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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.

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78 records · Page 5

Towards the stable chelation of radium for biomedical applications with an 18-membered macrocyclic ligand

Targeted alpha therapy is an emerging strategy for the treatment of disseminated cancer. [ 223 Ra]RaCl 2 is the only clinically approved alpha particle-emitting drug, and it is used to treat castrate-resistant prostate cancer bone metastases, to which [ 223 Ra]Ra 2+ localizes. To specifically direct [ 223 Ra]Ra 2+ to non-osseous disease sites, chelation and conjugation to a cancer-targeting moiety is necessary. Although previous efforts to stably chelate [223Ra]Ra2+ for this purpose have had limited success, here we report a biologically stable radiocomplex with the 18-membered macrocyclic chelator macropa. Quantitative labeling of macropa with [ 223 Ra]Ra 2+ was accomplished within 5 min at room temperature with a radiolabeling efficiency of >95%, representing a significant advancement over conventional chelators such as DOTA and EDTA, which were unable to completely complex [ 223 Ra]Ra 2+ under these conditions. [ 223 Ra][Ra(macropa)] was highly stable in human serum and exhibited dramatically reduced bone and spleen uptake in mice in comparison to bone-targeted [ 223 Ra]RaCl 2 , signifying that [ 223 Ra][Ra(macropa)] remains intact in vivo. Upon conjugation of macropa to a single amino acid b-alanine as well as to the prostate-specific membrane antigen-targeting peptide DUPA, both constructs retained high affinity for 223 Ra, complexing >95% of Ra 2+ in solution. Furthermore, [ 223 Ra][Ra(macropa-b-alanine)] was rapidly cleared from mice and showed low 223 Ra bone absorption, indicating that this conjugate is stable under biological conditions. Unexpectedly, this stability was lost upon conjugation of macropa to DUPA, which suggests a role of targeting vectors in complex stability in vivo for this system. Nonetheless, our successful demonstration of efficient radiolabeling of the b-alanine conjugate with 223 Ra and its subsequent stability in vivo establishes for the first time the possibility of delivering [ 223 Ra]Ra 2+ to metastases outside of the bone using functionalized chelators, marking a significant expansion of the therapeutic utility of this radiometal in the clinic.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multidimensional quantitative phenotypic and molecular analysis reveals neomorphic behaviors of p53 missense mutants

Abstract Mutations in the TP53 tumor suppressor gene occur in >80% of the triple-negative or basal-like breast cancer. To test whether neomorphic functions of specific TP53 missense mutations contribute to phenotypic heterogeneity, we characterized phenotypes of non-transformed MCF10A-derived cell lines expressing the ten most common missense mutant p53 proteins and observed a wide spectrum of phenotypic changes in cell survival, resistance to apoptosis and anoikis, cell migration, invasion and 3D mammosphere architecture. The p53 mutants R248W, R273C, R248Q, and Y220C are the most aggressive while G245S and Y234C are the least, which correlates with survival rates of basal-like breast cancer patients. Interestingly, a crucial amino acid difference at one position—R273C vs. R273H—has drastic changes on cellular phenotype. RNA-Seq and ChIP-Seq analyses show distinct DNA binding properties of different p53 mutants, yielding heterogeneous transcriptomics profiles, and MD simulation provided structural basis of differential DNA binding of different p53 mutants. Integrative statistical and machine-learning-based pathway analysis on gene expression profiles with phenotype vectors across the mutant cell lines identifies quantitative association of multiple pathways including the Hippo/YAP/TAZ pathway with phenotypic aggressiveness. Further, comparative analyses of large transcriptomics datasets on breast cancer cell lines and tumors suggest that dysregulation of the Hippo/YAP/TAZ pathway plays a key role in driving the cellular phenotypes towards basal-like in the presence of more aggressive p53 mutants. Overall, our study describes distinct gain-of-function impacts on protein functions, transcriptional profiles, and cellular behaviors of different p53 missense mutants, which contribute to clinical phenotypic heterogeneity of triple-negative breast tumors.

60 APPLIED LIFE SCIENCES↗

A multi-plex protein expression system for production of complex enzyme formulations in Trichoderma reesei

Abstract Heterologous protein production has been challenging in the hyper-cellulolytic fungus, Trichoderma reesei as the species is known for poor transformation efficiency, low homologous recombination frequency, and marginal screening systems for the identification of successful transformants. We have applied the 2A-peptide multi-gene expression system to co-express four proteins, which include three cellulases: a cellobiohydrolase (CBH1), an endoglucanase (EG1), and a β-D-glucosidase (BGL1), as well as the enhanced green fluorescent protein (eGFP) marker protein. We designed a new chassis vector, pTrEno-4X-2A, for this work. Expression of these cellulase enzymes was confirmed by real-time quantitative reverse transcription PCR and immunoblot analysis. The activity of each cellulase was assessed using chromogenic substrates, which confirmed the functionality of the enzymes. Expression and activity of these enzymes were proportional to the level of eGFP fluorescence, thereby validating the reliability of this screening technique. An 18-fold differencein protein expression was observed between the first and third genes within the 2A-peptide construct. The availability of this new multi-gene expression and screening tool is expected to greatly impact multi-enzyme applications, such as the production of complex commercial enzyme formulations and metabolic pathway enzymes, especially those destined for cell-free applications.

