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At least 145 records · Page 8

Magnetically responsive nanocultures for direct microbial assessment in soil environments

Cultivating microorganisms in native-like conditions is vital for bioprospecting and accessing now unculturable species. However, there remains a gap in scalable tools that can both mimic native microenvironments and enable targeted recovery of microbes from complex settings. Such approaches are essential to advance our understanding of microbial ecology, predict community functions, and discover previously unidentified biotherapeutics. We present magnetic nanocultures—a high-throughput microsystem for isolating and growing environmental microbes under near-native conditions. These nanoliter-scale bioreactors are encapsulated in semipermeable membranes that form magnetic polymeric microcapsules using iron oxide nanoparticles within polydimethylsiloxane-based shells. This design offers mechanical stability and magnetic actuation, enabling efficient retrieval from soil-like environments. The nanocultures are optimized for optical and biological properties to support microbial encapsulation, growth, and sorting. Our study demonstrates the feasibility of using magnetically responsive microenvironments to cultivate elusive microbes, offering a promising platform for bioprospecting previously uncultured or unknown microbial species.

Usman, Huda [Department of Chemical Engineering, C↗

ChemComp: A Compilation Framework for Computing with Chemical Reaction Networks

The acceleration of scientific computation, data analytics, and artificial intelligence is driving a surge in computational requirements. Yet, state-of-the-art high-performance computing systems are approaching physical limitations that impede further significant improvements in energy efficiency. As we move towards post-exascale computing systems, innovative approaches are necessary to overcome this barrier in power consumption. Novel analog and hybrid digital-analog architectures hold promise for enhancing energy efficiency by several orders of magnitude. Biochemical computation stands out among the various solutions being explored due to its potential to enable new classes of devices with immense computational capabilities. These devices can capitalize on the inherent efficacy of biological cells in solving optimization problems and are scalable through increasing reaction system size or vessel capacity, potentially satisfying scientific computing's high-performance requirements. Nonetheless, several theoretical and practical limitations persist, including problem formulation and mapping to chemical reaction networks (CRNs) and implementation of actual CRN devices. In this paper, we propose a framework for biochemical computation using systems chemistry. We present the initial components of our approach: an abstract chemical reaction dialect implemented as a multi-level intermediate representation (MLIR) compiler extension and a pathway to represent mathematical problems with CRNs. To showcase the potential of this approach, we emulate a simplified chemical reservoir device. This work lays the groundwork for leveraging chemistry's computing potential in creating energy-efficient, high-performance computing systems tailored to contemporary computational needs.

artificial intelligence↗

Open Source Visualization and Analysis Platform for 3D Reconstructions of Materials by Transmission Electron Microscopy

Three-dimensional characterization of materials at the nano- and meso-scale has become possible with transmission and scanning transmission electron microscopes (S/TEM). Its importance has extended to a wide class of nanomaterials such as hydrogen fuel cells, solar cells, industrial catalysts, new battery materials and semiconductor devices, as well as spanning high-tech industry, universities, and national labs. While capable instrumentation is abundant, this rapidly expanding demand for high-resolution tomography is bottlenecked by software that is instead tailored for lower-dose, biological applications and not optimized for higher-resolution materials applications. Existing tomography fails to utilize the chemical information provided by S/TEM spectrometers. To address this problem, this project delivered a scalable, fully functional, freely-distributable, open Source materials tomography package with a modern user interface that enables automated acquisition, alignment, and real-time reconstruction of raw tomography data, and provides advanced segmentation, three-dimensional chemical visualization and analysis optimized for materials applications. It has established an extendable framework capable of automation for high-throughput for the tomography of materials from data acquisition to visualization. Phase I and II delivered a full-featured, cross-platform, clean and integrated application for S/TEM materials tomography. It can read projection data from the microscope, with graphical tools for alignment of data, tomographic reconstruction, segmentation, and visualization of the reconstructed 3D volume. The entire pipeline can be saved to an XML state file, enabling fully reproducible data processing and analysis with a full Python environment for the development of custom algorithms, processing, and analysis requirements. Phase IIB extended the application to provide real-time tomographic reconstruction, "live updates" as data is processed, analysis of big data, and multi-channel tomography. Here, quantitative assessment of nanomaterials can occur as data is being recorded on a 3D visualization platform that accommodates additional information from multiple channels. We provide unmatched high-throughput tomography, where the complete tomographic pipeline from measurement to 3D visualization can occur rapidly. The project was extended to offer capabilities for micro-CT, X-ray, neutron, focused ion beam, atomic electron tomography and atom probe tomography. With over 600 transmission electron microscopes worldwide and approximately 50 coming online each year, the demand and impact of an open-source tomography tool is large. Significant opportunities exist in high-tech industry, universities, and national labs to enable or enhance three-dimensional imaging at the nanoscale and bring automated high-throughput approaches that will accelerate progress in materials characterization and metrology. The project supports a service based business model by enabling lab-specific acquisition and processing customization and integration-support and development that will be provided into Phase III and beyond.

