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Open Access Publications from the University of California

Scholarly Works (16 results)

  • Thesis
  • Peer Reviewed
UCLA Electronic Theses and Dissertations (2022)

This work focuses on exploring the site identity of ion exchanged Zn sites in BEA zeolites and their role in the conversion of biomass-derived oxygenates. Careful preparation of ion exchanged Zn in BEA (Zn-BEA) allowed for the generation of different catalytic sites within the pores of the zeolite. Depending on the preparation method, Zn species have been suggested to exist as extra-pore large ZnO clusters, isolated Zn2+ ions at the cation-exchange site, Zn(OH)+ ions exchanged to one aluminum sites, binuclear [Zn-O-Zn]2+ clusters formed from the coupling of neighboring Zn(OH)+ species, and Zn2+ exchanged to two aluminum sites. In order to probe the oxidation state and local structure of the Zn, in situ Zn K-edge x-ray absorption spectroscopy was conducted at SLAC National Accelerator Laboratory. Spectra were taken of Zn-BEA before and after the temperature treatment process. The increase in Zn absorption edge energies in these catalysts compared to Zn standards suggests increased oxidation of Zn sites. The features at the absorption edge change during the temperature treatment, splitting from a single peak into two peaks. The lasting changes at the white line suggests the coordination sphere of Zn sites changes significantly during the activation process. Analysis of the EXAFS region was conducted to examine the local structure of Zn in the catalysts. Fitting was carried out simultaneously through the samples, effectively constraining fits with shared parameters to allow for more reliable models. There was a lack of Zn-Zn and Zn-Si contributions in the first and second coordination shell, which indicates that Zn atoms were exchanged into isolated exchange positions without the formation of a significant amount of Zn clusters. In situ thermal treatment of Zn-BEA caused the number of oxygen neighbors to decrease in the first coordination shell. This supports the theory that as-prepared samples of Zn-BEA have water coordinated to Zn sites within the pores of the zeolite and the temperature treatment process dehydrates the catalyst. There was a strong correlation between oxygen bond distance and Zn concentration, suggesting that Zn has an increasingly strong interaction with framework oxygen as the degree of ion exchange decreases. Changes in bond distance as more Zn is introduced to the pores can be explained shifts in the preferential ion exchange positions for Zn. As Zn replaces Br�nsted acid sites during the ion exchange process, the lowest energy exchange locations may shift between the four-, five-, and six-member rings. Br�nsted and Lewis acid site density was measured by in situ titration during acid catalyzed isopropanol dehydration using probe molecules of pyridine and 2,6-di-tert-butylpyridine. By measuring the acid site densities, Zn-BEA has been shown to lose Br�nsted acid sites during the temperature treatment process. Changes in the calculated Lewis acid site concentrations can suggest the presence of shifts in preferred site structures as Zn concentration increases. The chemical compositions of the catalysts were determined by inductively coupled plasma – optical emission spectrometry. This catalyst characterization was combined with the activity of Zn-BEA for methanol dehydration to determine the reactivity of different Zn sites. The conversion of butyraldehyde over a range of Zn loadings on Zn-BEA was also conducted to probe how the local structure of Zn sites influence the rates and selectivity of the various pathways in reactions of butyraldehyde.

