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Register a new userMid-infrared Chemical Nano-imaging for Intra-cellular Drug Localisation
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In the past two decades a range of fluorescence cell microscopy techniques have been developed which can achieve ~10 nm spatial resolution, i.e. substantially beating the usual limits set by optical diffraction. However, these methods rely on specialised labelling. This limits the applicability, risks perturbing the biology, and it also makes them so-called discovery techniques that can only be used when there is prior knowledge about the biological problem. The alternative, electron microscopy (EM), requires complex and time-consuming sample preparation, that risks compromising the samples integrity. Samples have to withstand vacuum, and staining with heavy metals to make them conductive, and give usable electron-contrast. None of these techniques can directly map out drug distributions at a sub-cellular level. Recently infrared light-based scanning probe techniques have demonstrated a capability for ~1 nm spatial resolution. However, they need samples that are flat, dry and dimensionally stable and they only probe down to a depth commensurate with the spatial resolution, so they yield essentially surface chemical information. Thus far they have been applied only to artificially produced test samples, e.g. gold particles, or isolated proteins on silicon. Here we show how these probe-based techniques can be adapted for use with routinely prepared general biological specimens. This allows for Mid-infrared Chemical Nano-imaging (MICHNI) that delivers chemical analysis at a ~10 nm spatial resolution, suitable for studying cellular ultrastructure. We demonstrate its utility by performing label-free mapping of the anti-cancer drug Bortezomib (BTZ) within a single human myeloma cell. We believe that this MICHNI technique has the potential to become a widely applicable adjunct to EM across the bio-sciences.
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Surface plasmons are collective oscillations of electrons in metals or semiconductors enabling confinement and control of electromagnetic energy at subwavelength scales. Rapid progress in plasmonics has largely relied on advances in device nano-fabrication, whereas less attention has been paid to the tunable properties of plasmonic media. One such medium-graphene-is amenable to convenient tuning of its electronic and optical properties with gate voltage. Through infrared nano-imaging we explicitly show that common graphene/SiO2/Si back-gated structures support propagating surface plasmons. The wavelength of graphene plasmons is of the order of 200 nm at technologically relevant infrared frequencies, and they can propagate several times this distance. We have succeeded in altering both the amplitude and wavelength of these plasmons by gate voltage. We investigated losses in graphene using plasmon interferometry: by exploring real space profiles of plasmon standing waves formed between the tip of our nano-probe and edges of the samples. Plasmon dissipation quantified through this analysis is linked to the exotic electrodynamics of graphene. Standard plasmonic figures of merits of our tunable graphene devices surpass that of common metal-based structures.
The human proteome is enriched in proteins that do not fold into a stable 3D structure. These intrinsically disordered proteins (IDPs) spontaneously fluctuate between a large number of configurations in their native form. Remarkably, the disorder does not lead to dysfunction as with denatured folded proteins. In fact, unlike denatured proteins, recent evidences strongly suggest that multiple biological functions stem from such structural plasticity. Here, focusing on the nanoscopic length-scale, we review the latest advances in IDP research and discuss some of the future directions in this highly promising field.
Elucidating quantum coherence effects and geometrical factors for efficient energy transfer in photosynthesis has the potential to uncover non-classical design principles for advanced organic materials. We study energy transfer in a linear light-harvesting model to reveal that dimerized geometries with strong electronic coherences within donor and acceptor pairs exhibit significantly improved efficiency, which is in marked contrast to predictions of the classical Forster theory. We reveal that energy tuning due to coherent delocalization of photoexcitations is mainly responsible for the efficiency optimization. This coherence-assisted energy-tuning mechanism also explains the energetics and chlorophyll arrangements in the widely-studied Fenna-Matthews-Olson complex. We argue that a clustered network with rapid energy relaxation among donors and resonant energy transfer from donor to acceptor states provides a basic formula for constructing efficient light-harvesting systems, and the general principles revealed here can be generalized to larger systems and benefit future innovation of efficient molecular light-harvesting materials.
Interstellar infrared observation shows featured spectrum due to polycyclic aromatic hydrocarbon (PAH)at wavelength 3.3,6.2,7.6,7.8,8.6,and 11.3 micrometer,which are ubiquitously observed in many astronomical dust clouds and galaxies. Our previous first principles calculation revieled that viod induced coronene (C23H12)2+ and circumcoronene (C53H18)1+ could reproduce such spectrum very well. In this study, quantum-mechanic origin was studied through atomic configuration change and atomic vibration mode analysis. By a high speed particle attack, carbon void would be introduced in PAH. Molecular configuration was deformed by the Jahn-Teller quantum effect. Carbon SP3 local bond was created among SP2 graphene like carbon network. Also, carbon tetrahedron local structure was created. Such peculiar structure is the quantum origin. Those metamorphosed molecules would be photo-ionized by the central star strong photon irradiation resulting cation molecules. Atomic vibration mode of cation molecule (C23H12)2+ was compared with that of neutral one (C23H12). At 3.3 micrometer, both molecules show show C-H stretching mode and give fairly large infrared intensity. At 6.2,7.6,7.8, and 8.6 micrometer bands, cation molecule show complex C-C stretching and shrinking mixing modes and remain large infrared emission. Whereas, neutral molecule gives harmonic motion, which cancelles each other resulting very small infrared intensity. At 11.3 micrometer, both neutral and cation molecules show C-H bending motion perpendicular to a molecular plane, which contributes to strong emission. Actual observed spectrum would be a sum of such quantum-mechanic origined molecules.
We theoretically investigate the plasmonic properties of mid-infrared graphene-based metamaterials and apply deep learning of a neural network for the inverse design. These artificial structures have square periodic arrays of graphene plasmonic resonators deposited on dielectric thin films. Optical spectra vary significantly with changes in structural parameters. Our numerical results are in accordance with previous experiments. Then, the theoretical approach is employed to generate data for training and testing deep neural networks. By merging the pre-trained neural network with the inverse network, we implement calculations for inverse design of the graphene-based metameterials. We also discuss the limitation of the data-driven approach.
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