09 BIOMASS FUELS↗

Knowledge graph-aided Bayesian active learning for top- K genetic interaction discovery

In silico methods for predicting the effects of multi-gene perturbations hold great promise for advancing functional genomics, computational drug discovery, and disease modeling. However, the development of these predictive algorithms for mammalian systems has been hampered by limited datasets and high experimental costs. In this study, we present a Bayesian active learning framework designed to discover pairwise host gene knockdowns that effectively inhibit viral proliferation in an in vitro HIV-1 infection model. Our method leverages a biological knowledge graph as side information and employs a computationally efficient batch diversification approach. We evaluated this framework using a dataset of viral load measurements obtained from multi-day dual-gene depletion experiments, encompassing all possible pairwise knockdowns of over 350 host genes associated with HIV infection. We demonstrate that our framework rapidly identifies the most effective gene knockdown pairs for reducing viral load. Furthermore, we show that incorporating side information enhances performance during the early stages of active learning (low data regime), while our batch diversification strategy significantly boosts performance in later stages (high data regime). This framework is general and can be adapted to explore gene interactions in other contexts, such as synthetic lethality prediction and mapping epistatic effects across quantitative trait loci.

Computational biology and bioinformatics↗

A proposed framework for the development and qualitative evaluation of West Nile virus models and their application to local public health decision-making

West Nile virus (WNV) is a globally distributed mosquito-borne virus of great public health concern. The number of WNV human cases and mosquito infection patterns vary in space and time. Many statistical models have been developed to understand and predict WNV geographic and temporal dynamics. However, these modeling efforts have been disjointed with little model comparison and inconsistent validation. In this paper, we describe a framework to unify and standardize WNV modeling efforts nationwide. WNV risk, detection, or warning models for this review were solicited from active research groups working in different regions of the United States. A total of 13 models were selected and described. The spatial and temporal scales of each model were compared to guide the timing and the locations for mosquito and virus surveillance, to support mosquito vector control decisions, and to assist in conducting public health outreach campaigns at multiple scales of decision-making. Our overarching goal is to bridge the existing gap between model development, which is usually conducted as an academic exercise, and practical model applications, which occur at state, tribal, local, or territorial public health and mosquito control agency levels. The proposed model assessment and comparison framework helps clarify the value of individual models for decision-making and identifies the appropriate temporal and spatial scope of each model. This qualitative evaluation clearly identifies gaps in linking models to applied decisions and sets the stage for a quantitative comparison of models. Specifically, whereas many coarse-grained models (county resolution or greater) have been developed, the greatest need is for fine-grained, short-term planning models (m–km, days–weeks) that remain scarce. We further recommend quantifying the value of information for each decision to identify decisions that would benefit most from model input.

60 APPLIED LIFE SCIENCES↗

Volatiles from the necrophagous fly Cochliomyia macellaria (Diptera: Calliphoridae) as indicators of Salmonella exposure

Blow flies (Diptera: Calliphoridae) are crucial in forensic investigations due to their association with both living and dead humans and other animals. Additionally, their interactions with various resources and potential as vectors of pathogens of humans and other animals, thus, make them potential tools for biosurveillance. This study investigated the potential of monitoring volatile organic compounds (VOCs) emitted by blow flies exposed to Salmonella as a method for pathogen surveillance. Adult blow flies ( Cochliomyia macellaria ) were exposed, or not, to Salmonella enterica . Following exposure, VOCs released by the blow flies were collected and analyzed using gas chromatography-mass spectrometry (GC-MS). Results indicate a treatment by time interaction (P < 0.01). Indicator species analysis identified a single compound significantly associated with S. enterica exposure (P = 0.02), Nonane, 2,2,4,4,6,8,8-heptamethyl, potentially indicating an immune system response. Given a compound indicating exposure was detected, future research should determine if more replicates could detect more differences after Salmonella ingestion. This research highlights the potential of blow flies as biosurveillance tools and the potential value of volatiles for assessing their exposure to pathogens.

59 BASIC BIOLOGICAL SCIENCES↗