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Open Access Publications from the University of California

Scholarly Works (57 results)

  • Article
  • Peer Reviewed
Dermatology Online Journal, Volume 12, Issue 4 (2006)
    • Peer Reviewed
    UC Berkeley Previously Published Works (2019)
    The chapter argues that Hindu nationalists reproduce queer identities and practices, even as they discursively reject lgbtqi people.
      Cover page: Queer Presence In/And Hindu Nationalism
      • Article
      • Peer Reviewed
      UCLA Previously Published Works (2021)
      The mechanism of the Lewis base F- catalyzed 1,3-dipolar cycloaddition between CO2 and nitrilimines is interrogated using DFT calculations. F- activates the nitrilimine, not CO2 as proposed in the literature, and imparts a significant rate enhancement for the cycloaddition. The origin of this catalysis is in the strength of the primary orbital interactions between the reactants. The Lewis base activated nitrilimine-F- has high-lying filled FMOs. The smaller FMO-LUMO gap promotes a rapid nucleophilic attack and overall cycloaddition with CO2.
        Cover page: How the Lewis Base F– Catalyzes the 1,3-Dipolar Cycloaddition between Carbon Dioxide and Nitrilimines
        • Article
        • Peer Reviewed
        The Proceedings of the International Plant Nutrition Colloquium XVI (2009)

        Phytic acid and proteins are believed to be important for the distribution and bio-availability of zinc and iron in the cereal grain, but little quantitative information is available on the relative importance of different organic ligands. We have used several chromatographic techniques including size exclusion chromatography (SEC) hyphenated to ICP-MS to analyse the molecular speciation of Fe and Zn in tissues of barley and rice seeds. The majority of Fe in barley embryos co-eluted with P as a species with the apparent mass of 12.3 kDa, whereas the majority of Zn co-eluted with S as a 3 kDa species, devoid of any co-eluting P. Subsequent ion pairing chromatography of the Fe/P peak showed that phytic acid (myo-inositol 1, 2, 3, 4, 5, 6-hexakisphosphate: IP6) was the main Fe binding ligand, with the stoichiometry Fe4(IP6)18. When incubating the embryo tissue with phytase, the enzyme responsible for degradation of phytic acid, the extraction efficiency of both Fe and P was doubled, whereas that of Zn and S was unaffected. Protein degradation on the other hand, using protease XIV, boosted the extraction of Zn and S, but not that of Fe and P. Similar observations were made for the endosperm of rice grains. It is concluded that Fe and Zn have a different molecular speciation in cereal grain tissues; Zn appears mainly bound to peptides, while Fe is mainly associated with phytic acid.

          Cover page: Zinc and iron speciation in the cereal grain
          • Article
          • Peer Reviewed
          The Proceedings of the International Plant Nutrition Colloquium XVI (2009)

          Plant tissue analysis is a valuable tool for evaluation of the nutritional quality of crops and for optimal fertilizer application. The majority of plant analyses are currently performed with “full-quantitative” ICP spectrometry, which relies on expensive and labor intensive analytical procedures. The costs for such analyses are often considered too high by farmers, gardeners and agricultural consultants, thus limiting its dispersal significantly. We have recently developed a fast “semi-quantitative” ICP-MS based method, which enabled simultaneous measurement of more than 70 elements of the periodic table. When combining the method with a high-throughput sample digestion procedure, the labor consumption and analytical costs were reduced significantly. A 5-fold reduction in sample preparation and data acquisition time was obtained, while more than three times as many elements were quantified compared to the traditional full-quantitative analysis. The developed method was tested on several plant tissue types with satisfactory results for a large number of elements. It is concluded that semi-quantitative ICP-MS represents a very promising analytical tool for plant tissue analysis. Combined with chemometrics it was also shown that semi-quantitative ICP-MS has the potential to mature into a routine procedure for testing e.g. the authenticity and adulteration of plant based food products.

