bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiple Archaean to Early Palaeozoic events of the northern Gondwana margin witnessed by detrital zircons from the Radzimowice Slates, Kaczawa Complex (Central European Variscides)
Authors: TYSZKA RAFAŁ , KRYZA RYSZARD , ZALASIEWICZ JAN A. , LARIONOV ALEXANDER N. 
Published: October 2007

AbstractSIMS dating of detrital zircons from the stratigraphically enigmatic Radzimowice Slates of the Kaczawa Mountains (Sudetes, SW Poland), near the eastern termination of the European Variscides, has yielded age populations of: (1) 493–512 Ma, corresponding to late Cambrian to early Ordovician magmatism and constraining a maximum depositional age; (2) between 550 and 650 Ma, reflecting input from diverse Cadomian sources; and (3) older inherited components ranging toc.3.3 Ga, with age spectra similar to those from Gondwanan North Africa. The new data show that the Radzimowice Slates cannot form a Proterozoic base to the Kaczawa Mountains succession, as suggested by earlier models, but was deposited, at the earliest, as an extensional basin-fill, during a relatively late stage of the break-up of this part of northern Gondwana.
A randomized controlled trial with 4-month follow-up of adjunctive repetitive transcranial magnetic stimulation of the left prefrontal cortex for depression
Authors: Mogg A. , Pluck G. , Eranti S. V. , Landau S. , Purvis R. , Brown R. G. , Curtis V. , Howard R. , Philpot M. , McLoughlin D. M. 
Published: October 2007

BackgroundEffectiveness of repetitive transcranial magnetic stimulation (rTMS) for major depression is unclear. The authors performed a randomized controlled trial comparing real and sham adjunctive rTMS with 4-month follow-up.MethodFifty-nine patients with major depression were randomly assigned to a 10-day course of either real (n=29) or sham (n=30) rTMS of the left dorsolateral prefrontal cortex (DLPFC). Primary outcome measures were the 17-item Hamilton Depression Rating Scale (HAMD) and proportions of patients meeting criteria for response (⩾50% reduction in HAMD) and remission (HAMD⩽8) after treatment. Secondary outcomes included mood self-ratings on Beck Depression Inventory-II and visual analogue mood scales, Brief Psychiatric Rating Scale (BPRS) score, and both self-reported and observer-rated cognitive changes. Patients had 6-week and 4-month follow-ups.ResultsOverall, Hamilton Depression Rating Scale (HAMD) scores were modestly reduced in both groups but with no significant group×time interaction (p=0.09) or group main effect (p=0.85); the mean difference in HAMD change scores was −0.3 (95% CI −3.4 to 2.8). At end-of-treatment time-point, 32% of the real group were responders compared with 10% of the sham group (p=0.06); 25% of the real group met the remission criterion compared with 10% of the sham group (p=0.2); the mean difference in HAMD change scores was 2.9 (95% CI −0.7 to 6.5). There were no significant differences between the two groups on any secondary outcome measures. Blinding was difficult to maintain for both patients and raters.ConclusionsAdjunctive rTMS of the left DLPFC could not be shown to be more effective than sham rTMS for treating depression.
Towards further understanding of the co-morbidity between attention deficit hyperactivity disorder and bipolar disorder: a MRI study of brain volumes
Authors: Biederman J. , Makris N. , Valera E. M. , Monuteaux M. C. , Goldstein J. M. , Buka S. , Boriel D. L. , Bandyopadhyay S. , Kennedy D. N. , Caviness V. S. , Bush G. , Aleardi M. , Hammerness P. , Faraone S. V. , Seidman L. J. 
Published: October 2007

