Global Strong Solutions for a Class of Heterogeneous Catalysis Models

We consider a mathematical model for heterogeneous catalysis in a finite three-dimensional pore of cylinder-like geometry, with the lateral walls acting as a catalytic surface. The system under consideration consists of a diffusion-advection system inside the bulk phase and a reaction-diffusion-sorption system modeling the processes on the catalytic wall and the exchange between bulk and surface. We assume Fickian diffusion with constant coefficients, sorption kinetics with linear growth bound and a network of chemical reactions which possesses a certain triangular structure. Our main result gives sufficient conditions for the existence of a unique global strong $L^2$-solution to this model, thereby extending by now classical results on reaction-diffusion systems to the more complicated case of heterogeneous catalysis.Comment: 30 page

Documenting Bronze Age Akrotiri on Thera using laser scanning, image-based modelling and geophysical prospection

The excavated architecture of the exceptional prehistoric site of Akrotiri on the Greek island of Thera/Santorini is endangered by gradual decay, damage due to accidents, and seismic shocks, being located on an active volcano in an earthquake-prone area. Therefore, in 2013 and 2014 a digital documentation project has been conducted with support of the National Geographic Society in order to generate a detailed digital model of Akrotiri’s architecture using terrestrial laser scanning and image-based modeling. Additionally, non-invasive geophysical prospection has been tested in order to investigate its potential to explore and map yet buried archaeological remains. This article describes the project and the generated results

Interaction of differently functionalized fluorescent silica nanoparticles with neural stem- and tissue-type cells.

Abstract Engineered amorphous silica nanoparticles (SiO2 NPs), due to simple and low cost production, are increasingly used in commercial products and produced on an industrial scale. Despite the potential benefits, there is a concern that exposure to certain types of SiO2 NPs may lead to adverse health effects. As some NPs can cross the blood--brain barrier and may, in addition, reach the central nervous system through the nasal epithelium, this study addresses the responses of different neural tissue-type cells including neural stem cells, neurons, astrocytes and microglia cells to increasing doses of 50 nm fluorescent core/shell SiO2 NPs with different [-NH2, -SH and polyvinylpyrrolidone (PVP)] surface chemistry. The SiO2 NPs are characterized using a variety of physicochemical methods. Assays of cytotoxicity and cellular metabolism indicates that SiO2 NPs cause cell death only at high particle doses, except PVP-coated SiO2 NPs which do not harm cells even at very high concentrations. All SiO2 NPs, except those coated with PVP, form large agglomerates in physiological solutions and adsorb a variety of proteins. Except PVP-NPs, all SiO2 NPs adhere strongly to cell surfaces, but internalization differs depending on neural cell type. Neural stem cells and astrocytes internalize plain SiO2, SiO2-NH2 and SiO2-SH NPs, while neurons do not take up any NPs. The data indicates that the PVP coat, by lowering the particle-biomolecular component interactions, reduces the biological effects of SiO2 NPs on the investigated neural cells

Automatic identification of relevant chemical compounds from patents

In commercial research and development projects, public disclosure of new chemical compounds often takes place in patents. Only a small proportion of these compounds are published in journals, usually a few years after the patent. Patent authorities make available the patents but do not provide systematic continuous chemical annotations. Content databases such as Elsevier’s Reaxys provide such services mostly based on manual excerptions, which are time-consuming and costly. Automatic text-mining approaches help overcome some of the limitations of the manual process. Different text-mining approaches exist to extract chemical entities from patents. The majority of them have been developed using sub-sections of patent documents and focus on mentions of compounds. Less attention has been given to relevancy of a compound in a patent. Relevancy of a compound to a patent is based on the patent’s context. A relevant compound plays a major role within a patent. Identification of relevant compounds reduces the size of the extracted data and improves the usefulness of patent resources (e.g. supports identifying the main compounds). Annotators of databases like Reaxys only annotate relevant compounds. In this study, we design an automated system that extracts chemical entities from patents and classifies their relevance. The goldstandard set contained 18 789 chemical entity annotations. Of these, 10% were relevant compounds, 88% were irrelevant and 2% were equivocal. Our compound recognition system was based on proprietary tools. The performance (F-score) of the system on compound recognition was 84% on the development set and 86% on the test set. The relevancy classification system had an F-score of 86% on the development set and 82% on the test set. Our system can extract chemical compounds from patents and classify their relevance with high performance. This enables the extension of the Reaxys database by means of automation

Adjunctive Dexamethasone Affects the Expression of Genes Related to Inflammation, Neurogenesis and Apoptosis in Infant Rat Pneumococcal Meningitis

