SEARCH · Engineering Papers
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.
Presentation to be presented during the Site-Directed Research and Development (SDRD) program FY 2021 review meeting (Webex), September 22–23, 2021.
The calcium-selective oncochannel TRPV6 is an important driver of cell proliferation in human cancers. Despite increasing interest of pharmacological research in developing synthetic inhibitors of TRPV6, natural compounds acting at this channel have been largely neglected. On the other hand, pharmacokinetics of natural small-molecule antagonists optimized by nature throughout evolution endows these compounds with a medicinal potential to serve as potent and safe next-generation anti-cancer drugs. Here we report the structure of human TRPV6 in complex with tetrahydrocannabivarin (THCV), a natural cannabinoid inhibitor extracted from Cannabis sativa . We use cryo-electron microscopy combined with electrophysiology, calcium imaging, mutagenesis, and molecular dynamics simulations to identify THCV binding sites in the portals that connect the membrane environment surrounding the protein to the central cavity of the channel pore and to characterize the allosteric mechanism of TRPV6 inhibition. We also propose the molecular pathway taken by THCV to reach its binding site. Our study provides a foundation for the development of new TRPV6-targeting drugs.
Abstract Morphological profiling is an omics-based approach for predicting intracellular targets of chemical compounds in which the dose-dependent morphological changes induced by the compound are systematically compared to the morphological changes in gene-deleted cells. In this study, we developed a reliable high-throughput (HT) platform for yeast morphological profiling using drug-hypersensitive strains to minimize compound use, HT microscopy to speed up data generation and analysis, and a generalized linear model to predict targets with high reliability. We first conducted a proof-of-concept study using six compounds with known targets: bortezomib, hydroxyurea, methyl methanesulfonate, benomyl, tunicamycin, and echinocandin B. Then we applied our platform to predict the mechanism of action of a novel diferulate-derived compound, poacidiene. Morphological profiling of poacidiene implied that it affects the DNA damage response, which genetic analysis confirmed. Furthermore, we found that poacidiene inhibits the growth of phytopathogenic fungi, implying applications as an effective antifungal agent. Thus, our platform is a new whole-cell target prediction tool for drug discovery.
Autonomous experimentation is an emerging area of research, primarily related to autonomous vehicles, scientific combinatorial discovery approaches in materials science and drug discovery, and iterative research loops of planning, experimentation, and analysis. However, autonomous approaches developed in these contexts are difficult to apply to high-dimensional mapping technologies, such as scanning hyperspectral imaging of biological systems, due to sample complexity and heterogeneity. We briefly cover the history of adaptive sampling algorithms and surrogate modeling in order to define autonomous adaptive data acquisition as an objective-based, flexible building block for future biological imaging experimentation driven by intelligent infrastructure. We subsequently summarize the recent implementations of autonomous adaptive data acquisition (AADA) for scanning hyperspectral imaging, assess how these address the difficulties of autonomous approaches in hyperspectral imaging, and highlight the AADA design variation from a goal-oriented perspective. Finally, we present a modular AADA architecture that embeds AADA-driven flexible building blocks to address the challenge of time resolution for high-dimensional scanning hyperspectral imaging of nonequilibrium dynamical systems. In our example research-driven experimental design case, we propose an AADA infrastructure for time-resolved, noninvasive, and label-free scanning hyperspectral imaging of living biological systems. This AADA infrastructure can accurately target the correct state of the system for experimental workflows that utilize subsequent expensive, high-information-content analytical techniques.
Membrane proteins remain the most challenging targets for structural characterization, yet their elucidation provides valuable insights into protein function, disease mechanisms, and drug specificity. Structural biology platforms have advanced rapidly in recent years, notably through the development and implementation of nanodiscs—discoidal lipid–protein complexes that encapsulate and solubilize membrane proteins within a controlled, native-like environment. While nanodiscs have become powerful tools for studying membrane proteins, faithfully reconstituting the compositional asymmetry intrinsic to nearly all biological membranes has not yet been achieved. Proper membrane leaflet lipid distribution is critical for accurate protein folding, stability, and insertion. Here, we share a protocol for reconstituting tailored compositional asymmetry within nanodiscs through membrane extraction from giant unilamellar vesicles (GUVs) treated with a leaflet-specific methyl-β-cyclodextrin (mβCD) lipid exchange. Nanodisc asymmetry is verified through a geometric approach: biotin-DPPE-preloaded mβCD engages in lipid exchange with the outer leaflet of POPC GUVs solubilized by the lipid-free membrane scaffold protein (MSP) Δ49ApoA-I to form nanodisc structures. Once isolated, nanodiscs are introduced to the biotin-binding bacterial protein streptavidin. High-speed atomic force microscopy imaging depicts nanodisc–dimer complexes, indicating that biotin-DPPE was successfully reconstituted into a single leaflet of the nanodiscs. This finding outlines the first step toward engineering tailored nanodisc asymmetry and mimicking the native environment of integral proteins—a potentially powerful tool for accurately reconstituting and structurally analyzing integral membrane proteins whose functions are modulated by lipid asymmetry.
