Target highlights in CASP14: Analysis of models by structure providers
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Alexander, Leila T.↗
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Unlocking the Spacecraft and Human Habitat Microbiome to Enable the Next Generation of Space Exploration
Planetary protection is the discipline that prevents harmful contamination of the solar system during exploration activities. The current international guidelines and NASA policy addressing biological contamination on spacecraft surfaces contains prescriptive guidelines of spore requirements (e.g., 300 spores/m2, 5×105 spores per spacecraft) applicable to spacecraft bound for Mars. To verify these requirements spacecraft engineers sample spacecraft surfaces throughout the assembly, test and launch operations phase of the mission using damp water cotton swabs and polyester wipes. After sampling, the potential biological contamination is enumerated using a series of traditional microbiology techniques to include sonication, heat shocking at 80°C for 15min to select for spores, and growth on tryptic soy agar at 32°C for 72 hours. To enable crewed missions to Mars and robotic exploration of the Ocean Worlds a risk informed decision making / performance-based approach to assess biological contamination offers a promising solution in the trade space. Recognizing the need for a performance-based approach, NASA’s new Planetary Protection policies now incorporate the agility for missions to be able to leverage a performance or prescriptive approach. One of top contenders in the option space is a coupled quantitative, descriptive and functional based approach to be able to assess the quantity, types and capabilities of the biological contamination present on spacecraft surfaces. A tailored, mission by mission assurance case could then be formulated by building an argument around the target body, projected capabilities surrounding the types of organisms their potential for survival and proliferation, and ability to be transported on the target body to contaminate an area of biological interest. A performance-based requirement would then be used to demonstrate the mission’s compliance in protecting the planetary environment safety objectives. This symposium talk will showcase the background and need case for NASA to develop such a capability as well as provide an update on the efforts underway in developing a transparent and responsible performance-based approach to biological contamination assessments on spacecraft surfaces.
Habitat Microbiome↗
An Electrochemical Electrode to Detect Theophylline Based on Copper Oxide Nanoparticles Composited with Graphene Oxide
The electrochemical analysis of theophylline (THP) was investigated by fabricating a carbon paste electrode (CPE) modified with graphene oxide (GO) along with copper oxide (CuO) nanoparticles (CuO-GO/CPE). The impact of electro-kinetic parameters such as the heterogeneous rate constant, the scan rate, the accumulation time, the pH, the transfer coefficient, and the number of electrons and protons transferred into the electro-oxidation mechanism of THP has been studied utilizing electrochemical methods such as cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The differential pulse voltammetry technique was employed to investigate THP in pharmaceutical and biological samples, confirming the limit of detection (LOD) and quantification (LOQ) of the THP. X-ray diffraction (XRD) and scanning electron microscopy (SEM) analysis were performed to characterize the CuO nanoparticles. The CuO-GO/CPE was more sensitive in THP detection because its electrocatalytic characteristics displayed an enhanced peak current in the 0.2 M supporting electrolyte of pH 6.0, proving the excellent sensing functioning of the modified electrode.
36 MATERIALS SCIENCE↗
Function, Structure, and Regulation of Nitrogen Fixation-like Metalloproteins for Nitrogen, Energy, Carbon, and Sulfur Metabolism
Nitrogenases (N 2 ases) and nitrogen fixation-like (NFL) systems play distinct roles in nitrogen, carbon, sulfur, and energy metabolism based on their fundamental differences in structure and metallocofactor identity. As new NFL systems have recently been identified and characterized, striking parallels and differences compared to N 2 ase structure, catalysis, and regulation have emerged. NFL systems use metallocofactors that span from simple [4Fe-4S] clusters to complex clusters akin to FeMo-co, previously only thought to occur in N 2 ase. This review describes the present state of knowledge on the function, structure, catalytic mechanisms, and regulation of NFL systems that perform distinct biological roles across all three domains of life. Recent advancements in N 2 ase spectroscopic techniques for probing metallocofactor structure and electronic states guide current and future work on how each NFL system catalyzes its specific biological reaction(s). Key knowledge gaps and needed areas of research for uncovering the specific metallocofactors and structural motifs that are at the heart of NFL system reaction specificity, along with how these systems are regulated, are discussed.
