Zukunftsweisende Technologie

Zukunftsweisende Technologie

Dienstag, 31 Juli 2012 00:00

Auf dieser Seite führt InVitroJobs eine Rubrik zum Thema „zukunftsweisende Entwicklungen“. Darunter sind Technologien zu verstehen, die geeignet sein könnten, in Zukunft den Tierverbrauch auf einem bestimmten Gebiet abzulösen.


Bildgebende Verfahren könnten an der einen oder anderen Stelle kognitionswissenschaftliche Versuche der Grundlagenforschung, z. B. solche mit nicht-humanen Primaten, durch humanspezifische, nicht-invasive Meßmethoden ersetzen. Sie erhalten hier Informationen in Form von Literaturquellen, die zum Abstract führen.

Für den Einsatz als Ersatzverfahren zu Tierversuchen sind diese vorgestellten Verfahren jedoch noch nicht hinreichend erprobt. Bislang sind die Technologien entwickelt worden, jedoch ist nicht bekannt, ob sie auf den Sachverhalt eines Tierversuchs übertragen worden sind. Es liegen derzeit noch keine Studien dazu vor, es sind keine Evaluierungen oder Validierungen bekannt.

 

 

Foto: Kasuga Huang.

1. Bildgebende Verfahren

Bisdas S, Lá Fougere C & Ernemann U (2015): Hybrid MR-PET in Neuroimaging. Clin Neuroradiol. 2015 Oct; 25 Suppl 2:275-81. doi: 10.1007/s00062-015-0427-6. Epub 2015 Jul 31.

Bouchard, M. B., Voleti, V., Mendes, C. S., Lacefield, C., Grueber, W. B., Mann, R. S., Bruno, R. M. & Hillman, E. C. M. (2015): Swept confocally-aligned planar excitation (SCAPE) microscopy for high-speed volumetric imaging of behaving organisms. Nature Photonics, DOI: 10.1038/nphoton.2014.323

Chhatwal, J. P., Schultz, A. P., Johnson, K., Benzinger, T. L. S., Jack, Jr., C., Ances, B. M., Sullivan, C. A., Salloway, S. P., Ringman, J. M., Koeppe, R. A., Marcus, D. S., Thompson, P., Saykin, A. J., Correia, S., Schofield, P. R., Rowe, C. C., Fox, N. C., Brickman, A. M., Mayeux, R., McDade, E., Bateman, R., Fagan, A. M., Goate, A. M., Xiong, C., Buckles, V. D., Morris, J., C. & Sperling, R. A. (2013): Impaired default network functional connectivity in autosomal dominant Alzheimer disease. Neurology 81. DOI 10.1212/WNL.0b013e3182a1aafe

Choi, Woo June & Wang, Ruikang K. (2015): Swept-source optical coherence tomography powered by a 1.3-μm vertical cavity surface emitting laser enables 2.3-mm-deep brain imaging in mice in vivo. J. Biomed. Opt. 20(10), 106004 (Oct 08, 2015). doi:10.1117/1.JBO.20.10.106004

Chojnacki, J., Staudt, T., Glass, B., Bingen, P., Engelhardt, J., Anders, M., Schneider, J.,  Müller, B., Hell, S. W. & Kräusslich, H.-G. (2012): Maturation-Dependent HIV-1 Surface Protein Redistribution Revealed by Fluorescence Nanoscopy. Science 338/6106: 524-528.

Connolly, C. G., Wu, J., Ho, T. C., Hoeft, F., Wolkowitz, O. Eisendrath, S., Frank, G., Hendren, R., Max, J. E., Paulus, M. P., Tapert, S. F., Banerjee, D., Simmons, A. N. & Yang, T. T. (2013): Resting-State Functional Connectivity of Subgenual Anterior Cingulate Cortex in Depressed Adolescents. Biol. Psychiatry.

Derix, J., Yang, S., Lüsebrink, F., Fiederer, L. D. J., Schulze-Bonhage, A., Aertsen, A., Speck, O. and Ball, T. (2014): Visualization of the amygdalo–hippocampal border and its structural variability by 7T and 3T magnetic resonance imaging. Hum. Brain Mapp. Early View (Online Version of Record published before inclusion in an issue). DOI: 10.1002/hbm.22477

Downing, P., Liu, J., & Kanwisher, N. (2001): Testing cognitive models of visual attention with fMRI and MEG. Neuropsychologia, 39/12: 1329-1342.

