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EGFR TKI improved the survival of metastatic EGFRm+NSCLC patients. Despite high response rates, resistance develops inevitably in every patient. In up to 13%, HER2 protein overexpression is found upon progression. We hypothesized that dual blockade of EGFR and HER2 by osimertinib combined with T-DM1 could re-induce tumor responses.

Abstract. The α-glucuronidase gene aguA from Aspergillus niger was cloned and characterised. Analysis of the promoter region of aguA revealed the presence of four putative binding sites for the major carbon catabolite repressor protein CREA and one putative binding site for the transcriptional activator XLNR. In addition, a sequence motif was detected which differed only in the last nucleotide from the XLNR consensus site. A construct in which part of the aguA coding region was deleted still resulted in production of a stable mRNA upon transformation of A. niger. The putative XLNR binding sites and two of the putative CREA binding sites were mutated individually in this construct and the effects on expression were examined in A. niger transformants. Northern analysis of the transformants revealed that the consensus XLNR site is not actually functional in the aguA promoter, whereas the sequence that diverges from the consensus at a single position is functional. This indicates that XLNR is also able to bind to the sequence GGCTAG, and the XLNR binding site consensus should therefore be changed to GGCTAR. Both CREA sites are functional, indicating that CREA has a strong influence on aguA expression. A detailed expression analysis of aguA in four genetic backgrounds revealed a second regulatory system involved in activation of aguA gene expression. This system responds to the presence of glucuronic and galacturonic acids, and is not dependent on XLNR.

Summary: The complete small ribosomal subunit RNA (srRNA) sequence was determined for the red algaPorphyra umbilicalis and the basidiomyceteLeucosporidium scottii, representing two taxa for which no srRNA sequences were hitherto known. These sequences were aligned with other published complete srRNA sequences of 58 eukaryotes. Evolutionary trees were reconstructed by a matrix optimization method from a dissimilarity matrix based on sections of the alignment that correspond to structurally conservative areas of the molecule that can be aligned unambiguously. The overall topology of the eukaryotic tree thus constructed is as follows: first there is a succession of early diverging branches, leading to a diplomonad, a microsporidian, a euglenoid plus kinetoplastids, an amoeba, and slime molds. Later, a nearly simultaneous radiation seems to occur into a number of taxa comprising the metazoa, the red alga, the sporozoa, the higher fungi, the ciliates, the green plants, plus some other less numerous groups. Because the red alga diverges late in the evolutionary tree, it does not seem to represent a very primitive organism as proposed on the basis of morphological and 5S rRNA sequence data. Asco- and basidiomycetes do not share a common ancestor in our tree as is generally accepted on the basis of conventional criteria. In contrast, when all alignment positions, rather than the more conservative ones, are used to construct the evolutionary tree, higher fungi do form a monophyletic cluster. The hypothesis that higher fungi and red algae might have shared a common origin has been put forward. Although the red alga and fungi seem to diverge at nearly the same time, no such relationship can be detected. The newly determined sequences can be fitted into a secondary structure model for srRNA, which is now relatively well established with the exception of uncertainties in a number of eukaryote-specific expansion areas. A specific structural model featuring a pseudoknot is proposed for one of these areas.

Summary 5S Ribosomal RNA sequences have proven to be useful tools in the study of evolutionary relationships among species. However, in reviewing previously published trees constructed from alignments of metazoan 5S RNAs, we noticed several discrepancies with classical evolutionary views. One such discrepancy concerned the phylum Arthropoda, where a crustacean,Artemia salina, seemed to be evolutionarily very remote from four insects. The cause of this phenomenon was studied by determining the 5S RNA sequences of additional arthropods, viz.Limulus polyphemus, Eurypelma californica, Lasiodora erythrocythara, Areneus diadematus, Daphnia magna, Ligia oceanica, Homarus gammarus, Cancer pagurus, Spirobolus sp.,Locusta migratoria, andTenebrio molitor. A tree was then constructed from a dissimilarity matrix by a clustering method known as weighted pair grouping. Application of a correction for unequal evolutionary rates improved the apparent evolutionary position of the arthropods and of some other metazoan species. However, neither the uncorrected nor the corrected tree permitted a completely acceptable reconstruction of metazoan evolution. We presume that this phenomenon is due to random deviations in the evolutionary rate of 5S RNA.

