesses the predictive power of global gene expression correlation measures in reconstructing biological systems of various functions and specificity. The developed computational network has immediate applications in detecting dubious pathway members and predicting novel member candidates.
Global Robustness and Identifiability of Random, Scale‐Free, and Small‐World Networks
Authors: Gong Yunchen , Zhang Zhaolei
Published: March 2009

We are interested in the relationships among network topology, robustness, and identifiability, and their implications in improving network reconstruction. We used three different types of artificial gene networks (AGNs) with distinct topologies: topologies random (RND), scale‐free (SF), and small‐world (SW), to investigate their robustness and identifiability. The robustness of a network is represented by structural reachability (existence of pathways between two nodes) and dynamic reachability (response on one node upon perturbation on another node). The identifiability of the network edges is assessed in silico with an established reverse‐engineering algorithm. We found that (1) structural reachability does not always lead to dynamic reachability; (2) network robustness is high and identifiability is low in all surveyed AGNs; (3) robustness is more sensitive to network topologies than is identifiability. We also devised a method for network dissection in which three subnets (set of alternative pathways or feedbacks, referred to as pathnet) are related to each node pair. This method allows us to identify the fine structural features underlying the distinct behaviors of the networks. For example, pathnet of the edge tail negatively contributes to the edge identifiability, and it is likely that extra perturbation at this pathnet would improve edge identifiability. We provide a case study to prove that double perturbations decrease the edge robustness and increase structural identifiability with a T helper cell–differentiation network model.
Uncovering Metabolic Objectives Pursued by Changes of Enzyme Levels
Authors: Hoffmann Sabrina , Holzhütter Hermann‐Georg
Published: March 2009

Expression profiling and proteomic techniques reveal significant variations in the levels of thousands of mRNAs and proteins in response to environmental changes such as substrate depletion, oxidative stress, and hormonal stimulation. However, in most cases the functional implications of these variations remain elusive. One crucial problem complicating the functional interpretation of high‐throughput data is that changes of protein levels do not simply translate into equivalent changes in the rate of the associated chemical processes due to various modes of enzyme regulation and the instantaneous effect of changed metabolite concentrations on adjacent flux rates. Here, we outline a theoretical concept to exploit information on (relative) changes in the level of metabolic enzymes for the prediction of (relative) flux changes in the underlying metabolic network. Our approach rests on the assumption that size and direction of fluxes (flux distribution) in the network are determined by an optimization principle in that the production of the physiologically relevant output metabolites is accomplished with minimal total flux. The prediction method comprises two main steps. First, we approximate (unknown) flux changes by a linear combination of so‐called minimal flux modes, each representing a specific flux distribution minimally required to accomplish the production of only one of the numerous functionally relevant output metabolites. Second, the unknown coefficients of this decomposition are chosen such that a maximal correlation with observed differential expression data is obtained. Based on simulated enzyme expression scenarios in a metabolic model of the human red blood cell, we demonstrate the predictive capacity of our method.
A Gene Network Simulator to Assess Reverse Engineering Algorithms
Authors: Di Camillo Barbara , Toffolo Gianna , Cobelli Claudio
Published: March 2009

In the context of reverse engineering of biological networks, simulators are helpful to test and compare the accuracy of different reverse‐engineering approaches in a variety of experimental conditions. A novel gene‐network simulator is presented that resembles some of the main features of transcriptional regulatory networks related to topology, interaction among regulators of transcription, and expression dynamics. The simulator generates network topology according to the current knowledge of biological network organization, including scale‐free distribution of the connectivity and clustering coefficient independent of the number of nodes in the network. It uses fuzzy logic to represent interactions among the regulators of each gene, integrated with differential equations to generate continuous data, comparable to real data for variety and dynamic complexity. Finally, the simulator accounts for saturation in the response to regulation and transcription activation thresholds and shows robustness to perturbations. It therefore provides a reliable and versatile test bed for reverse engineering algorithms applied to microarray data. Since the simulator describes regulatory interactions and expression dynamics as two distinct, although interconnected aspects of regulation, it can also be used to test reverse engineering approaches that use both microarray and protein–protein interaction data in the process of learning. A first software release is available athttp://www.dei.unipd.it/~dicamill/software/netsimas an R programming language package.
Inference of Regulatory Gene Interactions from Expression Data Using Three‐Way Mutual Information
Authors: Watkinson John , Liang Kuo‐ching , Wang Xiadong , Zheng Tian , Anastassiou Dimitris
Published: March 2009

