Cell wall composition and biofilm formation of azoles-susceptible and -resistant Candida glabrata strains

In the present study, three strains of Candida glabrata have been investigated to shed light on the mechanisms involved in azole resistance during adherence and biofilm formation. In particular, a clinical isolate, susceptible to azole-based drugs, DSY562 and two different resistant mutagenic strains deriving from DSY562, SFY114 and SFY115, have been analysed with different approaches for their cell wall composition and properties. A proteomic analysis revealed that the expression of six cell wall-related proteins and biofilm formation varied between the strains. The SFY114 and SFY115 strains resulted to be less hydrophobic than the susceptible parental counterpart DSY562, on the other hand they showed a higher amount in total cell wall polysaccharides fraction in the total cell wall. Accordingly to the results obtained from the hydrophobicity and adherence assays, in the resistant strain SFY115 the biofilm formation decreased compared to the parental strain DSY562. Finally, the total glucose amount in resistant SFY115 was about halved in comparison to other strains. Taken together all these data suggest that azole drugs may affect the cell wall composition of C. glabrata, in relation to the different pathogenic behaviours

Cell wall composition and biofilm formation of azoles-susceptible and -resistant Candida glabrata strains

In the present study, three strains of Candida glabrata have been investigated to shed light on the mechanisms involved in azole resistance during adherence and biofilm formation. In particular, a clinical isolate, susceptible to azole-based drugs, DSY562 and two different resistant mutagenic strains deriving from DSY562, SFY114 and SFY115, have been analysed with different approaches for their cell wall composition and properties. A proteomic analysis revealed that the expression of six cell wall-related proteins and biofilm formation varied between the strains. The SFY114 and SFY115 strains resulted to be less hydrophobic than the susceptible parental counterpart DSY562, on the other hand they showed a higher amount in total cell wall polysaccharides fraction in the total cell wall. Accordingly to the results obtained from the hydrophobicity and adherence assays, in the resistant strain SFY115 the biofilm formation decreased compared to the parental strain DSY562. Finally, the total glucose amount in resistant SFY115 was about halved in comparison to other strains. Taken together all these data suggest that azole drugs may affect the cell wall composition of C. glabrata, in relation to the different pathogenic behaviours

A Framework for Collaborative Curation of Neuroscientific Literature

Large models of complex neuronal circuits require specifying numerous parameters, with values that often need to be extracted from the literature, a tedious and error-prone process. To help establishing shareable curated corpora of annotations, we have developed a literature curation framework comprising an annotation format, a Python API (NeuroAnnotation Toolbox; NAT), and a user-friendly graphical interface (NeuroCurator). This framework allows the systematic annotation of relevant statements and model parameters. The context of the annotated content is made explicit in a standard way by associating it with ontological terms (e.g., species, cell types, brain regions). The exact position of the annotated content within a document is specified by the starting character of the annotated text, or the number of the figure, the equation, or the table, depending on the context. Alternatively, the provenance of parameters can also be specified by bounding boxes. Parameter types are linked to curated experimental values so that they can be systematically integrated into models. We demonstrate the use of this approach by releasing a corpus describing different modeling parameters associated with thalamo-cortical circuitry. The proposed framework supports a rigorous management of large sets of parameters, solving common difficulties in their traceability. Further, it allows easier classification of literature information and more efficient and systematic integration of such information into models and analyses

Salivary Proteomic Analysis and Acute Graft-versus-Host Disease after Allogeneic Hematopoietic Stem Cell Transplantation

Abstract Graft-versus-host disease (GVHD) is the major life-threatening complication after allogeneic hematopoietic stem cell transplantation (allo-HSCT), developing in 35%-70% of all allo-HSCT recipients despite immunosuppressive prophylaxis. The recent application of proteomic tools that allow screening for differentially expressed or excreted proteins in body fluids could possibly identify specific biomarkers for GVHD. Whole saliva is highly attractive for noninvasive specimen collection. In the present study, we collected saliva specimens from 40 consecutives patients who underwent allo-HSCT between December 2008 and March 2011 at our institution. The specimens were analyzed by HPLC coupled to electrospray-ionization mass spectrometry. Variable expression of S100 protein family members (S100A8, S100A9, and S100A7) was detected. Fourteen of 23 patients with GVHD demonstrated the presence of S100A8, compared with only 2 patients without GVHD and 0 patients in the control group ( P = .001). S100A7 was detectable in 11 of the 23 patients with GVHD but was absent in the other 2 groups ( P = .0001). S100A9-short was detected in 20 patients with GVHD, in 9 patients without GVHD, and in 8 healthy volunteers ( P = .01) Further studies are needed to clarify the role of these proteins as a marker of GVHD or as an index of mucosal inflammation

Experimentally-constrained biophysical models of tonic and burst firing modes in thalamocortical neurons