Chapare virus (CHAPV) is an emerging New World arenavirus that is the causative agent of Chapare hemorrhagic fever (CHHF) responsible for recent outbreaks with alarmingly high case fatality rates in Bolivia near the Brazilian border. Here, we describe a nonhuman primate (NHP) model of CHHF infection which represents an essential tool to understand this emerging biological threat agent. Cynomolgus macaques challenged intravenously with CHAPV develop clinical disease, which recapitulates several key features of human CHHF. All subjects lost weight and had clinical scores following CHAPV challenge. Notably, one of four NHPs developed lethal disease with viral hepatitis and hemorrhagic features. Clinical chemistry and hematology revealed leukopenia, anemia, thrombocytopenia, and increased transaminase levels. In all four subjects, viremia was detectable for the first week following challenge and viral RNA was detectable in serum and many tissues persisting 35 days-post challenge. Several medical countermeasures (MCM) have efficacy against CHAPV infection in vitro, but the current model for MCM testing and approval of new drugs is reliant on the availability of animal models. This work lays the foundation for future CHHF MCM development.
SARS-CoV-2 has caused a global pandemic, and has taken over 1.7 million lives as of mid-December, 2020. Although great progress has been made in the development of effective countermeasures, with several pharmaceutical companies approved or poised to deliver vaccines to market, there is still an unmet need of essential antiviral drugs with therapeutic impact for the treatment of moderate-to-severe COVID-19. Towards this goal, a high-throughput assay was used to screen SARS-CoV-2 nsp15 uracil-dependent endonuclease (endoU) function against 13 thousand compounds from drug and lead repurposing compound libraries. While over 80% of initial hit compounds were pan-assay inhibitory compounds, three hits were confirmed as nsp15 endoU inhibitors in the 1–20 μM range in vitro. Furthermore, Exebryl-1, a ß-amyloid anti-aggregation molecule for Alzheimer’s therapy, was shown to have antiviral activity between 10 to 66 μM, in Vero 76, Caco-2, and Calu-3 cells. Although the inhibitory concentrations determined for Exebryl-1 exceed those recommended for therapeutic intervention, our findings show great promise for further optimization of Exebryl-1 as an nsp15 endoU inhibitor and as a SARS-CoV-2 antiviral.
The pharmaceutical industry continuously looks for ways to improve its development and manufacturing efficiency. In recent years, such efforts have been driven by the transition from batch to continuous manufacturing and digitalization in process development. To facilitate this transition, integrated data management and informatics tools need to be developed and implemented within the framework of Industry 4.0 technology. Here, in this regard, the work aims to guide the data integration development of continuous pharmaceutical manufacturing processes under the Industry 4.0 framework, improving digital maturity and enabling the development of digital twins. This paper demonstrates two instances where a data integration framework has been successfully employed in academic continuous pharmaceutical manufacturing pilot plants. Details of the integration structure and information flows are comprehensively showcased. Approaches to mitigate concerns in incorporating complex data streams, including integrating multiple process analytical technology tools and legacy equipment, connecting cloud data and simulation models, and safeguarding cyber-physical security, are discussed. Critical challenges and opportunities for practical considerations are highlighted.
