Frequency Dependence of Signal Power and Spatial Reach of the Local Field Potential

Despite its century-old use, the interpretation of local field potentials (LFPs), the low-frequency part of electrical signals recorded in the brain, is still debated. In cortex the LFP appears to mainly stem from transmembrane neuronal currents following synaptic input, and obvious questions regarding the ‘locality’ of the LFP are: What is the size of the signal-generating region, i.e., the spatial reach, around a recording contact? How far does the LFP signal extend outside a synaptically activated neuronal population? And how do the answers depend on the temporal frequency of the LFP signal? Experimental inquiries have given conflicting results, and we here pursue a modeling approach based on a well-established biophysical forward-modeling scheme incorporating detailed reconstructed neuronal morphologies in precise calculations of population LFPs including thousands of neurons. The two key factors determining the frequency dependence of LFP are the spatial decay of the single-neuron LFP contribution and the conversion of synaptic input correlations into correlations between single-neuron LFP contributions. Both factors are seen to give low-pass filtering of the LFP signal power. For uncorrelated input only the first factor is relevant, and here a modest reduction (<50%) in the spatial reach is observed for higher frequencies (>100 Hz) compared to the near-DC () value of about . Much larger frequency-dependent effects are seen when populations of pyramidal neurons receive correlated and spatially asymmetric inputs: the low-frequency () LFP power can here be an order of magnitude or more larger than at 60 Hz. Moreover, the low-frequency LFP components have larger spatial reach and extend further outside the active population than high-frequency components. Further, the spatial LFP profiles for such populations typically span the full vertical extent of the dendrites of neurons in the population. Our numerical findings are backed up by an intuitive simplified model for the generation of population LFP.     

Phagocytosis Escape by a Staphylococcus aureus Protein That Connects Complement and Coagulation Proteins at the Bacterial Surface

Upon contact with human plasma, bacteria are rapidly recognized by the complement system that labels their surface for uptake and clearance by phagocytic cells. Staphylococcus aureus secretes the 16 kD Extracellular fibrinogen binding protein (Efb) that binds two different plasma proteins using separate domains: the Efb N-terminus binds to fibrinogen, while the C-terminus binds complement C3. In this study, we show that Efb blocks phagocytosis of S. aureus by human neutrophils. In vitro, we demonstrate that Efb blocks phagocytosis in plasma and in human whole blood. Using a mouse peritonitis model we show that Efb effectively blocks phagocytosis in vivo, either as a purified protein or when produced endogenously by S. aureus. Mutational analysis revealed that Efb requires both its fibrinogen and complement binding residues for phagocytic escape. Using confocal and transmission electron microscopy we show that Efb attracts fibrinogen to the surface of complement-labeled S. aureus generating a ‘capsule’-like shield. This thick layer of fibrinogen shields both surface-bound C3b and antibodies from recognition by phagocytic receptors. This information is critical for future vaccination attempts, since opsonizing antibodies may not function in the presence of Efb. Altogether we discover that Efb from S. aureus uniquely escapes phagocytosis by forming a bridge between a complement and coagulation protein.     

Fungi Benefit from Two Decades of Increased Nutrient Availability in Tundra Heath Soil

If microbial degradation of carbon substrates in arctic soil is stimulated by climatic warming, this would be a significant positive feedback on global change. With data from a climate change experiment in Northern Sweden we show that warming and enhanced soil nutrient availability, which is a predicted long-term consequence of climatic warming and mimicked by fertilization, both increase soil microbial biomass. However, while fertilization increased the relative abundance of fungi, warming caused only a minimal shift in the microbial community composition based on the phospholipid fatty acid (PLFA) and neutral lipid fatty acid (NLFA) profiles. The function of the microbial community was also differently affected, as indicated by stable isotope probing of PLFA and NLFA. We demonstrate that two decades of fertilization have favored fungi relative to bacteria, and increased the turnover of complex organic compounds such as vanillin, while warming has had no such effects. Furthermore, the NLFA-to-PLFA ratio for ¹³C-incorporation from acetate increased in warmed plots but not in fertilized ones. Thus, fertilization cannot be used as a proxy for effects on warming in arctic tundra soils. Furthermore, the different functional responses suggest that the biomass increase found in both fertilized and warmed plots was mediated via different mechanisms.     

An Iterative Framework for EEG-based Image Search: Robust Retrieval with Weak Classifiers

We revisit the framework for brain-coupled image search, where the Electroencephalography (EEG) channel under rapid serial visual presentation protocol is used to detect user preferences. Extending previous works on the synergy between content-based image labeling and EEG-based brain-computer interface (BCI), we propose a different perspective on iterative coupling. Previously, the iterations were used to improve the set of EEG-based image labels before propagating them to the unseen images for the final retrieval. In our approach we accumulate the evidence of the true labels for each image in the database through iterations. This is done by propagating the EEG-based labels of the presented images at each iteration to the rest of images in the database. Our results demonstrate a continuous improvement of the labeling performance across iterations despite the moderate EEG-based labeling (AUC <75%). The overall analysis is done in terms of the single-trial EEG decoding performance and the image database reorganization quality. Furthermore, we discuss the EEG-based labeling performance with respect to a search task given the same image database.     

