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Reducing neuronal size results in less cell membrane and therefore lower input conductance. Smaller neurons are thus more excitable as seen in their voltage responses to current injections in the soma. However, the impact of a neuron’s size and shape on its voltage responses to synaptic activation in dendrites is much less understood. Here we use analytical cable theory to predict voltage responses to distributed synaptic inputs and show that these are entirely independent of dendritic length. For a given synaptic density, a neuron’s response depends only on the average dendritic diameter and its intrinsic conductivity. These results remain true for the entire range of possible dendritic morphologies irrespective of any particular arborisation complexity. Also, spiking models result in morphology invariant numbers of action potentials that encode the percentage of active synapses. Interestingly, in contrast to spike rate, spike times do depend on dendrite morphology. In summary, a neuron’s excitability in response to synaptic inputs is not affected by total dendrite length. It rather provides a homeostatic input-output relation that specialised synapse distributions, local non-linearities in the dendrites and synaptic plasticity can modulate. Our work reveals a new fundamental principle of dendritic constancy that has consequences for the overall computation in neural circuits.
Excess neuronal branching allows for innervation of specific dendritic compartments in cortex
(2019)
The connectivity of cortical microcircuits is a major determinant of brain function; defining how activity propagates between different cell types is key to scaling our understanding of individual neuronal behaviour to encompass functional networks. Furthermore, the integration of synaptic currents within a dendrite depends on the spatial organisation of inputs, both excitatory and inhibitory. We identify a simple equation to estimate the number of potential anatomical contacts between neurons; finding a linear increase in potential connectivity with cable length and maximum spine length, and a decrease with overlapping volume. This enables us to predict the mean number of candidate synapses for reconstructed cells, including those realistically arranged. We identify an excess of putative connections in cortical data, with densities of neurite higher than is necessary to reliably ensure the possible implementation of any given connection. We show that potential contacts allow the particular implementation of connectivity at a subcellular level.
Inspired by the physiology of neuronal systems in the brain, artificial neural networks have become an invaluable tool for machine learning applications. However, their biological realism and theoretical tractability are limited, resulting in poorly understood parameters. We have recently shown that biological neuronal firing rates in response to distributed inputs are largely independent of size, meaning that neurons are typically responsive to the proportion, not the absolute number, of their inputs that are active. Here we introduce such a normalisation, where the strength of a neuron’s afferents is divided by their number, to various sparsely-connected artificial networks. The learning performance is dramatically increased, providing an improvement over other widely-used normalisations in sparse networks. The resulting machine learning tools are universally applicable and biologically inspired, rendering them better understood and more stable in our tests.
Memory Concerns, Memory Performance and Risk of Dementia in Patients with Mild Cognitive Impairment
(2014)
Background: Concerns about worsening memory (“memory concerns”; MC) and impairment in memory performance are both predictors of Alzheimer's dementia (AD). The relationship of both in dementia prediction at the pre-dementia disease stage, however, is not well explored. Refined understanding of the contribution of both MC and memory performance in dementia prediction is crucial for defining at-risk populations. We examined the risk of incident AD by MC and memory performance in patients with mild cognitive impairment (MCI).
Methods: We analyzed data of 417 MCI patients from a longitudinal multicenter observational study. Patients were classified based on presence (n = 305) vs. absence (n = 112) of MC. Risk of incident AD was estimated with Cox Proportional-Hazards regression models.
Results: Risk of incident AD was increased by MC (HR = 2.55, 95%CI: 1.33–4.89), lower memory performance (HR = 0.63, 95%CI: 0.56–0.71) and ApoE4-genotype (HR = 1.89, 95%CI: 1.18–3.02). An interaction effect between MC and memory performance was observed. The predictive power of MC was greatest for patients with very mild memory impairment and decreased with increasing memory impairment.
Conclusions: Our data suggest that the power of MC as a predictor of future dementia at the MCI stage varies with the patients' level of cognitive impairment. While MC are predictive at early stage MCI, their predictive value at more advanced stages of MCI is reduced. This suggests that loss of insight related to AD may occur at the late stage of MCI.
