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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

An Economic Model and Experiments to Understand Aluminum-Cerium Alloy Recycling

We provide an economic model to understand the impact of adoption, sorting and pricing of scrap on the recycling of a new aluminum-cerium (AlCe) alloy for use in engine blocks in the automobile industry. The goal of the laboratory portion of this study is to investigate possible effects of cerium contamination on well-established aluminum recycling streams. Here, our methodology includes three components: (1) focused data gathering from industry supply chain participants, (2) experimental data through laboratory experiments to understand the impact of cerium on existing alloys and (3) an economic model to understand pricing incentives on a recycler’s separation of AlCe engine blocks.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Group purchasing organization design: a clustering approach

Supply chain management is monitoring of activities involved in supply chain, for integrating and coordinating between suppliers, manufacturing, inventory and transportation both within and among members. The ultimate aim of supply chains is to reduce costs and increase market coverage. Procuring and purchasing requested items in a timely manner are the two most important issues for supply chain stockholders. Group purchasing is one of the purchasing strategies in supply chains. It offers great potential by ordering large volumes to decrease expenses which can increase services to customers. A clustering optimization approach is employed to model group purchasing for a set of pharmacies in the field of healthcare. The proposed model determines a cooperation strategy based on factors such as distance between pharmacies and procurement expenditure in this network. Moreover, the proposed multi-objective group purchasing model is optimized using both goal programming and non-dominated sorting genetic algorithm. To illustrate the application of the proposed model, designing a purchasing group organization for Chalus city pharmacies is investigated. Purchasing groups are established in the way that sum of pharmacies ordering quantity has been located in the second or the third level of discount rate. Thus, the results show that GPOs can take the advantage of this cooperation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Enhancement of a Process Flowsheet for Recovering and Concentrating Critical Materials from Bituminous Coal Sources

Recovery of rare earth elements (REE) from coal-related resources has recently received significant interest due to supply concerns and their key roles in critical industries and defense-related technologies. In this study, an integrated flowsheet consisting of sorting, crushing/grinding, physical separation, acid leaching, solvent extraction, and selective precipitation was designed to achieve continuous production of rare earth products from various coal-related resources such as coarse refuse and acid mine drainage. A pilot plant was constructed that enabled continuous testing of the circuitry on a range of different coal-based feedstocks. Despite achieving significant success in producing high-grade rare earth oxide products, low REE recovery values and high operational costs necessitated a re-evaluation of the process flowsheet. This article describes the circuitry improvements that were based on both laboratory and pilot plant test results. Roasting as a pre-leach treatment was found to significantly improve the leaching rate and overall REE recovery values. After roasting West Kentucky No. 13 and Fire Clay coal refuse materials at 600 °C, REE recovery increased by 60 and 40 absolute percentage points, respectively. Rare earth concentration in the pregnant leachate solution (PLS) was increased to around 700 ppm prior to solvent extraction using a staged precipitation method. REEs in the precipitate were re-dissolved, purified, and extracted from the PLS using solvent extraction and selective precipitation to values of around 80%. As a result of the improvements, chemical consumption in the acid leaching and solvent extraction processes was significantly reduced. A techno-economical assessment of the improved flowsheet indicated significant commercialization potential.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2017

Computation of entropies and phase equilibria in refractory V-Nb-Mo-Ta-W high-entropy alloys

Here, we have applied the first-principles phonon method to the refractory V-Nb-Mo-Ta-W high-entropy alloys (HEAs) to predict the major phase separations in the temperature-compositional space and hence the associated entropy changes within the systems, taking into account vibrational, electronic, and configurational contributions to the total entropy. The first-principles calculations covered 178 phases ranging from pure elements, the ordered B2, B32, B2 3 , B2 2 , hR8, hR7, tI6, C15, and D0 3 binary phases, two ordered MoNbTaW quaternary phases, and the partially disordered and completely disordered bcc phases. By sorting their relative phase stabilities with the Dantzig's simplex minimization algorithm, the possibilities of phase separation for the refractory quaternary and quinary HEAs were thermodynamically found in the temperature range of 500e907 K.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Nuclear genome shuffling significantly increases production of chloroplast-based recombinant protein in Chlamydomonas reinhardtii