Espy, M., Matlachov, A., Volegov, P., Mosher, J.C., & Kraus, R.H., Jr. (2005): SQUID-based simultaneous detection of NMR and biomagnetic signals at ultra-low magnetic fields. IEEE Trans. Appl. Supercond., 15: 635-639.

Haynes, J.D. & Rees, G. 2005. Predicting the orientation of invisible stimuli from activity in human primary visual cortex. Nat.Neurosci., 8/5: 686-691.

Heinz, A., Siessmeier, T., Wrase, J., Hermann, D., Klein, S., Grusser, S.M., Flor, H., Braus, D.F., Buchholz, H.G., Grunder, G., Schreckenberger, M., Smolka, M. N., Rosch, F., Mann, K., & Bartenstein, P. (2004): Correlation between dopamine D(2) receptors in the ventral striatum and central processing of alcohol cues and craving. Am J Psychiatry, 161/10: 1783-1789.

Höfner, N., Albrecht, H. H., Cassara, A. M., Curio, G., Hartwig, S., Haueisen, J., Hilschenz, I., Korber, R., Martens, S., Scheer, H. J., Voigt, J., Trahms, L., & Burghoff, M. (2011): Are brain currents detectable by means of low-field NMR? A phantom study. Magn Reson. Imaging 29/10: 1365-1373.

Kaiplavil, Sreekumar & Mandelis, Andreas (2014): Truncated-correlation photothermal coherence tomography for deep subsurface analysis. Nature Photonics. doi:10.1038/nphoton.2014.111

Kamitani, Y. & Tong, F. (2006): Decoding seen and attended motion directions from activity in the human visual cortex. Curr.Biol, 16/11: 1096-1102.

Klippel, S., Döpfert, J., Jabadurai Jayapaul, J., Kunth, M., Rossella, F., Schnurr, M., Witte, C., Freund, C. & Schröder, L. (2013: Cell tracking with Caged Xenon: Using Cryptophanes as MRI Reporters upon Cellular Internalization. (Epub ahead of print) DOI:10.1002/anie.201307290

König, K & Ostendorf, A (Eds.): Optically Induced Nanostructures. Biomedical and Technical Applications. Verlag DeGruyter (2015).

Kraus, R. H., Jr., Volegov, P., Matlachov, A., & Espy, M. (2008): Toward direct neural current imaging by resonant mechanisms at ultra-low field. Neuroimage., 39/1: 310-317.

Le Bihan, D., Mangin, J.-F., Poupon, C., Clark, C. A., Pappata, S., Molko, N., & Chabriat, H. (2001): Diffusion Tensor Imaging: Concepts and Applications. Journal of Magnetic Resonance Imaging. 13: 534–546.

Lee, M. H., Smyser, C. D. & Shimony, J. S. (2012): Resting-State fMRI: A Review of Methods and Clinical Applications. AJNR Am. J. Neuroradiol. 10.3174/ajnr.A3263

Lee, T, Cai, LX, Lelyveld, VS, Aviad Hai & Alan Jasanoff (2014): Molecular-Level Functional Magnetic Resonance Imaging of Dopaminergic Signaling. Science 344: 533-535.

Liangzhong Xiang, Bo Wang, Lijun Ji & Huabei Jiang (2013): 4-D Photoacoustic Tomography. Scientific Reports 3 : 1113, DOI: 10.1038/srep01113.

Loretz, M., Rosskopf, T., Boss, J.M., Pezzagna, S., Meijer, J. & C. L. Degen (2014): Single-proton spin detection by diamond magnetometry. Science Express Reports. doi: 10.1126/science.1259464

Mahamid, J., Pfeffer, S., Schaffer, M., Villa, E., Danev, R., Kuhn-Cuellar, L., Förster, F., Hyman, A. A., Plitzko, J. M., Baumeister, W. (2016): Visualizing the molecular sociology at the HeLa cell nuclear periphery. Science 351 (6276): 969-972. DOI: 10.1126/science.aad8857

Nielles-Vallespin, S., Mekkaoui,C., Gatehouse, P., Reese, T. G., Keegan, J., Ferreira, P. F., Collins, S., Speier, P., Feiweier, T., de Silva, R., Jackowski, M. P., Pennell, D. J., Sosnovik, D. E. & Firmin, D. (2013): In Vivo Diffusion Tensor MRI of the Human Heart: Reproducibility of Breath-Hold and Navigator-Based Approaches. Magnetic Resonance in Medicine. 70: 454–465.

