Tissue-specific expression of high-voltage-activated dihydropyridine-sensitive L-type calcium channels

The cloning of the cDNA for the α1 subunit of L-type calcium channels revealed that at least two genes (CaCh1 and CaCh2) exist which give rise to several splice variants. The expression of mRNA for these α1 subunits and the skeletal muscle α2/δ, β and γ subunits was studied in rabbit tissues and BC3H1 cells. Nucleic-acid-hybridization studies showed that the mRNA of all subunits are expressed in skeletal muscle, brain, heart and aorta. However, the α1-, β- and γ-specific transcripts had different sizes in these tissues. Smooth muscle and heart contain different splice variants of the CaCh2 gene. The α1, β and γ mRNA are expressed together in differentiated but not in proliferating BC3H1 cells. A probe specific for the skeletal muscle α2/δ subunit did not hybridize to poly(A)-rich RNA from BC3H1 cells. These results suggest that different splice variants of the genes for the α1, β and γ subunits exist in tissues containing L-type calcium channels, and that their expression is regulated in a coordinate manner

On the Lebesgue measure of Li-Yorke pairs for interval maps

We investigate the prevalence of Li-Yorke pairs for $C^2$ and $C^3$ multimodal maps $f$ with non-flat critical points. We show that every measurable scrambled set has zero Lebesgue measure and that all strongly wandering sets have zero Lebesgue measure, as does the set of pairs of asymptotic (but not asymptotically periodic) points. If $f$ is topologically mixing and has no Cantor attractor, then typical (w.r.t. two-dimensional Lebesgue measure) pairs are Li-Yorke; if additionally $f$ admits an absolutely continuous invariant probability measure (acip), then typical pairs have a dense orbit for $f \times f$. These results make use of so-called nice neighborhoods of the critical set of general multimodal maps, and hence uniformly expanding Markov induced maps, the existence of either is proved in this paper as well. For the setting where $f$ has a Cantor attractor, we present a trichotomy explaining when the set of Li-Yorke pairs and distal pairs have positive two-dimensional Lebesgue measure.Comment: 41 pages, 3 figure

Laplace Operators on Fractals and Related Functional Equations

We give an overview over the application of functional equations, namely the classical Poincar\'e and renewal equations, to the study of the spectrum of Laplace operators on self-similar fractals. We compare the techniques used to those used in the euclidean situation. Furthermore, we use the obtained information on the spectral zeta function to define the Casimir energy of fractals. We give numerical values for this energy for the Sierpi\'nski gasket

Point sets on the sphere S2\mathbb{S}^2 with small spherical cap discrepancy

In this paper we study the geometric discrepancy of explicit constructions of uniformly distributed points on the two-dimensional unit sphere. We show that the spherical cap discrepancy of random point sets, of spherical digital nets and of spherical Fibonacci lattices converges with order $N^{-1/2}$. Such point sets are therefore useful for numerical integration and other computational simulations. The proof uses an area-preserving Lambert map. A detailed analysis of the level curves and sets of the pre-images of spherical caps under this map is given

CADM1 inhibits squamous cell carcinoma progression by reducing STAT3 activity.

Although squamous cell carcinomas (SqCCs) of the lungs, head and neck, oesophagus, and cervix account for up to 30% of cancer deaths, the mechanisms that regulate disease progression remain incompletely understood. Here, we use gene transduction and human tumor xenograft assays to establish that the tumour suppressor Cell adhesion molecule 1 (CADM1) inhibits SqCC proliferation and invasion, processes fundamental to disease progression. We determine that the extracellular domain of CADM1 mediates these effects by forming a complex with HER2 and integrin α6β4 at the cell surface that disrupts downstream STAT3 activity. We subsequently show that treating CADM1 null tumours with the JAK/STAT inhibitor ruxolitinib mimics CADM1 gene restoration in preventing SqCC growth and metastases. Overall, this study identifies a novel mechanism by which CADM1 prevents SqCC progression and suggests that screening tumours for loss of CADM1 expression will help identify those patients most likely to benefit from JAK/STAT targeted chemotherapies

RIP4 inhibits STAT3 signaling to sustain lung adenocarcinoma differentiation.

Loss of epithelial differentiation and extracellular matrix (ECM) remodeling are known to facilitate cancer progression and are associated with poor prognosis in patients with lung cancer. We have identified Receptor-interacting serine/threonine protein kinase 4 (RIP4) as a regulator of tumor differentiation in lung adenocarcinoma (AC). Bioinformatics analyses of human lung AC samples showed that poorly differentiated tumors express low levels of RIP4, whereas high levels are associated with better overall survival. In vitro, lung tumor cells expressing reduced RIP4 levels showed enhanced activation of STAT3 signaling and had a greater ability to invade through collagen. In contrast, overexpression of RIP4 inhibited STAT3 activation, which abrogated interleukin-6-dependent induction of lysyl oxidase, a collagen cross-linking enzyme. In an autochthonous mouse model of lung AC initiated by Kras(G12D) expression with loss of p53, Rip4 knockdown tumors progressed to a poorly differentiated state marked by an increase in Hmga2, reduced Ttf1, and enrichment of genes regulating extracellular remodeling and Jak-Stat signaling. Tail vein injections of cells overexpressing Rip4 showed a reduced potential to invade and form tumors, which was restored by co-expression of Stat3. Altogether, our work has identified that loss of RIP4 enhances STAT3 signaling in lung cancer cells, promoting the expression of ECM remodeling genes and cancer dedifferentiation

30 years of collaboration

We highlight some of the most important cornerstones of the long standing and very fruitful collaboration of the Austrian Diophantine Number Theory research group and the Number Theory and Cryptography School of Debrecen. However, we do not plan to be complete in any sense but give some interesting data and selected results that we find particularly nice. At the end we focus on two topics in more details, namely a problem that origins from a conjecture of Rényi and Erdős (on the number of terms of the square of a polynomial) and another one that origins from a question of Zelinsky (on the unit sum number problem). This paper evolved from a plenary invited talk that the authors gaveat the Joint Austrian-Hungarian Mathematical Conference 2015, August 25-27, 2015 in Győr (Hungary)

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects