Bisacylphosphane oxides as photo-latent cytotoxic agents and potential photo-latent anticancer drugs

Bisacylphosphane oxides (BAPOs) are established as photoinitiators for industrial applications. Light irradiation leads to their photolysis, producing radicals. Radical species induce oxidative stress in cells and may cause cell death. Hence, BAPOs may be suitable as photolatent cytotoxic agents, but such applications have not been investigated yet. Herein, we describe for the first time a potential use of BAPOs as drugs for photolatent therapy. We show that treatment of the breast cancer cell lines MCF-7 and MDA-MB-231 and of breast epithelial cells MCF-10A with BAPOs and UV irradiation induces apoptosis. Cells just subjected to BAPOs or UV irradiation alone are not affected. The induction of apoptosis depend on the BAPO and the irradiation dose. We proved that radicals are the active species since cells are rescued by an antioxidant. Finally, an optimized BAPO-derivative was designed which enters the cells more efficiently and thus leads to stronger effects at lower doses

Accurate phase retrieval of complex point spread functions with deep residual neural networks

Phase retrieval, i.e. the reconstruction of phase information from intensity information, is a central problem in many optical systems. Here, we demonstrate that a deep residual neural net is able to quickly and accurately perform this task for arbitrary point spread functions (PSFs) formed by Zernike-type phase modulations. Five slices of the 3D PSF at different focal positions within a two micron range around the focus are sufficient to retrieve the first six orders of Zernike coefficients.Comment: 8 pages, 4 figure

Supersensitive Multifluorophore RNA‐FISH for Early Virus Detection and Flow‐FISH by Using Click Chemistry

The reliable detection of transcription events through the quantification of the corresponding mRNA is of paramount importance for the diagnostics of infections and diseases. The quantification and localization analysis of the transcripts of a particular gene allows disease states to be characterized more directly compared to an analysis on the transcriptome wide level. This is particularly needed for the early detection of virus infections as now required for emergent viral diseases, e. g. Covid‐19. In situ mRNA analysis, however, is a formidable challenge and currently performed with sets of single‐fluorophore‐containing oligonucleotide probes that hybridize to the mRNA in question. Often a large number of probe strands (>30) are required to get a reliable signal. The more oligonucleotide probes are used, however, the higher the potential off‐target binding effects that create background noise. Here, we used click chemistry and alkyne‐modified DNA oligonucleotides to prepare multiple‐fluorophore‐containing probes. We found that these multiple‐dye probes allow reliable detection and direct visualization of mRNA with only a very small number (5–10) of probe strands. The new method enabled the in situ detection of viral transcripts as early as 4 hours after infection

New insights into the intracellular distribution pattern of cationic amphiphilic drugs

Cationic amphiphilic drugs (CADs) comprise a wide variety of different substance classes such as antidepressants, antipsychotics, and antiarrhythmics. It is well recognized that CADs accumulate in certain intracellular compartments leading to specific morphological changes of cells. So far, no adequate technique exists allowing for ultrastructural analysis of CAD in intact cells. Azidobupramine, a recently described multifunctional antidepressant analogue, allows for the first time to perform high-resolution studies of CADs on distribution pattern and morphological changes in intact cells. We showed here that the intracellular distribution pattern of azidobupramine strongly depends on drug concentration and exposure time. The mitochondrial compartment (mDsRed) and the late endolysosomal compartment (CD63-GFP) were the preferred localization sites at low to intermediate concentrations (i.e. 1 mu M, 5 mu M). In contrast, the autophagosomal compartment (LC3-GFP) can only be reached at high concentrations (10 mu M) and long exposure times (72 hrs). At the morphological level, LC3-clustering became only prominent at high concentrations (10 mu M), while changes in CD63 pattern already occurred at intermediate concentrations (5 mu M). To our knowledge, this is the first study that establishes a link between intracellular CAD distribution pattern and morphological changes. Therewith, our results allow for gaining deeper understanding of intracellular effects of CADs

Accurate phase retrieval of complex 3D point spread functions with deep residual neural networks.

Phase retrieval, i.e., the reconstruction of phase information from intensity information, is a central problem in many optical systems. Imaging the emission from a point source such as a single molecule is one example. Here, we demonstrate that a deep residual neural net is able to quickly and accurately extract the hidden phase for general point spread functions (PSFs) formed by Zernike-type phase modulations. Five slices of the 3D PSF at different focal positions within a two micrometer range around the focus are sufficient to retrieve the first six orders of Zernike coefficients

Accurate and rapid background estimation in single-molecule localization microscopy using the deep neural network BGnet.

Background fluorescence, especially when it exhibits undesired spatial features, is a primary factor for reduced image quality in optical microscopy. Structured background is particularly detrimental when analyzing single-molecule images for 3-dimensional localization microscopy or single-molecule tracking. Here, we introduce BGnet, a deep neural network with a U-net-type architecture, as a general method to rapidly estimate the background underlying the image of a point source with excellent accuracy, even when point-spread function (PSF) engineering is in use to create complex PSF shapes. We trained BGnet to extract the background from images of various PSFs and show that the identification is accurate for a wide range of different interfering background structures constructed from many spatial frequencies. Furthermore, we demonstrate that the obtained background-corrected PSF images, for both simulated and experimental data, lead to a substantial improvement in localization precision. Finally, we verify that structured background estimation with BGnet results in higher quality of superresolution reconstructions of biological structures