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The world faces two seemingly unrelated challenges—a shortfall in the STEM workforce and increasing antibiotic resistance among bacterial pathogens. We address these two challenges with Tiny Earth, an undergraduate research course that excites students about science and creates a pipeline for antibiotic discovery.
Background. Induced pluripotent stem cells and their differentiated cardiomyocytes (iCMs) have tremendous potential as patient-specific therapy for ischemic cardiomyopathy following myocardial infarctions, but difficulties in viable transplantation limit clinical translation. Exosomes secreted from iCMs (iCM-Ex) can be robustly collected in vitro and injected in lieu of live iCMs as a cell-free therapy for myocardial infarction. Methods and Results. iCM-Ex were precipitated from iCM supernatant and characterized by protein marker expression, nanoparticle tracking analysis, and functionalized nanogold transmission electron microscopy. iCM-Ex were then used in in vitro and in vivo models of ischemic injuries. Cardiac function in vivo was evaluated by left ventricular ejection fraction and myocardial viability measurements by magnetic resonance imaging. Cardioprotective mechanisms were studied by JC-1 (tetraethylbenzimidazolylcarbocyanine iodide) assay, immunohistochemistry, quantitative real-time polymerase chain reaction, transmission electron microscopy, and immunoblotting. iCM-Ex measured ≈140 nm and expressed CD63 and CD9. iCM and iCM-Ex microRNA profiles had significant overlap, indicating that exosomal content was reflective of the parent cell. Mice treated with iCM-Ex demonstrated significant cardiac improvement post–myocardial infarction, with significantly reduced apoptosis and fibrosis. In vitro iCM apoptosis was significantly reduced by hypoxia and exosome biogenesis inhibition and restored by treatment with iCM-Ex or rapamycin. Autophagosome production and autophagy flux was upregulated in iCM-Ex groups in vivo and in vitro. Conclusions. iCM-Ex improve post–myocardial infarction cardiac function by regulating autophagy in hypoxic cardiomyoytes, enabling a cell-free, patient-specific therapy for ischemic cardiomyopathy.
Background Alcohol consumption is a risk factor for impaired fracture healing, though the mechanism(s) by which this occurs are not well understood. Our laboratory has previously shown that episodic alcohol exposure of rodents negatively affects fracture callus development, callus biomechanics, and cellular signaling which regulates stem cell differentiation. Here, we examine whether alcohol alters chemokine expression and/or signaling activity in the mouse fracture callus during early fracture healing. Methods A mouse model for alcohol-impaired tibia fracture healing was utilized. Early fracture callus was examined for alcohol-effects on tissue composition, expression of chemokines involved in MSC migration to the fracture site, and biomechanics. The effects of alcohol on MSC migration and cell adhesion receptors were examined in an in vitro system. Results Mice exposed to alcohol showed decreased evidence of external callus formation, decreased callus-related osteopontin (OPN) expression levels, and decreased biomechanical stiffness. Alcohol exposure decreased rOPN-mediated MSC migration and integrin β1 receptor expression in vitro. Conclusions The effects of alcohol exposure demonstrated here on fracture callus-associated OPN expression, rOPN-mediated MSC migration in vitro, and MSC integrin β1 receptor expression in vitro have not been previously reported. Understanding the effects of alcohol exposure on the early stages of fracture repair may allow timely initiation of treatment to mitigate the long-term complications of delayed healing and/or fracture non-union.