BackgroundAlthough attention deficit hyperactivity disorder (ADHD) and bipolar disorder (BPD) co-occur frequently and represent a particularly morbid clinical form of both disorders, neuroimaging research addressing this co-morbidity is scarce. Our aim was to evaluate the morphometric magnetic resonance imaging (MRI) underpinnings of the co-morbidity of ADHD with BPD, testing the hypothesis that subjects with this co-morbidity would have neuroanatomical correlates of both disorders.MethodMorphometric MRI findings were compared between 31 adults with ADHD and BPD and with those of 18 with BPD, 26 with ADHD, and 23 healthy controls. The volumes (cm3) of our regions of interest (ROIs) were estimated as a function of ADHD status, BPD status, age, sex, and omnibus brain volume using linear regression models.ResultsWhen BPD was associated with a significantly smaller orbital prefrontal cortex and larger right thalamus, this pattern was found in co-morbid subjects with ADHD plus BPD. Likewise, when ADHD was associated with significantly less neocortical gray matter, less overall frontal lobe and superior prefrontal cortex volumes, a smaller right anterior cingulate cortex and less cerebellar gray matter, so did co-morbid ADHD plus BPD subjects.ConclusionsOur results support the hypothesis that ADHD and BPD independently contribute to volumetric alterations of selective and distinct brain structures. In the co-morbid state of ADHD plus BPD, the profile of brain volumetric abnormalities consists of structures that are altered in both disorders individually. Attention to co-morbidity is necessary to help clarify the heterogeneous neuroanatomy of both BPD and ADHD.
A genetically informative developmental study of the relationship between conduct disorder and peer deviance in males
Authors: Kendler K. S. , Jacobson K. , Myers J. M. , Eaves L. J. 
Published: October 2007

BackgroundConduct disorder (CD) and peer deviance (PD) both powerfully predict future externalizing behaviors. Although levels of CD and PD are strongly correlated, the causal relationship between them has remained controversial and has not been examined by a genetically informative study.MethodLevels of CD and PD were assessed in 746 adult male–male twin pairs at personal interview for ages 8–11, 12–14 and 15–17 years using a life history calendar. Model fitting was performed using the Mx program.ResultsThe best-fit model indicated an active developmental relationship between CD and PD including forward transmission of both traits over time and strong causal relationships between CD and PD within time periods. The best-fit model indicated that the causal relationship for genetic risk factors was from CD to PD and was constant over time. For common environmental factors, the causal pathways ran from PD to CD and were stronger in earlier than later age periods.ConclusionA genetically informative model revealed causal pathways difficult to elucidate by other methods. Genes influence risk for CD, which, through social selection, impacts on the deviance of peers. Shared environment, through family and community processes, encourages or discourages adolescent deviant behavior, which, via social influence, alters risk for CD. Social influence is more important than social selection in childhood, but by late adolescence social selection becomes predominant. These findings have implications for prevention efforts for CD and associated externalizing disorders.
An electron-beam accelerator based on spiral water PFL
Authors: Liu J.L. , Yin Yi , Ge Bin , Zhan T.W. , Chen X.B. , Feng J.H. , Shu Ting , ZHANG J.D. , Wang X. Xinxin 
Published: October 2007

AbstractAn electron-beam accelerator based on spiral water pulse forming line which consists of a primary storage capacitor system, an air core spiral strip transformer, a spiral pulse forming line of water dielectric, and a field-emission diode, is described. The experimental results showed that the diode voltage is more than 500 kV, the electron beam current of diode is about 24 kA, and the pulse duration is about 200 ns. The main parameters of the accelerator were calculated theoretically. The distributions for electrical field in the pulse forming line were obtained by the simulations. In addition, the process of the accelerator charging a spiral pulse forming line was simulated through the Pspice software to get the waveforms of charging voltage of pulse forming line, the diode voltage and diode current of accelerator. The theoretical and simulated results agree with the experimental results. This accelerator is very compact and works stably and reliably.
Saturation effect at high laser pulse energies in laser-induced breakdown spectroscopy for elemental analysis in water
Authors: Fang Xiao , Rafi Ahmad S. 
Published: October 2007