Current HER2-targeted therapies including monoclonal antibodies, antibody-drug conjugates (ADCs) and small-molecule tyrosine kinase inhibitors face limitations such as hepatotoxicity, development of treatment resistance, and subsequent disease relapse. To overcome these challenges, this study combines the specificity of a HER2-targeting affibody molecule (Z HER2:2891 -Cys) with the photothermal properties of gold nanorods (AuNRs), forming bioconjugates (Affi–AuNRs) for selective treatment of HER2-positive cancer cells. Affi–AuNRs were fabricated via a two-step surface modification: (i) ligand exchange to displace cetyltrimethylammonium bromide (CTAB) with poly(ethylene glycol) methyl ether thiol (mPEG-SH), and (ii) covalent attachment of the affibody molecule via Au–S chemistry. Affi-AuNRs exhibited a photothermal conversion efficiency of 64 ± 5%, comparable to that of CTAB-stabilized AuNRs (59 ± 4%). Confocal microscopy confirmed that Affi-AuNRs are selectively internalized by HER2-positive SKOV-3 cells, with minimal uptake by HEK293T cells, which have low HER2 expression. Upon exposure to 808 nm near-infrared (NIR) LED irradiation (408 mW cm –2 , 15 min), Affi-AuNRs significantly reduced SKOV-3 cell viability by 85 ± 9% (p < 0.001) relative to untreated controls with no detectable cytotoxicity in HEK293T cells. These results demonstrate HER2-selective photothermal cytotoxicity mediated by Affi–AuNRs under defined 808 nm LED irradiation conditions, supporting their continued development as nanotheranostic tools that integrate affibody-mediated specificity with plasmonic heating.
Mechanistic models of how single cells respond to different perturbations can help integrate disparate big data sets or predict response to varied drug combinations. However, the construction and simulation of such models have proved challenging. Here, we developed a python-based model creation and simulation pipeline that converts a few structured text files into an SBML standard and is high-performance- and cloud-computing ready. We applied this pipeline to our large-scale, mechanistic pan-cancer signaling model (named SPARCED) and demonstrate it by adding an IFNγ pathway submodel. We then investigated whether a putative crosstalk mechanism could be consistent with experimental observations from the LINCS MCF10A Data Cube that IFNγ acts as an anti-proliferative factor. The analyses suggested this observation can be explained by IFNγ-induced SOCS1 sequestering activated EGF receptors. This work forms a foundational recipe for increased mechanistic model-based data integration on a single-cell level, an important building block for clinically-predictive mechanistic models.
Restricted Boltzmann Machines (RBMs) have been proposed for developing neural networks for a variety of unsupervised machine learning applications such as image recognition, drug discovery, and materials design. The Boltzmann probability distribution is used as a model to identify network parameters by optimizing the likelihood of predicting an output given hidden states trained on available data. Training such networks often requires sampling over a large probability space that must be approximated during gradient based optimization. Quantum annealing has been proposed as a means to search this space more efficiently which has been experimentally investigated on D-Wave hardware. D-Wave implementation requires selection of an effective inverse temperature or hyperparameter (β) within the Boltzmann distribution which can strongly influence optimization. Here, we show how this parameter can be estimated as a hyperparameter applied to D-Wave hardware during neural network training by maximizing the likelihood or minimizing the Shannon entropy. We find both methods improve training RBMs based upon D-Wave hardware experimental validation on an image recognition problem. Neural network image reconstruction errors are evaluated using Bayesian uncertainty analysis which illustrate more than an order magnitude lower image reconstruction error using the maximum likelihood over manually optimizing the hyperparameter. The maximum likelihood method is also shown to out-perform minimizing the Shannon entropy for image reconstruction.
Surfaces with tunable microscale textures are vital in a large variety of technological applications, including heat transfer, antifouling and adhesion. To facilitate such broad-scale use, there is a need to create surfaces that undergo reconfigurable changes in topology and thus, enable switchable functionality. To date, there is a relative dearth of methods for engineering surfaces that can be actuated to change topography over a range of length scales, and hence, form tunable hierarchically structured layers. Combining modeling and experiments, we design a geometrically patterned, thermo-responsive poly (N-isopropylacrylamide) gel film that undergoes controllable hierarchical changes in topology with changes in temperature. At the bottom, the film is covalently bound to a solid, curved substrate; at the top, the film encompasses longitudinal rectangular ridges that are oriented perpendicular to the underlying cylindrical curves. At temperatures below lower critical solution temperature (LCST), the swollen gel exhibits 3D variations in polymer density and thickness defined by the gel's top and bottom topography. As the temperature rises above LCST, the interplay between the upper ridges and lower curves in the gel drives non-uniform, directional solvent transport, the nucleation and propagation of a phase-separated higher-density skin layer, and the resulting pressure buildup within the film. These different, interacting kinetic processes lead to an instability, which produces transient microscopic blisters in the film. Through simulations, we show how tuning the width of the ridges modifies the propagation of a skin layer and creates localized pressure build-up points, which enables control over the emergence, distribution, and alignment of the microscopic blisters. Futhermore, we provide a simple argument to predict the size of such microscopic features. Experiments confirm our predictions and further highlight how our computational model enables the rational design of topographical transitions in these tunable films. The development of actuatable, hierarchically structured films provides new routes for achieving switchable functionality in actuators, drug release systems and adhesives.