Shibata, M., Uchihashi, T., Ando, T. & Yasuda, R. (2015): Long-tip high-speed atomic force microscopy for nanometer-scale imaging in live cells. SCIENTIFIC REPORTS 5: 8724, DOI: 10.1038/srep08724.

Schindler, A. & Bartels, A. (2013): Parietal Cortex Codes for Egocentric Space beyond the Field of View. Current Biology 23, 1–6. http://dx.doi.

Schneider, J., Zahn, J., Maglione, M., Sigrist, S. J., Marquard, J., Chojnacki, J.,  Kräusslich, H.-G., Sahl, S. J., Engelhardt, J. & Hell, S. W.
(2015): Ultrafast, temporally stochastic STED nanoscopy of millisecond dynamics. Nature Methods 2015, 10.1038/nmeth.3481

Stirman, JN, Smith, IT, Kudenov, MW & Smith, SL (2016): Wide field-of-view, multi-region, two-photon imaging of neuronal activity in the mammalian brain. Nature Biotechnology, advance online publication, doi:10.1038/nbt.3594.

-> Neu: Stratis Tzoumas, Antonio Nunes, Ivan Olefir, Stefan Stangl, Panagiotis Symvoulidis, Sarah Glasl, Christine Bayer, Gabriele Multhoff & Vasilis Ntziachristos (2016): Eigenspectra optoacoustic tomography achieves quantitative blood oxygenation imaging deep in tissues. Nature Communications 7, Article number: 12121 doi:10.1038/ncomms12121.

Tong, F. Harrison S. A., Dewey, J. A., Kamitani, Y (2013): Relationship between BOLD amplitude and pattern classification of orientation-selective activity in the human visual cortex. NeuroImage 63 (2012) 1212–1222.

Wehrl, H. F., Hossain, M., Lankes, K., Liu, C.-C., Bezrukov, I., Martirosian, P., Schick, F., Reischl, G. & Pichler, B. J. (2013): Simultaneous PET-MRI reveals brain function in activated and resting state on metabolic, hemodynamic and multiple temporal scales. Nature Medicine.

Weizenecker, J., Gleich, B., Rahmer, J., Dahnke, H. & Borgert, J. (2009): Three-dimensional real-time in vivo magnetic particle imaging. Phys. Med. Biol. 54: L1–L10.

Foto: Paul Wicks.

 

2. Nicht-invasive Gehirn-Computer-Schnittstellen

Herff, C, Heger, D, de Pesters, A, Telaar, D, Brunner, P, Schalk, G & Schultz, T. (2015): Brain-to-text: decoding spoken phrases from phone representations in the brain. Front. Neurosci. http://dx.doi.org/10.3389/fnins.2015.00217

Quandt, F., Reichert, C., Hinrichs, H., Heinze, H. J., Knight, R. T., & Rieger, J. W. (2012): Single trial discrimination of individual finger movements on one hand: a combined MEG and EEG study. Neuroimage., 59/4: 3316-3324.

Waldert, S., Preissl, H., Demandt, E., Braun, C., Birbaumer, N., Aertsen, A., & Mehring, C. (2008): Hand movement direction decoded from MEG and EEG. J Neurosci., 28/4: 1000-1008.



3. Nicht-invasive Verfahren zur Hirnstimulierung

Tufail, Y., Matyushov, A., Baldwin, N., Tauchmann, M. L., Georges, J., Yoshihiro, A., Tillery, S. I., & Tyler, W. J. (2010): Transcranial pulsed ultrasound stimulates intact brain circuits. Neuron, 66/5: 681-694.

Foto: Sven Hoppe, Fotolia.com



4. Human-spezifische Krankheitsmodelle
(Diseases-in-a-dish)


Callaway, E. (2011): Cells snag top modelling job. Nature 469/7330: 279.

Se Hoon Choi, Young Hye Kim, Matthias Hebisch, Christopher Sliwinski, Seungkyu Lee, Carla D’Avanzo, Hechao Chen, Basavaraj Hooli, Caroline Asselin, Julien Muffat, Justin B. Klee, Can Zhang, Brian J. Wainger, Michael Peitz, Dora M. Kovacs,    Clifford J. Woolf, Steven L. Wagner, Rudolph E. Tanzi & Doo Yeon Kim (2014): A three-dimensional human neural cell culture model of Alzheimer’s disease. doi:10.1038/nature13800

-> Neu: Dekkers, JF, Berkers, G, Kruisselbrink, E, et al. (2016): Characterizing responses to CFTR-modulating drugs using rectal organoids derived from subjects with cystic fibrosis. Science 8/344.

