Orientierende Untersuchungen über die Einwirkung von gasförmigem Formaldehyd auf die grüne Pflanze

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Status and perspectives of neuroprotective therapies in glaucoma: The European Glaucoma Society White Paper

Glaucoma, a chronic progressive neuropathy and the most frequent cause of irreversible blindness worldwide, is commonly treated by medication or surgery aimed at lowering intraocular pressure. In view of the limited therapeutic options, the European Glaucoma Society (EGS) sponsored two Think Tank Meetings with the goal of assessing the current status and the overall perspectives for neuroprotective treatment strategies in glaucoma. The results of the meetings are summarized in this EGS White Paper.     

Lineage and Genogroup-Defining Single Nucleotide Polymorphisms of Escherichia coli O157:H7

Escherichia coli O157:H7 is a zoonotic human pathogen for which cattle are an important reservoir host. Using both previously published and new sequencing data, a 48-locus single nucleotide polymorphism (SNP)-based typing panel was developed that redundantly identified 11 genogroups that span six of the eight lineages recently described for E. coli O157:H7 (J. L. Bono, T. P. Smith, J. E. Keen, G. P. Harhay, T. G. McDaneld, R. E. Mandrell, W. K. Jung, T. E. Besser, P. Gerner-Smidt, M. Bielaszewska, H. Karch, M. L. Clawson, Mol. Biol. Evol. 29:2047–2062, 2012) and additionally defined subgroups within four of those lineages. This assay was applied to 530 isolates from human and bovine sources. The SNP-based lineage groups were concordant with previously identified E. coli O157:H7 genotypes identified by other methods and were strongly associated with carriage of specific Stx genes. Two SNP lineages (Ia and Vb) were disproportionately represented among cattle isolates, and three others (IIa, Ib, and IIb) were disproportionately represented among human clinical isolates. This 48-plex SNP assay efficiently and economically identifies biologically relevant lineages within E. coli O157:H7.     

Deep learning for computational biology

Technological advances in genomics and imaging have led to an explosion of molecular and cellular profiling data from large numbers of samples. This rapid increase in biological data dimension and acquisition rate is challenging conventional analysis strategies. Modern machine learning methods, such as deep learning, promise to leverage very large data sets for finding hidden structure within them, and for making accurate predictions. In this review, we discuss applications of this new breed of analysis approaches in regulatory genomics and cellular imaging. We provide background of what deep learning is, and the settings in which it can be successfully applied to derive biological insights. In addition to presenting specific applications and providing tips for practical use, we also highlight possible pitfalls and limitations to guide computational biologists when and how to make the most use of this new technology.     

Rapid Assessment of Tablet Film Coating Quality by Multispectral UV Imaging

Chemical imaging techniques are beneficial for control of tablet coating layer quality as they provide spectral and spatial information and allow characterization of various types of coating defects. The purpose of this study was to assess the applicability of multispectral UV imaging for assessment of the coating layer quality of tablets. UV images were used to detect, characterize, and localize coating layer defects such as chipped parts, inhomogeneities, and cracks, as well as to evaluate the coating surface texture. Acetylsalicylic acid tablets were prepared on a rotary tablet press and coated with a polyvinyl alcohol-polyethylene glycol graft copolymer using a pan coater. It was demonstrated that the coating intactness can be assessed accurately and fast by UV imaging. The different types of coating defects could be differentiated and localized based on multivariate image analysis and Soft Independent Modeling by Class Analogy applied to the UV images. Tablets with inhomogeneous texture of the coating could be identified and distinguished from those with a homogeneous surface texture. Consequently, UV imaging was shown to be well-suited for monitoring of the tablet coating layer quality. UV imaging is a promising technique for fast quality control of the tablet coating because of the high data acquisition speed and its nondestructive analytical nature.     

Egg development and hatching success in alpine chironomids

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Cell cycle and biochemical effects of PD 0183812. A potent inhibitor of the cyclin D-dependent kinases CDK4 and CDK6

Progression through the G1 phase of the cell cycle requires phosphorylation of the retinoblastoma gene product (pRb) by the cyclin D-dependent kinases CDK4 and CDK6, whose activity can specifically be blocked by the CDK inhibitor p16(INK4A). Misregulation of the pRb/cyclin D/p16(INK4A) pathway is one of the most common events in human cancer and has lead to the suggestion that inhibition of cyclin D-dependent kinase activity may have therapeutic value as an anticancer treatment. Through screening of a chemical library, we initially identified the [2,3-d]pyridopyrimidines as inhibitors of CDK4. Chemical modification resulted in the identification of PD 0183812 as a potent and highly selective inhibitor of both CDK4 and CDK6 kinase activity, which is competitive with ATP. Flow cytometry experiments showed that of the cell lines tested, only those expressing pRb demonstrated a G1 arrest when treated with PD 0183812. This arrest correlated in terms of incubation time and potency with a loss of pRb phosphorylation and a block in proliferation, which was reversible. These results suggest a potential use of this chemical class of compounds as therapeutic agents in the treatment of tumors with functional pRb, possessing cell cycle aberrations in other members of the pRb/cyclin D/p16(INK4A) pathway.     

Rapid assessment of adenovirus serum neutralizing antibody titer based on quantitative, morphometric evaluation of capsid binding and intracellular trafficking: population analysis of adenovirus capsid association with cells is predictive of adenovirus infectivity

Neutralizing antiviral antibodies are typically detected on the basis of inhibition of viral function, such as propagation of a viral infection or inhibition of viral gene expression. Evidence is presented that anti-adenovirus neutralizing antibodies can be evaluated by analysis of cell-associated capsids or by analysis of intracellular trafficking of the capsids within 1 h after infection. Quantitative analyses of these morphologic parameters represent rapid, broadly applicable, functional assays for the detection of anti-adenovirus neutralizing antibodies.