    Cover page: Catalytic site requirements for conversion of oxygenates on Zinc-exchanged BEA zeolites
    • Article
    • Peer Reviewed
    UCLA Previously Published Works (2022)
      Cover page: Applying molecular algorithms to predict decreased susceptibility to ceftriaxone from a report of strains of Neisseria gonorrhoeae in Amsterdam, the Netherlands
      • Article
      UCLA Previously Published Works (2022)
      Abstract Antimicrobial resistance in Neisseria gonorrhoeae is an urgent global health issue 1. Resistance to ceftriaxone, the mainstay of gonorrhea treatment, is increasing2,3. Many genotypic mutations are associated with decreased susceptibility to ceftriaxone 4,5. In this study, N. gonorrhoeae genomes from the PathogenWatch database were downloaded and used to train and test different machine learning (ML) models to predict ceftriaxone susceptibility/decreased susceptibility (S/DS). We evaluated seven different ML algorithms with 97 SNPs that are known to be associated with ceftriaxone resistance. After identifying the ML algorithm with the highest performance metrics, the impact score of individual SNPs were calculated. The algorithm was then retrained using various combinations of top scoring SNPs to measure performance. The study identified 5 SNPs that performed well to predict decreased susceptibility and might be promising targets for molecular assays to predict S/DS to ceftriaxone. The ML methods reported here might have applications for predicting AMR within other pathogens.
        • Article
        • Peer Reviewed
        UCLA Previously Published Works (2021)
        Neisseria gonorrhoeae is the second most common bacterial sexually transmitted infection in the world after Chlamydia trachomatis. The pathogen has developed resistance to every antibiotic currently approved for treatment, and multidrug-resistant strains have been identified globally. The current treatment recommended by the World Health Organization is ceftriaxone and azithromycin dual therapy. However, resistance to azithromycin and ceftriaxone are increasing and treatment failures have been reported. As a result, there is a critical need to develop novel strategies for mitigating the spread of antimicrobial-resistant N. gonorrhoeae through improved diagnosis and treatment of resistant infections. Strategies that are currently being pursued include developing molecular assays to predict resistance, utilizing higher doses of ceftriaxone, repurposing older antibiotics, and developing newer agents. In addition, efforts to discover a vaccine for N. gonorrhoeae have been reignited in recent years with the cross-protectivity provided by the N. meningitidis vaccine, with several new strategies and targets. Despite the significant progress that has been made, there is still much work ahead to combat antimicrobial-resistant N. gonorrhoeae globally.
          Cover page: Epidemiology, Treatments, and Vaccine Development for Antimicrobial-Resistant Neisseria gonorrhoeae: Current Strategies and Future Directions
          • Article
          • Peer Reviewed
          UCLA Previously Published Works (2023)
          Antimicrobial resistance in Neisseria gonorrhoeae is an urgent global health issue. The objectives of the study were to use a global collection of 12,936 N. gonorrhoeae genomes from the PathogenWatch database to evaluate different machine learning models to predict ceftriaxone susceptibility/decreased susceptibility using 97 mutations known to be associated with ceftriaxone resistance. We found the random forest classifier model had the highest performance. The analysis also reported the relative contributions of different mutations within the ML model predictions, allowing for the identification of the mutations with the highest importance for ceftriaxone resistance. A machine learning model retrained with the top five mutations performed similarly to the model using all 97 mutations. These results could aid in the development of molecular tests to detect resistance to ceftriaxone in N. gonorrhoeae. Moreover, this approach could be applied to building and evaluating machine learning models for predicting antimicrobial resistance in other pathogens.
            Cover page: Machine learning to predict ceftriaxone resistance using single nucleotide polymorphisms within a global database of Neisseria gonorrhoeae genomes.Creative Commons 'BY' version 4.0 license
            • Article
            • Peer Reviewed
            UCLA Previously Published Works (2021)

            Background

            Globally, decreased susceptibility to ceftriaxone in Neisseria gonorrhoeae is rising. We aimed to compile a global collection of N. gonorrhoeae strains and assess the genetic characteristics associated with decreased susceptibility to ceftriaxone.

            Methods

            We performed a literature review of all published reports of N. gonorrhoeae strains with decreased susceptibility to ceftriaxone (>0.064 mg/L minimum inhibitory concentration) through October 2019. Genetic mutations in N. gonorrhoeae genes (penA, penB, mtrR, and ponA), including determination of penA mosaicism, were compiled and evaluated for predicting decreased susceptibility to ceftriaxone.

            Results

            There were 3821 N. gonorrhoeae strains identified from 23 countries and 684 (18%) had decreased susceptibility to ceftriaxone. High sensitivities or specificities (>95%) were found for specific genetic mutations in penA, penB, mtrR, and ponA, both with and without determination of penA mosaicism. Four algorithms to predict ceftriaxone susceptibility were proposed based on penA mosaicism determination and penA or non-penA genetic mutations, with sensitivity and specificity combinations up to 95% and 62%, respectively.