This paper describes the technique designated best performer in the 2nd conference on Dialogue for Reverse Engineering Assessments and Methods (DREAM2) Challenge 5 (unsigned genome‐scale network prediction from blinded microarray data). Existing algorithms use the pairwise correlations of the expression levels of genes, which provide valuable but insufficient information for the inference of regulatory interactions. Here we present a computational approach based on the recently developed context likelihood of related (CLR) algorithm, extracting additional complementary information using the information theoretic measure of synergy and assigning a score to each ordered pair of genes measuring the degree of confidence that the first gene regulates the second. When tested on a set of publicly available Escherichia coli gene‐expression data with known assumed ground truth, the synergy augmented CLR (SA‐CLR) algorithm had significantly improved prediction performance when compared to CLR. There is also enhanced potential for biological discovery as a result of the identification of the most likely synergistic partner genes involved in the interactions.
A Data Integration Framework for Prediction of Transcription Factor Targets
Authors: Nykter Matti , Lähdesmäki Harri , Rust Alistair , Thorsson Vesteinn , Shmulevich Ilya
Published: March 2009

We present a computational framework for predicting targets of transcription factor regulation. The framework is based on the integration of a number of sources of evidence, derived from DNA‐sequence and gene‐expression data, using a weighted sum approach. Sources of evidence are prioritized based on a training set, and their relative contributions are then optimized. The performance of the proposed framework is demonstrated in the context of BCL6 target prediction. We show that this framework is able to uncover BCL6 targets reliably when biological prior information is utilized effectively, particularly in the case of sequence analysis. The framework results in a considerable gain in performance over scores in which sequence information was not incorporated. This analysis shows that with assessment of the quality and biological relevance of the data, reliable predictions can be obtained with this computational framework.
NIRest: A Tool for Gene Network and Mode of Action Inference
Authors: Lauria Mario , Iorio Francesco , Di Bernardo Diego
Published: March 2009

A novel algorithm for the identification of genetic networks from gene expression data is presented. Our approach is based on an ordinary differential equations (ODE) model of the network, and on an assumption of linearity around an equilibrium point of the cell machinery. Here we start by describing the application of NIR (Network Identification by multiple Regression) to a state‐of‐the‐art in silico gene expression dataset provided by the Dialogue for Reverse Engineering Assessment and Methods 2 (DREAM2) reverse‐engineering competition (challenge 4). Then we present NIRest (NIR with perturbation Estimate), a tool that builds upon the original NIR and extends its use to cases in which the generating perturbations are not known. The remarkable results obtained with in silico datasets support the validity of NIR and NIRest assumptions and the effectiveness of our approach. Comparison with other leading methods based on Bayesian networks and mutual information shows the performance advantage of NIRest, which at the same time provides directed and undirected versions of the inferred network and an estimate of the mode of action.
Replaying the Evolutionary Tape: Biomimetic Reverse Engineering of Gene Networks
Authors: Marbach Daniel , Mattiussi Claudio , Floreano Dario
Published: March 2009

