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Biomedical subjects

Richard D Smith

Publications and source records attributed to Richard D Smith.

At least 19 recordsLinked to original sources
PubMed2026

Proteogenomic analysis of pediatric and AYA high-grade glioma reveals age-dependent biology, female-male differences, and kinase targets.

High-grade gliomas (HGGs) in children and adolescents and young adults (AYA) exhibit distinct biology across the neurodevelopmental spectrum. To dissect tumor-intrinsic molecular characteristics independent of developmental variation, we perform comprehensive proteogenomic analyses of tumors from 112 HGG patients aged 0-40 years. Our multi-omics analysis identifies two AYA subgroups-adolescents (aged 15-26 years) and young adults (aged 26-40 years)-with distinct molecular profiles and survival outcomes. Tumor-normal comparisons and survival modeling highlight roles of oxidative phosphorylation and neuronal system biology in glioma progression. Causal network analysis and cell line studies provide a rationale for personalized therapies targeting candidate kinases, such as CDK8. Survival modeling, clustering, and immune-landscape analyses identify proteins, post-translational modifications, and immune signatures linked to outcomes and reveal clinically relevant differences between male and female patients.

adolescent and young adult glioma↗
PubMed2025

Dysregulation of lung epithelial cell homeostasis and immunity contributes to Middle East respiratory syndrome coronavirus disease severity.

Coronaviruses (CoV) emerge suddenly from animal reservoirs to cause novel diseases in new hosts. Discovered in 2012, the Middle East respiratory syndrome coronavirus (MERS-CoV) is endemic in camels in the Middle East and is continually causing local outbreaks and epidemics. While all three newly emerging human CoVs from the past 20 years (SARS-CoV, SARS-CoV-2, and MERS-CoV) cause respiratory disease, each CoV has unique host interactions that drive differential pathogeneses. To better understand the virus and host interactions driving lethal MERS-CoV infection, we performed a longitudinal multi-omics analysis of sublethal and lethal MERS-CoV infection in mice. Significant differences were observed in body weight loss, virus titers, and acute lung injury among lethal and sub-lethal virus doses. Virus-induced apoptosis of type I and II alveolar epithelial cells suggests that loss or dysregulation of these key cell populations was a major driver of severe disease. Omics analysis suggested differential pathogenesis was multi-factorial with clear differences among innate and adaptive immune pathways as well as those that regulate lung epithelial homeostasis. Infection of mice lacking functional T and B cells showed that adaptive immunity was important in controlling viral replication but also increased pathogenesis. In summary, we provide a high-resolution host response atlas for MERS-CoV infection and disease severity. Multi-omics studies of viral pathogenesis offer a unique opportunity to not only better understand the molecular mechanisms of disease but also to identify genes and pathways that can be exploited for therapeutic intervention all of which is important for our future pandemic preparedness.IMPORTANCEEmerging coronaviruses like SARS-CoV, SARS-CoV-2, and MERS-CoV cause a range of disease outcomes in humans from an asymptomatic, moderate, and severe respiratory disease that can progress to death but the factors causing these disparate outcomes remain unclear. Understanding host responses to mild and life-threatening infections provides insight into virus-host networks within and across organ systems that contribute to disease outcomes. We used multi-omics approaches to comprehensively define the host response to moderate and severe MERS-CoV infection. Severe respiratory disease was associated with dysregulation of the immune response. Key lung epithelial cell populations that are essential for lung function get infected and die. Mice lacking key immune cell populations experienced greater virus replication but decreased disease severity implicating the immune system in both protective and pathogenic roles in response to MERS-CoV. These data could be utilized to design new therapeutic strategies targeting specific pathways that contribute to severe disease.

Animals↗
PubMed2013

The identification of novel potential injury mechanisms and candidate biomarkers in renal allograft rejection by quantitative proteomics.

