bluuebunny/crossref_metadata_2025_split huggingface dataset:
Susceptibility evaluation of Picea abies and Cupressus lusitanica to the pine wood nematode (Bursaphelenchus xylophilus)
Authors: Nunes da Silva M. , Lima M. R. M. , Vasconcelos M. W. 
Published: February 2013

Pine wilt disease (PWD), recently introduced into Europe, is caused by the pine wood nematode (PWN) Bursaphelenchus xylophilus and is a devastating illness that affects mainly pine trees. It is known that the PWN is capable of infecting other conifers; however, there is currently no information on which other plant species may be susceptible to PWD. In this study, the potential susceptibility of two common species of European forests, Picea abies and Cupressus lusitanica, to PWN was assessed through the monitoring of visual external symptoms, dimension and localization of the nematode population in stems, quantification of total chlorophyll, total soluble phenolics and lignin, at 7, 14, 21 and 28 days after inoculation. The degree of susceptibility was established through the comparison of symptoms with Pinus pinaster, a well‐known PWN host. Furthermore, the stem ultrastructure of P. abies, C. lusitanica and Pn. pinaster was analysed by scanning electron microscopy. The results suggest that P. abies and C. lusitanica are resistant to PWN, and that lignin biosynthesis in these species is affected at an early stage of the infestation. Nevertheless, P. abies seems to be a compatible host that could act as a repository for PWN.
A case of pili torti in a young adult domestic short‐haired cat
Authors: Maina Elisa , Colombo Silvia , Abramo Francesca , Pasquinelli Gianandrea 
Published: February 2013

BackgroundPili torti is a congenital or acquired human disease characterized by flattening and twisting of the hair shaft by 180 degrees. A similar condition has been previously reported in a litter of kittens with generalized hair loss, associated with systemic signs and followed by death at a young age.AnimalA 1‐year‐old castrated male domestic short‐haired cat was presented for noninflammatory and nonpruritic symmetrical multifocal alopecia involving the head, pinnae, forelimbs, tail and chest. The cat was otherwise healthy.Methods and resultsMicroscopic examination of hair shafts revealed pili torti and a typical combination of anagen and telogen roots, occasionally spiral in shape, without evidence of mites or dermatophytes. Histopathological examination showed the same hair shaft abnormality, with normal epidermis, dermis, hair follicles and other adnexa. Scanning electron microscopy confirmed a hair shaft dysplasia characterized by pili torti, similar to that described in humans.Conclusions and clinical importanceTo the best of the authors' knowledge, this is the first case report of pili torti in a healthy young adult cat.
Differential responses of fast‐ and slow‐conducting pyramidal tract neurons to changes in accuracy demands during locomotion
Authors: Stout Erik E. , Beloozerova Irina N. 
Published: February 2013

Key points
The motor cortex is highly involved in performing complex movements including skilled locomotion.
Slow‐conducting pyramidal tract neurons (PTNs) in the motor cortex are much more numerous than fast‐conducting PTNs, but little is known about their function during movements.
We find here that slow‐conducting PTNs show vigorous and concerted changes to their activities during accurate targeted stepping versus simple locomotion over a flat surface, while changes to the activities of fast‐conducting PTNs vary.
This suggests that slow‐conducting PTNs are involved to a greater extent in control of accuracy during locomotion.
The results may be relevant to developing therapies for stroke and traumatic brain injury.
Abstract  Most movements need to be accurate. The neuronal mechanisms controlling accuracy during movements are poorly understood. In this study we compare the activity of fast‐ and slow‐conducting pyramidal tract neurons (PTNs) of the motor cortex in cats as they walk over both a flat surface, a task that does not require accurate stepping and can be accomplished without the motor cortex, as well as along a horizontal ladder, a task that requires accuracy and the activity of the motor cortex to be successful. Fast‐ and slow‐conducting PTNs are known to have distinct biophysical properties as well as different afferent and efferent connections. We found that while the activity of all PTNs changes substantially upon transition from simple locomotion to accurate stepping on the ladder, slow‐conducting PTNs respond in a much more concerted manner than fast‐conducting ones. As a group, slow‐conducting PTNs increase discharge rate, especially during the late stance and early swing phases, decrease discharge variability, have a tendency to shift their preferred phase of the discharge into the swing phase, and almost always produce a single peak of activity per stride during ladder locomotion. In contrast, the fast‐conducting PTNs do not display such concerted changes to their activity. In addition, upon transfer from simple locomotion to accurate stepping on the ladder slow‐conducting PTNs more profoundly increase the magnitude of their stride‐related frequency modulation compared with fast‐conducting PTNs. We suggest that slow‐conducting PTNs are involved in control of accuracy of locomotor movements to a greater degree than fast‐conducting PTNs.
Inhibitors of eIF2α Dephosphorylation Slow Replication and Stabilize Latency in Toxoplasma gondii
Authors: Konrad Christian , Queener Sherry F. , Wek Ronald C. , Sullivan William J. 
Published: February 2013

