Multiscale Modeling of Binary Polymer Mixtures: Scale Bridging in the Athermal and Thermal Regime

Obtaining a rigorous and reliable method for linking computer simulations of polymer blends and composites at different length scales of interest is a highly desirable goal in soft matter physics. In this paper a multiscale modeling procedure is presented for the efficient calculation of the static structural properties of binary homopolymer blends. The procedure combines computer simulations of polymer chains on two different length scales, using a united atom representation for the finer structure and a highly coarse-grained approach on the meso-scale, where chains are represented as soft colloidal particles interacting through an effective potential. A method for combining the structural information by inverse mapping is discussed, allowing for the efficient calculation of partial correlation functions, which are compared with results from full united atom simulations. The structure of several polymer mixtures is obtained in an efficient manner for several mixtures in the homogeneous region of the phase diagram. The method is then extended to incorporate thermal fluctuations through an effective chi parameter. Since the approach is analytical, it is fully transferable to numerous systems.Comment: in press, 13 pages, 7 figures, 6 table

Satellite detection of dinoflagellate blooms off California by UV reflectance ratios

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Kahru, M., Anderson, C., Barton, A. D., Carter, M. L., Catlett, D., Send, U., Sosik, H. M., Weiss, E. L., & Mitchell, B. G. Satellite detection of dinoflagellate blooms off California by UV reflectance ratios. Elementa: Science of the Anthropocene, 9(1), (2021): 00157, https://doi.org/10.1525/elementa.2020.00157.As harmful algae blooms are increasing in frequency and magnitude, one goal of a new generation of higher spectral resolution satellite missions is to improve the potential of satellite optical data to monitor these events. A satellite-based algorithm proposed over two decades ago was used for the first time to monitor the extent and temporal evolution of a massive bloom of the dinoflagellate Lingulodinium polyedra off Southern California during April and May 2020. The algorithm uses ultraviolet (UV) data that have only recently become available from the single ocean color sensor on the Japanese GCOM-C satellite. Dinoflagellates contain high concentrations of mycosporine-like amino acids and release colored dissolved organic matter, both of which absorb strongly in the UV part of the spectrum. Ratios 1, consistent with historical observations showing a sharp transition from dinoflagellate- to diatom-dominated waters in these areas. UV bands are thus potentially useful in the remote sensing of phytoplankton blooms but are currently available only from a single ocean color sensor. As several new satellites such as the NASA Plankton, Aerosol, Cloud, and marine Ecosystem mission will include UV bands, new algorithms using these bands are needed to enable better monitoring of blooms, especially potentially harmful algal blooms, across large spatiotemporal scales.Part of this work was funded by National Science Foundation (NSF) grants to the CCE-LTER Program, most recently OCE-1637632. Processing of Second-Generation Global Imager satellite data was funded by Japan Aerospace Exploration Agency. Data shown in Figure 1 were collected by BGM and MK with support from the NASA SIMBIOS project. DC was supported by the NASA Biodiversity and Ecological Forecasting Program (Grant NNX14AR62A), the Bureau of Ocean and Energy Management Ecosystem Studies Program (BOEM award MC15AC00006), and the NOAA through the Santa Barbara Channel Marine Biodiversity Observation Network. HMS was supported by NSF (Grant OCE-1810927) and the Simons Foundation (Grant 561126). ELW was supported by NSF GRFP (Grant DGE-1650112). Funding for Scripps and Santa Monica Piers sampling was through the Southern California Coastal Ocean Observing Harmful Algal Bloom Monitoring Program by NOAA NA16NOS0120022

Metabolic Synergy between Human Symbionts \u3ci\u3eBacteroides\u3c/i\u3e and \u3ci\u3eMethanobrevibacter\u3c/i\u3e

ABSTRACT Trophic interactions between microbes are postulated to determine whether a host microbiome is healthy or causes predisposition to disease. Two abundant taxa, the Gram-negative heterotrophic bacterium Bacteroides thetaiotaomicron and the methanogenic archaeon Methanobrevibacter smithii, are proposed to have a synergistic metabolic relationship. Both organisms play vital roles in human gut health; B. thetaiotaomicron assists the host by fermenting dietary polysaccharides, whereas M. smithii consumes end-stage fermentation products and is hypothesized to relieve feedback inhibition of upstream microbes such as B. thetaiotaomicron. To study their metabolic interactions, we defined and optimized a coculture system and used software testing techniques to analyze growth under a range of conditions representing the nutrient environment of the host. We verify that B. thetaiotaomicron fermentation products are sufficient for M. smithii growth and that accumulation of fermentation products alters secretion of metabolites by B. thetaiotaomicron to benefit M. smithii. Studies suggest that B. thetaiotaomicron metabolic efficiency is greater in the absence of fermentation products or in the presence of M. smithii. Under certain conditions, B. thetaiotaomicron and M. smithii form interspecies granules consistent with behavior observed for syntrophic partnerships between microbes in soil or sediment enrichments and anaerobic digesters. Furthermore, when vitamin B12, hematin, and hydrogen gas are abundant, coculture growth is greater than the sum of growth observed for monocultures, suggesting that both organisms benefit from a synergistic mutual metabolic relationship. IMPORTANCE The human gut functions through a complex system of interactions between the host human tissue and the microbes which inhabit it. These diverse interactions are difficult to model or examine under controlled laboratory conditions. We studied the interactions between two dominant human gut microbes, B. thetaiotaomicron and M. smithii, using a seven-component culturing approach that allows the systematic examination of the metabolic complexity of this binary microbial system. By combining high-throughput methods with machine learning techniques, we were able to investigate the interactions between two dominant genera of the gut microbiome in a wide variety of environmental conditions. Our approach can be broadly applied to studying microbial interactions and may be extended to evaluate and curate computational metabolic models. The software tools developed for this study are available as user-friendly tutorials in the Department of Energy KBase

