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Open Access Publications from the University of California

Scholarly Works (13 results)

  • Thesis
  • Peer Reviewed
UC San Diego Electronic Theses and Dissertations (2016)

Many previous studies have shown that artery calcification is linked to increased bone loss. Other studies have suggested that an agent released from bone causes artery calcification by traveling through blood. Previous studies have also shown that serum has crystal formation activity, and our goal is to develop a quantitative assay for this activity. Our long term goal is to determine if serum crystal forming activity is elevated in patients with increased bone loss.

In previous studies, Erin Hourigan developed a method to monitor serum crystal formation activity by diluting serum 50 fold with 2mM Calcium and Phosphate at 37C and pH 7.4. Hourigan’s assay measured Calcium decline at multiple time-points, and was very labor intensive. In contrast, my assay allows the Calcium decline to go to completion and then directly monitors serum’s crystal formation activity by counting the number of crystals present in solution in addition to measuring Calcium decline in solution.

The number of crystals counted by our assay were significantly higher (p<.0005) in human neonates than in human adults, which may be due to the fact that the rate of bone turnover is significantly higher in newborns than in adults, causing a rise in neonate’s serum crystal formation activity. We found that crystals counted by our assay probably originate from the growth of much smaller crystals already present in serum and are not formed by a serum catalyst. This assay is the first demonstration that human serum has crystals that can be directly counted.

    Cover page: A Novel Assay For The Crystal Formation Activity in Human Serum
    • Thesis
    • Peer Reviewed
    UC San Diego Electronic Theses and Dissertations (2016)

    Throughout one’s life a person’s bone constantly goes through bone resorption and bone formation in a process called bone remodelling. Bone diseases such as osteoporosis are caused by a dysregulation of this bone remodelling. Bone resorption is well understood, but the molecular mechanism and biology of bone formation is not fully understood. It is known that osteoblasts (bone forming cells) form a 5-10 um layer of osteoid (bone matrix) and calcify (mineralize) it to form bone. However, the exact process by which osteoblasts calcify osteoid is not fully understood. In this study we show that it is possible for lamellar bone formation to occur via a two step “seed-grow” mechanism. In this mechanism osteoblasts first seed osteoid with many small mineral crystals, after which the seed crystals go on to grow and calcify osteoid to form the final bone tissue. The seed crystals grow by taking calcium and phosphate from the circulating blood that bathes osteoid and therefore do not require osteoblasts for mineral growth past the initial seeding step. The seed-grow mechanism was tested via a trabecular bone block model system, where blocks of bovine trabecular bone were decalcified (demineralized) to recreate the initial osteoid material (bone collagen blocks). Bone collagen blocks were then artificially seeded with many small crystals via a previously developed technique and incubated in adult bovine serum without osteoblasts. The bone collagen blocks recalcified (remineralized) and hardened, eventually forming a complete, freestanding mineral continuum – a characteristic of the mineral phase in normal bone.

