404 research outputs found
spin-state and metal coordination revealed from resonant inelastic X-ray scattering and electronic structure calculations
The local electronic structure of the cobalt centre-ion of Co(III)
protoporphyrin IX chloride dissolved in dimethyl sulfoxide (DMSO) liquid
solution is studied by resonant inelastic X-ray scattering (RIXS) spectroscopy
at the cobalt L-edge. The resulting cobalt 2p partial-fluorescence-yield (PFY)
X-ray absorption (XA) spectrum, integrated from RIXS spectra, is simulated for
various possible spin-states and coordination of the cobalt centre by using
the newly developed density functional theory/restricted open shell single
excitation configuration interaction (DFT/ROCIS) method. Comparison between
experiment and calculation shows that the cobalt ion (3d6 electronic
configuration) adopts a low-spin state with all six 3d electrons paired, and
the cobalt centre is either 5-coordinated by its natural ligands (one chloride
ion and four nitrogen atoms), or 6-coordinated, when binding to an oxygen atom
of a DMSO solvent molecule. Analysis of the measured RIXS spectra reveals weak
3d–3d electron correlation, and in addition a value of the local HOMO–LUMO gap
at the Co sites is obtained
oxygen K-edge X-ray absorption and emission spectroscopy on micro-jets
Oxygen K-edge X-ray absorption, emission, and resonant inelastic X-ray
scattering spectra were measured to site selectively gain insights into the
electronic structure of aqueous zinc acetate solution. The character of the
acetate ion and the influence of zinc and water on its local electronic
structure are discussed
The structure of the ternary Eg5–ADP–ispinesib complex
The human kinesin Eg5 is responsible for bipolar spindle formation during early mitosis. Inhibition of Eg5 triggers the formation of monoastral spindles, leading to mitotic arrest that eventually causes apoptosis. There is increasing evidence that Eg5 constitutes a potential drug target for the development of cancer chemotherapeutics. The most advanced Eg5-targeting agent is ispinesib, which exhibits potent antitumour activity and is currently in multiple phase II clinical trials. In this study, the crystal structure of the Eg5 motor domain in complex with ispinesib, supported by kinetic and thermodynamic binding data, is reported. Ispinesib occupies the same induced-fit pocket in Eg5 as other allosteric inhibitors, making extensive hydrophobic interactions with the protein. The data for the Eg5-ADP-ispinesib complex suffered from pseudo-merohedral twinning and revealed translational noncrystallographic symmetry, leading to challenges in data processing, space-group assignment and structure solution as well as in refinement. These complications may explain the lack of available structural information for this important agent and its analogues. The present structure represents the best interpretation of these data based on extensive data-reduction, structure-solution and refinement trials
All-optical image denoising using a diffractive visual processor
Image denoising, one of the essential inverse problems, targets to remove
noise/artifacts from input images. In general, digital image denoising
algorithms, executed on computers, present latency due to several iterations
implemented in, e.g., graphics processing units (GPUs). While deep
learning-enabled methods can operate non-iteratively, they also introduce
latency and impose a significant computational burden, leading to increased
power consumption. Here, we introduce an analog diffractive image denoiser to
all-optically and non-iteratively clean various forms of noise and artifacts
from input images - implemented at the speed of light propagation within a thin
diffractive visual processor. This all-optical image denoiser comprises passive
transmissive layers optimized using deep learning to physically scatter the
optical modes that represent various noise features, causing them to miss the
output image Field-of-View (FoV) while retaining the object features of
interest. Our results show that these diffractive denoisers can efficiently
remove salt and pepper noise and image rendering-related spatial artifacts from
input phase or intensity images while achieving an output power efficiency of
~30-40%. We experimentally demonstrated the effectiveness of this analog
denoiser architecture using a 3D-printed diffractive visual processor operating
at the terahertz spectrum. Owing to their speed, power-efficiency, and minimal
computational overhead, all-optical diffractive denoisers can be transformative
for various image display and projection systems, including, e.g., holographic
displays.Comment: 21 Pages, 7 Figure
Delineation of the TRAK binding regions of the kinesin-1 motor proteins
Understanding specific cargo distribution in differentiated cells is a major challenge. Trafficking kinesin proteins (TRAKs) are kinesin adaptors. They bind the cargo binding domain of kinesin-1 motor proteins forming a link between the motor and their cargoes. To refine the TRAK1/2 binding sites within the kinesin-1 cargo domain, rationally designed C-terminal truncations of KIF5A and KIF5C were generated and their co-association with TRAK1/2 determined by quantitative co-immunoprecipitations following co-expression in mammalian cells. Three contributory regions forming the TRAK2 binding site within KIF5A and KIF5C cargo binding domains were delineated. Differences were found between TRAK1/2 with respect to association with KIF5A
Training deep neural density estimators to identify mechanistic models of neural dynamics