Auranofin, initially developed as a treatment for rheumatoid arthritis, is currently under extensive investigation as a potential drug for various conditions, including cancer, bacterial infections, and parasitic infections. The compound is a known inhibitor of thioredoxin reductase (TXNRD1) and related selenoproteins. Although preliminary studies on the auranofin crystal polymorphism exist, and a low-quality crystal structure has been reported, a comprehensive crystallographic characterization remains unexplored. Utilizing X-ray crystallography techniques, we conducted detailed structural analysis of auranofin and compared our findings with related organogold compounds. Implementation of Hirshfeld atom refinement (HAR) enabled a more accurate hydrogen atom positioning in the structure. The crystal packing reveals a layered arrangement stabilised by numerous weak hydrogen bonds and dispersive interactions. Notably, our attempts to reproduce the previously reported polymorphic form of auranofin, purportedly more water-soluble, were unsuccessful despite following published protocols. To our knowledge, this is the first study describing a “disappearing polymorph” phenomenon of any pharmaceutically relevant transition metal coordination compound. Our findings may have significant implications for medicinal chemistry and pharmacology of coordination complexes, suggesting the need for systematic revision of historical crystallographic data in this field.
Abstract Higher vascular disease burden increases the likelihood of developing dementia, including Alzheimer’s disease. Better understanding the association between vascular risk factors and Alzheimer’s disease pathology at the predementia stage is critical for developing effective strategies to delay cognitive decline. In this work, we estimated the impact of six vascular risk factors on the presence and severity of in vivo measured brain amyloid-beta (Aβ) plaques in participants from the population-based Rotterdam Study. Vascular risk factors (hypertension, hypercholesterolaemia, diabetes, obesity, physical inactivity and smoking) were assessed 13 (2004–2008) and 7 years (2009–2014) prior to 18F-florbetaben PET (2018–2021) in 635 dementia-free participants. Vascular risk factors were associated with binary amyloid PET status or continuous PET readouts (standard uptake value ratios, SUVrs) using logistic and linear regression models, respectively, adjusted for age, sex, education, APOE4 risk allele count and time between vascular risk and PET assessment. Participants’ mean age at time of amyloid PET was 69 years (range: 60–90), 325 (51.2%) were women and 190 (29.9%) carried at least one APOE4 risk allele. The adjusted prevalence estimates of an amyloid-positive PET status markedly increased with age [12.8% (95% CI 11.6; 14) in 60–69 years versus 35% (36; 40.8) in 80–89 years age groups] and APOE4 allele count [9.7% (8.8; 10.6) in non-carriers versus 38.4% (36; 40.8) to 60.4% (54; 66.8) in carriers of one or two risk allele(s)]. Diabetes 7 years prior to PET assessment was associated with a higher risk of a positive amyloid status [odds ratio (95% CI) = 3.68 (1.76; 7.61), P < 0.001] and higher standard uptake value ratios, indicating more severe Aβ pathology [standardized beta = 0.40 (0.17; 0.64), P = 0.001]. Hypertension was associated with higher SUVr values in APOE4 carriers (mean SUVr difference of 0.09), but not in non-carriers (mean SUVr difference 0.02; P = 0.005). In contrast, hypercholesterolaemia was related to lower SUVr values in APOE4 carriers (mean SUVr difference −0.06), but not in non-carriers (mean SUVr difference 0.02). Obesity, physical inactivity and smoking were not related to amyloid PET measures. The current findings suggest a contribution of diabetes, hypertension and hypercholesterolaemia to the pathophysiology of Alzheimer’s disease in a general population of older non-demented adults. As these conditions respond well to lifestyle modification and drug treatment, further research should focus on the preventative effect of early risk management on the development of Alzheimer’s disease neuropathology.
Abstract Endohedral metallofullerenes (EMFs) are excellent carriers of rare‐earth element (REE) ions in biomedical applications because they preclude the release of toxic metal ions. However, existing approaches to synthesize water‐soluble EMF derivatives yield mixtures that inhibit precise drug design. Here we report the synthesis of metallobuckytrio (MBT), a three‐buckyball system, as a modular platform to develop structurally defined water‐soluble EMF derivatives with ligands by choice. Demonstrated with PEG ligands, the resulting water‐soluble MBTs show superb biocompatibility. The Gd MBTs exhibit superior T 1 relaxivity than typical Gd complexes, potentially superseding current clinical MRI contrast agents in both safety and efficiency. The Lu MBTs generated reactive oxygen species upon light irradiation, showing promise as photosensitizers. With their modular nature to incorporate other ligands, we anticipate the MBT platform to open new paths towards bio‐specific REE drugs.