36 MATERIALS SCIENCE↗

Process Optimization and Real-Time Control of Synergistic Microalgae Cultivation and Wastewater Treatment (Final Technical Report)

The overarching goal of this work was to accelerate the commercialization of high productivity, mixed community microalgal treatment technologies for the synergistic treatment of wastewater and the production of biofuel feedstocks. This project addressed a critical barrier to the financial viability and energy efficiency of algal wastewater treatment: an inability to design and operate high-rate processes that reliably achieve target effluent qualities, areal productivities, and biochemical compositions (lipid, protein, carbohydrate content) despite fluctuations in wastewater composition, weather, and microbial communities. Key outcomes from this work include an optimized and controlled Advanced Biological Nutrient Recovery (ABNR) design as well as a suite of open-source tools that include a calibrated and validated algae process simulator in QSDsan and a novel low-cost, real-time microbial monitoring tool. These tools can be leveraged by other algal cultivation and wastewater treatment technology developers in future work.

09 BIOMASS FUELS↗

Developing a Carbon Negative Biorefinery for Organic Waste Valorization

Production of bio-based chemicals have become increasingly attractive as efforts to meet carbon neutrality goals expand. Diverse organic waste feedstocks can be valorized via arrested anaerobic digestion and chain elongation to produce important key intermediates, such as medium chain carboxylic acids. Our work aims to develop a carbon negative biorefinery that funnels multiple organic waste feedstocks into a chemically consistent stream of carboxylic acids that are then upgraded to exemplary carbon negative products. The pairing of a hydrolysis reactor with a chain elongation reactor will allow each biological step to be optimized to improve the ability to valorize a variety of organic waste streams. Specifically, this work has so far been aimed at screening for potential chain elongating organisms to produce VFAs and MCCAs of interest. Four chain elongating organisms were tested for their chain elongation potential with diverse single and mixed substrates. So far, Megasphaera elsdenii and Actinobacillus succinogenes have been tested to determine potential differences in titer as well as product speciation due to variations in pH. To do this, each organism was tested under 3 different substrate combinations with pH maintained at either 5.5, 6, or 7. With better understanding of their metabolic needs and optimal operating conditions, these chain elongating organisms could provide a valuable option to facilitate the chain elongation necessary to produce precursor molecules. In addition to optimizing the bioconversion steps, downstream processing of carboxylic acids is also a key component for the overall feasibility of the process. Our group previously developed a downstream in-situ product recovery (ISPR) process for continuously recovering bio-based carboxylic acids from fermentation broth. The ISPR includes: (i) a solid-liquid separation as a cell retention device, (ii) a liquid-liquid extraction (LLE) to selectively extract the desired bio-based acids, and (iii) a distillation to obtain the neat product. The integrated process was demonstrated at bench-scale and is now scaled up for pilot-scale operations. A more cost-efficient membrane-based emulsion separation is introduced for LLE in downstream separation process with greatly promoted mass transfer, leading to -2800 times smaller needed membrane area than membrane contactors to achieve the same butyric acid extraction rate.

BIOMASS FUELS↗

WE-AB-207B-11: Optimizing Tumor Control Probability in Radiation Therapy Treatment - Application to HDR Cervical Cancer