In this paper, we suggest a new approach for reverse engineering gene regulatory networks, which consists of using a reconstruction process that is similar to the evolutionary process that created these networks. The aim is to integrate prior knowledge into the reverse‐engineering procedure, thus biasing the search toward biologically plausible solutions. To this end, we propose an evolutionary method that abstracts and mimics the natural evolution of gene regulatory networks. Our method can be used with a wide range of nonlinear dynamical models. This allows us to explore novel model types such as the log‐sigmoid model introduced here. We apply the biomimetic method to a gold‐standard dataset from an in vivo gene network. The obtained results won a reverse engineering competition of the second DREAM conference (Dialogue on Reverse Engineering Assessments and Methods 2007, New York, NY).
Combining Multiple Results of a Reverse‐Engineering Algorithm: Application to the DREAM Five‐Gene Network Challenge
Authors: Marbach Daniel , Mattiussi Claudio , Floreano Dario
Published: March 2009

The output of reverse‐engineering methods for biological networks is often not a single network prediction, but an ensemble of networks that are consistent with the experimentally measured data. In this paper, we consider the problem of combining the information contained within such an ensemble in order to (1) make more accurate network predictions and (2) estimate the reliability of these predictions. We review existing methods, discuss their limitations, and point out possible research directions toward more advanced methods for this purpose. The potential of considering ensembles of networks, rather than individual inferred networks, is demonstrated by showing how an ensemble voting method achieved winning performance on the Five‐Gene Network Challenge of the second DREAM conference (Dialogue on Reverse Engineering Assessments and Methods 2007, New York, NY).
Inferring Gene Networks: Dream or Nightmare?
Authors: Baralla Angela , Mentzen Wieslawa I. , De La Fuente Alberto
Published: March 2009

Inferring gene networks is a daunting task. We here describe several algorithms we used in the Dialogue for Reverse Engineering Assessments and Methods (DREAM2) Reverse Engineering Competition 2007: an algorithm based on first‐order partial correlation for discovering BCL6 targets in Challenge 1 and an algorithm using nonlinear optimization with winning performance in Challenge 3. After the gold standards for the challenges were released, the performance of alternative variants of the algorithms could be evaluated. The DREAM competition taught us some strong lessons. Amazingly, simpler methods performed in general better than more advanced, theoretically motivated approaches. Also, the challenges strongly showed that inferring gene networks requires controlled experimentation using a well‐defined experimental design. Analyzing data obtained through merging many unrelated datasets indeed resulted in weak performances of all algorithms, while algorithms that explicitly took the experimental design into account performed best.
Inferring Gene Networks: Dream or Nightmare?
Authors: Scheinine Alan , Mentzen Wieslawa I. , Fotia Giorgio , Pieroni Enrico , Maggio Fabio , Mancosu Gianmaria , De La Fuente Alberto
Published: March 2009

We describe several algorithms with winning performance in the Dialogue for Reverse Engineering Assessments and Methods (DREAM2) Reverse Engineering Competition 2007. After the gold standards for the challenges were released, the performance of the algorithms could be thoroughly evaluated under different parameters or alternative ways of solving systems of equations. For the analysis of Challenge 4, the “In‐silico” challenges, we employed methods to explicitly deal with perturbation data and time‐series data. We show that original methods used to produce winning submissions could easily be altered to substantially improve performance. For Challenge 5, the genome‐scaleEscherichia colinetwork, we evaluated a variety of measures of association. These data are troublesome, and no good solutions could be produced, either by us or by any other teams. Our best results were obtained when analyzing subdatasets instead of considering the dataset as a whole.
Neuroimaging and the Vegetative State
Authors: Monti Martin M. , Coleman Martin R. , Owen Adrian M.
Published: March 2009