Bacteria↗
3P Program: Phenotyping X Prediction = Productivity (Final Scientific/Technical Report)
The goal of the 3P Program was to establish integrated, real-time phenotyping and to analyze above- and below-ground plant architecture and total carbon partitioning and allocation to predict heterosis and develop superior crop hybrids by fully leveraging the Sorghum gene pool. There were two overarching themes: 1) the development of a new crop improvement approach utilizing advances in high-throughput phenotyping (HTP), computing, and genomics for public dissemination and 2) leveraging this platform for sorghum crop improvement and commercialization. The Clemson team worked on creating genomic resources and using both statistical learning and high-throughput phenotyping in genomics-assisted breeding. Research was broadly interested in the genetics of carbon partitioning, with the aim of improving crop performance and achieving sustainability. The technology and resources created can be readily found in the public domain and serve to advance scientific understanding of crop genomics and breeding. Genomic prediction was able to identify top crosses to be made, and a hybrid prediction pipeline is in place to drive year-over-year genetic gain. Roots have long been ignored by plant breeders and agronomists, not because they are unimportant but because they are hard to measure. This is an untapped white space of potential insight and innovation. To address this, Hi Fidelity Genetics developed the RootTracker to measure roots in the field on a continuous basis. A database system called RootTracker Tracker was developed to handle data coming from the RootTrackers. In using this device, valuable data was observed for plant breeding, hydrochemical development, and other agricultural biology applications. Carnegie Mellon’s goal was developing new techniques to generate high-resolution 3D models of plants from data collected in the field. The idea was that more useful and more informative phenotypes could be extracted by resolving small features, such as seeds and flowers, and that by modeling in 3D, the spatial structure of plants could be examined. To achieve this, multiple images collected by a new small format structured light stereo imager were fused together. A sorghum panicle modeling pipeline was developed to allow the collection and processing of data. Carolina Seed Systems is an agricultural technology company focused on decarbonizing the agricultural system. Their technology pipeline serves to drive fundamental progress towards creation and distribution of carbon negative crops. The genomic and the engineering technology developed through the 3P Program was leveraged to deliver both value and sustainability from the grower to the consumer. Promising sorghum hybrids were scaled up and commercialized. The overall goal of our research was to integrate, create, and deploy genetic and engineering concepts and technologies to enhance crop productivity in a sustainable fashion. The combination of public and private partners allowed the basic research and hypothesis testing to be quickly accelerated for commercial application by the companies yet maintained that the core framework and academic insights remain in the public domain for continued market disruption, competition, and innovation.
59 BASIC BIOLOGICAL SCIENCES↗
2022 AI Testbed Expeditions Report
By exploiting the coherent properties of a light source, coherent diffraction imaging (CDI) is able to obtain the sample image at a nanoscale resolution using the measured diffraction pattern. Bragg Coherent Diffraction Imaging (BCDI) has become valuable for recovering the displacement and strain field of crystals, providing a valuable tool in material science and solid-state physics. X-ray ptychography is another emerging CDI technique that can produce a high-resolution image of the extended sample and has become popular in many research areas (e.g., materials science, biology, electronics, and optics characterization). CDI including BCDI and ptychography has become an established technique in Synchrotron Facilities including the Advanced Photon Source (APS) and will greatly benefit from the 100x coherent flux increase of the upcoming APS Upgrade (APSU). The current image formation process in CDI employs iterative phase retrieval algorithms, which is a time-consuming and computationally expensive process. Especially after APSU, the traditional iterative methods will not be able to match the experimental data acquisition speed. We employ deep learning (DL) approach to replace the iterative approaches, therefore allowing hundreds of times faster recovery of the object. We developed AutoPhaseNN, a DL-based approach which learns to solve the inverse problem without labeled data. Taking 3D BCDI as a representative technique, AutoPhaseNN has been demonstrated to be one hundred times faster than traditional iterative phase retrieval methods while providing comparable image quality. The current network is trained with 64 x 64 x 64 data size, to achieve higher resolution imaging, we will need to scale the network to input and train/infer 3D arrays of size 256 x 256 x 256 (today) and of size 2560x2560x2560 (APSU). However, the scalability of the network is restricted due to the memory-intensive training process. To perform the training for a 256 x 256 x 256 data size, the required memory exceeds the capacity of the current machine. In this project, we explore using Sambanova system to train the network for the direct data inversion for CDI.