Background and Objectives: Identifying protein targets that provide cognitive reserve is a strategy to prevent and treat Alzheimer disease and Alzheimer disease related dementias (AD/ADRD). Previous studies using bulk human brain tissue reported 12 proteins associated with cognitive reserve. This study examined whether the same proteins from induced neurons (iNs) are associated with cognitive reserve of their human donors. Methods: Here, induced pluripotent stem cell (iPSC) lines were generated from cryopreserved peripheral blood mononuclear cells of older adults who were autopsied as part of the Religious Orders Study or Rush Memory and Aging Project. Neurons were induced from iPSCs using a standard neurogenin2 protocol. Tandem mass tag proteomics analyses were conducted on iNs day 21. Cognitive reserve of their human donors was measured as person-specific slopes of cognitive change not accounted for by common neuropathologies. Results: The 53 human donors died at a mean age of 91 years, all were non-Latino White, and 36 (67.9%) were female. Eighteen were diagnosed with Alzheimer dementia proximate to death, and 34 had pathologic AD diagnosis at autopsy. Approximately 60% of the donors had above-average cognitive reserve such that their cognition declined slower than an average person with comparable burdens of neuropathologies. Eight of the 12 candidate proteins were quantified in iNs proteomics analyses. Higher adenylate kinase 4 (AK4) expression in iNs was associated with lower cognitive reserve, consistent with the previous report for brain AK4 expression. Discussion: By replicating cortical protein associations with cognitive reserve in human iNs, these data provide a valuable molecular readout for studying complex clinical phenotypes such as cognitive reserve in a dish.
Comprehensive analysis of cis-regulatory elements is key to understanding the dynamic gene regulatory networks that control embryonic development. While transgenic animals represent the gold standard assay, their generation is costly, entails significant animal usage, and in utero development complicates time-course studies. As an alternative, embryonic stem (ES) cells can readily be differentiated in a process that correlates well with developing embryos. Here, we describe a highly effective platform for enhancer assays using an Hsp68/ Venus reporter cassette that targets to the Hprt locus in mouse ES cells. This platform combines the flexibility of Gateway H cloning, live cell trackability of a fluorescent reporter, low background and the advantages of single copy insertion into a defined genomic locus. We demonstrate the successful recapitulation of tissue-specific enhancer activity for two cardiac and two haematopoietic enhancers. In addition, we used this assay to dissect the functionality of the highly conserved Ets/Ets/Gata motif in the Scl+19 enhancer, which revealed that the Gata motif is not required for initiation of enhancer activity. We further confirmed that Gata2 is not required for endothelial activity of the Scl+19 enhancer using Gata2 -/- Scl+19 transgenic embryos. We have therefore established a valuable toolbox to study gene regulatory networks with broad applicability.
Sm-doped BiFeO3 STEM datasets collected by Chris Nelson. Sample created at University of Maryland.
Graphene STEM datasets created by Ondrej Dyck. Datasets from July 2, 2018 C1 ArO graphene box1 lot 4670 (high res images, 100kV video graphene degradation).
This is supplemental information to a paper tentatively titled Applying Data Analytics Methods to X-ray Spectrum Images. Datasets are in the format of .h5 in the pyUSID flavor. SEM_small.h5 is 5 keV beam energy map of a TiB2 ceramic puck. SEM_large.h5 is a 20 keV map of the same sample. STEM.h5 is a STEM 200 keV map of neutron-irradiated tungsten (due to transmutation burnout, it has become a W-Re-Os alloy).
DFT is used to optimize defects in monolayer MX2 phases. We calculate ~600 optimized defect structures, then use multislice simulations in abTEM to generate STEM digital twins, which can be used to train experimental ML. The reference paper for procedures and demonstration of their utility is https://arxiv.org/abs/2305.02917, and the images here correspond with the discussed Messy dataset.
DFT is used to optimize defects in monolayer MX2 phases. We calculate ~600 optimized defect structures, then use multislice simulations in abTEM to generate STEM digital twins, which can be used to train experimental ML. The reference paper for procedures and demonstration of their utility is https://arxiv.org/abs/2305.02917, and the images here correspond with the discussed Messy dataset. Version 2 includes an auxiliary dataset matched with experiment.