The accurate assessment of patients with impaired consciousness following a brain injury often remains a challenge to the most experienced clinician. A diagnosis of vegetative or minimally conscious state is made on the basis of the patient's clinical history and detailed behavioral examinations, which rely upon the patient being able to move or speak in order to demonstrate residual cognitive function. Recently, the development of noninvasive neuroimaging techniques has fostered a rapid increase in the exploration of residual cognitive abilities in these patient populations. However, while this body of literature is growing rapidly, at present the enterprise remains one of scientific endeavor with no inclusion in standard clinical practice. Correctly administered behavioral testing in survivors of brain injury may provide sufficient information to identify patients who are aware and are able to signal that this is the case via a recognized motor output. However, it remains possible that a subgroup of these patients may retain some level of awareness, but lack the ability to produce any motor output and are therefore mistakenly diagnosed as vegetative. It is in this latter situation that functional neuroimaging may prove to be most valuable, as a unique clinical tool for probing volition and residual cognition without necessarily assuming that the patient is able to produce any motor output.
A Brain–Computer Interface Controlled Auditory Event‐Related Potential (P300) Spelling System for Locked‐In Patients
Authors: Kübler Andrea , Furdea Adrian , Halder Sebastian , Hammer Eva Maria , Nijboer Femke , Kotchoubey Boris
Published: March 2009

Using brain–computer interfaces (BCI) humans can select letters or other targets on a computer screen without any muscular involvement. An intensively investigated kind of BCI is based on the recording of visual event‐related brain potentials (ERP). However, some severely paralyzed patients who need a BCI for communication have impaired vision or lack control of gaze movement, thus making a BCI depending on visual input no longer feasible. In an effort to render the ERP–BCI usable for this group of patients, the ERP–BCI was adapted to auditory stimulation. Letters of the alphabet were assigned to cells in a 5 × 5 matrix. Rows of the matrix were coded with numbers 1 to 5, and columns with numbers 6 to 10, and the numbers were presented auditorily. To select a letter, users had to first select the row and then the column containing the desired letter. Four severely paralyzed patients in the end‐stage of a neurodegenerative disease were examined. All patients performed above chance level. Spelling accuracy was significantly lower with the auditory system as compared with a similar visual system. Patients reported difficulties in concentrating on the task when presented with the auditory system. In future studies, the auditory ERP–BCI should be adjusted by taking into consideration specific features of severely paralyzed patients, such as reduced attention span. This adjustment in combination with more intensive training will show whether an auditory ERP–BCI can become an option for visually impaired patients.
Coma
Authors: Young G. Bryan
Published: March 2009

Coma is a state of unarousable unconsciousness due to dysfunction of the brain's ascending reticular activating system (ARAS), which is responsible for arousal and the maintenance of wakefulness. Anatomically and physiologically the ARAS has a redundancy of pathways and neurotransmitters; this may explain why coma is usually transient (seldom lasting more than 3 weeks). Emergence from coma is succeeded by outcomes ranging from the vegetative state to complete recovery, depending on the severity of damage to the cerebral cortex, the thalamus, and their integrated function. The clinical and laboratory assessments of the comatose patient are reviewed here, along with an analysis of how various conditions (structural brain lesions, metabolic and toxic disorders, trauma, infections, seizures, hypothermia, and hyperthermia) produce coma. Management issues include the determination of the cause and reversibility (prognosis) of neurological impairment, support of the patient, definitive treatment when possible, and the ethical considerations for those situations where marked disability is predicted with certainty.
Theories of Impaired Consciousness in Epilepsy
Authors: Yu Lissa , Blumenfeld Hal
Published: March 2009

Although the precise mechanisms for control of consciousness are not fully understood, emerging data show that conscious information processing depends on the activation of certain networks in the brain and that the impairment of consciousness is related to abnormal activity in these systems. Epilepsy can lead to transient impairment of consciousness, providing a window into the mechanisms necessary for normal consciousness. Thus, despite differences in behavioral manifestations, cause, and electrophysiology, generalized tonic–clonic, absence, and partial seizures engage similar anatomical structures and pathways. We review prior concepts of impaired consciousness in epilepsy, focusing especially on temporal lobe complex partial seizures, which are a common and debilitating form of epileptic unconsciousness. We discuss a “network inhibition hypothesis” in which focal temporal lobe seizure activity disrupts normal cortical–subcortical interactions, leading to depressed neocortical function and impaired consciousness. This review of the major prior theories of impaired consciousness in epilepsy allows us to put more recent data into context and to reach a better understanding of the mechanisms important for normal consciousness.
Wh‐in‐situ, from the 1980s to Now
Authors: Cheng Lisa Lai‐Shen
Published: March 2009