Purpose: The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor-control-probability(TCP) with an acceptable normal-tissue-complication probability(NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. We design treatment plans that optimize TCP directly and contrast them with the clinical dose-based plans. PET image is incorporated to evaluate gain in TCP for dose escalation. Methods: We build a nonlinear mixed integer programming optimization model that maximizes TCP directly while satisfying the dose requirements on the targeted organ and healthy tissues. The solution strategy first fits the TCP function with a piecewise-linear approximation, then solves the problem that maximizes the piecewise linear approximation of TCP, and finally performs a local neighborhood search to improve the TCP value. To gauge the feasibility, characteristics, and potential benefit of PET-image guided dose escalation, initial validation consists of fifteen cervical cancer HDR patient cases. These patients have all received prior 45Gy of external radiation dose. For both escalated strategies, we consider 35Gy PTV-dose, and two variations (37Gy-boost to BTV vs 40Gy-boost) to PET-image-pockets. Results: TCP for standard clinical plans range from 59.4% - 63.6%. TCP for dose-based PET-guided escalated-dose-plan ranges from 63.8%–98.6% for all patients; whereas TCP-optimized plans achieves over 91% for all patients. There is marginal difference in TCP among those with 37Gy-boosted vs 40Gy-boosted. There is no increase in rectum and bladder dose among all plans. Conclusion: Optimizing TCP directly results in highly conformed treatment plans. The TCP-optimized plan is individualized based on the biological PET-image of the patients. The TCP-optimization framework is generalizable and has been applied successfully to other external-beam delivery modalities. A clinical trial is on-going to gauge the clinical significance. Partially supported by the National Science Foundation.

60 APPLIED LIFE SCIENCES↗

Genetic-evolution-based optimization methods for engineering design

This paper presents the applicability of a biological model, based on genetic evolution, for engineering design optimization. Algorithms embodying the ideas of reproduction, crossover, and mutation are developed and applied to solve different types of structural optimization problems. Both continuous and discrete variable optimization problems are solved. A two-bay truss for maximum fundamental frequency is considered to demonstrate the continuous variable case. The selection of locations of actuators in an actively controlled structure, for minimum energy dissipation, is considered to illustrate the discrete variable case.

Rao, S. S.↗

The Effect of Geometry, Spin, and Orbital Optimization in Achieving Accurate, Correlated Results for Iron–Sulfur Cubanes

Iron–sulfur clusters comprise an important functional motif in the catalytic centers of biological systems, capable of enabling important chemical transformations at ambient conditions. This remarkable capability derives from a notoriously complex electronic structure that is characterized by a high density of states that is sensitive to geometric changes. The spectral sensitivity to subtle geometric changes has received little attention from correlated, large active space calculations, owing partly to the exceptional computational complexity for treating these large and correlated systems accurately. Here, to provide insight into this aspect, we report the first Complete Active Space Self Consistent Field (CASSCF) calculations for different geometries of the [Fe(II/III) 4 S 4 (SMe) 4 ] -2 clusters using two complementary, correlated solvers: spin-pure Adaptive Sampling Configuration Interaction (ASCI) and Density Matrix Renormalization Group (DMRG). We find that the previously established picture of a double-exchange driven magnetic structure, with minute energy gaps (<1 mHa) between consecutive spin states, has a weak dependence on the underlying geometry. However, the spin gap between the singlet and the spin state 2S + 1 = 19, corresponding to a maximal number of Fe-d electrons being unpaired and of parallel spin, is strongly geometry dependent, changing by a factor of 3 upon slight deformations that are still within biologically relevant parameters. The CASSCF orbital optimization procedure, using active spaces as large as 86 electrons in 52 orbitals, was found to reduce this gap compared to typical mean-field orbital approaches. Our results show the need for performing large active space calculations to unveil the challenging electronic structure of these complex catalytic centers and should serve as accurate starting points for fully correlated treatments upon inclusion of dynamical correlation outside the active space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ultrafast Dynamics of Photosynthetic Light Harvesting: Strategies for Acclimation Across Organisms

Photosynthetic light harvesting exhibits near-unity quantum efficiency. The high efficiency is achieved through a series of energy and charge transfer steps within a network of pigment-containing proteins. Remarkably, high efficiency is conserved across many organisms despite differences in the protein structures and organization that allow each organism to respond to its own biological niche and the stressors within. In this review, we highlight recent progress toward understanding how organisms maintain optimal light-harvesting ability by acclimating to their environment. First, we review the building blocks of photosynthetic light harvesting, energy transfer, and time-resolved spectroscopic techniques. Then, we explore how three classes of photosynthetic organisms—purple bacteria, cyanobacteria, and green plants—optimize their light-harvesting apparatuses to their particular environment. Overall, research has shown that photosynthetic energy transfer is robust to changing environmental conditions, with each organism utilizing its own strategies to optimize photon capture in its particular biological niche.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