36 MATERIALS SCIENCE↗
A Novel Non‐Destructive Rapid Tool for Estimating Amino Acid Composition and Secondary Structures of Proteins in Solution
Abstract Amino‐acid protein composition plays an important role in biology, medicine, and nutrition. Here, a groundbreaking protein analysis technique that quickly estimates amino acid composition and secondary structure across various protein sizes, while maintaining their natural states is introduced and validated. This method combines multivariate statistics and the thermostable Raman interaction profiling (TRIP) technique, eliminating the need for complex preparations. In order to validate the approach, the Raman spectra are constructed of seven proteins of varying sizes by utilizing their amino acid frequencies and the Raman spectra of individual amino acids. These constructed spectra exhibit a close resemblance to the actual measured Raman spectra. Specific vibrational modes tied to free amino and carboxyl termini of the amino acids disappear as signals linked to secondary structures emerged under TRIP conditions. Furthermore, the technique is used inversely to successfully estimate amino acid compositions and secondary structures of unknown proteins across a range of sizes, achieving impressive accuracy ranging between 1.47% and 5.77% of root mean square errors (RMSE). These results extend the uses for TRIP beyond interaction profiling, to probe amino acid composition and structure.
Chemistry↗
Emerging multiscale insights on microbial carbon use efficiency in the land carbon cycle
Microbial carbon use efficiency (CUE) affects the fate and storage of carbon in terrestrial ecosystems, but its global importance remains uncertain. Accurately modeling and predicting CUE on a global scale is challenging due to inconsistencies in measurement techniques and the complex interactions of climatic, edaphic, and biological factors across scales. The link between microbial CUE and soil organic carbon relies on the stabilization of microbial necromass within soil aggregates or its association with minerals, necessitating an integration of microbial and stabilization processes in modeling approaches. In this perspective, we propose a comprehensive framework that integrates diverse data sources, ranging from genomic information to traditional soil carbon assessments, to refine carbon cycle models by incorporating variations in CUE, thereby enhancing our understanding of the microbial contribution to carbon cycling.
54 ENVIRONMENTAL SCIENCES↗
Using electron energy-loss spectroscopy to measure nanoscale electronic and vibrational dynamics in a TEM
Electron energy-loss spectroscopy (EELS) can measure similar information to x-ray, UV–Vis, and IR spectroscopies but with atomic resolution and increased scattering cross-sections. Recent advances in electron monochromators have expanded EELS capabilities from chemical identification to the realms of synchrotron-level core-loss measurements and to low-loss, 10–100 meV excitations, such as phonons, excitons, and valence structures. EELS measurements are easily correlated with electron diffraction and atomic-scale real-space imaging in a transmission electron microscope (TEM) to provide detailed local pictures of quasiparticle and bonding states. This perspective provides an overview of existing high-resolution EELS (HR-EELS) capabilities while also motivating the powerful next step in the field—ultrafast EELS in a TEM. Ultrafast EELS aims to combine atomic-level, element-specific, and correlated temporal measurements to better understand spatially specific excited-state phenomena. Ultrafast EELS measurements also add to the abilities of steady-state HR-EELS by being able to image the electromagnetic field and use electrons to excite photon-forbidden and momentum-specific transitions. We discuss the technical challenges ultrafast HR-EELS currently faces, as well as how integration with in situ and cryo measurements could expand the technique to new systems of interest, especially molecular and biological samples.