ABSTRACT

Toxoplasma gondii
is an obligate intracellular parasite that permanently infects warm-blooded vertebrates through its ability to convert into a latent tissue cyst form. The latent form (bradyzoite) can reinitiate a life-threatening acute infection if host immunity wanes, most commonly in AIDS or organ transplant patients. We have previously shown that bradyzoite development is accompanied by phosphorylation of the parasite eukaryotic initiation factor 2 alpha subunit (eIF2α), which dampens global protein synthesis and reprograms gene expression. In this study, we analyzed the activities of two specific inhibitors of eIF2α dephosphorylation, salubrinal (SAL) and guanabenz (GA). We establish that these drugs are able to inhibit the dephosphorylation of
Toxoplasma
eIF2α. Our results show that SAL and GA reduce tachyzoite replication
in vitro
and
in vivo
. Furthermore, both drugs induce bradyzoite formation and inhibit the reactivation of latent bradyzoites
in vitro
. To address whether the antiparasitic activities of SAL and GA involve host eIF2α phosphorylation, we infected mutant mouse embryonic fibroblast (MEF) cells incapable of phosphorylating eIF2α, which had no impact on the efficacies of SAL and GA against
Toxoplasma
infection. Our findings suggest that SAL and GA may serve as potential new drugs for the treatment of acute and chronic toxoplasmosis.
Effects of Biofilm Growth on Plasmid Copy Number and Expression of Antibiotic Resistance Genes in Enterococcus faecalis
Authors: Cook L. C. , Dunny G. M. 
Published: February 2013

ABSTRACT

Biofilm growth causes increased average plasmid copy number as well as increased copy number heterogeneity in
Enterococcus faecalis
cells carrying plasmid pCF10. In this study, we examined whether biofilm growth affected the copy number and expression of antibiotic resistance determinants for several plasmids with diverse replication systems. Four different
E. faecalis
plasmids, unrelated to pCF10, demonstrated increased copy number in biofilm cells. In biofilm cells, we also observed increased transcription of antibiotic resistance genes present on these plasmids. The increase in plasmid copy number correlated with increased plating efficiency on high concentrations of antibiotics. Single-cell analysis of strains carrying two different plasmids suggested that the increase in plasmid copy number associated with biofilm growth was restricted to a subpopulation of biofilm cells. Regrowth of harvested biofilm cells in liquid culture resulted in a rapid reduction of plasmid copy number to that observed in the planktonic state. These results suggest a possible mechanism by which biofilm growth could reduce susceptibility to antibiotics in clinical settings.
Time Series Analysis as a Tool To Predict the Impact of Antimicrobial Restriction in Antibiotic Stewardship Programs Using the Example of Multidrug-Resistant Pseudomonas aeruginosa
Authors: Willmann Matthias , Marschal Matthias , Hölzl Florian , Schröppel Klaus , Autenrieth Ingo B. , Peter Silke 
Published: February 2013