Pluripotent embryonic stem cells are of paramount importance for biomedical sciences because of their innate ability for self-renewal and differentiation into all major cell lines. The fateful decision to exit or remain in the pluripotent state is regulated by complex genetic regulatory networks. The rapid growth of single-cell sequencing data has greatly stimulated applications of statistical and machine learning methods for inferring topologies of pluripotency regulating genetic networks. The inferred network topologies, however, often only encode Boolean information while remaining silent about the roles of dynamics and molecular stochasticity inherent in gene expression. Herein we develop a framework for systematically extending Boolean-level network topologies into higher resolution models of networks which explicitly account for the promoter architectures and gene state switching dynamics. We show the framework to be useful for disentangling the various contributions that gene switching, external signaling, and network topology make to the global heterogeneity and dynamics of transcription factor populations. We find the pluripotent state of the network to be a steady state which is robust to global variations of gene switching rates which we argue are a good proxy for epigenetic states of individual promoters. The temporal dynamics of exiting the pluripotent state, on the other hand, is significantly influenced by the rates of genetic switching which makes cells more responsive to changes in extracellular signals.
Nanoparticles of heavy materials such as gold can be used as markers in quantitative electron microscopic studies of protein distributions in cells with nanometer spatial resolution. Studying nanoparticles within the context of cells is also relevant for nanotoxicological research. Here, we report a method to quantify the locations and the number of nanoparticles, and of clusters of nanoparticles inside whole eukaryotic cells in three dimensions using scanning transmission electron microscopy (STEM) tomography. Whole-mount fixed cellular samples were prepared, avoiding sectioning or slicing. The level of membrane staining was kept much lower than is common practice in transmission electron microscopy (TEM), such that the nanoparticles could be detected throughout the entire cellular thickness. Tilt-series were recorded with a limited tilt-range of 80° thereby preventing excessive beam broadening occurring at higher tilt angles. The 3D locations of the nanoparticles were nevertheless determined with high precision using computation. The obtained information differed from that obtained with conventional TEM tomography data since the nanoparticles were highlighted while only faint contrast was obtained on the cellular material. Similar as in fluorescence microscopy, a particular set of labels can be studied. This method was applied to study the fate of sequentially up-taken low-density lipoprotein (LDL) conjugated to gold nanoparticles in macrophages. Analysis of a 3D reconstruction revealed that newly up-taken LDL-gold was delivered to lysosomes containing previously up-taken LDL-gold thereby forming onion-like clusters.
The presence of cancer stem cells (CSCs) and the induction of epithelial-to-mesenchymal transition (EMT) in tumors are associated with tumor aggressiveness, metastasis, drug resistance, and poor prognosis, necessitating the development of reagents for unambiguous detection of CSC- and EMT-associated proteins in tumor specimens. To this end, we generated novel antibodies to EMT- and CSC-associated proteins, including Goosecoid, Sox9, Slug, Snail, and CD133. Importantly, unlike several widely used antibodies to CD133, the anti-CD133 antibodies we generated recognize epitopes distal to known glycosylation sites, enabling analyses that are not confounded by differences in CD133 glycosylation. For all target proteins, we selected antibodies that yielded the expected target protein molecular weights by Western analysis and the correct subcellular localization patterns by immunofluorescence microscopy assay (IFA); binding selectivity was verified by immunoprecipitation-mass spectrometry and by immunohistochemistry and IFA peptide blocking experiments. Finally, we applied these reagents to assess modulation of the respective markers of EMT and CSCs in xenograft tumor models by IFA. We observed that the constitutive presence of human hepatocyte growth factor (hHGF) in the tumor microenvironment of H596 non-small cell lung cancer tumors implanted in homozygous hHGF knock-in transgenic mice induced a more mesenchymal-like tumor state (relative to the epithelial-like state when implanted in control SCID mice), as evidenced by the elevated expression of EMT-associated transcription factors detected by our novel antibodies. Similarly, our new anti-CD133 antibody enabled detection and quantitation of drug-induced reductions in CD133-positive tumor cells following treatment of SUM149PT triple-negative breast cancer xenograft models with the CSC/focal adhesion kinase (FAK) inhibitor VS-6063. Thus, our novel antibodies to CSC- and EMT-associated factors exhibit sufficient sensitivity and selectivity for immunofluorescence microscopy studies of these processes in preclinical xenograft tumor specimens and the potential for application with clinical samples.