Algae biotechnology holds great promise for the production of sustainable and environmentally friendly products, however more robust strains of microalgae must be developed before algae can be used as a commercially relevant production platform. Here we demonstrate a timely and effective approach to significantly improve a desired phenotype in algae through a combination of mutagenesis and genome shuffling. In this study, we engineered a strain of Chlamydomonas reinhardtii to produce recombinant green fluorescent protein in the chloroplast and then subjected the nuclear genome to various rounds of UV-induced mutagenesis and genome shuffling via sexual recombination, followed by isolation of strains with enhanced recombinant protein expression using fluorescence-activated cell sorting (FACS). Here, the greatest success came from first UV-mutagenizing the host strain to create mutations in the nuclear genome, followed by FACS to isolate the best GFP-expressing mutant, then shuffling the nuclear genome of that mutant by mating it with selected wild-type strains, and then again isolating the best progeny via FACS. Using this strategy, a novel strain was evolved in <3 months to express GFP over 2% total soluble protein (TSP), a 15-fold increase from the initial recombinant strain which expressed GFP at 0.14% TSP. Furthermore, this significant increase in GFP expression from the chloroplast was accomplished without altering the GFP gene itself or reducing the growth rate of the strain, demonstrating the effectiveness of this strategy to enhance a specific phenotype and significantly improve product production within an algal species in a commercially relevant timeframe.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

The use of multi-objective optimization to improve the design process of nuclear power plant systems

Multi-objective optimization is proposed to address the problem of design optimality in the nuclear power plant design process. This is done via the creation/development of the Optimization and Preference Tool for the Improvement of Nuclear Systems (OPTIONS). This work details applications of multi-objective optimization methods (in Python 3) to two different nuclear system design problems: the flash-Rankine power conversion system (PCS) of the I 2 S-LWR and the Passive Endothermic Reaction Cooling System (PERCS) attached to a standard PWR primary system (in RELAP5). The PCS design problem is first solved for three configurations using a specific particle swarm optimization method, achieving a thermodynamic efficiency of 34.81%. A new method, the Mixed-Integer Non-dominated Sorting Genetic Algorithm (MI-NSGA), is created and then used, solving a PCS superstructure of 22 configurations and achieving an efficiency of 35.63%. Finally, the OPTIONS tool is used to optimize the PERCS, improving cost, core temperature control, and cooling longevity.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Local gravity theories in conformal superspace

The conformal method for the initial value formulation of GR is one of the most powerful and widely usedtools in both analytical studies and numerical simulations of solutions. As is well-known, it exploits a hidden spatial conformal symmetry that can be extracted from the equations. But why conformal symmetry? Motivated by these questions and by well-known obstacles to quantum gravity, I look for the most general geometrodynamical symmetries compatible with a reduced physical configuration space for metric gravity. I argue that they are indeed spatial conformal diffeomorphisms. The next question is: what sort of theories most naturally incorporate this symmetry? Demanding locality for an action for metric gravity compatible with these principles determines the allowed operators, both for the purely gravitational part as well as matter couplings. The symmetries guarantee that there are two gravitational propagating physical degrees of freedom, but no explicit refoliation-invariance. The simplest such system has a geometric interpretation as a geodesic model in infinite-dimensional conformal superspace. One example of solution to the equations of motion corresponds to a static Bianchi IX spatial ansatz. The unique coupling to electromagnetism forces the electromagnetic equations to be hyperbolic, enabling us to “build” a standard space–time causal structure. There are, however, deviations from the standard Maxwell equations when space–time anisotropies become too large. Regarding quantization, with the geometric interpretation and the lack of refoliation invariance, the path integral treatment of the symmetries becomes much less involved than the similar approaches to GR. The symmetries form an (infinite-dimensional) Lie algebra, and no BFV treatment is necessary. Moreover, one can use gauge-invariant variational principles for selecting the boundary conditions of the path integral. We find that the propagator around the homogeneous solution has up to 6th order spatial derivatives, giving it plausible regularization properties as in Horava–Lifschitz.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Electric-vehicle battery second-life and recycling pathways: How economics depend on chemistry, processing, and application

We assess the economics of repurposing and recycling electric vehicle (EV) batteries by estimating the maximum acquisition price repurposers and recyclers could pay for used EV packs across cathode chemistries, first-life conditions, second-life applications, and recycling processes. We develop a novel open-source process-based cost model of a UL-1974-certified repurposing facility and leverage battery degradation models to estimate the maximum acquisition price repurposers could pay for used EV batteries while producing second-life battery energy storage systems with life-adjusted costs equivalent to new systems. We compare these maximum price estimates to maximum prices for recyclers based on cost and revenue estimates from the EverBatt model. We find that repurposing is more economical than recycling for lithium iron phosphate (LFP) batteries, due to their relatively long life and low value materials; recycling is generally more economical than repurposing for lithium nickel cobalt aluminum oxide (NCA) batteries, due to their shorter life and higher value materials; and the economics for lithium nickel manganese cobalt oxide (NMC) batteries depend more heavily on first life retirement conditions and second life application intensity. These results suggest an overall strategy: reuse LFP, recycle NCA, and sort NMC into recycling or repurposing pathways based on state of health and second-life application.