            Conclusion

            Molecular algorithms based on genetic mutations were proposed to predict decreased susceptibility to ceftriaxone in N. gonorrhoeae. Those algorithms can serve as a foundation for the development of future assays predicting ceftriaxone decreased susceptibility within N. gonorrhoeae globally.
              Cover page: Establishing Novel Molecular Algorithms to Predict Decreased Susceptibility to Ceftriaxone in Neisseria gonorrhoeae Strains
              • Article
              • Peer Reviewed
              UCLA Previously Published Works (2022)
              Antimicrobial resistance in N. gonorrhoeae is increasing globally, and ceftriaxone is the recommended treatment for empirical therapy in most settings. Developing molecular assays to detect decreased ceftriaxone susceptibility is critical. Using PathogenWatch, a public database of N. gonorrhoeae genomes, antibiotic susceptibility data and DNA sequences of different genes associated with ceftriaxone resistance were extracted. That information was used to determine the sensitivity and specificity of different molecular markers and algorithms to predict decreased susceptibility to ceftriaxone. A total of 12,943 N. gonorrhoeae genomes were extracted from the PathogenWatch database, of which 9,540 genomes were used in the analysis. The sensitivity and specificity of specific molecular markers and algorithms were largely consistent with prior reports. Small variation (<10%) in either sensitivity or specificity occurred. Certain algorithms using different molecular markers at various prevalence of decreased ceftriaxone susceptibility identified a potentially clinically useful range of positive and negative predictive values. We validated previously described mutations and algorithms in a large public database containing a global collection of N. gonorrhoeae genomes. Certain mutations and algorithms resulted in sensitivity and specificity values consistent with those of prior studies. Further research is needed to integrate these markers and algorithms into the development of molecular assays to predict decreased ceftriaxone susceptibility. IMPORTANCE Antimicrobial resistance in Neisseria gonorrhoeae (N. gonorrhoeae), the causative agent of gonorrhea, is rising globally. Ceftriaxone is the last remaining antibiotic for empirical treatment of gonorrhea. Developing molecular tests to predict ceftriaxone resistance can help to improve detection and surveillance of ceftriaxone resistance. Here, we utilized PathogenWatch, a public global online database of N. gonorrhoeae genomes, to evaluate different genetic markers in predicting decreased susceptibility to ceftriaxone. We compiled MICs for ceftriaxone from the PathogenWatch database and used a computational approach to extract all the genetic markers from the genomic data. We determined the sensitivity and specificity for predicting decreased ceftriaxone susceptibility among several combinations of genetic markers. We identified several combinations of genetic markers with high predictive values for decreased susceptibility to ceftriaxone. These combinations of genetic markers might be promising candidates for future molecular tests to predict ceftriaxone resistance.
                Cover page: Reliability of Genetic Alterations in Predicting Ceftriaxone Resistance in Neisseria gonorrhoeae GloballyCreative Commons 'BY' version 4.0 license
                • Article
                • Peer Reviewed
                UCLA Previously Published Works (2021)

                Background

                Antimicrobial resistance (AMR) in Neisseria gonorrhoeae is an urgent global health threat. Zoliflodacin is a novel antibiotic undergoing clinical trials for the treatment of gonorrhoea. While there are limited data regarding zoliflodacin resistance in N. gonorrhoeae, three amino acid mutations have been associated with increased MICs of zoliflodacin.

                Objectives

                To determine the prevalence of three amino acid mutations associated with zoliflodacin resistance within a large, public database of nearly 13 000 N. gonorrhoeae genomes.

                Methods

                PathogenWatch is an online genomic epidemiology platform with a public database of N. gonorrhoeae genomes. That database was used to extract gyrB sequence data and a Basic Local Alignment Search Tool (BLAST) search was performed to identify any of the three amino acid mutations in GyrB that are associated with increased zoliflodacin MICs: D429N, K450N or K450T. As a control for the search methodology, all GyrA sequences were also extracted and S91F mutations were identified and compared with the PathogenWatch database.

                Results

                In total, 12 493 N. gonorrhoeae genomes from the PathogenWatch database were included. Among those genomes, none was identified that harboured any of the three mutations associated with increased zoliflodacin MICs. One genome was identified to have a mutation at position 429 in GyrB (D429V).