Abstract Endohedral metallofullerenes (EMFs) are excellent carriers of rare‐earth element (REE) ions in biomedical applications because they preclude the release of toxic metal ions. However, existing approaches to synthesize water‐soluble EMF derivatives yield mixtures that inhibit precise drug design. Here we report the synthesis of metallobuckytrio (MBT), a three‐buckyball system, as a modular platform to develop structurally defined water‐soluble EMF derivatives with ligands by choice. Demonstrated with PEG ligands, the resulting water‐soluble MBTs show superb biocompatibility. The Gd MBTs exhibit superior T 1 relaxivity than typical Gd complexes, potentially superseding current clinical MRI contrast agents in both safety and efficiency. The Lu MBTs generated reactive oxygen species upon light irradiation, showing promise as photosensitizers. With their modular nature to incorporate other ligands, we anticipate the MBT platform to open new paths towards bio‐specific REE drugs.
Highlights: • Highly expressed integrin α5 was observed in in vitro three-dimensional NPC spheroids. • The overexpression of integrin α5 in NPC spheroids demonstrated a correlation with intrinsic cisplatin resistance. • The integrin α5-induced intrinsic cisplatin resistance was mediated by an inactivation of ERK/caspase-3-induced apoptosis. • ATN-161, an integrin α5β1 inhibitor, reduced integrin α5 expression and increased sensitization to cisplatin in NPC spheroids. • ATN-161 reversed the intrinsic cisplatin resistance in NPC spheroids by reactivating ERK/caspase-3-induced apoptosis. Nasopharyngeal carcinoma (NPC) originates in the nasopharynx epithelium. Although concurrent chemoradiation therapy followed by chemotherapy is considered as an effective treatment, there is substantial drug resistance in locally advanced NPC patients. One major contributor to the chemoresistance includes aberrant expression of cell adhesion molecules, such as integrin α and β subunits, giving rise to cell adhesion-mediated drug resistance. Thus, the aim of this study was to investigate the effect of integrin α5 on the development of intrinsic cisplatin resistance in NPC and the associated underlying mechanisms using in vitro three-dimensional (3D) spheroid models, as well as induced cisplatin-resistant NPC (NPCcisR). We demonstrated that established 3D highly- (5-8F) and lowly- (6-10B) metastatic NPC spheroids overexpressed integrin α5 and aggravated their resistance to cisplatin. Besides, enhanced integrin α5 resulted in substantially reduced growth, corresponding to G{sub 0}/G{sub 1} and G{sub 2}/M cell cycle arrest. In addition, 5-8FcisR and 6-10BcisR cells in 3D forms synergistically strengthened endurance of their spheroids to cisplatin treatment as observed by increased resistance index (RI) and decreased apoptosis. Mechanistically, the aberrantly expressed integrin α5 decreased drug susceptibility in NPC spheroids by inactivating ERK and inhibition of caspase-3 inducing apoptosis. Furthermore, the effect of integrin α5 inducing intrinsic resistance was verified via treatment with ATN-161, a peptide inhibitor for integrin α5β1. The results showed dramatic reduction in integrin α5 expression, reversal of ERK phosphorylation and caspase-3 cleavage, together with elevated cisplatin sensitivity, indicating regulation of innate drug resistance via integrin α5. Taken together, our findings suggest that integrin α5 could act as a promising target to enhance the chemotherapeutic sensitivity in NPC.
Wetting and dewetting transitions play a central role in controlling the hydrophobicity of the lining of biological channels in order to regulate aqueous solution permeation. Understanding of the operational characteristics of biological nanochannels led to experimental efforts to mimic their behavior and to achieve potential-induced, repeatedly-switchable wettability transitions in synthetic nanochannels in the early 2010s. Since then, research has identified conditions needed to produce reversible wettability transitions using a number of different environmental stimuli - such as light, pH, and electrostatic charge - in addition to potential. Furthermore, nascent understanding of the underlying phenomena in synthetic nanochannels was rapidly followed by practical applications, including oil-water separations, drug release, and electroactive flow control based on switchable wettability. Furthermore, more practical applications are being developed continuously, as the physical and chemical principles that govern hydrophobic gating at the nanoscale are further elucidated, making it possible to exploit wettability as a design element in nanofluidic systems.