New high-throughput endstation to accelerate the experimental optimization pipeline for synchrotron X-ray footprinting

Synchrotron X-ray footprinting (XF) is a growing structural biology technique that leverages radiation-induced chemical modifications via X-ray radiolysis of water to produce hydroxyl radicals that probe changes in macromolecular structure and dynamics in solution states of interest. The X-ray Footprinting of Biological Materials (XFP) beamline at the National Synchrotron Light Source II provides the structural biology community with access to instrumentation and expert support in the XF method, and is also a platform for development of new technological capabilities in this field. Hee, the design and implementation of a new high-throughput endstation device based around use of a 96-well PCR plate form factor and supporting diagnostic instrumentation for synchrotron XF is described. This development enables a pipeline for rapid comprehensive screening of the influence of sample chemistry on hydroxyl radical dose using a convenient fluorescent assay, illustrated here with a study of 26 organic compounds. The new high-throughput endstation device and sample evaluation pipeline now available at the XFP beamline provide the worldwide structural biology community with a robust resource for carrying out well optimized synchrotron XF studies of challenging biological systems with complex sample compositions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

WE-B-304-03: Biological Treatment Planning

The ultimate goal of radiotherapy treatment planning is to find a treatment that will yield a high tumor control probability (TCP) with an acceptable normal tissue complication probability (NTCP). Yet most treatment planning today is not based upon optimization of TCPs and NTCPs, but rather upon meeting physical dose and volume constraints defined by the planner. It has been suggested that treatment planning evaluation and optimization would be more effective if they were biologically and not dose/volume based, and this is the claim debated in this month’s Point/Counterpoint. After a brief overview of biologically and DVH based treatment planning by the Moderator Colin Orton, Joseph Deasy (for biological planning) and Charles Mayo (against biological planning) will begin the debate. Some of the arguments in support of biological planning include: this will result in more effective dose distributions for many patients DVH-based measures of plan quality are known to have little predictive value there is little evidence that either D95 or D98 of the PTV is a good predictor of tumor control sufficient validated outcome prediction models are now becoming available and should be used to drive planning and optimization Some of the arguments against biological planning include: several decades of experience with DVH-based planning should not be discarded we do not know enough about the reliability and errors associated with biological models the radiotherapy community in general has little direct experience with side by side comparisons of DVH vs biological metrics and outcomes it is unlikely that a clinician would accept extremely cold regions in a CTV or hot regions in a PTV, despite having acceptable TCP values Learning Objectives: To understand dose/volume based treatment planning and its potential limitations To understand biological metrics such as EUD, TCP, and NTCP To understand biologically based treatment planning and its potential limitations.

60 APPLIED LIFE SCIENCES↗

Ultrastructural cellular signatures: does cellular form follow function?

In his watershed 1896 essay The Tall Office Building Artistically Considered, protomodern architect Louis Sullivan famously declared that ‘form follows function’. Could this concept also hold true in biology? Have cells, through evolutionary optimization, adopted a 3D architecture (‘form’) that reflects their function? Or, to keep with the architectural metaphor, how does ‘form’ relate to the cell’s ‘intended function or purpose’? Is there an ultrastructural signature that reflects the ‘constraints and requirements’ of a cell’s function in its specific spatial and temporal context?

59 BASIC BIOLOGICAL SCIENCES↗

Scaling Laws of Microactuators and Potential Applications of Electroactive Polymers in MEMS

Besides the scale factor that distinguishes the various species, fundamentally biological muscles changes little between species, indicating a highly optimized system. Electroactive polymer actuators offer the closest resemblance to biological muscles, however besides the large actuation displacement these materials are falling short with regards to the actuation force. As improved materials are emerging it is becoming necessary to address key issues such as the need for effective electromechanical modeling and guiding parameters in scaling the actuators. In this paper, we will review the scaling laws for three major actuation mechanisms that are of relevance to micro electromechanical systems: electrostatic actuation, magnetic actuation, thermal bimetallic actuation, and piezoelectric actuation.

Liu, Chang↗

Scaling Laws of Microactuators and Potential Applications of Electroactive Polymers in MEMS

Besides the scale factor that distinguishes the various spices fundamentally biological muscles changes little between species indicating a highly optimized system. Electroactive polymer actuators offer the closest resemblance to biological muscles however beside the large actuation displacement these materials are falling short with regards to the actuation force.

MEMS↗