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One of the main sources of uncertainty for understanding global warming is understanding the formation of larger secondary aerosols.
more » « less- Award ID(s):
- 2018427
- NSF-PAR ID:
- 10467364
- Publisher / Repository:
- RSC
- Date Published:
- Journal Name:
- Environmental Science: Atmospheres
- Volume:
- 3
- Issue:
- 9
- ISSN:
- 2634-3606
- Page Range / eLocation ID:
- 1335 to 1351
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Recently, slow molecular dynamics of poly(
l ‐lactic acid) (PLLA) by using 1D and 2D exchange NMR are investigated. In this work, slow molecular dynamics of PLLA chains in the α′, a stereocomplex (SC) with poly(d ‐lactic acid), and glassy states are investigated in terms of centerband‐only detection of exchange (CODEX) NMR. The mixing‐time dependence of the CODEX data demonstrates that the molecular dynamics of stems become slower in the order of α′, α, and SC. The temperature dependence of the correlation time 〈τc〉 of the helical jump motions in the α and SC phases simply exhibits Arrhenius behaviors, with activation energy,E a, values of 91 ± 1 and 97 ± 1 kJ mol−1, respectively. In contrast, the temperature dependence of 〈τc〉 in the α′ sample exhibits two Arrhenius lines with substantially differentE avalues of 273 ± 12 and 16 ± 14 kJ mol−1at temperatures below and above 84 °C. The obtained kinetics of molecular dynamics not only establish the relationship between packing structure and dynamics in PLLA polymorphs and in the SC, but also allow for an understanding of the coupled dynamics between the crystalline and amorphous regions at approximatelyT g. -
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ABSTRACT Glioblastoma multiforme (GBM) is the deadliest form of primary brain tumor. GBM tumors are highly heterogeneous, being composed of tumor cells as well as glioblastoma stem cells (GSCs) that contribute to drug resistance and tumor recurrence following treatment. To develop therapeutic strategies, an improved understanding of GSC behavior in their microenvironment is critical. Herein, we have employed three‐dimensional (3D) hyaluronic acid (HA) hydrogels that allow the incorporation of brain microenvironmental cues to investigate GSC behavior. U87 cell line and patient‐derived D456 cells were cultured as suspension cultures (serum‐free) and adherently (in the presence of serum) and were then encapsulated in HA hydrogels. We observed that all the seeded single cells expanded and formed spheres, and the size of the spheres increased with time. Increasing the initial cell seeding density of cells influenced the sphere size distribution. Interestingly, clonal expansion of serum‐free grown tumor cells in HA hydrogels was observed. Also, stemness marker expression of serum and/or serum‐free grown cells was altered when cultured in HA hydrogels. Finally, we demonstrated that HA hydrogels can support long‐term GSC culture (up to 60 days) with retention of stemness markers. Overall, such biomimetic culture systems could further our understanding of the microenvironmental regulation of GSC phenotypes.
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Abstract Compound‐specific stable isotope analysis of individual amino acids (CSIA‐AA) has emerged as a transformative approach to estimate consumer trophic positions (TPCSIA) that are internally indexed to primary producer nitrogen isotope baselines. Central to accurate TPCSIAestimation is an understanding of beta (
β ) values—the differences between trophic and source AA δ15N values in the primary producers at the base of a consumers’ food web. Growing evidence suggests higher taxonomic and tissue‐specificβ value variability than typically appreciated.This meta‐analysis fulfils a pressing need to comprehensively evaluate relevant sources of
β value variability and its contribution to TPCSIAuncertainty. We first synthesized all published primary producer AA δ15N data to investigate ecologically relevant sources of variability (e.g. taxonomy, tissue type, habitat type, mode of photosynthesis). We then reviewed the biogeochemical mechanisms underpinning AA δ15N andβ value variability. Lastly, we evaluated the sensitivity of TPCSIAestimates to uncertainty in meanβ Glx‐Phevalues and Glx‐Phe trophic discrimination factors (TDFGlx‐Phe).We show that variation in
β Glx‐Phevalues is two times greater than previously considered, with degree of vascularization, not habitat type (terrestrial vs. aquatic), providing the greatest source of variability (vascular autotroph = −6.6 ± 3.4‰; non‐vascular autotroph = +3.3 ± 1.8‰). Within vascular plants, tissue type secondarily contributed toβ Glx‐Phevalue variability, but we found no clear distinction among C3, C4and CAM plantβ Glx‐Phevalues. Notably, we found that vascular plantβ Glx‐Lysvalues (+2.5 ± 1.6‰) are considerably less variable thanβ Glx‐Phevalues, making Lys a useful AA tracer of primary production sources in terrestrial systems. Our multi‐trophic level sensitivity analyses demonstrate that TPCSIAestimates are highly sensitive to changes in bothβ Glx‐Pheand TDFGlx‐Phevalues but that the relative influence ofβ values dissipates at higher trophic levels.Our results highlight that primary producer
β values are integral to accurate trophic position estimation. We outline four key recommendations for identifying, constraining and accounting forβ value variability to improve TPCSIAestimation accuracy and precision moving forward. We must ultimately expand libraries of primary producer AA δ15N values to better understand the mechanistic drivers ofβ value variation. -
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Rationale Protein studies in archaeology and paleontology have been dominated by stable isotope studies to understand diet and trophic levels, but recent applications of proteomic techniques have resulted in a more complete understanding of protein diagenesis than stable isotopes alone. In stable isotope analyses, samples are retained or discarded based on their properties. Proteomics can directly determine what proteins are present within the sample and may be able to allow previously discarded samples to be analyzed.
Methods Protein samples that had been previously analyzed for stable isotopes, including those with marginal and poor sample quality, were characterized by liquid chromatography/mass spectrometry using an LTQ Orbitrap Velos mass spectrometer after separation on a Dionex Ultimate 3000 LC system. Data were analyzed using MetaMorpheus and custom R scripts.
Results We found a variety of proteins in addition to collagen, although collagen I was found in the majority of the samples (most samples >80%). We also found a positive correlation between total deamidation and wt% N, suggesting that deamidation may impact the overall nitrogen signal in bulk analyses. The amino acid profiles of samples, including those of marginal or poor stable isotope quality, reflect the expected collagen I percentages, allowing their use in single amino acid stable isotope analyses.
Conclusions All the samples regardless of quality were found to have high concentrations of collagen I, making interpretations of dietary routing based on collagen I reasonably valid. The amino acid profiles on the marginal and poor samples reflect an expected collagen I profile and allow these samples to be recovered for single amino acid analyses.