ABSTRACT

The association between antimicrobial consumption and resistance in nonfermentative Gram-negative bacteria is well-known. Antimicrobial restriction, implemented in clinical routines by antibiotic stewardship programs (ASPs), is considered a means to reduce resistance rates. Whether and how antimicrobial restriction can accomplish this goal is still unknown though. This leads to an element of uncertainty when designing strategies for ASPs. From January 2002 until December 2011, an observational study was performed at the University Hospital Tübingen, Tübingen, Germany, to investigate the association between antimicrobial use and resistance rates in
Pseudomonas aeruginosa
. Transfer function models were used to determine such associations and to simulate antimicrobial restriction strategies. Various positive associations between antimicrobial consumption and resistance were observed in our setting. Surprisingly, impact estimations of different antimicrobial restriction strategies revealed relatively low intervention expenses to effectively attenuate the observed increase in resistance. For example, a simulated intervention of an annual 4% reduction in the use of meropenem over 3 years from 2009 until 2011 yielded a 62.5% attenuation (95% confidence interval, 15% to 110%) in the rising trend of multidrug-resistant
Pseudomonas aeruginosa
(three- and four-class-resistant
P. aeruginosa
[34MRGN-PA]). Time series analysis models derived from past data may be a tool to predict the outcome of antimicrobial restriction strategies, and could be used to design ASPs.
Efficacy of Tenofovir in Patients with Lamivudine Failure Is Not Different from That in Nucleoside/Nucleotide Analogue-Naïve Patients with Chronic Hepatitis B
Authors: Baran Bulent , Soyer Ozlem Mutluay , Ormeci Asli Cifcibasi , Gokturk Suut , Evirgen Sami , Bozbey Hamza Ugur , Akyuz Filiz , Karaca Cetin , Demir Kadir , Besisik Fatih , Onel Derya , Gulluoglu Mine , Badur Selim , Kaymakoglu Sabahattin 
Published: February 2013

ABSTRACTWe evaluated the efficacy of tenofovir disoproxil fumarate (TDF) in patients with lamivudine failure (LAM-F) in comparison with that in nucleoside/nucleotide analogue (NA)-naïve patients with chronic hepatitis B (CHB). The criteria for inclusion were being NA naïve or having previous LAM-F and receiving TDF therapy for at least 6 months. Biochemical and virological tests were performed at the baseline, at 3-month intervals in the first year, and every 6 months thereafter. The primary outcome measure for efficacy was a complete virological response (CVR), defined as an HBV DNA level of <20 IU/ml. CVR rates were calculated by Kaplan-Meier analysis, and a multivariate Cox proportional-hazard model was generated in order to find predictive factors independently associated with the time to a CVR. We included 197 patients in the study (136 males; mean age, 43 ± 12 years; 105 patients were NA naïve). Sixty-five patients had hepatitis B e antigen (HBeAg)-positive CHB. The median duration of TDF treatment was 29 (range, 6 to 52) months. Seventy-one patients (77%) in the LAM-F group were treated with TDF add-on therapy. The CVR rates of the NA-naïve and LAM-F groups were comparable in HBeAg-negative (94% versus 96% at month 36,P= 0.10) and HBeAg-positive patients (67% versus 83% at month 36,P= 0.48). According to the multivariate Cox regression model, only HBeAg positivity (hazard ratio [HR], 0.39; 95% confidence interval [CI], 0.26 to 0.59;P< 0.001) and a high baseline HBV DNA level (HR, 0.44; 95% CI, 0.29 to 0.67;P< 0.001) had a significant influence on the time to a CVR. The similar cumulative CVR rates during the follow-up show that TDF has comparable efficacy in lamivudine-experienced and NA-naïve patients, and the presence of resistance mutations did not alter the response rates.
SR-Like RNA-Binding Protein Slr1 Affects Candida albicans Filamentation and Virulence
Authors: Ariyachet Chaiyaboot , Solis Norma V. , Liu Yaoping , Prasadarao Nemani V. , Filler Scott G. , McBride Anne E. 
Published: February 2013