Chemistry↗
Broadband coherent anti-Stokes Raman scattering (BCARS) microscopy for rapid, label-free biological imaging
Broadband coherent anti-Stokes Raman scattering (BCARS) microscopy is a label-free imaging approach that provides detailed chemical information at high spatial resolution in a sample through nonlinear, coherent excitation of molecular vibrations and detection of Raman spectra. While its utility for biological imaging has been demonstrated, many aspects of this technique must mature before it can be widely adopted. One of the areas of required improvement is imaging speed—most BCARS implementations involve sample rastering, which limits imaging speed. Beam scanning can provide faster BCARS imaging but presents some unique challenges. Here, we describe a beam-scanning BCARS microscopy system that improves spatial resolution twofold and imaging speed by fivefold over a previous beam-scanning implementation. These enhancements were enabled by an improvement in supercontinuum power and the use of a sCMOS camera for its high data transfer rate and low read noise. Implementation of the sCMOS camera required correction for the significant pixel-to-pixel background and photon response nonuniformity. Here, we report on the method that we implemented for calibrating and correcting the pixel-to-pixel differences in sCMOS camera noise.
Dixon, Jessica Z. [Georgia Institute of Technology↗
Nanoscale chemical imaging with structured X-ray illumination
High-resolution imaging with compositional and chemical sensitivity is crucial for a wide range of scientific and engineering disciplines. Although synchrotron X-ray imaging through spectromicroscopy has been tremendously successful and broadly applied, it encounters challenges in achieving enhanced detection sensitivity, satisfactory spatial resolution, and high experimental throughput simultaneously. In this work, based on structured illumination, we develop a single-pixel X-ray imaging approach coupled with a generative image reconstruction model for mapping the compositional heterogeneity with nanoscale resolvability. This method integrates a full-field transmission X-ray microscope with an X-ray fluorescence detector and eliminates the need for nanoscale X-ray focusing and raster scanning. We experimentally demonstrate the effectiveness of our approach by imaging a battery sample composed of mixed cathode materials and successfully retrieving the compositional variations of the imaged cathode particles. Bridging the gap between structural and chemical characterizations using X-rays, this technique opens up vast opportunities in the fields of biology, environmental, and materials science, especially for radiation-sensitive samples.
Li, Jizhou↗
Imaging plant metabolism in situ
Abstract Mass spectrometry imaging (MSI) has emerged as an invaluable analytical technique for investigating the spatial distribution of molecules within biological systems. In the realm of plant science, MSI is increasingly employed to explore metabolic processes across a wide array of plant tissues, including those in leaves, fruits, stems, roots, and seeds, spanning various plant systems such as model species, staple and energy crops, and medicinal plants. By generating spatial maps of metabolites, MSI has elucidated the distribution patterns of diverse metabolites and phytochemicals, encompassing lipids, carbohydrates, amino acids, organic acids, phenolics, terpenes, alkaloids, vitamins, pigments, and others, thereby providing insights into their metabolic pathways and functional roles. In this review, we present recent MSI studies that demonstrate the advances made in visualizing the plant spatial metabolome. Moreover, we emphasize the technical progress that enhances the identification and interpretation of spatial metabolite maps. Within a mere decade since the inception of plant MSI studies, this robust technology is poised to continue as a vital tool for tackling complex challenges in plant metabolism.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Imaging Bragg Edge Analysis TooLs for Engineering Structures (iBeatles)
The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) provides pulsed neutrons with energies varying from epithermal to cold. In preparation for VENUS, the neutron imaging beamline to be located at beam port 10, we have performed a series of experiments focused on wavelength-dependent radiography and computed tomography for a broad range of applications, from materials science to biological tissues.One of the time-of-flight (TOF) techniques that is of interest to the scientific community is the 2-dimensional mapping of phases and average crystalline plane orientation in samples both ex-situ and during applied stresses such as tensile loading and heating. This technique is known as Bragg edgeimaging and relies on the identification of changes of transmission values, fitting of the edge to measure its displacement, and thus identify the shift in lattice parameter due to stresses. One of the challenges of TOF imaging measurements is the amount of data and the inability to observe Bragg edge shifts in real time during an experiment. Thus, we