            Cover page: Recent developments in plant tissue analysis
            • Article
            • Peer Reviewed
            UC San Francisco Previously Published Works (2023)
            Until recently, intronic lariats were regarded as short-lasting splicing byproducts with no apparent function; however, increasing evidence of stable derivatives suggests regulatory roles. Yet little is known about their characteristics, functions, distribution, and expression in healthy and tumor tissue. Here, we profiled and characterized circular stable intronic sequence RNAs (sisRNAs) using total RNA-Seq data from bladder cancer (BC; n = 457, UROMOL cohort), healthy tissue (n = 46), and fractionated cell lines (n = 5). We found that the recently-discovered full-length intronic circles and the stable lariats formed distinct subclasses, with a surprisingly high intronic circle fraction in BC (∼45%) compared to healthy tissues (0-20%). The stable lariats and their host introns were characterized by small transcript sizes, highly conserved BP regions, enriched BP motifs, and localization in multiple cell fractions. Additionally, circular sisRNAs showed tissue-specific expression patterns. We found nine circular sisRNAs as differentially expressed across early-stage BC patients with different prognoses, and sisHNRNPK expression correlated with progression-free survival. In conclusion, we identify distinguishing biological features of circular sisRNAs and point to specific candidates (incl. sisHNRNPK, sisWDR13 and sisMBNL1) that were highly expressed, had evolutionary conserved sequences, or had clinical correlations, which may facilitate future studies and further insights into their functional roles.
              Cover page: Circular stable intronic RNAs possess distinct biological features and are deregulated in bladder cancer.
              • Article
              • Peer Reviewed
              UC Irvine Previously Published Works (2023)
              Understanding the causes and limits of population divergence in phenotypic traits is a fundamental aim of evolutionary biology, with the potential to yield predictions of adaptation to environmental change. Reciprocal transplant experiments and the evaluation of optimality models suggest that local adaptation is common but not universal, and some studies suggest that trait divergence is highly constrained by genetic variances and covariances of complex phenotypes. We analyze a large database of population divergence in plants and evaluate whether evolutionary divergence scales positively with standing genetic variation within populations (evolvability), as expected if genetic constraints are evolutionarily important. We further evaluate differences in divergence and evolvability-divergence relationships between reproductive and vegetative traits and between selfing, mixed-mating, and outcrossing species, as these factors are expected to influence both patterns of selection and evolutionary potentials. Evolutionary divergence scaled positively with evolvability. Furthermore, trait divergence was greater for vegetative traits than for floral (reproductive) traits, but largely independent of the mating system. Jointly, these factors explained ~40% of the variance in evolutionary divergence. The consistency of the evolvability-divergence relationships across diverse species suggests substantial predictability of trait divergence. The results are also consistent with genetic constraints playing a role in evolutionary divergence.
                Cover page: Evolvability and trait function predict phenotypic divergence of plant populations.
                • Article
                • Peer Reviewed
                LBL Publications (2023)
                Reconstruction of the exit wave function is an important route to interpreting high-resolution transmission electron microscopy (HRTEM) images. Here we demonstrate that convolutional neural networks can be used to reconstruct the exit wave from a short focal series of HRTEM images, with a fidelity comparable to conventional exit wave reconstruction. We use a fully convolutional neural network based on the U-Net architecture, and demonstrate that we can train it on simulated exit waves and simulated HRTEM images of graphene-supported molybdenum disulphide (an industrial desulfurization catalyst). We then apply the trained network to analyse experimentally obtained images from similar samples, and obtain exit waves that clearly show the atomically resolved structure of both the MoS2 nanoparticles and the graphene support. We also show that it is possible to successfully train the neural networks to reconstruct exit waves for 3400 different two-dimensional materials taken from the Computational 2D Materials Database of known and proposed two-dimensional materials.
                  Cover page: Reconstructing the exit wave of 2D materials in high-resolution transmission electron microscopy using machine learningCreative Commons 'BY' version 4.0 license
                  • Article
                  • Peer Reviewed
                  UC San Diego Previously Published Works (2020)
                  Circulating inflammatory markers are essential to human health and disease, and they are often dysregulated or malfunctioning in cancers as well as in cardiovascular, metabolic, immunologic and neuropsychiatric disorders. However, the genetic contribution to the physiological variation of levels of circulating inflammatory markers is largely unknown. Here we report the results of a genome-wide genetic study of blood concentration of ten cytokines, including the hitherto unexplored calcium-binding protein (S100B). The study leverages a unique sample of neonatal blood spots from 9,459 Danish subjects from the iPSYCH initiative. We estimate the SNP-heritability of marker levels as ranging from essentially zero for Erythropoietin (EPO) up to 73% for S100B. We identify and replicate 16 associated genomic regions (p < 5 x 10-9), of which four are novel. We show that the associated variants map to enhancer elements, suggesting a possible transcriptional effect of genomic variants on the cytokine levels. The identification of the genetic architecture underlying the basic levels of cytokines is likely to prompt studies investigating the relationship between cytokines and complex disease. Our results also suggest that the genetic architecture of cytokines is stable from neonatal to adult life.
                    Cover page: Genome-wide association study identifies 16 genomic regions associated with circulating cytokines at birth
                    • Article
                    • Peer Reviewed
                    UCLA Previously Published Works (2020)
                    Genome-wide association studies have discovered hundreds of loci associated with complex brain disorders, but it remains unclear in which cell types these loci are active. Here we integrate genome-wide association study results with single-cell transcriptomic data from the entire mouse nervous system to systematically identify cell types underlying brain complex traits. We show that psychiatric disorders are predominantly associated with projecting excitatory and inhibitory neurons. Neurological diseases were associated with different cell types, which is consistent with other lines of evidence. Notably, Parkinson's disease was genetically associated not only with cholinergic and monoaminergic neurons (which include dopaminergic neurons) but also with enteric neurons and oligodendrocytes. Using post-mortem brain transcriptomic data, we confirmed alterations in these cells, even at the earliest stages of disease progression. Our study provides an important framework for understanding the cellular basis of complex brain maladies, and reveals an unexpected role of oligodendrocytes in Parkinson's disease.
                      Cover page: Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson’s disease
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