ABSTRACT

Candida albicans
causes both mucosal and disseminated infections, and its capacity to grow as both yeast and hyphae is a key virulence factor. Hyphal formation is a type of polarized growth, and members of the SR (serine-arginine) family of RNA-binding proteins influence polarized growth of both
Saccharomyces cerevisiae
and
Aspergillus nidulans
. Therefore, we investigated whether SR-like proteins affect filamentous growth and virulence of
C. albicans
. BLAST searches with
S. cerevisiae
SR-like protein Npl3 (ScNpl3) identified two
C. albicans
proteins: CaNpl3, an apparent ScNpl3 ortholog, and Slr1, another
S
R-
l
ike
R
NA-binding protein with no close
S. cerevisiae
ortholog. Whereas ScNpl3 was critical for growth, deletion of
NPL3
in
C. albicans
resulted in few phenotypic changes. In contrast, the
slr1
Δ/Δ mutant had a reduced growth rate
in vitro
, decreased filamentation, and impaired capacity to damage epithelial and endothelial cells
in vitro
. Mice infected intravenously with the
slr1
Δ/Δ mutant strain had significantly prolonged survival compared to that of mice infected with the wild-type or
slr1
Δ/Δ mutant complemented with
SLR1
(
slr1
Δ/Δ+
SLR1
) strain, without a concomitant decrease in kidney fungal burden. Histopathology, however, revealed differential localization of
slr1
Δ/Δ hyphal and yeast morphologies within the kidney. Mice infected with
slr1
Δ/Δ cells also had an increased brain fungal burden, which correlated with increased invasion of brain, but not umbilical vein, endothelial cells
in vitro
. The enhanced brain endothelial cell invasion was likely due to the increased surface exposure of the Als3 adhesin on
slr1
Δ/Δ cells. Our results indicate that Slr1 is an SR-like protein that influences
C. albicans
growth, filamentation, host cell interactions, and virulence.
Staphylococcus aureus Nuclease Is an SaeRS-Dependent Virulence Factor
Authors: Olson Michael E. , Nygaard Tyler K. , Ackermann Laynez , Watkins Robert L. , Zurek Oliwia W. , Pallister Kyler B. , Griffith Shannon , Kiedrowski Megan R. , Flack Caralyn E. , Kavanaugh Jeffrey S. , Kreiswirth Barry N. , Horswill Alexander R. , Voyich Jovanka M. 
Published: February 2013

ABSTRACT

Several prominent bacterial pathogens secrete nuclease (Nuc) enzymes that have an important role in combating the host immune response. Early studies of
Staphylococcus aureus
Nuc attributed its regulation to the
agr
quorum-sensing system. However, recent microarray data have indicated that
nuc
is under the control of the SaeRS two-component system, which is a major regulator of
S. aureus
virulence determinants. Here we report that the
nuc
gene is directly controlled by the SaeRS two-component system through reporter fusion, immunoblotting, Nuc activity measurements, promoter mapping, and binding studies, and additionally, we were unable identify a notable regulatory link to the
agr
system. The observed SaeRS-dependent regulation was conserved across a wide spectrum of representative
S. aureus
isolates. Moreover, with community-associated methicillin-resistant
S. aureus
(CA MRSA) in a mouse model of peritonitis, we observed
in vivo
expression of Nuc activity in an SaeRS-dependent manner and determined that Nuc is a virulence factor that is important for
in vivo
survival, confirming the enzyme's role as a contributor to invasive disease. Finally, natural polymorphisms were identified in the SaeRS proteins, one of which was linked to Nuc regulation in a CA MRSA USA300 endocarditis isolate. Altogether, our findings demonstrate that Nuc is an important
S. aureus
virulence factor and part of the SaeRS regulon.
GENE EXPRESSION DATA CLASSIFICATION COMBINING HIERARCHICAL REPRESENTATION AND EFFICIENT FEATURE SELECTION
Authors: BOSIO MATTIA , BELLOT PAU , SALEMBIER PHILIPPE , OLIVERAS-VERGÉS ALBERT 
Published: February 2013