Effective Soft-Core Potentials and Mesoscopic Simulations of Binary Polymer Mixtures

Mesoscopic molecular dynamics simulations are used to determine the large scale structure of several binary polymer mixtures of various chemical architecture, concentration, and thermodynamic conditions. By implementing an analytical formalism, which is based on the solution to the Ornstein-Zernike equation, each polymer chain is mapped onto the level of a single soft colloid. From the appropriate closure relation, the effective, soft-core potential between coarse-grained units is obtained and used as input to our mesoscale simulations. The potential derived in this manner is analytical and explicitly parameter dependent, making it general and transferable to numerous systems of interest. From computer simulations performed under various thermodynamic conditions the structure of the polymer mixture, through pair correlation functions, is determined over the entire miscible region of the phase diagram. In the athermal regime mesoscale simulations exhibit quantitative agreement with united atom simulations. Furthermore, they also provide information at larger scales than can be attained by united atom simulations and in the thermal regime approaching the phase transition.Comment: 19 pages, 11 figures, 3 table

Big data and data repurposing – using existing data to answer new questions in vascular dementia research

Introduction: Traditional approaches to clinical research have, as yet, failed to provide effective treatments for vascular dementia (VaD). Novel approaches to collation and synthesis of data may allow for time and cost efficient hypothesis generating and testing. These approaches may have particular utility in helping us understand and treat a complex condition such as VaD. Methods: We present an overview of new uses for existing data to progress VaD research. The overview is the result of consultation with various stakeholders, focused literature review and learning from the group’s experience of successful approaches to data repurposing. In particular, we benefitted from the expert discussion and input of delegates at the 9th International Congress on Vascular Dementia (Ljubljana, 16-18th October 2015). Results: We agreed on key areas that could be of relevance to VaD research: systematic review of existing studies; individual patient level analyses of existing trials and cohorts and linking electronic health record data to other datasets. We illustrated each theme with a case-study of an existing project that has utilised this approach. Conclusions: There are many opportunities for the VaD research community to make better use of existing data. The volume of potentially available data is increasing and the opportunities for using these resources to progress the VaD research agenda are exciting. Of course, these approaches come with inherent limitations and biases, as bigger datasets are not necessarily better datasets and maintaining rigour and critical analysis will be key to optimising data use

LLL-3 inhibits STAT3 activity, suppresses glioblastoma cell growth and prolongs survival in a mouse glioblastoma model

Persistent activation of the signal transducer and activator of transcription 3 (STAT3) signalling has been linked to oncogenesis and the development of chemotherapy resistance in glioblastoma and other cancers. Inhibition of the STAT3 pathway thus represents an attractive therapeutic approach for cancer. In this study, we investigated the inhibitory effects of a small molecule compound known as LLL-3, which is a structural analogue of the earlier reported STAT3 inhibitor, STA-21, on the cell viability of human glioblastoma cells, U87, U373, and U251 expressing constitutively activated STAT3. We also investigated the inhibitory effects of LLL-3 on U87 glioblastoma cell growth in a mouse tumour model as well as the impact it had on the survival time of the treated mice. We observed that LLL-3 inhibited STAT3-dependent transcriptional and DNA binding activities. LLL-3 also inhibited viability of U87, U373, and U251 glioblastoma cells as well as induced apoptosis of these glioblastoma cell lines as evidenced by increased poly (ADP-ribose) polymerase (PARP) and caspase-3 cleavages. Furthermore, the U87 glioblastoma tumour-bearing mice treated with LLL-3 exhibited prolonged survival relative to vehicle-treated mice (28.5 vs 16 days) and had smaller intracranial tumours and no evidence of contralateral invasion. These results suggest that LLL-3 may be a potential therapeutic agent in the treatment of glioblastoma with constitutive STAT3 activation. Originally published in British Journal of Cancer 2009 Vol. 110, No.