Dieser Bericht stellt die wesentlichen Ergebnisse der sozialwissenschaftlichen und ökologischen Begleitforschung in der Modellregion Elektromobilität Rhein-Main (SÖB) dar. Dabei wird zunächst das Projektumfeld vorgestellt, indem auf die Rahmenbedingungen des Förderprogramms sowie weitere Programme und Projekte im Bereich Elektromobilität eingegangen wird. Im zweiten Kapitel wird das Projektkonsortium und dessen Einbettung in die Modellregion Rhein-Main erläutert, sowie die Verknüpfung mit der überregionalen Begleitforschung der Nationalen Organisation Wasser- und Brennstoffzellentechnologie (NOW). Im Kapitel 3 wird das Forschungsdesign der SÖB skizziert. Dazu werden einige Erkenntnisse aus der ersten Förderperiode beleuchtet, die für die Forschungsziele der aktuellen Förderperiode ausschlaggebend waren. Des Weiteren erfolgt eine Ausführung der methodischen Vorgehensweisen der Projektpartner. Das darauf folgende Kapitel 4 stellt die wesentlichen Ergebnisse des Projekts dar. Dabei wurde bewusst versucht, die verschie¬denen Erkenntnisse der einzelnen Partner thematisch miteinander zu verknüpfen. Aus den Ergeb¬nissen wurden Handlungsempfehlungen für verschiedene Bereiche und Akteure generiert, die in Kapitel 5 einfließen. Abschließend rundet ein Fazit mit zusammenfassenden Erkenntnissen den Bericht ab.
A new global synthesis and biomization of long (> 40 kyr) pollen-data records is presented, and used with simulations from the HadCM3 and FAMOUS climate models to analyse the dynamics of the global terrestrial biosphere and carbon storage over the last glacial–interglacial cycle. Global modelled (BIOME4) biome distributions over time generally agree well with those inferred from pollen data. The two climate models show good agreement in global net primary productivity (NPP). NPP is strongly influenced by atmospheric carbon dioxide (CO2) concentrations through CO2 fertilization. The combined effects of modelled changes in vegetation and (via a simple model) soil carbon result in a global terrestrial carbon storage at the Last Glacial Maximum that is 210–470 Pg C less than in pre-industrial time. Without the contribution from exposed glacial continental shelves the reduction would be larger, 330–960 Pg C. Other intervals of low terrestrial carbon storage include stadial intervals at 108 and 85 kaBP, and between 60 and 65 kaBP during Marine Isotope Stage 4. Terrestrial carbon storage, determined by the balance of global NPP and decomposition, influences the stable carbon isotope composition (δ 13C) of seawater because terrestrial organic carbon is depleted in 13C. Using a simple carbon-isotope mass balance equation we find agreement in trends between modelled ocean δ 13C based on modelled land carbon storage, and palaeo-archives of ocean δ 13C, confirming that terrestrial carbon storage variations may be important drivers of ocean δ 13 C changes.
A new global synthesis and biomization of long (> 40 kyr) pollen-data records is presented and used with simulations from the HadCM3 and FAMOUS climate models and the BIOME4 vegetation model to analyse the dynamics of the global terrestrial biosphere and carbon storage over the last glacial–interglacial cycle. Simulated biome distributions using BIOME4 driven by HadCM3 and FAMOUS at the global scale over time generally agree well with those inferred from pollen data. Global average areas of grassland and dry shrubland, desert, and tundra biomes show large-scale increases during the Last Glacial Maximum, between ca. 64 and 74 ka BP and cool substages of Marine Isotope Stage 5, at the expense of the tropical forest, warm-temperate forest, and temperate forest biomes. These changes are reflected in BIOME4 simulations of global net primary productivity, showing good agreement between the two models. Such changes are likely to affect terrestrial carbon storage, which in turn influences the stable carbon isotopic composition of seawater as terrestrial carbon is depleted in 13C.
