Small Molecule Inhibitors Targeting the Interaction of Ricin Toxin A Subunit with Ribosomes
Explore the source record for details and available documents.
SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Synthetic aperture radar (SAR) along-track interferometry (ATI) is a technique for sensing Earth-surface motion. The technique involves interferometrically combining data from two radar images acquired from phase centers separated along the platform flight track.
Protein analysis of small numbers of human cells is primarily achieved by targeted proteomics with antibody-based immunoassays, which have inherent limitations (e.g., low multiplex and unavailability of antibodies for new proteins). Mass spectrometry (MS)-based targeted proteomics has emerged as an alternative because it is antibody-free, high multiplex, and has high specificity and quantitation accuracy. Recent advances in MS instrumentation make MS-based targeted proteomics possible for multiplexed quantification of highly abundant proteins in single cells. However, there is a technical challenge for effective processing of single cells with minimal sample loss for MS analysis. To address this issue, we have recently developed a convenient protein carrier-assisted one-pot sample preparation coupled with liquid chromatography (LC) - selected reaction monitoring (SRM) termed cLC-SRM for targeted proteomics analysis of small numbers of human cells. This method capitalizes on using the combined excessive exogenous protein as a carrier and low-volume one-pot processing to greatly reduce surface adsorption losses as well as high-specificity LC-SRM to effectively address the increased dynamic concentration range due to the addition of exogeneous carrier protein. Its utility has been demonstrated by accurate quantification of most moderately abundant proteins in small numbers of cells (e.g., 10-100 cells) and highly abundant proteins in single cells. The easy-to-implement features and no need for specific devices make this method readily accessible to most proteomics laboratories. In this study, we have provided a detailed protocol for cLC-SRM analysis of small numbers of human cells including cell sorting, cell lysis and digestion, LC-SRM analysis, and data analysis. Further improvements in detection sensitivity and sample throughput are needed towards targeted single-cell proteomics analysis. We anticipate that cLC-SRM will be broadly applied to biomedical research and systems biology with the potential of facilitating precision medicine.
Comparisons were made between subscenes from the first TM scene acquired of the Washington, D.C. area and a MSS scene acquired approximately one year earlier. Three types of analyses were conducted to compare TM and MSS data: a water body analysis, a principal components analysis and a spectral clustering analysis. The water body analysis compared the capability of the TM to the MSS for detecting small uniform targets. Of the 59 ponds located on aerial photographs 34 (58%) were detected by the TM with six commission errors (15%) and 13 (22%) were detected by the MSS with three commission errors (19%). The smallest water body detected by the TM was 16 meters; the smallest detected by the MSS was 40 meters. For the principal components analysis, means and covariance matrices were calculated for each subscene, and principal components images generated and characterized. In the spectral clustering comparison each scene was independently clustered and the clusters were assigned to informational classes. The preliminary comparison indicated that TM data provides enhancements over MSS in terms of (1) small target detection and (2) data dimensionality (even with 4-band data). The extra dimension, partially resultant from TM band 1, appears useful for built-up/non-built-up area separation.
In high precision flight maneuvres a pilot is a part of a closed loop pilot/aircraft system. The assessment of the flying qualities is highly dependent on the closed loop characteristics related to precision maneuvres like approach, landing, air-to-air tracking, air-to-ground tracking, close formation flying and air-to air refueling of the receiver. The object of a research program at DFVLR is the final flight phase of an air to ground mission. In this flight phase the pilot has to align the aircraft with the target, correct small deviations from the target direction and keep the target in his sights for a specific time period. To investigate the dynamic behavior of the pilot-aircraft system a special ground attack flight test technique with a prolonged tracking maneuvres was developed. By changing the targets during the attack the pilot is forced to react continously on aiming errors in his sights. Thus the closed loop pilot/aircraft system is excited over a wide frequency range of interest, the pilot gets more information about mission oriented aircraft dynamics and suitable flight test data for a pilot/aircraft analysis can be generated.
The formation of tektites in general and layered tektites in particular seems to require a very special kind of cratering event. Evidence for the formation of pools of melt free of unmelted clasts has not been reported for the well-studied terrestrial craters such as Manicouagan or Ries. It is suggested that large amounts of relict-free melt were produced only when a sizeable fraction of the cratered target consisted of dry, high-porosity materials such as aeolian sediments. Since dry, high-porosity target materials are always confined to the outer 100 to 200 m of the Earth, the fraction of melt produced melt is probably higher in small (radius 50 to 500 m) craters than in large (r greater than 1 km) craters. Another reason to infer that the Southeast Asian tektites were produced in a multitude of small craters is the wide distribution of layered tektites. The file spans at least 1200 km, which would require ballistic ejection at velocities greater than 2 km s(-1) if all melt was generated in a single crater. It seems impossible to devise a scenario that would lead to the deposition of primary melt as a crystal-free pool at a distance of 600 km from the crater.