have been focusing on creating a Python-based interface that allows fast data processing and instantaneous mapping and fitting of the Bragg edges, and their evolution through time. Python libraries and Jupyter notebooks have been implemented to facilitate decision making during an experiment. The advantage of the notebooks is the possibility to guide an experiment as they can quickly process and display Bragg edge data. These notebooks can be used independently, or can be combined in a Python Graphical User Interface (GUI) tool called iBeatles. This interface permits visualization and fitting of the Bragg edges, and ultimately back-projects the fitting results onto the radiographs to display a strain map. Assuming data collection has sufficient statistics, the strain mapping analysis can be performed on a pixel-by-pixel basis. This development is a step forward toward a better user experience at the future VENUS beamline in terms of live feedback and productivity. Analysis that used to take days of switching between different applications can now be done in minutes within the
Bilheux, JeanChristophe [Oak Ridge National Labora↗
Leveraging Prior Concept Learning Improves Generalization From Few Examples in Computational Models of Human Object Recognition
Humans quickly and accurately learn new visual concepts from sparse data, sometimes just a single example. The impressive performance of artificial neural networks which hierarchically pool afferents across scales and positions suggests that the hierarchical organization of the human visual system is critical to its accuracy. These approaches, however, require magnitudes of order more examples than human learners. We used a benchmark deep learning model to show that the hierarchy can also be leveraged to vastly improve the speed of learning. We specifically show how previously learned but broadly tuned conceptual representations can be used to learn visual concepts from as few as two positive examples; reusing visual representations from earlier in the visual hierarchy, as in prior approaches, requires significantly more examples to perform comparably. These results suggest techniques for learning even more efficiently and provide a biologically plausible way to learn new visual concepts from few examples.
Rule, Joshua S.↗
Applications of spectroscopy to remote determination of water quality
The use of remote laser Raman and molecular spectroscopic techniques to measure water quality is examined. Measurements cover biological, chemical, and physical properties of the water. Experimental results show chemical properties are harder to obtain remotely than biological or physical properties and that molecular spectroscopy seems to be the best method for obtaining water quality data.
Goldberg, M. C.↗
Photoacoustic spectroscopy of condensed matter
Photoacoustic spectroscopy is a new analytical tool that provides a simple nondestructive technique for obtaining information about the electronic absorption spectrum of samples such as powders, semisolids, gels, and liquids. It can also be applied to samples which cannot be examined by conventional optical methods. Numerous applications of this technique in the field of inorganic and organic semiconductors, biology, and catalysis have been described. Among the advantages of photoacoustic spectroscopy, the signal is almost insensitive to light scattering by the sample and information can be obtained about nonradiative deactivation processes. Signal saturation, which can modify the intensity of individual absorption bands in special cases, is a drawback of the method.
Somoano, R. B.↗
Cell partition in two phase polymer systems
Aqueous phase-separated polymer solutions can be used as support media for the partition of biological macromolecules, organelles and cells. Cell separations using the technique have proven to be extremely sensitive to cell surface properties but application of the systems are limited to cells or aggregates which do not significantly while the phases are settling. Partition in zero g in principle removes this limitation but an external driving force must be applied to induce the phases to separate since their density difference disappears. We have recently shown that an applied electric field can supply the necessary driving force. We are proposing to utilize the NASA FES to study field-driven phase separation and cell partition on the ground and in zero g to help define the separation/partition process, with the ultimate goal being to develop partition as a zero g cell separation technique.
Brooks, D. E.↗
Free-Flow Open-Chamber Electrophoresis
Free-flow open-chamber electrophoresis variant of free-flow electrophoresis performed in chamber with open ends and in which velocity of electro-osmotic flow adjusted equal to and opposite mean electrophoretic velocity of sample. Particles having electrophoretic mobilities greater than mean mobility of sample particles move toward cathode, those with mobilities less move toward anode. Technique applied to separation of components of mixtures of biologically important substances. Sensitivity enhanced by use of tapered chamber.
Sharnez, Rizwan↗