25 ENERGY STORAGE↗
DOE OSTI2023

Analysis of an optical imaging system prototype for autonomously monitoring zooplankton in an aquaculture facility

Traditional approaches to biomonitoring in aquatic systems, such as sample collection, sorting, and identification, require significant time and effort, thereby limiting the spatiotemporal resolution of sample collection. Additionally, collection and preservation of samples for subsequent taxonomic identification and enumeration leads to mortality of organisms. Recent advances in technologies that utilize optical imaging and machine learning have provided new opportunities to expedite biomonitoring and lead to significant cost savings. These technologies can be advantageous to scientists or managers that conduct routine biomonitoring to inform operations, as in the case of aquaculture facilities. The Small Aquatic Organism optical imaging system (SAO) is a high-throughput optical imaging and classification prototype system that relies on computer vision and machine learning (Support Vector Machines, or SVMs) to autonomously identify and enumerate aquatic organisms. The SAO provides a more sustainable method of collecting large volumes of data and has the benefit of being used in situ. In this study, we tested the performance of the SAO in providing comparable results to manual zooplankton community monitoring in ten ponds at an aquaculture facility. We performed a side-by-side study comparing the sampling methods of plankton tow nets, where major zooplankton taxonomic classes were manually identified and enumerated, to sampling with the SAO. Vouchered samples were used to develop a training library for the SAO, where classes consisted of water boatman and zooplankton groups: cladocerans, copepod adults, copepod nauplii, and rotifers. SAO imagery was manually classified and compared with predicted results for validation. Accuracy for the SVM classifier of the SAO was 37.4 %. Convolutional Neural Networks (CNN) and Random Forest classifiers were also applied to SAO imagery and image features for comparison. The best CNN model and our Random Forest model had accuracies of 80.4 % and 46.6 % respectively. Challenges faced included the small size of copepod nauplii and rotifers and the limited resolution of the imaging camera, although there are tradeoffs between imaging resolution and the sample processing rate. Furthermore, our comparison shows that advancement in both optical imaging and ML are needed in order for the SAO prototype to yield comparable results to manual community monitoring in an aquaculture facility.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Hybrid data-driven cement-stabilized soil design: An integration of machine learning, multi-objective optimization, and life cycle assessment

Soil stabilization is crucial in geotechnical engineering, yet conventional methods are often time-consuming, resource-intensive, and environmentally unsustainable. Despite growing interest in Machine Learning (ML) and optimization tools for mix design, few studies integrate these methods with decision-making techniques and environmental assessment to support practical implementation. This study proposes a hybrid data-driven framework for predicting strength, optimizing mix compositions, and evaluating environmental impacts via life cycle assessment of cement-stabilized soft soils. Six ML models were evaluated, and the top-performing eXtreme Gradient Boosting (XGB) model was further improved using the Grey Wolf Optimizer (GWO). The optimized XGB-GWO model, integrated with a polynomial cost function, served as the objective function in a multi-objective optimization problem solved via the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), with final mix selection guided by the entropy-weighted TOPSIS method. Validation through a case study produced mix designs offering superior strength-cost trade-offs, with the optimal mix achieving 2243.2 kPa unconfined compressive strength and a 16.07 % reduction in carbon emissions compared to the highest-cost design. In conclusion, this study offers a sustainable, scalable approach to soil stabilization and supports informed decision-making in construction.