S1P and its receptors have been reported to play important roles in the development of renal fibrosis. Although S1P5 has barely been investigated so far, there are indications that it can influence inflammatory and fibrotic processes. Here, we report the role of S1P5 in renal inflammation and fibrosis. Male S1P5 knockout mice and wild-type mice on a C57BL/6J background were fed with an adenine-rich diet for 7 days or 14 days to induce tubulointerstitial fibrosis. The kidneys of untreated mice served as respective controls. Kidney damage, fibrosis, and inflammation in kidney tissues were analyzed by real-time PCR, Western blot, and histological staining. Renal function was assessed by plasma creatinine ELISA. The S1P5 knockout mice had better renal function and showed less kidney damage, less proinflammatory cytokine release, and less fibrosis after 7 days and 14 days of an adenine-rich diet compared to wild-type mice. S1P5 knockout ameliorates tubular damage and tubulointerstitial fibrosis in a model of adenine-induced nephropathy in mice. Thus, targeting S1P5 might be a promising goal for the pharmacological treatment of kidney diseases.
Shrew-1 wurde bei der Suche invasivitätsassoziierter Gene mittels eines DDRT-PCR-Ansatzes aus invasiven Zellen isoliert. Wie computergestützte Analysen der Sequenz ergaben, wies das bis dahin unbekannte Protein keinerlei Ähnlichkeiten mit bereits bekannten Proteinen auf und homologe Proteine wurden bisher nur in Vertebraten gefunden. Expressionsanalysen mit einem GFP-markierten shrew-1 zeigten, dass es an der basolateralen Plasmamembran lokalisiert, wo es mit dem E-Cadherin vermittelten Adhäsions-Komplex kolokalisiert. Eine Integration in diesen Komplex geschieht höchstwahrscheinlich durch direkte Interaktion mit β-Catenin. Ein weiteres Molekül das als potenzieller Interaktionspartner von shrew-1 identifiziert wurde und das in der Literatur oft als Tumorsuppressor diskutiert wird, ist Caveolin-1. Ferner konnten Überexpressionexperimente bereits zeigen, dass shrew-1 die Invasivität von HT1080-Zellen erhöhen kann. Das Ziel dieser Arbeit war es, zum einen mit Hilfe des Hefe-Split-Ubiquitin-Systems eine Interaktion von shrew-1 und Caveolin-1 zu bestätigen und zum anderen neue Interaktionspartner zu identifizieren, die helfen könnten, die Rolle von shrew-1 in invasiven Vorgängen zu erklären. Um eine mögliche Verbindung von shrew-1 und einem neuen Interaktionspartner in Bezug auf die Zellinvasivität zu untersuchen, sollten sowohl shrew-1 als auch der potenzielle Interaktionspartner mittels RNAi ausgeschaltet werden. Mit Hilfe des Split-Ubiquitin-Systems war es möglich, die Interaktion zwischen shrew-1 und caveolin-1 zu bestätigen und zu zeigen, dass diese durch die zytoplasmatische Domäne von shrew-1 vermittelt wird. Weiterhin konnte CD147 als neuer Interaktionpartner identifiziert werden. Eine Interaktion beider Proteine konnte ferner mit Hilfe des Bimolekularen-Fluoreszens-Komplementations-Systems (BIFC), des Fluoreszens-Resonanz-Energie-Transfers (FRET) und Coimmunoprezipitationen bestätigt werden. Die Interaktion von shrew-1 und CD147 scheint allerdings abhängig vom zellulären Kontext zu sein, wie die FRET-Analysen vermuten lassen. So konnte nämlich mit diesen Analysen eine starke Interaktion in MCF7-Zellen gezeigt werden, wohingegen die Interaktion in MDCK-Zellen schwächer war. Einer der auffälligsten Unterschiede dieser beiden Zelllinien im Bezug auf diese Interaktion könnte sein, dass MCF7-Zellen im Gegensatz zu MDCK-Zellen kein Caveolin-1 exprimieren. Caveolin-1 konnte seinerseits als Interaktionspartner von shrew-1 mit Hilfe des Hefe-Split-Ubiquitin-Systems bestätigt werden und andererseits wurde von einer anderen Arbeitsgruppe eine Interaktion