Lipoprotein lipase (LPL) purified from bovine milk showed variable abilities to stimulate the binding of low density lipoprotein (LDL) to J774 macrophages. The presence of a 37 kDa protein in the LPL sample seemed to be of importance for its stimulatory capacity. In order to investigate this, we isolated LPL from bovine milk via heparin Sepharose chromatography using a continuous salt gradient. Fractions containing the 37 kDa protein (as shown by SDS/PAGE under reducing conditions) eluted first from the column, followed by the 56 kDa LPL protein. The LPL enzymatic activity co-eluted with the 56 kDa protein, whereas the amount of 37 kDa protein fully paralleled the stimulatory effect on the binding of LDL to J774 cells. Samples not containing the 37 kDa protein were far less effective in stimulating the binding. Western blotting using a monoclonal antibody 5D2 against amino acids 396-405 in the carboxy-terminal domain of LPL, showed that the 37 kDa protein may be the C-terminal domain of LPL, presumably generated by proteolytic degradation of the mature LPL protein by milk proteases during its isolation. Furthermore, the functional mass of LPL for stimulation of the binding of LDL, as determined by radiation inactivation, was shown to be 30.9±1.8 kDa. We therefore suggest that cleavage of LPL at protease-sensitive sites causes a conformational change, generating an LPL protein which is more effective in mediating the binding and uptake of lipoproteins by cells.

Abstract: Mutations at codons 717 and 670/671 in the amyloid precursor protein (APP) are rare genetic causes of familial Alzheimer’s disease (AD). A mutation at codon 693 of APP has also been described as the genetic defect in hereditary cerebral hemorrhage with amyloidosis of the Dutch type (HCHWA-D). We have reported a APP692Ala→Gly (Flemish) mutation as a cause of intracerebral hemorrhage and presenile dementia diagnosed as probable AD in a Dutch family. We now describe the post-mortem examination of two demented patients with the APP692 mutation. The neuropathological findings support the diagnosis of AD. Leptomeningial and parenchymal vessels showed extensive deposition of Aβ amyloid protein. Numerous senile plaques consisted of large Aβ amyloid cores, often measuring more than 30 μm in diameter and were surrounded by a fine meshwork of dystrophic neurites. In addition, there were a large number of paired helical filaments in pyramidal neurons and dystrophic neurites. Our findings show that the APP692 mutation leads to morphological abnormalities that are similar to AD, but the morphology of senile plaques is clearly distinct from that described in sporadic and chromosome 14-linked AD patients, in patients with APP717 mutations causing familial, presenile AD and in patients with the APP693 mutation causing HCHWA-D.

We develop a novel method based on machine-learning principles to achieve optimal initiation of CPU-intensive computations for forward asteroseismic modeling in a multi-dimensional parameter space. A deep neural network is trained on a precomputed asteroseismology grid containing about 62 million coherent oscillation-mode frequencies derived from stellar evolution models. These models are representative of the core-hydrogen-burning stage of intermediate-mass and high-mass stars. The evolution models constitute a 6D parameter space and their predicted low-degree pressure- and gravity-mode oscillations are scanned using a genetic algorithm. A software pipeline is created to find the best-fitting stellar parameters for a given set of observed oscillation frequencies. The proposed method finds the optimal regions in the 6D parameter space in less than a minute, hence providing the optimal starting point for further and more detailed forward asteroseismic modeling in a high-dimensional context. We test and apply the method to seven pulsating stars that were previously modeled asteroseismically by classical grid-based forward modeling based on a ?2statistic, and obtain good agreement with past results. Our deep-learning methodology opens up the application of asteroseismic modeling in +6D parameter space for thousands of stars pulsating in coherent modes with long lifetimes observed by the Keplerspace telescope and to be discovered with the TESSand PLATOspace missions, while applications so far have been done star-by-star for only a handful of cases. Our method is open source and can be freely used by anyone.3