Pattern theorems, ratio limit theorems and Gumbel maximal clusters for random fields

We study occurrences of patterns on clusters of size n in random fields on Z^d. We prove that for a given pattern, there is a constant a>0 such that the probability that this pattern occurs at most an times on a cluster of size n is exponentially small. Moreover, for random fields obeying a certain Markov property, we show that the ratio between the numbers of occurrences of two distinct patterns on a cluster is concentrated around a constant value. This leads to an elegant and simple proof of the ratio limit theorem for these random fields, which states that the ratio of the probabilities that the cluster of the origin has sizes n+1 and n converges as n tends to infinity. Implications for the maximal cluster in a finite box are discussed.Comment: 23 pages, 2 figure

HIF prolyl hydroxylase 2/3 deletion disrupts astrocytic integrity and exacerbates neuroinflammation

Astrocytes constitute the parenchymal border of the blood-brain barrier (BBB), modulate the exchange of soluble and cellular elements, and are essential for neuronal metabolic support. Thus, astrocytes critically influence neuronal network integrity. In hypoxia, astrocytes upregulate a transcriptional program that has been shown to boost neuroprotection in several models of neurological diseases. We investigated transgenic mice with astrocyte-specific activation of the hypoxia-response program by deleting the oxygen sensors, HIF prolyl-hydroxylase domains 2 and 3 (Phd2/3). We induced astrocytic Phd2/3 deletion after onset of clinical signs in experimental autoimmune encephalomyelitis (EAE) that led to an exacerbation of the disease mediated by massive immune cell infiltration. We found that Phd2/3-ko astrocytes, though expressing a neuroprotective signature, exhibited a gradual loss of gap-junctional Connexin-43 (Cx43), which was induced by vascular endothelial growth factor-alpha (Vegf-a) expression. These results provide mechanistic insights into astrocyte biology, their critical role in hypoxic states, and in chronic inflammatory CNS diseases

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Modelling of the near-field of metallic nanoparticle gratings: localized surface plasmon resonance and SERS applications

1 - ArticleWe numerically study the influence of the shape of gold nanostructures on the spectral position of their localized surface plasmon resonance and on Surface Enhanced Raman Scattering efficiency. Calculations are performed using a Finite-Difference Time-Domain (FDTD) method, whose accuracy for dispersive media is enhanced through the use of a Drude-Lorentz model. The relevance of this method is then pointed out by comparing the calculations with experimental data for both the plasmon resonance and the Raman signal enhancement. The influence of a thin layer of water is also investigated

Aggregation-induced changes in the chemical exchange saturation transfer (CEST) signals of proteins

Chemical exchange saturation transfer (CEST) is an MRI technique that allows mapping of biomolecules (small metabolites, proteins) with nearly the sensitivity of conventional water proton MRI. In living organisms, several tissue-specific CEST effects have been observed and successfully applied to diagnostic imaging. In these studies, particularly the signals of proteins showed a distinct correlation with pathological changes. However, as CEST effects depend on various properties that determine and affect the chemical exchange processes, the origins of the observed signal changes remain to be understood. In this study, protein aggregation was identified as an additional process that is encoded in the CEST signals of proteins. Investigation of distinct proteins that are involved in pathological disorders, namely amyloid beta and huntingtin, revealed a significant decrease of all protein CEST signals upon controlled aggregation. This finding is of particular interest with regard to diagnostic imaging of patients with neurodegenerative diseases that involve amyloidogenesis, such as Alzheimer's or Huntington's disease. To investigate whether the observed CEST signal decrease also occurs in heterogeneous mixtures of aggregated cellular proteins, and thus prospectively in tissue, heat-shocked yeast cell lysates were employed. Additionally, investigation of different cell compartments verified the assignment of the protein CEST signals to the soluble part of the proteome. The results of in vitro experiments demonstrate that aggregation affects the CEST signals of proteins. This observation can enable hypotheses for CEST imaging as a non-invasive diagnostic tool for monitoring pathological alterations of the proteome in vivo