Somatosensory thalamocortical (TC) neurons from the ventrobasal (VB) thalamus are central components in the flow of sensory information between the periphery and the cerebral cortex, and participate in the dynamic regulation of thalamocortical states including wakefulness and sleep. This property is reflected at the cellular level by the ability to generate action potentials in two distinct firing modes, called tonic firing and low-threshold bursting. Although the general properties of TC neurons are known, we still lack a detailed characterization of their morphological and electrical properties in the VB thalamus. The aim of this study was to build biophysically-detailed models of VB TC neurons explicitly constrained with experimental data from rats. We recorded the electrical activity of VB neurons (N = 49) and reconstructed morphologies in 3D (N = 50) by applying standardized protocols. After identifying distinct electrical types, we used a multi-objective optimization to fit single neuron electrical models (e-models), which yielded multiple solutions consistent with the experimental data. The models were tested for generalization using electrical stimuli and neuron morphologies not used during fitting. A local sensitivity analysis revealed that the e-models are robust to small parameter changes and that all the parameters were constrained by one or more features. The e-models, when tested in combination with different morphologies, showed that the electrical behavior is substantially preserved when changing dendritic structure and that the e-models were not overfit to a specific morphology. The models and their analysis show that automatic parameter search can be applied to capture complex firing behavior, such as co-existence of tonic firing and low-threshold bursting over a wide range of parameter sets and in combination with different neuron morphologies

Computer-aided cognitive training in patients with neurocognitive vascular impairment: effects on cognition, depression and behavior

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ANGPT2 and NOS3 Polymorphisms and Clinical Outcome in Advanced Hepatocellular Carcinoma Patients Receiving Sorafenib

Sorafenib represents the standard of care for advanced hepatocellular carcinoma (HCC), even though a large number of patients have reported limited ecacy. The aim of the present study was to evaluate the prognostic value of single-nucleotide polymorphisms on angiopoietin-2 (ANGPT2) and endothelial-derived nitric oxide synthase (NOS3) genes in 135 patients with advanced HCC receiving sorafenib. Eight ANGPT2 polymorphisms were analyzed by direct sequencing in relation to overall survival (OS) and progression-free survival (PFS). In univariate analysis, ANGPT2rs55633437 and NOS3 rs2070744 were associated with OS and PFS. In particular, patients with ANGPT2rs55633437 TT/GT genotypes had significantly lower median OS (4.66 vs. 15.5 months, hazard ratio (HR) 4.86, 95% CI 2.73\u20138.67, p < 0.001) and PFS (1.58 vs. 6.27 months, HR 4.79, 95% CI 2.73\u20138.35, p < 0.001) than those homozygous for the G allele. Moreover, patients with NOS3 rs2070744 TC/CC genotypes had significantly higher median OS (15.6 vs. 9.1 months, HR 0.65, 95% CI 0.44\u20130.97; p = 0.036) and PFS (7.03 vs. 3.5 months, HR 0.43, 95% CI 0.30\u20130.63; p < 0.001) than patients homozygous for the T allele. Multivariate analysis confirmed these polymorphisms as independent prognostic factors. Our results suggest that ANGPT2rs55633437 and NOS3 rs2070744 polymorphisms could identify a subset of HCC patients more resistant to sorafenib

Quasiperiodic rhythms of the inferior olive

Inferior olivary activity causes both short-term and long-term changes in cerebellar output underlying motor performance and motor learning. Many of its neurons engage in coherent subthreshold oscillations and are extensively coupled via gap junctions. Studies in reduced preparations suggest that these properties promote rhythmic, synchronized output. However, the interaction of these properties with torrential synaptic inputs in awake behaving animals is not well understood. Here we combine electrophysiological recordings in awake mice with a realistic tissue-scale computational model of the inferior olive to study the relative impact of intrinsic and extrinsic mechanisms governing its activity. Our data and model suggest that if subthreshold oscillations are present in the awake state, the period of these oscillations will be transient and variable. Accordingly, by using different temporal patterns of sensory stimulation, we found that complex spike rhythmicity was readily evoked but limited to short intervals of no more than a few hundred milliseconds and that the periodicity of this rhythmic activity was not fixed but dynamically related to the synaptic input to the inferior olive as well as to motor output. In contrast, in the long-term, the average olivary spiking activity was not affected by the strength and duration of the sensory stimulation, while the level of gap junctional coupling determined the stiffness of the rhythmic activity i

A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience

The curation of neuroscience entities is crucial to ongoing efforts in neuroinformatics and computational neuroscience, such as those being deployed in the context of continuing large-scale brain modelling projects. However, manually sifting through thousands of articles for new information about modelled entities is a painstaking and low-reward task. Text mining can be used to help a curator extract relevant information from this literature in a systematic way. We propose the application of text mining methods for the neuroscience literature. Specifically, two computational neuroscientists annotated a corpus of entities pertinent to neuroscience using active learning techniques to enable swift, targeted annotation. We then trained machine learning models to recognise the entities that have been identified. The entities covered are Neuron Types, Brain Regions, Experimental Values, Units, Ion Currents, Channels, and Conductances and Model organisms. We tested a traditional rule-based approach, a conditional random field and a model using deep learning named entity recognition, finding that the deep learning model was superior. Our final results show that we can detect a range of named entities of interest to the neuroscientist with a macro average precision, recall and F1 score of 0.866, 0.817 and 0.837 respectively. The contributions of this work are as follows: 1) We provide a set of Named Entity Recognition (NER) tools that are capable of detecting neuroscience entities with performance above or similar to prior work. 2) We propose a methodology for training NER tools for neuroscience that requires very little training data to get strong performance. This can be adapted for any sub-domain within neuroscience. 3) We provide a small corpus with annotations for multiple entity types, as well as annotation guidelines to help others reproduce our experiments

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)