Paper Roundup: March 2016

  • Coupled robotics, imaging, and machine learning to automatically determine effects of compounds on protein localization [1]
  • Combining lattice light sheet microscopy and PAINT staining to achieve 3D super-resolution localization microscopy over large volumes [2]
  • A scanning Bessel beam light sheet scope for imaging of 3D cell behavior [3]
  • Building an interferometric scattering microscope [4]
  • A detailed analysis of the Beer-Lambert law and absorption spectroscopy [5]
  • An optofluidic gradient refractive index lens [6]
  • Combined spectral and lifetime imaging for imaging many cellular labels at once [7]
  • A nice review of clearing methods [8]
  • A 3D visualization tool for light sheet data [9]
  • Monomeric streptavidin as a probe for super-resolution imaging of biotinylated proteins [10]
  • Use of phase masks at the pupil plane to make more uniform light sheets [11]
  • A light sheet microscope compatible with multiwell plates and other coverslip bottom chambers [12]
  • Combining light sheet microscopy with RESOLFT to improve the Z-resolution of light sheet microscopy [13]
  • Using split GFP as a protein tagging system [14]
  • Tiling light sheet to optimize both field of view and spatial resolution [15]
  • Improved refractive index matching for sample clearing [16]
  • An open source structured illumination (SIM) reconstruction program [17]
  • A post hoc algorithm for estimating shading corrections [18]
  • Reprogramming CRISPR-Cas9 for fluorescent labeling of RNA [19]
  • Diagonal scanning light sheet microscopy for high resolution imaging of adherent cells [20]


  1. A.W. Naik, J.D. Kangas, D.P. Sullivan, and R.F. Murphy, "Active machine learning-driven experimentation to determine compound effects on protein patterns", eLife, vol. 5, 2016.
  2. W.R. Legant, L. Shao, J.B. Grimm, T.A. Brown, D.E. Milkie, B.B. Avants, L.D. Lavis, and E. Betzig, "High-density three-dimensional localization microscopy across large volumes", Nature Methods, vol. 13, pp. 359-365, 2016.
  3. E. Welf, M. Driscoll, K. Dean, C. Schäfer, J. Chu, M. Davidson, M. Lin, G. Danuser, and R. Fiolka, "Quantitative Multiscale Cell Imaging in Controlled 3D Microenvironments", Developmental Cell, vol. 36, pp. 462-475, 2016.
  4. J. Ortega Arroyo, D. Cole, and P. Kukura, "Interferometric scattering microscopy and its combination with single-molecule fluorescence imaging", Nature Protocols, vol. 11, pp. 617-633, 2016.
  5. T.G. Mayerhöfer, H. Mutschke, and J. Popp, "Employing Theories Far beyond Their Limits-The Case of the (Boguer-) Beer-Lambert Law", ChemPhysChem, vol. 17, pp. 1948-1955, 2016.
  6. H.T. Zhao, Y. Yang, L.K. Chin, H.F. Chen, W.M. Zhu, J.B. Zhang, P.H. Yap, B. Liedberg, K. Wang, G. Wang, W. Ser, and A.Q. Liu, "Optofluidic lens with low spherical and low field curvature aberrations", Lab on a Chip, vol. 16, pp. 1617-1624, 2016.
  7. T. Niehörster, A. Löschberger, I. Gregor, B. Krämer, H. Rahn, M. Patting, F. Koberling, J. Enderlein, and M. Sauer, "Multi-target spectrally resolved fluorescence lifetime imaging microscopy", Nature Methods, vol. 13, pp. 257-262, 2016.
  8. V. Marx, "Optimizing probes to image cleared tissue", Nature Methods, vol. 13, pp. 205-209, 2016.
  9. A. Bria, G. Iannello, L. Onofri, and H. Peng, "TeraFly: real-time three-dimensional visualization and annotation of terabytes of multidimensional volumetric images", Nature Methods, vol. 13, pp. 192-194, 2016.
  10. I. Chamma, M. Letellier, C. Butler, B. Tessier, K. Lim, I. Gauthereau, D. Choquet, J. Sibarita, S. Park, M. Sainlos, and O. Thoumine, "Mapping the dynamics and nanoscale organization of synaptic adhesion proteins using monomeric streptavidin", Nature Communications, vol. 7, 2016.
  11. D. Wilding, P. Pozzi, O. Soloviev, G. Vdovin, C.J. Sheppard, and M. Verhaegen, "Pupil filters for extending the field-of-view in light-sheet microscopy", Optics Letters, vol. 41, pp. 1205, 2016.
  12. R. McGorty, and B. Huang, "Selective-plane illumination microscopy for high-content volumetric biological imaging", High-Speed Biomedical Imaging and Spectroscopy: Toward Big Data Instrumentation and Management, 2016.
  13. P. Hoyer, G. de Medeiros, B. Balázs, N. Norlin, C. Besir, J. Hanne, H. Kräusslich, J. Engelhardt, S.J. Sahl, S.W. Hell, and L. Hufnagel, "Breaking the diffraction limit of light-sheet fluorescence microscopy by RESOLFT", Proceedings of the National Academy of Sciences, vol. 113, pp. 3442-3446, 2016.
  14. D. Kamiyama, S. Sekine, B. Barsi-Rhyne, J. Hu, B. Chen, L.A. Gilbert, H. Ishikawa, M.D. Leonetti, W.F. Marshall, J.S. Weissman, and B. Huang, "Versatile protein tagging in cells with split fluorescent protein", Nature Communications, vol. 7, 2016.
  15. Q. Fu, B.L. Martin, D.Q. Matus, and L. Gao, "Imaging multicellular specimens with real-time optimized tiling light-sheet selective plane illumination microscopy", Nature Communications, vol. 7, 2016.
  16. M. Ke, Y. Nakai, S. Fujimoto, R. Takayama, S. Yoshida, T. Kitajima, M. Sato, and T. Imai, "Super-Resolution Mapping of Neuronal Circuitry With an Index-Optimized Clearing Agent", Cell Reports, vol. 14, pp. 2718-2732, 2016.
  17. M. Müller, V. Mönkemöller, S. Hennig, W. Hübner, and T. Huser, "Open-source image reconstruction of super-resolution structured illumination microscopy data in ImageJ", Nature Communications, vol. 7, 2016.
  18. P. KASK, K. PALO, C. HINNAH, and T. POMMERENCKE, "Flat field correction for high‐throughput imaging of fluorescent samples", Journal of Microscopy, vol. 263, pp. 328-340, 2016.
  19. D. Nelles, M. Fang, M. O’Connell, J. Xu, S. Markmiller, J. Doudna, and G. Yeo, "Programmable RNA Tracking in Live Cells with CRISPR/Cas9", Cell, vol. 165, pp. 488-496, 2016.
  20. K. Dean, P. Roudot, C. Reis, E. Welf, M. Mettlen, and R. Fiolka, "Diagonally Scanned Light-Sheet Microscopy for Fast Volumetric Imaging of Adherent Cells", Biophysical Journal, vol. 110, pp. 1456-1465, 2016.