Mechanistic modeling in neuroscience aims to explain observed phenomena in terms of underlying causes. However, determining which model parameters agree with complex and stochastic neural data presents a significant challenge. We address this challenge with a machine learning tool which uses deep neural density estimators—trained using model simulations—to carry out Bayesian inference and retrieve the full space of parameters compatible with raw data or selected data features. Our method is scalable in parameters and data features and can rapidly analyze new data after initial training. We demonstrate the power and flexibility of our approach on receptive fields, ion channels, and Hodgkin–Huxley models. We also characterize the space of circuit configurations giving rise to rhythmic activity in the crustacean stomatogastric ganglion, and use these results to derive hypotheses for underlying compensation mechanisms. Our approach will help close the gap between data-driven and theory-driven models of neural dynamics
Hybrid plasmonic nanostructures for enhanced single-molecule detection sensitivity
Biosensing applications based on fluorescence detection often require single-molecule sensitivity in the presence of strong background signals. Plasmonic nanoantennas are particularly suitable for these tasks, as they can confine and enhance light in volumes far below the diffraction limit. The recently introduced antenna-in-box (AiB) platforms achieved high single-molecule detection sensitivity at high fluorophore concentrations by placing gold nanoantennas in a gold aperture. However, hybrid AiB platforms with alternative aperture materials such as aluminum promise superior performance by providing better background screening. Here, we report on the fabrication and optical characterization of hybrid AiBs made of gold and aluminum for enhanced single-molecule detection sensitivity. We computationally optimize the optical properties of AiBs by controlling their geometry and materials and find that hybrid nanostructures not only improve signal-to-background ratios but also provide additional excitation intensity and fluorescence enhancements. We further establish a two-step electron beam lithography process to fabricate hybrid material AiB arrays with high reproducibility and experimentally validate the higher excitation and emission enhancements of the hybrid nanostructures as compared to their gold counterpart. We foresee that biosensors based on hybrid AiBs will provide improved sensitivity beyond the capabilities of current nanophotonic sensors for a plethora of biosensing applications ranging from multicolor fluorescence detection to label-free vibrational spectroscopy
A cost effectiveness analysis of salt reduction policies to reduce coronary heart disease in four Eastern Mediterranean countries.
BACKGROUND: Coronary Heart Disease (CHD) is rising in middle income countries. Population based strategies to reduce specific CHD risk factors have an important role to play in reducing overall CHD mortality. Reducing dietary salt consumption is a potentially cost-effective way to reduce CHD events. This paper presents an economic evaluation of population based salt reduction policies in Tunisia, Syria, Palestine and Turkey. METHODS AND FINDINGS: Three policies to reduce dietary salt intake were evaluated: a health promotion campaign, labelling of food packaging and mandatory reformulation of salt content in processed food. These were evaluated separately and in combination. Estimates of the effectiveness of salt reduction on blood pressure were based on a literature review. The reduction in mortality was estimated using the IMPACT CHD model specific to that country. Cumulative population health effects were quantified as life years gained (LYG) over a 10 year time frame. The costs of each policy were estimated using evidence from comparable policies and expert opinion including public sector costs and costs to the food industry. Health care costs associated with CHDs were estimated using standardized unit costs. The total cost of implementing each policy was compared against the current baseline (no policy). All costs were calculated using 2010 PPP exchange rates. In all four countries most policies were cost saving compared with the baseline. The combination of all three policies (reducing salt consumption by 30%) resulted in estimated cost savings of 39,000,000 and 31674 LYG in Syria; 1,3000,000,000 and 378439 LYG in Turkey. CONCLUSION: Decreasing dietary salt intake will reduce coronary heart disease deaths in the four countries. A comprehensive strategy of health education and food industry actions to label and reduce salt content would save both money and lives
Tribo-mechanical properties evaluation of HA/TiO2/CNT nanocomposite
In this study, a combination of reverse microemulsion and hydrothermal techniques were used to synthesize HA. A hydrothermal method was used to synthesize HA/TiO2/CNT nanocomposite powders. Cold and hot isostatic pressing techniques were used to fabricate tablet-shaped samples. To investigate the biocompatibility and tribo-mechanical properties of HA/TiO2 and HA/TiO2/CNTs, four samples were prepared with different percentages of CNTs, namely, HA/TiO2 (S0), HA/TiO2/CNT (S1.0), HA/TiO2/CNT (S2.0), and HA/TiO2/CNT (S3.0). The microstructure and morphology of the HA/TiO2/CNTs were characterized by transmission electron microscopy, scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction. Hardness test results show that S3.0 displayed the highest surface hardness (285 HV) compared to other samples. The wear rate of HA/TiO2/CNT with the highest CNT content showed a decrease compared with those of the other samples. The results from nanoindentation tests showed that Young's modulus of the S3.0 sample was 58.1% greater than that of the S0 sample. Furthermore, the human MDA-MB-231 cell line demonstrated good binding to the surface of the samples in the in-vitro biocompatibility evaluation of the HA/TiO2/CNT composites. 2021, The Author(s).This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2020R1A4A1019074).Scopu
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