von CD147 mit Caveolin-1 publiziert. Um dies näher zu untersuchen, wurde Caveolin-1 in MCF7-Zellen exprimiert und die FRET-Analysen in diesen wiederholt. Wie vermutet kam es zu einer Reduktion der Interaktion in Caveolin-1 exprimierenden MCF7-Zellen. CD147 ist neben vielen anderen Funktionen auch maßgeblich an der Regulation von Matrix-Metalloproteinasen beteiligt und kann somit die Invasivität von Zellen beeinflussen. Um einen Einfluß von shrew-1 und CD147 auf die Invasivität zu untersuchen, wurden beide Proteine mittels RNAi in HeLa-Zellen ausgeschaltet. Nachdem ein negativer Einfluss dieses Ansatzes auf das Proliferationsverhalten der Zellen ausgeschlossen werden konnte, wurde ein möglicher Effekt auf die Invasivität der Zellen untersucht. Durch die Analyse in Matrigel-Invasionsassays konnte gezeigt werden, dass das unabhängige Ausschalten beider Proteine die Invasivität der Zellen auf 35-55% im Vergleich zu Kontrollzellen reduziert. Die Ergebnisse dieser Arbeit untermauern die Annahme, dass shrew-1 eine Rolle bei invasiven Vorgängen spielt und weisen darauf hin, dass dies möglicherweise durch eine Interaktion mit CD147 geschieht. Die Interaktion mit CD147 und damit eine mögliche Funktion von shrew-1 bei invasiven Vorgängen scheinen dabei abhängig vom zellulären Kontext zu sein.
Background and Aims: Monocyte chemotactic protein-1 (MCP-1) is a potent chemoattractant for monocytes. It is involved in pathogenesis of several inflammatory diseases. Hepatic MCP-1 is a readout of macrophage activation. While inflammation is a major driver of liver disease progression, the origin and role of circulating MCP-1 as a biomarker remains unclear.
Methods: Hepatic CC-chemokine ligand 2 (CCL2) expression and F4/80 staining for Kupffer cells were measured and correlated in a mouse model of chronic liver disease (inhalative CCl4 for 7 weeks). Next, hepatic RNA levels of CCL2 were measured in explanted livers of 39 patients after transplantation and correlated with severity of disease. Changes in MCP-1 were further evaluated in a rat model of experimental cirrhosis and acute-on-chronic liver failure (ACLF). Finally, we analyzed portal and hepatic vein levels of MCP-1 in patients receiving transjugular intrahepatic portosystemic shunt insertion for complications of portal hypertension.
Results: In this mouse model of fibrotic hepatitis, hepatic expression of CCL2 (P = 0.009) and the amount of F4/80 positive cells in the liver (P < 0.001) significantly increased after induction of hepatitis by CCl4 compared to control animals. Moreover, strong correlation of hepatic CCL2 expression and F4/80 positive cells were seen (P = 0.023). Furthermore, in human liver explants, hepatic transcription levels of CCL2 correlated with the MELD score of the patients, and thus disease severity (P = 0.007). The experimental model of ACLF in rats revealed significantly higher levels of MCP-1 plasma (P = 0.028) and correlation of hepatic CCL2 expression (R = 0.69, P = 0.003). Particularly, plasma MCP-1 levels did not correlate with peripheral blood monocyte CCL2 expression. Finally, higher levels of MCP-1 were observed in the hepatic compared to the portal vein (P = 0.01) in patients receiving TIPS. Similarly, a positive correlation of MCP-1 with Child-Pugh score was observed (P = 0.018). Further, in the presence of ACLF, portal and hepatic vein levels of MCP-1 were significantly higher compared to patients without ACLF (both P = 0.039).
Conclusion: Circulating levels of MCP-1 mainly derive from the injured liver and are associated with severity of liver disease. Therefore, liver macrophages contribute significantly to disease progression. Circulating MCP-1 may reflect the extent of hepatic macrophage activation.