AbstractSaturation effects in laser-induced breakdown spectroscopy in water for elemental analysis have been investigated. Existing theoretical model of laser-induced plasma in solids has been applied to liquid phase under some simplifying assumptions to take account of the laser pulse energy dependence of atomic emissions from Na and Cu in aqueous solution. The theory was found to explain the emission process for laser energies up to but below the saturation level. The saturation limit of the emission with laser pulse energy corresponds well with that of the plasma temperature deduced from blackbody emission considerations. The saturation energies for atomic emissions were found to be lower for bulk excitations compared to water jet excitations. The dependence of signal strength on sample concentration indicated that the concentration values at saturation are lower at higher laser energies, as is expected from the theoretical model.
Race and food store availability in an inner-city neighbourhood
Authors: Galvez Maida P , Morland Kimberly , Raines Cherita , Kobil Jessica , Siskind Jodi , Godbold James , Brenner Barbara 
Published: October 2007

AbstractBackgroundA growing body of research has shown that disparities in resources, including food stores, exist at the neighbourhood level and the greatest disparities are seen in minority neighbourhoods, the same neighbourhoods at increased risk of obesity and diabetes. Less is known about whether differences in availability of resources by African American or Latino race/ethnicity exist within a single minority community.ObjectiveThe present study examined whether census blocks either 75% African American (AA) or 75% Latino (L) are associated with food store availability, as compared with racially mixed (RM) census blocks, in East Harlem, New York.Design/methodsA cross-sectional study utilising a walking survey of East Harlem was performed. Food stores were classified into: supermarkets, grocery stores, convenience stores, specialty stores, full-service restaurants and fast-food stores.ResultsOne hundred and sixty-five East Harlem census blocks were examined; 17 were AA, 34 were L and 114 were RM. Of AA census blocks, 100% had neither supermarkets nor grocery stores. AA census blocks were less likely to have convenience stores (prevalence ratio (PR) = 0.25, 95% confidence interval (CI) 0.07–0.86) compared with RM census blocks. In contrast, predominantly L census blocks were more likely to have convenience stores (PR = 1.8, 95% CI 1.20–2.70), specialty food stores (PR = 3.74, 95% CI 2.06–7.15), full-service restaurants (PR = 1.87, 95% CI 1.04–3.38) and fast-food restaurants (PR = 2.14, 95% CI 1.33–3.44) compared with RM census blocks.ConclusionsWe found that inequities in food store availability exist by race/ethnicity in East Harlem, New York. This has implications for racial/ethnic differences in dietary quality, obesity and obesity-related disorders.
Is cooking food in iron pots an appropriate solution for the control of anaemia in developing countries? A randomised clinical trial in Benin
Authors: Sharieff Waseem , Dofonsou Joyce , Zlotkin Stanley 
Published: October 2007

AbstractObjectiveTo evaluate the effect of two types of iron pots on haemoglobin (Hb) and serum ferritin (SF) concentrations in young children (6–24 months), adolescent girls (11–15 years) and women of reproductive age (15–44 years), whose households were provided with iron pots for cooking food over a period of 6 months, compared with controls.Design and methodsWe randomly assigned 161 households including 339 individuals from the three subgroups to cast iron pots, blue steel pots or oral iron supplements (control). In the control group, children received micronutrient Sprinkles™, and adolescent girls and women received iron tablets daily for 6 months. We measured Hb, SF and C-reactive protein concentrations at baseline and 6 months, and compared groups using regression models.ResultsAnaemia prevalence (Hb < 110 g l−1in infants, Hb < 120 g l−1in girls or women) was 47% (cast iron group), 50% (blue steel group) and 50% (control) at baseline. At 6 months, there were no significant differences in Hb concentrations among groups; however, differences in SF concentrations were significant (P< 0.0001) – the control group had higher SF concentrations compared with the groups using iron pots. Also, differences in the prevalence of iron-deficiency anaemia (IDA; anaemia plus SF < 15 μg l−1) were almost significant between cast iron and control groups (P= 0.08), and blue steel and control groups (P= 0.05).ConclusionThere is no evidence that iron cooking pots are effective against IDA. Further research is warranted to determine whether the iron leached from the pots is bioavailable.
Modeling and Parameter Identification of the Simultaneous Saccharification‐Fermentation Process for Ethanol Production
Authors: Ochoa Silvia , Yoo Ahrim , Repke Jens‐Uwe , Wozny Günter , Yang Dae Ryook 
Published: October 2007