Life cycle assessment↗
DOE OSTI2021

Quantifying physical parameterization uncertainties associated with land-atmosphere interactions in the WRF model over Amazon

The Weather Research and Forecasting (WRF) model can be used to diagnose regional land-atmosphere (L-A) coupling strength in the absence of sufficient observations but subjected to uncertainties associated with model physical parameterizations. In this study, we propose a framework to quantify and reduce model physical parameterization uncertainties associated with surface fluxes and L-A coupling. An ensemble of WRF simulations with different physical schemes is used to simulate surface fluxes and land-atmosphere coupling strength over the Amazon region. The physical parameterizations investigated include cloud microphysics (MP), land surface processes (LSM), planetary boundary layer (PBL), surface layer (SL), and cumulus (CU). We perform 120 ensemble simulations using the WRF model and different combinations of six MPs, three LSMs, six PBLs and SLs and three CUs. The measurements from the GoAMAZON field campaign and satellite data are used to evaluate model performance. A Multi-way analysis of variance (ANOVA) approach is applied to quantify the relative importance of different physics processes on L-A coupling. The Tukey’s test is used to sort schemes that have no significant differences into one group. The suite of physics that result in the best simulations of the corresponding variables are selected based on the Taylor skill score. Results show that the relative importance of processes and their interaction vary with the variables of interest. For example, CU was the most important process in modulating soil moisture, 2 m-humidity, latent heat, and net radiation. LSM showed dominant effects on 2 m-temperature and also has the largest impact on sensible heat and the lifting condensation level. The best physical parameterization ensembles show much narrower ranges of the variables of interest than the priori ensemble. Results of this study show the roles of different physical processes in modulating L-A interactions, quantify model uncertainties from physical processes, and provide insights for improving the model physics parameterizations.

Wang, Chen↗
DOE OSTI2017

Integration of in silico approaches to determination of endocrine-disrupting perfluorinated chemicals binding potency with steroidogenic acute regulatory protein

A myriad of perfluorinated compounds (PFCs) have the ability to interfere with steroidogenic acute regulatory (StAR) protein. Consequently, PFCs breaches cholesterol biotransformation in mitochondria and cause fatal consequences in steroidogenesis, however, these were poorly characterized. In the present study, we have evaluated toxic potencies, nuclear mediated probabilities and interaction profiles with StAR of PFCs using computational system biology tools. Toxicity endpoints revealed that PFCs contain high carcinogenicity, developmental toxicity, skin sensitization effects with low mutagenic activity. Consensus qualitative nuclear receptor agonist models show higher probability rates towards ER and PPAR-γ receptor than AR and AhR models were observed. To poise the subtle fluctuations of actual predictions, balanced accuracy and MCC were computed, and they signify perfect correlation ranges in all models. Screening studies resulting protein-ligand interaction profiles showed that residues Asn148, Asn150, Glu169, Ala171, Arg182, Phe184, Arg188, Trp241, Thr263 and Phe267 were identified as novel hotspots, participated in halogen bonds, H-bonds, atomic π-stacking, π-cation interactions and salt-bridges formation. Thus, the additional bonds contribute conformer stability that holds the protein structure at flexible state, so that PFCs acts as a barrier to cholesterol binding. From docking outcomes, representation space was created, that specifies high and medium StAR binders were occupied in toxic endpoints space with active concern. PFCs restrain molecular features and mitochondrial membrane disruption functions were revealed by efficient toxicogenomics studies. These data indicate toxicity and StAR protein binding levels of PFCs, sorted pinpoints could be useful in a promising way to know the other environmental pollutants and health risks. - Highlights: • In this study, QSAR models were revealed that PFCs have greater adverse toxicity along with nuclear receptors interaction potencies. • Binding potencies of PFCs against the StAR protein revealed only potential novel residue hotspots showed various bond patterns, and they sustain stability and complexity of StAR. • Through that, PFCs acts as a barrier in cholesterol binding and leads fatal consequences in steroidogenesis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Overexpression of SNX7 reduces Aβ production by enhancing lysosomal degradation of APP

Highlights: • SNX7 has been proposed to be linked with Alzheimer's disease. • Overexpression of SNX7 reduces the production of Aβ and sAPPβ. • It also reduces the cellular level of APP. • The reduction of APP is reversed by inhibitors of lysosomal degradation. • Our results suggest that SNX7 takes part in directing APP for degradation. Abnormal production of amyloid-β peptides (Aβ) by proteolytic processing of amyloid precursor protein (APP) is thought to be central to the pathogenesis of Alzheimer's disease (AD). Although many efforts have been made to investigate mechanisms that regulate APP processing, many details remain incompletely understood. Sorting nexins (SNXs) are a family of proteins which are involved in many intracellular trafficking events. Several SNXs have been implicated in APP processing and Aβ production. In this study, we extended the investigation to SNX7. We found that overexpression of SNX7 in HEK293T cells reduces the levels of secreted Aβ and β-cleaved N-terminal APP fragments (sAPPβ). Moreover, SNX7 overexpression caused a significant reduction of the steady-state levels of APP as well as of the cell surface APP levels. By using NH{sub 4}Cl and Bafilomycin A1 to inhibit the lysosomal degradative pathway, we found that the reduction of APP induced by SNX7 overexpression was prevented by such inhibition. No change in the cell surface distribution or steady-state levels of BACE1 was detected after overexpression of SNX7. Taken together, these results suggest that SNX7 regulates Aβ production by directing APP for degradation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