Two-color laser-ranging systems can be used to estimate the atmospheric delay by measuring the difference in propagation times between two optical pulses transmitted at different wavelengths. This paper describes horizontal-path ranging experiments that were conducted using flat diffuse targets and cube-corner reflector arrays. Measurements of the timing accuracy of the cross-correlation estimator, atmospheric delay, received pulse shapes, and signal power spectra are presented. The results are in general agreement with theory and indicate that target speckle can be the dominant noise source when the target is small and is located far from the ranging system or when the target consists of a small number of cube-corner reflectors.
Explore the source record for details and available documents.
Aldehyde dehydrogenases (ALDHs) are promising cancer drug targets, as certain isoforms are required for the survival of stem-like tumor cells. We have discovered selective inhibitors of ALDH1B1, a mitochondrial enzyme that promotes colorectal and pancreatic cancer. We describe bicyclic imidazoliums and guanidines that target the ALDH1B1 active site with comparable molecular interactions and potencies. Both pharmacophores abrogate ALDH1B1 function in cells; however, the guanidines circumvent an off-target mitochondrial toxicity exhibited by the imidazoliums. Our lead isoform-selective guanidinyl antagonists of ALDHs exhibit proteome-wide target specificity, and they selectively block the growth of colon cancer spheroids and organoids. Finally, we have used genetic and chemical perturbations to elucidate the ALDH1B1-dependent transcriptome, which includes genes that regulate mitochondrial metabolism and ribosomal function. Our findings support an essential role for ALDH1B1 in colorectal cancer, provide molecular probes for studying ALDH1B1 functions and yield leads for developing ALDH1B1-targeting therapies.
Here, a model developed to represent the progress of erosion damage in liquid-metal spallation target vessels was modified to incorporate the effect of gas injection on the erosion rate. The liquid mercury target system for the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory now operates with helium gas injection to reduce target vessel fatigue stress and cavitation-induced erosion damage. Erosion damage is a primary degradation phenomenon affecting the service life of SNS target vessels, and cavitation mitigation techniques, such as small-bubble gas injection, have been implemented to reduce damage and extend target lifetimes. Erosion depths in samples removed from SNS targets after operation were measured using laser line scanning. These measurements confirmed that gas injection reduced erosion damage. However, quantifying the damage reduction due to gas injection was complicated by variations in lifetime, power, and gas injection rates between different targets. In this study, the operating power and gas injection rate of targets were incorporated into an erosion damage prediction model to quantify their effects on erosion damage reduction. Values of a power scaling factor, β, were calculated by comparing modeled with measured erosion damage. These values indicate that the use of gas injection at the SNS reduced damage to a level equivalent to operating targets without gas injection at 35–47% of the actual beam power. To account for the gas injection effect on the cavitation damage, a simple exponential form based on analysis of the scaling factor β was developed to incorporate the gas rate history with a scaling factor γ in the erosion damage modeling.
Radiation quality effects are largely determined by energy deposition in small volumes of characteristic sizes less than 10 nm representative of short-segments of DNA, the DNA nucleosome, or molecules initiating oxidative stress in the nucleus, mitochondria, or extra-cellular matrix. On this scale, qualitatively distinct types of molecular damage are possible for high linear energy transfer (LET) radiation such as heavy ions compared to low LET radiation. Unique types of DNA lesions or oxidative damages are the likely outcome of the energy deposition. The frequency distribution for energy imparted to 1-20 nm targets per unit dose or particle fluence is a useful descriptor and can be evaluated as a function of impact parameter from an ions track. In this work, the simulation of 1-Gy irradiation of a cubic volume of 5 micron by: 1) 450 (1)H(+) ions, 300 MeV; 2) 10 (12)C(6+) ions, 290 MeV/amu and 3) (56)Fe(26+) ions, 1000 MeV/amu was done with the Monte-Carlo simulation code RITRACKS. Cylindrical targets are generated in the irradiated volume, with random orientation. The frequency distribution curves of the energy deposited in the targets is obtained. For small targets (i.e. <25 nm size), the probability of an ion to hit a target is very small; therefore a large number of tracks and targets as well as a large number of histories are necessary to obtain statistically significant results. This simulation is very time-consuming and is difficult to perform by using the original version of RITRACKS. Consequently, the code RITRACKS was adapted to use multiple CPU on a workstation or on a computer cluster. To validate the simulation results, similar calculations were performed using targets with fixed position and orientation, for which experimental data are available [5]. Since the probability of single- and double-strand breaks in DNA as function of energy deposited is well know, the results that were obtained can be used to estimate the yield of DSB, and can be extended to include other targeted or non-target effects.