      Cover page: A New, Potential Mechanism for Osteoblast Initiated Lamellar Bone Formation During Bone Remodelling
      • Article
      • Peer Reviewed
      Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 14 (1992)
      We investigated multivariable function learning--the acquisition of quantitative mappings between multiple continuous stimulus dimensions and a single continuous response dimension. Our subjects learned to predict amounts of time that a ball takes to roll down inclined planes varying in length and angle of inclination. Performance with respect to the length of the plane was quite good, even very early in learning. On the other hand, performance with respect to the angle of the plane was systematically biased early in learning, but eventually became quite good. An extension of K o h and Meyer's (1991) adaptive regression model accounts well for the results. Implications for the study of intuitive physics mcffe generally are discussed.
        Cover page: Multivariable Function Learning: Applications of the Adaptive Regression Model to Intuitive Physics
        • Article
        • Peer Reviewed
        UC San Diego Previously Published Works (2018)
        It takes on average 6-12 years to develop new anticancer drugs from discovery to approval. Effective new agents prolong survival. To demonstrate the importance of rapid drug approval, we calculated life-years potentially saved if selected agents were approved more rapidly. As illustrative examples, we used 27 trials documenting improvements in survival. We multiplied improvement in median survival by numbers of patients dying annually and multiplied this by number of years from drug discovery until approval. For every year by which time to drug approval could have been shortened, there would have been a median number of life-years potentially saved of 79,920 worldwide per drug. Median number of life-years lost between time of drug discovery and approval was 1,020,900 per example. If we were able to use available opportunities to decrease the time required to take a drug from discovery to approval to 5 years, the median number of life-years saved per example would have been 523,890 worldwide. Various publications have identified opportunities to speed drug development without sacrificing patient safety. While many investigational drugs prove to be ineffective, some significantly prolong survival and/or reduce suffering. These illustrative examples suggest that a substantial number of life-years could potentially be saved by increasing the efficiency of development of new drugs for advanced malignancies.
          • Article
          • Peer Reviewed
          UC Davis Previously Published Works (2019)
          Prioritizing the potential risk posed to human health by chemicals requires tools that can estimate exposure from limited information. In this study, chemical structure and physicochemical properties were used to predict the probability that a chemical might be associated with any of four exposure pathways leading from sources-consumer (near-field), dietary, far-field industrial, and far-field pesticide-to the general population. The balanced accuracies of these source-based exposure pathway models range from 73 to 81%, with the error rate for identifying positive chemicals ranging from 17 to 36%. We then used exposure pathways to organize predictions from 13 different exposure models as well as other predictors of human intake rates. We created a consensus, meta-model using the Systematic Empirical Evaluation of Models framework in which the predictors of exposure were combined by pathway and weighted according to predictive ability for chemical intake rates inferred from human biomonitoring data for 114 chemicals. The consensus model yields an R2 of ∼0.8. We extrapolate to predict relevant pathway(s), median intake rate, and credible interval for 479 926 chemicals, mostly with minimal exposure information. This approach identifies 1880 chemicals for which the median population intake rates may exceed 0.1 mg/kg bodyweight/day, while there is 95% confidence that the median intake rate is below 1 μg/kg BW/day for 474572 compounds.
            Cover page: Consensus Modeling of Median Chemical Intake for the U.S. Population Based on Predictions of Exposure Pathways
            • Article
            • Peer Reviewed
            UC Irvine Previously Published Works (2010)
            Cell misidentification and cross-contamination have plagued biomedical research for as long as cells have been employed as research tools. Examples of misidentified cell lines continue to surface to this day. Efforts to eradicate the problem by raising awareness of the issue and by asking scientists voluntarily to take appropriate actions have not been successful. Unambiguous cell authentication is an essential step in the scientific process and should be an inherent consideration during peer review of papers submitted for publication or during review of grants submitted for funding. In order to facilitate proper identity testing, accurate, reliable, inexpensive, and standardized methods for authentication of cells and cell lines must be made available. To this end, an international team of scientists is, at this time, preparing a consensus standard on the authentication of human cells using short tandem repeat (STR) profiling. This standard, which will be submitted for review and approval as an American National Standard by the American National Standards Institute, will provide investigators guidance on the use of STR profiling for authenticating human cell lines. Such guidance will include methodological detail on the preparation of the DNA sample, the appropriate numbers and types of loci to be evaluated, and the interpretation and quality control of the results. Associated with the standard itself will be the establishment and maintenance of a public STR profile database under the auspices of the National Center for Biotechnology Information. The consensus standard is anticipated to be adopted by granting agencies and scientific journals as appropriate methodology for authenticating human cell lines, stem cells, and tissues.
              Cover page: Recommendation of short tandem repeat profiling for authenticating human cell lines, stem cells, and tissues
              • Article
              • Peer Reviewed
              UC Berkeley Previously Published Works (2022)
              We present high-fidelity cosmology results from a blinded joint analysis of galaxy-galaxy weak lensing (Δς) and projected galaxy clustering (wp) measured from the Hyper Suprime-Cam Year-1 (HSC-Y1) data and spectroscopic Sloan Digital Sky Survey (SDSS) galaxy catalogs in the redshift range 0.15
                Cover page: Cosmological inference from an emulator based halo model. II. Joint analysis of galaxy-galaxy weak lensing and galaxy clustering from HSC-Y1 and SDSSCreative Commons 'BY' version 4.0 license
                • Article
                • Peer Reviewed
                LBL Publications (2016)
                We present a recalibration of the Sloan Digital Sky Survey (SDSS) photometry with new flat fields and zero points derived from Pan-STARRS1. Using point-spread function (PSF) photometry of 60 million stars with 16 < r < 20, we derive a model of amplifier gain and flat-field corrections with per-run rms residuals of 3 millimagnitudes (mmag) in griz bands and 15 mmag in u band. The new photometric zero points are adjusted to leave the median in the Galactic north unchanged for compatibility with previous SDSS work. We also identify transient non-photometric periods in SDSS ("contrails") based on photometric deviations co-temporal in SDSS bands. The recalibrated stellar PSF photometry of SDSS and PS1 has an rms difference of {9, 7, 7, 8} mmag in griz, respectively, when averaged over 15′ regions.
                  • Article
                  • Peer Reviewed
                  UC Berkeley Previously Published Works (2023)
                  We perform a blinded cosmology analysis with cosmic shear two-point correlation functions measured from more than 25 million galaxies in the Hyper Suprime-Cam three-year shear catalog in four tomographic redshift bins ranging from 0.3 to 1.5. After conservative masking and galaxy selection, the survey covers 416 deg2 of the northern sky with an effective galaxy number density of 15 arcmin-2 over the four redshift bins. The 2PCFs adopted for cosmology analysis are measured in the angular range; 7.1<θ/arcmin<56.6 for ζ+ and 31.2<θ/arcmin<248 for ζ-, with a total signal-to-noise ratio of 26.6. We apply a conservative, wide, flat prior on the photometric redshift errors on the last two tomographic bins, and the relative magnitudes of the cosmic shear amplitude across four redshift bins allow us to calibrate the photometric redshift errors. With this flat prior on redshift errors, we find ωm=0.256-0.044+0.056 and S8σ8ωm/0.3=0.769-0.034+0.031 (both 68% C.I.) for a flat Λ cold dark matter cosmology. We find, after unblinding, that our constraint on S8 is consistent with the Fourier space cosmic shear and the 3×2 pt analyses on the same HSC dataset. We carefully study the potential systematics from astrophysical and systematic model uncertainties in our fiducial analysis using synthetic data, and report no biases (including projection bias in the posterior space) greater than 0.5σ in the estimation of S8. Our analysis hints that the mean redshifts of the two highest tomographic bins are higher than initially estimated. In addition, a number of consistency tests are conducted to assess the robustness of our analysis. Comparing our result with Planck-2018 cosmic microwave background observations, we find a ∼2σ tension for the ΛCDM model.
                    Cover page: Hyper Suprime-Cam Year 3 results: Cosmology from cosmic shear two-point correlation functionsCreative Commons 'BY' version 4.0 license
                    • Article
                    • Peer Reviewed
                    LBL Publications (2021)
                    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.
                      Cover page: Tiny Earth: A Big Idea for STEM Education and Antibiotic Discovery
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