AbstractDespite many environmental advantages of using alcohol as a fuel, there are still serious questions about its economical feasibility when compared with oil‐based fuels. The bioethanol industry needs to be more competitive, and therefore, all stages of its production process must be simple, inexpensive, efficient, and “easy” to control. In recent years, there have been significant improvements in process design, such as in the purification technologies for ethanol dehydration (molecular sieves, pressure swing adsorption, pervaporation, etc.) and in genetic modifications of microbial strains. However, a lot of research effort is still required in optimization and control, where the first step is the development of suitable models of the process, which can be used as a simulated plant, as a soft sensor or as part of the control algorithm. Thus, toward developing good, reliable, and simple but highly predictive models that can be used in the future for optimization and process control applications, in this paper an unstructured and a cybernetic model are proposed and compared for the simultaneous saccharification‐fermentation process (SSF) for the production of ethanol from starch by a recombinant Saccharomyces cerevisiae strain. The cybernetic model proposed is a new one that considers the degradation of starch not only into glucose but also into dextrins (reducing sugars) and takes into account the intracellular reactions occurring inside the cells, giving a more detailed description of the process. Furthermore, an identification procedure based on the Metropolis Monte Carlo optimization method coupled with a sensitivity analysis is proposed for the identification of the modelapos;s parameters, employing experimental data reported in the literature.
Modeling of Effects of Nutrient Gradients on Cell Proliferation in Microfluidic Bioreactor
Authors: Hu Guoqing , Quaranta Vito , Li Dongqing 
Published: October 2007

AbstractPrecise control of the microenvironment is highly desirable in cell culture to study the cell biology. Microfluidic based bioreactors provide a promising method for the spatial and temporal control of cell growth and stimuli. A three‐dimensional nutrient transport model, incorporating the monolayer cell growth model, has been developed to investigate the influence of gradients of oxygen and epidermal growth factor (EGF) on the cell culture in the continuous‐flow microchannel bioreactor. Our results demonstrate that applying inlet concentration gradients of oxygen and EGF can induce variations of cell density in the y‐direction. It is further found that compared to the oxygen gradients the EGF concentration gradients are more efficient in regulating the cell growth.
InterProSurf: a web server for predicting interacting sites on protein surfaces
Authors: Negi Surendra S. , Schein Catherine H. , Oezguen Numan , Power Trevor D. , Braun Werner 
Published: October 2007

AbstractSummary: A new web server, InterProSurf, predicts interacting amino acid residues in proteins that are most likely to interact with other proteins, given the 3D structures of subunits of a protein complex. The prediction method is based on solvent accessible surface area of residues in the isolated subunits, a propensity scale for interface residues and a clustering algorithm to identify surface regions with residues of high interface propensities. Here we illustrate the application of InterProSurf to determine which areas of Bacillus anthracis toxins and measles virus hemagglutinin protein interact with their respective cell surface receptors. The computationally predicted regions overlap with those regions previously identified as interface regions by sequence analysis and mutagenesis experiments.Availability: The InterProSurf web server is available at http://curie.utmb.edu/Contact: webraun@utmb.eduSupplementary information: Other test examples are available as Supplementary Material at Bioinformatics online.
Creating protein models from electron-density maps using particle-filtering methods
Authors: DiMaio Frank , Kondrashov Dmitry A. , Bitto Eduard , Soni Ameet , Bingman Craig A. , Phillips George N. , Shavlik Jude W. 
Published: October 2007