This article provides an overview of the issues and proposals surroundingwh‐in‐situ since the 1980s. In particular, it discusses the question of whether or not in‐situwh‐phrases undergo covertwh‐movement. Aside from reviewing the basic arguments for and against covertwh‐movement, it considers alternative proposals put forth, ranging from movement of elements other thanwh‐phrases themselves, interpreting in‐situwh‐phrases using choice function, to disguised movements in various forms. The article concludes with a discussion of intervention effects, as well as a special kind of multiplewh‐questions, illustrating that covertwh‐movement is still much needed.
Hypertension in Athletes
Authors: Leddy John J. , Izzo Joseph
Published: March 2009

Regular physical activity and training are associated with reductions in blood pressure (BP), yet elevated BP is one of the most common abnormalities found during the pre‐participation physical evaluation of athletes. Hypertension (HTN) remains the most common cardiovascular condition encountered in athletic populations, therefore all athletes require screening for HTN. Because athletes often have white coat HTN, BP recordings outside the office are also necessary. The 36th Bethesda Conference classified sports according to their varying physiologic demands and provided specific recommendations for the evaluation, treatment, and sport participation of athletes with HTN. In general, angiotensin‐converting enzyme inhibitors and other vasodilators are the medications of choice for active and athletic patients because of their limited interference with cardiovascular conditioning. Other agents can be used but some sports governing bodies proscribe the use of certain antihypertensive medications such as β‐blockers for elite athletes.
Screening of ESTs from Mytilus for the detection of SSR markers in Mytilus californianus
Authors: VIDAL R. , PEÑALOZA C. , URZÚA R. , TORO J. E.
Published: March 2009

A set of expressed sequence tag‐simple sequence repeat (EST‐SSR) markers for the genus Mytilus was developed through bioinformatic mining of the GenBank public database. A total of 33 782 EST sequences from GenBank were downloaded and screened for di‐, tri‐ and tetranucleotide, with 1274 EST containing SSR markers. Nine microsatellite markers were characterized in Mytilus californianus with a number of alleles per locus ranging from two to six, and total observed and expected heterozygosities ranging from 0.490 to 0.730 and from 0.510 to 0.860 respectively. Cross‐species amplification was achieved in several other species, confirming the usefulness of these markers in Mytilus genetics.
A NOTE ON BANTU EDUCATION, 1953 TO 1970
Authors: Giliomee Hermann
Published: March 2009

In 1954 Hendrik Verwoerd, one of the main architects of the apartheid system, said that blacks ought not to be trained above certain “forms of labour”. These words, often quoted out of context, are commonly interpreted as based on a view of black inferiority and as designed to keep blacks in a position of servitude. This note argues that other considerations should also be taken into account, including the need for providing appropriate labour on a mass basis in an industrialising society and for establishing control over urbanised black youths.
AN INVESTIGATION INTO THE IMPACT OF TUTORIALS ON THE PERFORMANCE OF ECONOMICS STUDENTS
Authors: Horn Pm , Jansen Ai
Published: March 2009

The deteriorating performance of first‐year economics students has become a concern at many South African universities. Addressing the issue requires an understanding of the factors influencing students' success. Studies analysing academic performance use the education production function approach. This approach identifies inputs that are crucial to learning and to achieving certain outputs. Factors that have been investigated in other studies include the impact of lecture attendance on performance, school‐leaving exam (matriculation) results, particularly performance in mathematics, and the gender and age of students.