High ALDH activity defines ovarian cancer stem-like cells with enhanced invasiveness and EMT progress which are responsible for tumor invasion

Highlights: • Pluripotent, invasive and EMT-related genes are positively correlated. • The definition of ovarian ALDH{sup high} CSCLs is verified by their higher colony-formation, multipotent-genes expression and tumorigenicity. • Ovarian ALDH{sup high} CSCLs display advanced invasiveness, EMT progress and apoptosis-resistance. • ALDH{sup high} CSCLs take chief charge of EOC invasion, due to their elevated stemness and metastatic features. Epithelial ovarian cancer (EOC) is highly metastatic and current therapeutics are unsatisfactory. Cancer stem/stem-like cells (CSCs/CSCLs) represent a rare population of undifferentiated oncogenic cells responsible for tumor initiation and maintenance. We identified ovarian cancer ALDH{sup high} (aldehyde dehydrogenase) population could perform not only strengthened CSCLs properties embodied in colony-formation, CSCs-markers expression, and tumorigenesis in vivo, but also a greater invasive capacity with advanced EMT progress and anti-apoptosis compared with ALDH{sup low} cells. Furthermore, both the stemness and aggressive features, along with ALDH{sup high} percentages were in positive association with the invasiveness of cell lines for sorting, indicating the promotive role of ALDH{sup high} CSCLs in EOC neoplasia and metastasis, since the whole tumor was derived from the CSCLs with hyperactive self-renewal and aggression. Collectively, this study illustrates the interplay between ALDH{sup high} CSCLs and EOC invasion, and offers a novel application target for the EOC oncotherapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Activation of TLR3 and its adaptor TICAM-1 increases miR-21 levels in extracellular vesicles released from human cells

Highlights: • Activation of TLR3 increases miR-21 levels in extracellular vesicles. • TLR3 requires TICAM-1 adaptor to increase miR-21 levels in extracellular vesicles. • YBX-1 is involved in TLR3-mediated increase of miR-21 levels. Pattern-recognition receptors (PRRs) recognizes viral RNAs and trigger the innate immune responses. Toll-like receptor 3 (TLR3), a PRR, recognizes viral double-stranded RNA (dsRNA) in endolysosomes, whereas cytoplasmic dsRNA is sensed by another PRR, MDA5. TLR3 and MDA5 utilize TICAM-1 and MAVS, respectively, to trigger the signal for inducing innate immune responses. Extracellular vesicles (EVs) include the exosomes and microvesicles; an accumulating body of evidence has shown that EVs delivers functional RNA, such as microRNAs (miRNAs), to other cells and thus mediate intercellular communications. Therefore, EVs carrying miRNAs affect innate immune responses in macrophages and dendritic cells. However, the mechanism underlying the regulation of miRNA levels in EVs remains unclear. To elucidate the mechanism, we sought to reveal the pathway that control miRNA expression levels in EVs. Here, we found that TLR3 stimulation increased miR-21 levels in EVs released from various types of human cells. Ectopic expression of the TLR3 adaptor, TICAM-1, increased miR-21 levels in EVs but not intracellular miR-21 levels, suggesting that TICAM-1 augmented sorting of miR-21 to EVs. In contrast, the MDA5 adaptor, MAVS, did not increase miR-21 levels in EVs. The siRNA for TICAM-1 reduced EV miR-21 levels after stimulation of TLR3. Collectively, our data indicate a novel role of the TLR3-TICAM-1 pathway in controlling miR-21 levels in EVs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Effect of long non-coding RNA H19 on oxidative stress and chemotherapy resistance of CD133+ cancer stem cells via the MAPK/ERK signaling pathway in hepatocellular carcinoma