Identification and Characterization of Antifungal Compounds Using a Saccharomyces cerevisiae Reporter Bioassay

New antifungal drugs are urgently needed due to the currently limited selection, the emergence of drug resistance, and the toxicity of several commonly used drugs. To identify drug leads, we screened small molecules using a Saccharomyces cerevisiae reporter bioassay in which S. cerevisiae heterologously expresses Hik1, a group III hybrid histidine kinase (HHK) from Magnaporthe grisea. Group III HHKs are integral in fungal cell physiology, and highly conserved throughout this kingdom; they are absent in mammals, making them an attractive drug target. Our screen identified compounds 13 and 33, which showed robust activity against numerous fungal genera including Candida spp., Cryptococcus spp. and molds such as Aspergillus fumigatus and Rhizopus oryzae. Drug-resistant Candida albicans from patients were also highly susceptible to compounds 13 and 33. While the compounds do not act directly on HHKs, microarray analysis showed that compound 13 induced transcripts associated with oxidative stress, and compound 33, transcripts linked with heavy metal stress. Both compounds were highly active against C. albicans biofilm, in vitro and in vivo, and exerted synergy with fluconazole, which was inactive alone. Thus, we identified potent, broad-spectrum antifungal drug leads from a small molecule screen using a high-throughput, S. cerevisiae reporter bioassay

Therapeutic effects of STAT3 decoy oligodeoxynucleotide on human lung cancer in xenograft mice

<p>Abstract</p> <p>Background</p> <p>Signal transducer and activator of transcription 3 (STAT3) is usually constitutively activated in a variety of malignancies. Therefore, STAT3 may be a promising target for treatment of tumor cells. To explore the possibility of a double-stranded decoy oligodeoxynucleotide (ODN) targeted blocking STAT3 over-activated tumor cells, we, here, evaluate the efficacy of STAT3 decoy ODN on human lung cancer cells <it>in vitro </it>and <it>in vivo</it>.</p> <p>Methods</p> <p>A STAT3 decoy ODN was transfected into A549 lung cancer cell line <it>in vitro </it>by using lipofectamine. The flow cytometry and fluorescent microscopy were used to detect the transfection efficiency and the sub-cellular localization of STAT3 decoy ODN in A549 cells. Cell proliferation was determined by counting cell numbers and [³H]-thymidine uptake. Cell apoptosis was examined with Annexin V and propidum iodide by flow cytometry. The expression levels of STAT3 target genes were identified by RT-PCR and immunoblot. For <it>in vivo </it>experiment, A549 lung carcinoma-nude mice xenograft was used as a model to examine the effect of the STAT3 decoy by intratumoral injection. At the end of treatment, TUNEL and immunohistochemistry were used to examine the apoptosis and the expression levels of bcl-xl and cyclin D1 in tumor tissues.</p> <p>Results</p> <p>STAT3 decoy ODN was effectively transfected into A549 lung cancer cells and mainly located in nucleus. STAT3-decoy ODN significantly induced apoptosis and reduced [³H]-thymidine incorporation of A549 cells as well as down-regulated STAT3-target genes <it>in vitro</it>. STAT3 decoy ODN also dramatically inhibited the lung tumor growth in xenografted nude mice and decreased gene expression of bcl-xl and cyclin D1.</p> <p>Conclusion</p> <p>STAT3 decoy ODN significantly suppressed lung cancer cells <it>in vitro </it>and <it>in vivo</it>, indicating that STAT3 decoy ODN may be a potential therapeutic approach for treatment of lung cancer.</p

LLL-3 inhibits STAT3 activity, suppresses glioblastoma cell growth and prolongs survival in a mouse glioblastoma model

Persistent activation of the signal transducer and activator of transcription 3 (STAT3) signalling has been linked to oncogenesis and the development of chemotherapy resistance in glioblastoma and other cancers. Inhibition of the STAT3 pathway thus represents an attractive therapeutic approach for cancer. In this study, we investigated the inhibitory effects of a small molecule compound known as LLL-3, which is a structural analogue of the earlier reported STAT3 inhibitor, STA-21, on the cell viability of human glioblastoma cells, U87, U373, and U251 expressing constitutively activated STAT3. We also investigated the inhibitory effects of LLL-3 on U87 glioblastoma cell growth in a mouse tumour model as well as the impact it had on the survival time of the treated mice. We observed that LLL-3 inhibited STAT3-dependent transcriptional and DNA binding activities. LLL-3 also inhibited viability of U87, U373, and U251 glioblastoma cells as well as induced apoptosis of these glioblastoma cell lines as evidenced by increased poly (ADP-ribose) polymerase (PARP) and caspase-3 cleavages. Furthermore, the U87 glioblastoma tumour-bearing mice treated with LLL-3 exhibited prolonged survival relative to vehicle-treated mice (28.5 vs 16 days) and had smaller intracranial tumours and no evidence of contralateral invasion. These results suggest that LLL-3 may be a potential therapeutic agent in the treatment of glioblastoma with constitutive STAT3 activation