AbstractMotivation: One bottleneck in high-throughput protein crystallography is interpreting an electron-density map, that is, fitting a molecular model to the 3D picture crystallography produces. Previously, we developed Acmi (Automatic Crystallographic Map Interpreter), an algorithm that uses a probabilistic model to infer an accurate protein backbone layout. Here, we use a sampling method known as particle filtering to produce a set of all-atom protein models. We use the output of Acmi to guide the particle filter's sampling, producing an accurate, physically feasible set of structures.Results: We test our algorithm on 10 poor-quality experimental density maps. We show that particle filtering produces accurate all-atom models, resulting in fewer chains, lower sidechain RMS error and reduced R factor, compared to simply placing the best-matching sidechains on Acmi's trace. We show that our approach produces a more accurate model than three leading methods—Textal, Resolve and ARP/WARP—in terms of main chain completeness, sidechain identification and crystallographic R factor.Availability: Source code and experimental density maps available at http://ftp.cs.wisc.edu/machine-learning/shavlik-group/programs/acmi/Contact: dimaio@cs.wisc.edu
MDQC: a new quality assessment method for microarrays based on quality control reports
Authors: Cohen Freue Gabriela V. , Hollander Zsuzsanna , Shen Enqing , Zamar Ruben H. , Balshaw Robert , Scherer Andreas , McManus Bruce , Keown Paul , McMaster W. Robert , Ng Raymond T. 
Published: October 2007

AbstractMotivation: The process of producing microarray data involves multiple steps, some of which may suffer from technical problems and seriously damage the quality of the data. Thus, it is essential to identify those arrays with low quality. This article addresses two questions: (1) how to assess the quality of a microarray dataset using the measures provided in quality control (QC) reports; (2) how to identify possible sources of the quality problems.Results: We propose a novel multivariate approach to evaluate the quality of an array that examines the ‘Mahalanobis distance’ of its quality attributes from those of other arrays. Thus, we call it Mahalanobis Distance Quality Control (MDQC) and examine different approaches of this method. MDQC flags problematic arrays based on the idea of outlier detection, i.e. it flags those arrays whose quality attributes jointly depart from those of the bulk of the data. Using two case studies, we show that a multivariate analysis gives substantially richer information than analyzing each parameter of the QC report in isolation. Moreover, once the QC report is produced, our quality assessment method is computationally inexpensive and the results can be easily visualized and interpreted. Finally, we show that computing these distances on subsets of the quality measures in the report may increase the method's ability to detect unusual arrays and helps to identify possible reasons of the quality problems.Availability: The library to implement MDQC will soon be available from BioconductorContact: gcohen@mrl.ubc.caSupplementary information: Supplementary data are available at Bioinformatics online.
Incorporating prior knowledge of gene functional groups into regularized discriminant analysis of microarray data
Authors: Tai Feng , Pan Wei 
Published: October 2007

AbstractMotivation: Discriminant analysis for high-dimensional and low-sample-sized data has become a hot research topic in bioinformatics, mainly motivated by its importance and challenge in applications to tumor classifications for high-dimensional microarray data. Two of the popular methods are the nearest shrunken centroids, also called predictive analysis of microarray (PAM), and shrunken centroids regularized discriminant analysis (SCRDA). Both methods are modifications to the classic linear discriminant analysis (LDA) in two aspects tailored to high-dimensional and low-sample-sized data: one is the regularization of the covariance matrix, and the other is variable selection through shrinkage. In spite of their usefulness, there are potential limitations with each method. The main concern is that both PAM and SCRDA are possibly too extreme: the covariance matrix in the former is restricted to be diagonal while in the latter there is barely any restriction. Based on the biology of gene functions and given the feature of the data, it may be beneficial to estimate the covariance matrix as an intermediate between the two; furthermore, more effective shrinkage schemes may be possible.Results: We propose modified LDA methods to integrate biological knowledge of gene functions (or variable groups) into classification of microarray data. Instead of simply treating all the genes independently or imposing no restriction on the correlations among the genes, we group the genes according to their biological functions extracted from existing biological knowledge or data, and propose regularized covariance estimators that encourages between-group gene independence and within-group gene correlations while maintaining the flexibility of any general covariance structure. Furthermore, we propose a shrinkage scheme on groups of genes that tends to retain or remove a whole group of the genes altogether, in contrast to the standard shrinkage on individual genes. We show that one of the proposed methods performed better than PAM and SCRDA in a simulation study and several real data examples.Contact: weip@biostat.umn.edu