                Conclusions

                The findings suggest that the prevalence of the three mutations associated with zoliflodacin resistance in N. gonorrhoeae is very low. However, further research into the mechanisms of zoliflodacin resistance in N. gonorrhoeae is needed. Genomic epidemiology platforms like PathogenWatch can be used to enhance the global surveillance of AMR.
                  Cover page: Using a public database of Neisseria gonorrhoeae genomes to detect mutations associated with zoliflodacin resistance
                  • Article
                  • Peer Reviewed
                  UCLA Previously Published Works (2023)
                  In vivo imaging using shortwave infrared light (SWIR, 1000–2000 nm) benefits from deeper penetration and higher resolution compared to using visible and near-infrared wavelengths. However, the development of biocompatible SWIR contrast agents remains challenging. Despite recent advancements, small molecule SWIR fluorophores are often hindered by their significant hydrophobicity. We report a platform for generating a panel of soluble and functional dyes for SWIR imaging by late-stage functionalization of a versatile fluorophore intermediate, affording water-soluble dyes with bright SWIR fluorescence in serum. Specifically, a tetra-sulfonate derivative enables clear video-rate imaging of vasculature with only 0.05 nmol dye, and a tetra-ammonium dye shows strong cellular retention for tracking of tumor growth. Additionally, incorporation of phosphonate functionality enables imaging of bone in awake mice. This modular design provides insights for facile derivatization of existing SWIR fluorophores to introduce both solubility and bioactivity towards in vivo bioimaging.eTOC blurbThe development of small molecule shortwave infrared (SWIR, 1000–2000 nm) fluorophores for in vivo imaging has recently exploded; however, most SWIR-emissive fluorophores are hydrophobic. Here, we performed late-stage functionalization of a chromenylium heptamethine dye to introduce aqueous solubility and/or bioactivity. With a modular synthesis, we accessed a panel of bright and water-soluble SWIR fluorophores, enabling SWIR imaging of veins, bones and tumor growth. This versatile design provides an avenue for modular construction of water-soluble SWIR fluorophores.Graphical AbstractOptical imaging is a safe, rapid, low-cost imaging modality for (pre)clinical applications; however, it suffers from low penetration of light through tissue. Moving to longer wavelengths such as the shortwave infrared (SWIR) region increases the penetration depth, which has resulted in significant efforts to develop biocompatible, small molecule SWIR fluorophores. Numerous fluorophores have been developed but most are too hydrophobic to be used without a delivery agent.Here, we report a series of water-soluble SWIR fluorophores that can be visualized in mice. Modification with different moieties brings distinct properties that enable the imaging of veins, bones or tumor growth in mice. This modular and facile synthesis renders one hydrophobic SWIR fluorophore core applicable to diverse applications, providing insights for future construction of functional SWIR fluorophores for in vivo imaging.
                    Cover page: Water-soluble chromenylium dyes for shortwave infrared imaging in mice
                    • Article
                    • Peer Reviewed
                    UCLA Previously Published Works (2022)
                    Developing chemical tools to detect and influence biological processes is a cornerstone of chemical biology. Here we combine two tools which rely on orthogonality– perfluorocarbons and multiplexed shortwave infrared fluorescence imaging– to track the biodistribution of nanoemulsions in real time in living mice. Drawing inspiration from fluorous and shortwave infrared (SWIR) fluorophore development, we prepared two SWIR-emissive, fluorous-soluble chromenylium polymethine dyes. These are the most red-shifted fluorous fluorophores– “fluorofluorophores”– to date. After characterizing the dyes, their utility was demonstrated by tracking perfluorocarbon nanoemulsion biodistribution in vivo. Using an excitation-multiplexed approach to visualize two variables simultaneously, we gained insight into the importance of size and surfactant identity on biodistribution.Graphical AbstractFluorofluorophores (fluoro references to fluorine and fluorescence) are chemical tools to study perfluorocarbons. To understand the biodistribution of perfluorocarbons in animals, fluorofluorophores that emit past 1000 nm are necessary. Here we describe the synthesis, characterization, and application of shortwave infrared (SWIR)-emissive fluorofluorophores towards understanding how to control the pharmacokinetics of perfluorocarbon nanoemulsions in mammals.
                      Cover page: Shortwave Infrared Fluorofluorophores for Multicolor In Vivo Imaging
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