-> Neu: Graffmann N, Ring S, Kawala MA, Wruck W, Ncube A, Trompeter HI, et al. (2016): Modelling NAFLD with human pluripotent stem cell derived immature hepatocyte like cells reveals activation of PLIN2 and confirms regulatory functions of PPARalpha. Stem cells and development.

Itzhaki, I., Maizels, L., Huber, I., Zwi-Dantsis, L., Caspi, O., Winterstern, A., Feldman, O., Gepstein, A., Arbel, G., Hammerman, H., Boulos, M., & Gepstein, L. (2011): Modelling the long QT syndrome with induced pluripotent stem cells. Nature, 471/7337: 225-229.

D. Huh, D. C. Leslie, B. D. Matthews, J. P. Fraser, S. Jurek, G. A. Hamilton, K. S. Thorneloe, M. A. McAlexander, D. E. Ingber, A Human Disease Model of Drug Toxicity–Induced Pulmonary Edema in a Lung-on-a-Chip Microdevice. Sci. Transl. Med. 4, 159ra147 (2012).

Jerome Mertens, Apuã C.M. Paquola, Manching Ku, Emily Hatch, Lena Böhnke, Shauheen Ladjevardi, Sean McGrath, Benjamin Campbell, Hyungjun Lee, Joseph R. Herdy, J. Tiago Goncalves, Tomohisa Toda, Yongsung Kim, Jürgen Winkler, Jun Yao, Martin Hetzer, and Fred H. Gage (2015): Directly Reprogrammed Human Neurons Retain Aging-Associated Transcriptomic Signatures and Reveal Age-Related Nucleocytoplasmic Defects. Cell Stem Cell 17, 1-14. DOI: http://dx.doi.org/10.1016/j.stem.2015.09.001

Moretti, A., Bellin, M., Welling, A., Jung, C.B., Lam, J.T., Bott-Flugel, L., Dorn, T., Goedel, A., Hohnke, C., Hofmann, F., Seyfarth, M., Sinnecker, D., Schomig, A., & Laugwitz, K.L. (2010): Patient-specific induced pluripotent stem-cell models for long-QT syndrome. N Engl. J Med 363/15: 1397-1409.

Nguyen, D.-H. T., Stapleton, S. C., Yang, M. T., Cha, S. S., Choi, C. K., Galie, P. A. & Chen, C. S. (2013): Biomimetic model to reconstitute angiogenic sprouting morphogenesis in vitro. PNAS 110/17: 6712-6717.

Takahashi, K., Tanabe, K., Ohnuki, M., Narita, M., Ichisaka, T., Tomoda, K., & Yamanaka, S. (2007): Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell, 131/5: 861-872.

Wang, G., McCain, M., et. al. (2014): Modeling the mitochondrial cardiomyopathy of Barth syndrome with iPSC and heart-on-a-chip technologies. Nature Medicine.



5. Mikrofludische Systeme

Huh, D., Matthews, B. D., Mammoto, A., Montoya-Zavala, M., Hsin, H.Y., & Ingber, D. E. (2010): Reconstituting organ-level lung functions on a chip. Science, 328/5986: 1662-1668.

Huh, D., Hamilton, G. A., & Ingber, D. E. (2011): From 3D cell culture to organs-on-chips. Trends Cell Biol, 21/12: 745-754.

Neuzil, P. et al. (2012): Revisiting lab-on-a-chip technology for drug discovery. Nat Rev Drug Discov. 11: 620 - 32.

Friedrich Schuler, Frank Schwemmer, Martin Trotter, Simon Wadle, Roland Zengerle, Felix von Stetten und Nils Paust (2015): Centrifugal step emulsification applied for absolute quantification of nucleic acids by digital droplet RPA. Lab Chip, 2015,15, 2759-2766. DOI: 10.1039/C5LC00291E

Tsai, M., Kita, A., Leach, J., Rounsevell, R., Huang, J. N., Moake, J., Ware, R. E., Fletcher, D. A., & Lam, W. A. (2012): In vitro modeling of the microvascular occlusion and thrombosis that occur in hematologic diseases using microfluidic technology. J Clin Invest, 122/1: 408-418.