Cellulosic butanol is a very promising renewable fuel to consider for the future transportation market. However, the seasonal availability of the raw materials, high maintenance cost, and high logistical cost of the biomass energy supply chain are the main factors impeding the commercialization and large-scale-production of this energy source. Furthermore, research focusing on an environmental or green supply chain network design of cellulosic butanol has been insufficient. Here, this study focused on designing a green supply chain network for cellulosic butanol. A life cycle analysis was integrated into a multi-objective linear programming model to optimize the cellulosic butanol supply chain network. With the objectives of maximizing the economic profits and minimizing the greenhouse gas emissions, the proposed model can optimize the location and size of a bio-butanol production plant. The mathematical model was applied to a case study in the state of Missouri, and solved the tradeoff between the feedstock and market availabilities of sorghum stem bio-butanol.
Cleaned midday and predawn water potential data from 14 stem psychrometers installed within the footprint of the US-CdM flux tower, from May-October 2021. These data were collected in order to link environmental drivers, vegetation responses to seasonal water stress, and ecosystem fluxes of carbon and water at a pinyon-juniper woodland in southeastern Utah.Data include a comma separated values file containing all water potential data used in the published paper. Data were first published in Kannenberg et al. 2023 Agricultural and Forest Meteorology (doi: 10.1016/j.agrformet.2022.109269). Flux data are publicly available from the AmeriFlux portal (doi: 10.17190/AMF/1865477). This data file and the AmeriFlux data are all that is necessary to replicate the analyses in Kannenberg et al. 2023 Agricultural and Forest Meteorology.
It is not yet known whether hematopoietic stem and progenitor cells (HSPCs) are compromised in the aging population of atomic bomb (A-bomb) survivors after their exposure nearly 70 years ago. To address this, we evaluated age- and radiation-related changes in different subtypes of circulating HSPCs among the CD34-positive/lineage marker-negative (CD34+Lin - ) cell population in 231 Hiroshima A-bomb survivors. We enumerated functional HSPC subtypes, including: cobblestone area-forming cells; long-term culture-initiating cells; erythroid burst-forming units; granulocyte and macrophage colony-forming units; and T-cell and natural killer cell progenitors using cell culture. We obtained the count of each HSPC subtype per unit volume of blood and the proportion of each HSPC subtype in CD34+Lin - cells to represent the lineage commitment trend. Multivariate analyses, using sex, age and radiation dose as variables, showed significantly decreased counts with age in the total CD34+Lin - cell population and all HSPC subtypes. As for the proportion, only T-cell progenitors decreased significantly with age, suggesting that the commitment to the T-cell lineage in HSPCs continuously declines with age throughout the lifetime. However, neither the CD34+Lin - cell population, nor HSPC subtypes showed significant radiation-induced dose-dependent changes in counts or proportions. Moreover, the correlations of the proportions among HSPC subtypes in the survivors properly revealed the hierarchy of lineage commitments. In conclusion, taken together, our findings suggest that many years after exposure to radiation and with advancing age, the number and function of HSPCs in living survivors as a whole may have recovered to normal levels.
Over the course of the last twelve weeks, I have been contributing to efforts in high efficiency solid state thermal neutron detection at Lawrence Livermore National Laboratory (LLNL) as a DHS HS-STEM intern. Reliable, high efficiency solid state thermal neutron detectors are desired to replace conventional 3 He gas filled tube technologies which have fieldability issues due to size, high operating voltage requirements, sensitivity to microphonics, and the recently rapidly diminishing supply of 3 He gas. Under the supervision of Rebecca Nikolić and Qinghui Shao, I have been developing an experimental plan to modify the doping profile of LLNL’s silicon-based pillar structured thermal neutron detector. The overall goal of this work is to reduce the capacitance and leakage current of the Pillar detector to enable the device area to be increased while maintaining a high thermal neutron detection efficiency.
Throughout my HS-STEM internship, I worked on two different projects with a systems analysis group at Sandia National Laboratories in Livermore, California (SNLCA). The first, and primary, project entailed building a conceptual model of health surveillance detection of a bioterror attack. The second project was much smaller in scope and looked at cost tradeoffs between volumetric and surface decontamination after the release of anthrax in a city. Both projects helped me to understand the challenges of planning for a bioterror attack and the importance of preparedness in the public health sector.