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Open Access Publications from the University of California

Scholarly Works (3 results)

  • Article
LBL Publications (2001)
In light of recent discoveries of its roles in varied cellular processes, RNA has become an exciting therapeutic target. The identification of potential RNA targets would allow a corresponding development of novel therapeutic approaches. Until recently, there has been no successful computational approach for identification of genes encoding novel functional RNAs (fRNAs) in genomic sequences. We have developed a machine learning approach that contrasts known RNA and non-coding sequences to extract common features that can distinguish functional RNAs. These trained computational machines are then used for prediction of new RNA genes in the unannotated regions of prokaryotic and archaeal gemones. The E. coli genome was used for development, but we have applied this method to several other bacterial and archaeal genomes. Computational neural networks based on nucleotide composition were 80-90% accurate in jackknife testing experiments for bacteria and 90-99% for hyperthermophilic archaea. We also achieved a significant in accuracy by combining these predictions with those obtained using a second set of parameters consisting of known RNA sequence/structure motifs and the calculated free energy of folding. Several known fRNAs not included in the training datasets were identified as well as several hundred predicted novel RNAs. These studies indicate that there are many unidentified RNAs in simple genomes that can be predicted computationally as a precursor to experimental study. We also noted that in several cases functional segments in the untranslated regions of mRNA were correctly identified by our networks. Preliminary results indicate that the method is applicable to fRNA prediction in higher organisms, including the human genome. The method, which is simple to run and is available via the web (http://rnagene.lbl.gov), may yield the discovery of thousands of novel fRNAs in these higher organisms.
    Cover page: Discovering new RNA targets in Genomic DNA
    • Article
    Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health, Volume 23, Issue 4.1 (2022)

    Learning Objectives: We sought to 1) teach the approach to core complaints in EM, 2) teach key skills in EM, 3) de-mystify the process of applying to an EM residency program, and 4) connect students with residents and faculty in the field of EM.

    Introduction/Background: Despite having a diverse patient population, emergency medicine (EM) remains among the medical specialties with the lowest number of residents and attendings underrepresented in medicine (URiM). Increasing awareness of the field of EM in medical schools that are affiliated with Historically Black Colleges and Universities (HBCUs) is one way to increase the pipeline of URiM in EM. Currently, however, there are zero HBCUs with academic emergency medicine departments. As representatives of four departments of EM, we partnered with one HBCU to attempt to fill this gap for EM-interested students on their 4th year EM home rotation.

    Educational Objectives: We sought to 1) teach the approach to core complaints in EM, 2) teach key skills in EM, 3) de-mystify the process of applying to an EM residency program, and 4) connect students with residents and faculty in the field of EM.

    Curricular Design: Educational objectives were developed in conjunction with the faculty advisor to the 4th year EM rotation. We created a 4-week didactic program, with content organized into weekly 4-hour blocks, each led by a different department of EM, on a virtual, interactive platform. Content was mapped and coordinated, pre-reading was assigned and each day included a mix of clinical topics and “advising” sessions.

    Impact/Effectiveness: A post-curricular survey found universal agreement from students on whether the curriculum was effective in meeting the above goals. Narrative feedback from students highlighted the value of meeting with faculty and residents from different programs, and from going through cases in real time. Informal feedback from supervising faculty at the host-institution was also very positive, particularly in terms of readying students for away rotations. Although our program was targeted towards students at one HBCU, it could be expanded to any medical school without an academic emergency medicine department.

      Cover page: Effectiveness of a collaborative, virtual outreach curriculum for 4th year EM-bound students at an HBCUCreative Commons 'BY' version 4.0 license
      • Article
      • Peer Reviewed
      UC San Francisco Previously Published Works (2012)

      Background

      Eosinophilic airway inflammation is heterogeneous in asthmatic patients. We recently described a distinct subtype of asthma defined by the expression of genes inducible by T(H)2 cytokines in bronchial epithelium. This gene signature, which includes periostin, is present in approximately half of asthmatic patients and correlates with eosinophilic airway inflammation. However, identification of this subtype depends on invasive airway sampling, and hence noninvasive biomarkers of this phenotype are desirable.

      Objective

      We sought to identify systemic biomarkers of eosinophilic airway inflammation in asthmatic patients.

      Methods

      We measured fraction of exhaled nitric oxide (Feno), peripheral blood eosinophil, periostin, YKL-40, and IgE levels and compared these biomarkers with airway eosinophilia in asthmatic patients.

      Results

      We collected sputum, performed bronchoscopy, and matched peripheral blood samples from 67 asthmatic patients who remained symptomatic despite maximal inhaled corticosteroid treatment (mean FEV(1), 60% of predicted value; mean Asthma Control Questionnaire [ACQ] score, 2.7). Serum periostin levels are significantly increased in asthmatic patients with evidence of eosinophilic airway inflammation relative to those with minimal eosinophilic airway inflammation. A logistic regression model, including sex, age, body mass index, IgE levels, blood eosinophil numbers, Feno levels, and serum periostin levels, in 59 patients with severe asthma showed that, of these indices, the serum periostin level was the single best predictor of airway eosinophilia (P = .007).

      Conclusion

      Periostin is a systemic biomarker of airway eosinophilia in asthmatic patients and has potential utility in patient selection for emerging asthma therapeutics targeting T(H)2 inflammation.
        Cover page: Periostin is a systemic biomarker of eosinophilic airway inflammation in asthmatic patients
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