A general framework for microarray data classification is proposed in this paper. It produces precise and reliable classifiers through a two-step approach. At first, the original feature set is enhanced by a new set of features called metagenes. These new features are obtained through a hierarchical clustering process on the original data. Two different metagene generation rules have been analyzed, called Treelets clustering and Euclidean clustering. Metagenes creation is attractive for several reasons: first, they can improve the classification since they broaden the available feature space and capture the common behavior of similar genes reducing the residual measurement noise. Furthermore, by analyzing some of the chosen metagenes for classification with gene set enrichment analysis algorithms, it is shown how metagenes can summarize the behavior of functionally related probe sets. Additionally, metagenes can point out, still undocumented, highly discriminant probe sets numerically related to other probes endowed with prior biological information in order to contribute to the knowledge discovery process. The second step of the framework is the feature selection which applies the Improved Sequential Floating Forward Selection algorithm (IFFS) to properly choose a subset from the available feature set for classification composed of genes and metagenes. Considering the microarray sample scarcity problem, besides the classical error rate, a reliability measure is introduced to improve the feature selection process. Different scoring schemes are studied to choose the best one using both error rate and reliability. The Linear Discriminant Analysis classifier (LDA) has been used throughout this work, due to its good characteristics, but the proposed framework can be used with almost any classifier. The potential of the proposed framework has been evaluated analyzing all the publicly available datasets offered by the Micro Array Quality Control Study, phase II (MAQC). The comparative results showed that the proposed framework can compete with a wide variety of state of the art alternatives and it can obtain the best mean performance if a particular setup is chosen. A Monte Carlo simulation confirmed that the proposed framework obtains stable and repeatable results.
UNCOVER CONTEXT-SPECIFIC GENE REGULATION BY TRANSCRIPTION FACTORS AND microRNAs USING BAYESIAN SPARSE NONNEGATIVE FACTOR REGRESSION
Authors: MENG JIA , CHEN YIDONG , HUANG YUFEI 
Published: February 2013

In multicellular organisms, transcription factors (TFs) and microRNAs (miRNA) embody two largest families of molecules that modulate messenger RNA (mRNA) expressions through transcriptional and post-transcriptional regulations. While mRNA and microRNA expressions can be measured by microarray technique, the activities of transcription factors manifested by their protein expression are still difficult to observe, making it usually a complex problem to reconstruct a collaborative gene regulatory network (GRN) by TFs and miRNAs from expression data. In this paper, a novel Bayesian sparse non-negative factor regression (BSNFR) model is proposed for modeling the joint regulations of mRNAs by TFs and miRNAs and integration of multiple data types including gene expressions, microRNA expressions, TF targeted genes, and microRNA targets. Powered by a Gibbs sampling solution, BSNFR can infer both the TF/microRNA-mediated mRNA regulations and the unknown TF activities. Additionally, since BSNFR directly models the non-negative activities of TFs, it avoids the common problem of sign ambiguity with factor models and is capable of accurate prediction of the types (up or down) of regulations as well. BSNFR also includes a nonparametric Bayesian model for the latent factor activities, which enables the discovery of the clustering effects among samples due to (disease) subtypes. The proposed BSNFR model and the developed Gibbs sampling solution were validated on simulated systems and applied to real data of glioblastoma multiforme (GBM) patients from The Cancer Genome Atlas (TCGA). A GBM specific gene regulatory network by TFs and miRNAs was reconstructed. This GBM network includes 107 regulations recorded in the existing databases and 16 new regulations. Functional analysis suggests that the regulated genes are enriched in cell cycle and P53 pathways. In addition, BSNFR also identified 3 clusters among GBM patient samples, two of which demonstrates significant survival differences (p=0.004). Finally, the estimated TF activities imply that EGR-1 is significantly correlated with patient survivals (p=0.004) and may be used as a prognostic biomarker. The data and matlab code are available at: http://compgenomics.cbi.utsa.edu/BSNFR .
X-Class
Authors: Costa Gianni , Ortale Riccardo , Ritacco Ettore 
Published: February 2013

The supervised classification of XML documents by structure involves learning predictive models in which certain structural regularities discriminate the individual document classes. Hitherto, research has focused on the adoption of prespecified substructures. This is detrimental for classification effectiveness, since the a priori chosen substructures may not accord with the structural properties of the XML documents. Therein, an unexplored question is how to choose the type of structural regularity that best adapts to the structures of the available XML documents.
We tackle this problem through X-Class, an approach that handles all types of tree-like substructures and allows for choosing the most discriminatory one. Algorithms are designed to learn compact rule-based classifiers in which the chosen substructures discriminate the classes of XML documents.
X-Class is studied across various domains and types of substructures. Its classification performance is compared against several rule-based and SVM-based competitors. Empirical evidence reveals that the classifiers induced by X-Class are compact, scalable, and at least as effective as the established competitors. In particular, certain substructures allow the induction of very compact classifiers that generally outperform the rule-based competitors in terms of effectiveness over all chosen corpora of XML data. Furthermore, such classifiers are substantially as effective as the SVM-based competitor, with the additional advantage of a high-degree of interpretability.