Highlights: • The H19 expression is higher in HCC tissues than in adjacent normal tissues. • CD133-positive Huh7 cells account for (99.4 ± 3.6)% by flow cytometry. • Inhibition of H19 induces OS in CD133 + cancer stem cells. • Inhibition of H19 reverses chemoresistance in CD133 + cancer stem cells. • Inhibition of H19 contributes to inactivation of MAPK/ERK signaling pathway. We explored the ability of a long non-coding RNA H19, to influence oxidative stress (OS) and chemotherapy resistance of CD133 + cancer stem cells via the MAPK/ERK signaling pathway in HCC. HCC tissues with corresponding adjacent normal tissues were collected. CD133 + HuH7 cells were sorted and assigned into five groups. Quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting were performed to determine expression levels mRNAs and proteins. Levels of reactive oxygen species (ROS) and malonaldehyde (MDA), and activity of superoxide dismutase (SOD) were measured. Cell viability was analyzed by MTT assay and cell apoptosis by flow cytometry. Compared with adjacent normal tissues, the H19 expression level was higher and MAPK and ERK protein levels were lower in HCC tissues. Compared with the blank group, in the pcDNA-H19 group, H19 expression level, MAPK and ERK protein levels, MDR1 and GST-π expression levels were increased, ROS and MDA levels were decreased, SOD activity was weakened, cell viability was promoted, and cell apoptosis was inhibited; in the siH19 group, H19 expression level, MAPK and ERK protein levels, MDR1 and GST-π expression levels were reduced, ROS and MDA levels were elevated, SOD activity was enhanced, cell viability was inhibited, and cell apoptosis was promoted. There was no significant difference among blank, NC and pcDNA-H19 + PD98059 groups. The study provides evidence that downregulation of H19 may induce OS and reverse chemotherapy resistance of CD133 + cancer stem cells by blocking the MAPK/ERK signaling pathway in HCC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Mouse model of chorea-acanthocytosis exhibits male infertility caused by impaired sperm motility as a result of ultrastructural morphological abnormalities in the mitochondrial sheath in the sperm midpiece

Chorea-acanthocytosis (ChAc) is an autosomal recessive hereditary disease characterized by neurodegeneration in the striatum and acanthocytosis caused by loss-of-function mutations in the Vacuolar Protein Sorting 13 Homolog A (VPS13A) gene, which encodes chorein. We previously produced a ChAc-model mouse with a homozygous deletion of exons 60–61 in Vps13a, which corresponded to the human disease mutation. We found that male ChAc-model mice exhibited complete infertility as a result of severely diminished sperm motility. Immunocytochemical study revealed that chorein-like immunoreactivity is abundant only in the midpiece, mitochondria-rich region, of the sperm of wild type mice. They showed no significant differences from wild types in terms of the adenosine 5′-triphosphate (ATP) concentration of their sperm, sperm count, or sexual activity. Electron microscopy revealed abnormal ultrastructural morphology of the mitochondria in the midpiece of sperm from ChAc-model mice. These results suggest that chorein is essential in mouse sperm for the maintenance of ultrastructural mitochondrial morphology and sperm motility.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Effects of Icaritin on the physiological activities of esophageal cancer stem cells

Highlights: • CSCs were used instead of using cancer cells. • The effect of Icaritin on the Hedgehog and Wnt signaling pathway was investigated. • Our study found that Icaritin down-regulated the level of Hedgehog, Smo and Gli in Hedgehog pathway, up-regulated GSK3β and down-regulated Wnt and β-catenin in Wnt pathway, indicating that Icaritin may inhibit the activity of esophageal CSCs through regulating the expression of proteins in important pathways related to esophageal cancer. Icaritin is a compound extracted from herb, recent study have found it is able to influence the activity of various types of cancer. Our aim was to investigate the effects of Icaritin on the physiological activities of esophageal cancer stem cells (CSCs). In this study, esophageal cancer cells were cultured and CD133 positive esophageal CSCs were sorted by flow cytometry. Changes in the physiological activity of esophageal CSCs following treatment with different concentrations of Icaritin (0, 12.5, 25, 50, and 100 μmol/L) were evaluated. The CCK-8 method and Transwell assay were used to determine the effects of Icaritin on the proliferation, migration, and invasion of esophageal CSCs. Flow cytometery was used to investigate its effect on the apoptosis of CSCs. The effect of Icaritin on the expression of proteins in Wnt and Hedgehog signaling pathways were determined using western blot test. Consequently, Icaritin inhibited the proliferation, migration, and invasion of esophageal CSCs in a dose-dependent manner. It promoted cell apoptosis, and influenced the levels of proteins in Wnt and Hedgehog signaling pathways. It may act as a promising drug in the therapy of esophageal cancer.

60 APPLIED LIFE SCIENCES↗