Streptococcus pneumoniae is the most common pathogen causing non-epidemic bacterial meningitis worldwide. The immune response and inflammatory processes contribute to the pathophysiology. Hence, the anti-inflammatory dexamethasone is advocated as adjuvant treatment although its clinical efficacy remains a question at issue. In experimental models of pneumococcal meningitis, dexamethasone increased neuronal damage in the dentate gyrus. Here, we investigated expressional changes in the hippocampus and cortex at 72 h after infection when dexamethasone was given to infant rats with pneumococcal meningitis. Nursing Wistar rats were intracisternally infected with Streptococcus pneumoniae to induce experimental meningitis or were sham-infected with pyrogen-free saline. Besides antibiotics, animals were either treated with dexamethasone or saline. Expressional changes were assessed by the use of GeneChip® Rat Exon 1.0 ST Arrays and quantitative real-time PCR. Protein levels of brain-derived neurotrophic factor, cytokines and chemokines were evaluated in immunoassays using Luminex xMAP® technology. In infected animals, 213 and 264 genes were significantly regulated by dexamethasone in the hippocampus and cortex respectively. Separately for the cortex and the hippocampus, Gene Ontology analysis identified clusters of biological processes which were assigned to the predefined categories “inflammation”, “growth”, “apoptosis” and others. Dexamethasone affected the expression of genes and protein levels of chemokines reflecting diminished activation of microglia. Dexamethasone-induced changes of genes related to apoptosis suggest the downregulation of the Akt-survival pathway and the induction of caspase-independent apoptosis. Signalling of pro-neurogenic pathways such as transforming growth factor pathway was reduced by dexamethasone resulting in a lack of pro-survival triggers. The anti-inflammatory properties of dexamethasone were observed on gene and protein level in experimental pneumococcal meningitis. Further dexamethasone-induced expressional changes reflect an increase of pro-apoptotic signals and a decrease of pro-neurogenic processes. The findings may help to identify potential mechanisms leading to apoptosis by dexamethasone in experimental pneumococcal meningitis

Functional imaging of the human medial temporal lobe

A neuroscientist's guide to fMRI pulse sequence optimizatio

Perception and the cognitive map - Deriving a stable world from visual inputs

Norsk sammendrag Hjernen skaper stabile og sammenhengende representasjoner av verden fra omskiftelige perseptuelle input. Denne prosessen involverer et omfattende nettverk i hjernen, fra de tidlige synssentrene på lavt nivå til hukommelsessentrene i den mediale tinninglapp på høyere nivå. Langs denne banen gjennomgår informasjon fra visuelle input en rekke endringer før den ender opp som del av det kognitive kartet, som utgjør en ikke-sensorisk representasjon av omgivelsene som understøtter hukommelse og atferd. I mitt doktarbeid undersøkte jeg det nevrale grunnlaget for spatial persepsjon og kognitive kart i menneskehjernen, samt hvordan det kan knyttes til hukommelse og atferd. Prosjektene som presenteres, tilnærmet seg problemstillingene fra flere vinkler ved å fokusere på ulike komputeringstrinn langs den hierarkiske rekkefølgen av kortikale områder. Vi undersøkte først hvordan synssystemet stabiliserer visuell persepsjon under bevegelse ved å observere menneskelig hjerneaktivitet ved bruk av magnetresonanstomografi (fMRI) under en visuell sporingsoppgave (VSO). Da oppdaget vi at et stort nettverk av områder kodet for visuell bevegelse uavhengig av selvbevegelse, inkludert i de tidlige synssentrene på laveste nivå. Denne mekanismen forankrer visuell persepsjon eksternt i ens omgivelser. Deretter undersøkte vi hvordan høyere kognitive områder representerer ens synlige omgivelser. Fremdeles ved bruk av fMRI og en VSO, observerte vi gittercellelignende aktivitet i entorhinal cortex, et hjerneområde vi vet kartlegger omgivelsene ved navigering. Vi fant en fMRI-signatur som lignet på denne aktiviteten som samsvarte med øyebevegelsene alene. Dette utgjør det første bevis på at entorhinal cortex også koder for et ikke-sensorisk kart over synsfeltet i mennesket. Det siste prosjektet samførte sensoriske og ikke-sensoriske spatiale representasjoner og fokuserte eksplisitt på atferden de understøtter. Jeg utviklet et toppmoderne prediktivt modelleringsrammeverk til studier av naturtro atferd ved bruk av virtuell virkelighet og ultrahøyfelts fMRI i mennesker. Undersøkelser av retningsstuning i regioner for navigasjon og visuell sceneprosessering viste at omgivelsesprosessering på tvers av nettverket er avhengig av korrekt innkoding av omgivelsene. Samlet sett opplyser dette verket om hvordan menneskehjernen integrerer perseptuelle opplevelser i kognitive kart over omgivelsene. Det demonstrerer sterk gjengjeldelse mellom visuell koding og høyere kognitiv koding, samt belyser videre at det spatiale kartleggingssystemet understøtter domenegenerelle funksjoner som understøtter atferd

Behavior-dependent directional tuning in the human visual-navigation network

The brain derives cognitive maps from sensory experience that guide memory formation and behavior. Despite extensive efforts, it still remains unclear how the underlying population activity unfolds during spatial navigation and how it relates to memory performance. To examine these processes, we combined 7T-fMRI with a kernel-based encoding model of virtual navigation to map world-centered directional tuning across the human cortex. First, we present an in-depth analysis of directional tuning in visual, retrosplenial, parahippocampal and medial temporal cortices. Second, we show that tuning strength, width and topology of this directional code during memory-guided navigation depend on successful encoding of the environment. Finally, we show that participants’ locomotory state influences this tuning in sensory and mnemonic regions such as the hippocampus. We demonstrate a direct link between neural population tuning and human cognition, where high-level memory processing interacts with network-wide visuospatial coding in the service of behavior

DeepMReye

Source data & exemplary data for training and testing DeepMRey