Intracellular Nucleic Acid Delivery by the Supercharged Dengue Virus Capsid Protein

Supercharged proteins are a recently identified class of proteins that have the ability to efficiently deliver functional macromolecules into mammalian cells. They were first developed as bioengineering products, but were later found in the human proteome. In this work, we show that this class of proteins with unusually high net positive charge is frequently found among viral structural proteins, more specifically among capsid proteins. In particular, the capsid proteins of viruses from the Flaviviridae family have all a very high net charge to molecular weight ratio (> +1.07/kDa), thus qualifying as supercharged proteins. This ubiquity raises the hypothesis that supercharged viral capsid proteins may have biological roles that arise from an intrinsic ability to penetrate cells. Dengue virus capsid protein was selected for a detailed experimental analysis. We showed that this protein is able to deliver functional nucleic acids into mammalian cells. The same result was obtained with two isolated domains of this protein, one of them being able to translocate lipid bilayers independently of endocytic routes. Nucleic acids such as siRNA and plasmids were delivered fully functional into cells. The results raise the possibility that the ability to penetrate cells is part of the native biological functions of some viral capsid proteins.     

Experimental Diabetes Induces Structural,Inflammatory and Vascular Changes of Achilles Tendons

This study aims to demonstrate how the state of chronic hyperglycemia from experimental Diabetes Mellitus can influence the homeostatic imbalance of tendons and, consequently, lead to the characteristics of tendinopathy. Twenty animals were randomly divided into two experimental groups: control group, consisting of healthy rats and diabetic group constituted by rats induced to Diabetes Mellitus I. After twenty-four days of the induction of Diabetes type I, the Achilles tendon were removed for morphological evaluation, cellularity, number and cross-sectional area of blood vessel, immunohistochemistry for Collagen type I, VEGF and NF-κB nuclear localization sequence (NLS) and nitrate and nitrite level. The Achilles tendon thickness (µm/100g) of diabetic animals was significantly increased and, similarly, an increase was observed in the density of fibrocytes and mast cells in the tendons of the diabetic group. The average number of blood vessels per field, in peritendinous tissue, was statistically higher in the diabetic group 3.39 (2.98) vessels/field when compared to the control group 0.89 (1.68) vessels/field p = 0.001 and in the intratendinous region, it was observed that blood vessels were extremely rare in the control group 0.035 (0.18) vessels/field and were often present in the tendons of the diabetic group 0.89 (0.99) vessels/field. The immunohistochemistry analysis identified higher density of type 1 collagen and increased expression of VEGF as well as increased immunostaining for NFκB p50 NLS in the nucleus in Achilles tendon of the diabetic group when compared to the control group. Higher levels of nitrite/nitrate were observed in the experimental group induced to diabetes. We conclude that experimental DM induces notable structural, inflammatory and vascular changes in the Achilles tendon which are compatible with the process of chronic tendinopathy.     

Models of the pharmacophoric pattern and affinity trend of methyl 2-(aminomethyl)-1-phenylcyclopropane-1-carboxylate derivatives as σ1 ligands

Sigma-1 (σ₁) affinities of methyl 2-(aminomethyl)-1-phenylcyclopropane-1-carboxylate (MAPCC) derivatives were modelled by the genetic algorithm with linear assignment of hypermolecular alignment of datasets (GALAHAD) and the comparative molecular field analysis (CoMFA)/comparative molecular similarity indices analysis (CoMSIA) methods. GALAHAD was used for deriving the 3D pharmacophore pattern that encompasses the most potent σ₁ ligands within this series. Five MAPCC derivatives with a high σ₁ affinity were used for deriving this model. The obtained model included a nitrogen atom, the hydrophobes and the hydrogen bond acceptor features; it was able to identify other potent σ₁ ligands. On the other hand, CoMFA and CoMSIA methods were used for deriving quantitative structure–activity relationship (QSAR) models. All QSAR models were trained with 17 compounds, after which they were evaluated for predictive ability with additional five compounds. The best QSAR model was obtained by using CoMSIA, including steric, electrostatic and hydrophobic fields, and had a good predictive quality according to both internal and external validation criteria. In general, the models described herein provide meaningful information relevant for the rational design of new σ₁ ligands.     

Collagen-binding Microbial Surface Components Recognizing Adhesive Matrix Molecule (MSCRAMM) of Gram-positive Bacteria Inhibit Complement Activation via the Classical Pathway

Members of a family of collagen-binding microbial surface components recognizing adhesive matrix molecules (MSCRAMMs) from Gram-positive bacteria are established virulence factors in several infectious diseases models. Here, we report that these adhesins also can bind C1q and act as inhibitors of the classical complement pathway. Molecular analyses of Cna from Staphylococcus aureus suggested that this prototype MSCRAMM bound to the collagenous domain of C1q and interfered with the interactions of C1r with C1q. As a result, C1r₂C1s₂ was displaced from C1q, and the C1 complex was deactivated. This novel function of the Cna-like MSCRAMMs represents a potential immune evasion strategy that could be used by numerous Gram-positive pathogens.     

Mechanical Resistance in Unstructured Proteins

Single-molecule pulling experiments on unstructured proteins linked to neurodegenerative diseases have measured rupture forces comparable to those for stable folded proteins. To investigate the structural mechanisms of this unexpected force resistance, we perform pulling simulations of the amyloid β-peptide (Aβ) and α-synuclein (αS), starting from simulated conformational ensembles for the free monomers. For both proteins, the simulations yield a set of rupture events that agree well with the experimental data. By analyzing the conformations occurring shortly before rupture in each event, we find that the mechanically resistant structures share a common architecture, with similarities to the folds adopted by Aβ and αS in amyloid fibrils. The disease-linked Arctic mutation of Aβ is found to increase the occurrence of highly force-resistant structures. Our study suggests that the high rupture forces observed in Aβ and αS pulling experiments are caused by structures that might have a key role in amyloid formation.