Abstract Background Nitrate (NO 3 − ) is one of the two major forms of inorganic nitrogen absorbed by plant roots, and the tissue nitrate concentration in roots is considered important for optimizing developmental programs. Technologies to quantify the expression levels of nitrate transporters and assimilating enzymes at the cellular level have improved drastically in the past decade. However, a technological gap remains for detecting nitrate at a high spatial resolution. Using extraction-based methods, it is challenging to reliably estimate nitrate concentration from a small volume of cells (i.e., with high spatial resolution), since targeting a small or specific group of cells is physically difficult. Alternatively, nitrate detection with microelectrodes offers subcellular resolution with high cell specificity, but this method has some limitations on cell accessibility and detection speed. Finally, optical nitrate biosensors have very good ( in-vivo ) sensitivity (below 1 mM) and cellular-level spatial resolution, but require plant transformation, limiting their applicability. In this work, we apply Raman microspectroscopy for high-dynamic range in-vivo mapping of nitrate in different developmental zones of Arabidopsis thaliana roots in-situ . Results As a proof of concept, we have used Raman microspectroscopy for in-vivo mapping of nitrate content in roots of Arabidopsis seedlings grown on agar media with different nitrate concentrations. Our results revealed that the root nitrate concentration increases gradually from the meristematic zone (~ 250 µm from the root cap) to the maturation zone (~ 3 mm from the root cap) in roots grown under typical growth conditions used for Arabidopsis, a trend that has not been previously reported. This trend was observed for plants grown in agar media with different nitrate concentrations (0.5–10 mM). These results were validated through destructive measurement of nitrate concentration. Conclusions We present a methodology based on Raman microspectroscopy for in-vivo label-free mapping of nitrate within small root tissue volumes in Arabidopsis. Measurements are done in-situ without additional sample preparation. Our measurements revealed nitrate concentration changes from lower to higher concentration from tip to mature root tissue. Accumulation of nitrate in the maturation zone tissue shows a saturation behavior. The presented Raman-based approach allows for in-situ non-destructive measurements of Raman-active compounds.
We consider the differential cross-section for single-inclusive jet production with transverse momentum 𝑃 ⊥ in deep inelastic scattering at small Bjorken 𝑥 Bj , mediated by a virtual photon with virtuality 𝑄 2 . Unlike most studies at small 𝑥, which focus on particle production in the current fragmentation region, we investigate the kinematic regime where the jet is produced in the target fragmentation hemisphere of the Breit frame, and with 𝑃 ⊥ ≪ 𝑄. For a longitudinally polarized photon, we demonstrate that this cross section is not power suppressed in 𝑃 ⊥ /𝑄 and we derive a factorized expression in terms of extended quark and gluon jet fracture functions. Our formula, valid at next-to-leading order in 𝛼 𝑠 at small 𝑥, is akin to the Altarelli-Martinelli identity for the longitudinal DIS structure function. Numerical estimates show that the extended quark jet fracture function is the most sensitive to saturation effects in large nuclei.
Software simulators play a critical role in the development of new algorithms and system architectures in any field of engineering. Neuromorphic computing, which has shown potential in building brain-inspired energy-efficient hardware, suffers a slow-down in the development cycle due to a lack of flexible and easy-to-use simulators of either neuromorphic hardware itself or of spiking neural networks (SNNs), the type of neural network computation executed on most neuromorphic systems. While there are several openly available neuromorphic or SNN simulation packages developed by a variety of research groups, they have mostly targeted computational neuroscience simulations, and only a few have targeted small-scale machine learning tasks with SNNs. Evaluations or comparisons of these simulators have often targeted computational neuroscience-style workloads. In this work, we seek to evaluate the performance of several publicly available SNN simulators with respect to non-computational neuroscience workloads, in terms of speed, flexibility, and scalability. We evaluate the performance of the NEST, Brian2, Brian2GeNN, BindsNET and Nengo packages under a common front-end neuromorphic framework. Our evaluation tasks include a variety of different network architectures and workload types to mimic the computation common in different algorithms, including feed-forward network inference, genetic algorithms, and reservoir computing. We also study the scalability of each of these simulators when running on different computing hardware, from single core CPU workstations to multi-node supercomputers. Our results show that the BindsNET simulator has the best speed and scalability for most of the SNN workloads (sparse, dense, and layered SNN architectures) on a single core CPU. However, when comparing the simulators leveraging the GPU capabilities, Brian2GeNN outperforms the others for these workloads in terms of scalability. NEST performs the best for small sparse networks and is also the most flexible simulator in terms of reconfiguration capability NEST shows a speedup of at least 2x compared to the other packages when running evolutionary algorithms for SNNs. The multi-node and multi-thread capabilities of NEST show at least 2x speedup compared to the rest of the simulators (single core CPU or GPU based simulators) for large and sparse networks. We conclude our work by providing a set of recommendations on the suitability of employing these simulators for different tasks and scales of operations. We also present the characteristics for a future generic ideal SNN simulator for different neuromorphic computing workloads.