This study adds to existing local empirical research by analysing the impact of the tutorial programme as an input. The case study investigates the tutorial programme for first‐year economics students at Stellenbosch University using quantitative analysis. Results confirm what previous studies have found, namely that lecture attendance, gender, and matriculation results contribute positively to the performance of first‐year economics students. The main finding of the paper is that tutorial attendance also contributes positively to academic performance.
CHANGE IN VOLATILITY REGIMES AND DIVERSIFICATION IN EMERGING STOCK MARKETS
Authors: Li Ming‐yuan leon
Published: March 2009

A multivariate Markov‐switching ARCH (MVSWARCH) model in which variance/correlations for stock returns is controlled by a state‐varying mechanism is introduced and used to design a state‐varying US‐EM (emerging market) portfolio establishment strategy. Additionally, a conventional random‐variance framework, the MVGARCH (multivariate GARCH) model, in which a time‐varying technique is involved is employed and subjected to comparative analysis. The empirical results are consistent with the following notions: First, as being consistent with a study conducted byRamchand and Susmel, the US‐EM market correlations are higher when the US market is more volatile. However, this study further indicates that the US‐EM market correlations increase relatively more when both the US and EM markets simultaneously experience a high variance condition. Moreover, the situation of both the US and EM stock markets at a high volatility state is associated with a minimum risk reduction benefit and a maximum cross‐market correlation. Second, the state‐varying portfolio loadings established by the MVSWARCH model could effectively enhance asset allocation effectiveness; however, this benefit arises more as a result of risk reduction than an increase in mean returns.
Social Optimal Location of Facilities with Fixed Servers, Stochastic Demand, and Congestion
Authors: Castillo Ignacio , Ingolfsson Armann , Sim Thaddeus
Published: March 2009

We consider two capacity choice scenarios for the optimal location of facilities with fixed servers, stochastic demand, and congestion. Motivating applications include virtual call centers, consisting of geographically dispersed centers, walk‐in health clinics, motor vehicle inspection stations, automobile emissions testing stations, and internal service systems. The choice of locations for such facilities influences both the travel cost and waiting times of users. In contrast to most previous research, we explicitly embed both customer travel/connection and delay costs in the objective function and solve the location–allocation problem and choose facility capacities simultaneously. The choice of capacity for a facility that is viewed as a queueing system with Poisson arrivals and exponential service times could mean choosing a service rate for the servers (Scenario 1) or choosing the number of servers (Scenario 2). We express the optimal service rate in closed form in Scenario 1 and the (asymptotically) optimal number of servers in closed form in Scenario 2. This allows us to eliminate both the number of servers and the service rates from the optimization problems, leading to tractable mixed‐integer nonlinear programs. Our computational results show that both problems can be solved efficiently using a Lagrangian relaxation optimization procedure.
How to Win “Spend” and Influence Partners: Lessons in Behavioral Operations from the Outsourcing Game
Authors: Amaral Jason , Tsay Andy A.
Published: March 2009

The Outsourcing Game is a role‐play simulation that has been deployed in industry and academic training courses worldwide. It incorporates the concepts of hidden actions, hidden information, and misaligned incentives, and conveys messages about power, trust, and reputation. The game depicts the adventures of Acme, the brand owner of a product manufactured by an outsourced supply chain. Through a series of negotiations, Acme attempts to influence its partners (two suppliers and two service providers) by distributing its procurement “spend.” These partners, in turn, sway each other via side payments. To simulate the non‐linear shifts in power that occur as outsourcing increases, we represent decision‐making by a voting scheme with uneven vote allocations. This paper analyzes a database of game results to reveal behavioral factors that can undermine conspicuous win–win process improvements. For instance, preferences can be sensitive to the sequence in which the alternatives are encountered; decision‐makers might value not only their own rewards, but also fairness in the allocation of total gains; and effectiveness of negotiation tactics will vary with community norms of acceptable behavior. Along the way we extend the political economics literature about power in block‐based voting by proposing a heuristic approach for incorporating voter preferences.