Early transplant dysfunction and failure because of immunological and nonimmunological factors still presents a significant clinical problem for transplant recipients. A critical unmet need is the noninvasive detection and prediction of immune injury such that acute injury can be reversed by proactive immunosuppression titration. In this study, we used iTRAQ -based proteomic discovery and targeted ELISA validation to discover and validate candidate urine protein biomarkers from 262 renal allograft recipients with biopsy-confirmed allograft injury. Urine samples were randomly split into a training set of 108 patients and an independent validation set of 154 patients, which comprised the clinical biopsy-confirmed phenotypes of acute rejection (AR) (n = 74), stable graft (STA) (n = 74), chronic allograft injury (CAI) (n = 58), BK virus nephritis (BKVN) (n = 38), nephrotic syndrome (NS) (n = 8), and healthy, normal control (HC) (n = 10). A total of 389 proteins were measured that displayed differential abundances across urine specimens of the injury types (p < 0.05) with a significant finding that SUMO2 (small ubiquitin-related modifier 2) was identified as a "hub" protein for graft injury irrespective of causation. Sixty-nine urine proteins had differences in abundance (p < 0.01) in AR compared with stable graft, of which 12 proteins were up-regulated in AR with a mean fold increase of 2.8. Nine urine proteins were highly specific for AR because of their significant differences (p < 0.01; fold increase >1.5) from all other transplant categories (HLA class II protein HLA-DRB1, KRT14, HIST1H4B, FGG, ACTB, FGB, FGA, KRT7, DPP4). Increased levels of three of these proteins, fibrinogen beta (FGB; p = 0.04), fibrinogen gamma (FGG; p = 0.03), and HLA DRB1 (p = 0.003) were validated by ELISA in AR using an independent sample set. The fibrinogen proteins further segregated AR from BK virus nephritis (FGB p = 0.03, FGG p = 0.02), a finding that supports the utility of monitoring these urinary proteins for the specific and sensitive noninvasive diagnosis of acute renal allograft rejection.

Acute Kidney Injury↗
PubMed2003

Duplex foldamers from assembly induced folding.

Oligoamide strands 1, 2, and 3, consisting of 4-H-bond units, were originally designed to form noncovalent polymers based on the expectation that they would adopt an extended conformation. Instead of assembling into the expected supramolecular polymer through their 4-H-bond units, the 1:1 mixture of 1 and 2 was found to form a highly stable dimeric species. To dimerize, the H-bonding sequences of 1 and 2 can only adopt a folded (stacked) conformation. The self-assembly of 3 was also found to adopt a similar folded duplex conformation. These novel duplex foldamers are very stable. They were characterized by 1D and 2D 1H NMR, VPO, and mass spectral (ESI) studies.

Biomimetic Materials↗
PubMed2003

Use of artificial neural networks for the accurate prediction of peptide liquid chromatography elution times in proteome analyses.

The use of artificial neural networks (ANNs) is described for predicting the reversed-phase liquid chromatography retention times of peptides enzymatically digested from proteome-wide proteins. To enable the accurate comparison of the numerous LC/MS data sets, a genetic algorithm was developed to normalize the peptide retention data into a range (from 0 to 1), improving the peptide elution time reproducibility to approximately 1%. The network developed in this study was based on amino acid residue composition and consists of 20 input nodes, 2 hidden nodes, and 1 output node. A data set of approximately 7000 confidently identified peptides from the microorganism Deinococcus radiodurans was used for the training of the ANN. The ANN was then used to predict the elution times for another set of 5200 peptides tentatively identified by MS/MS from a different microorganism (Shewanella oneidensis). The model was found to predict the elution times of peptides with up to 54 amino acid residues (the longest peptide identified after tryptic digestion of S. oneidensis) with an average accuracy of approximately 3%. This predictive capability was then used to distinguish with high confidence isobar peptides otherwise indistinguishable by accurate mass measurements as well as to uncover peptide misidentifications. Thus, integration of ANN peptide elution time prediction in the proteomic research will increase both the number of protein identifications and their confidence.

Amino Acid Sequence↗
PubMed2003

High mass measurement accuracy determination for proteomics using multivariate regression fitting: application to electrospray ionization time-of-flight mass spectrometry.

Important factors that limit the mass measurement accuracy from a mass spectrometer are related to (1) the type of mass analyzer used and (2) the data processing/calibration methods used to obtain mass values from the raw data. Here, two data processing methods are presented that correct for systematic deviations when the mass of ions is measured using a time-of-flight (TOF) mass spectrometer. The first fitting method is one where m/z values are obtained from fitting peak distributions using double Gaussian functions. A second calibration method takes into account the slight nonlinear response of the TOF analyzer in addition to the drift in the calibration over time. Using multivariate regression, both of these two effects can be corrected for using a single calibration formula. Achievable performance was evaluated with a trypsin digestion of serum albumin and proteins from the organism D. radiodurans that was analyzed using gradient reversed-phase liquid chromatography combined with an electrospray ionization orthogonal TOF mass spectrometer. The root-mean-square deviation between the theoretical and experimental m/z values for serum albumin tryptic peptides was found to be 8 ppm using the double Gaussian-multivariate method compared to 29 ppm determined using linear calibration and normal peak centroiding. An advantage of the methods presented here is that no calibrant compounds need to be added to the mobile phase, thereby avoiding interference effects and signal suppression of analytes.

Bacterial Proteins↗
PubMed2003

Proteome analysis by mass spectrometry.

The coupling of high-performance mass spectrometry instrumentation with highly efficient chromatographic and electrophoretic separations has enabled rapid qualitative and quantitative analysis of thousands of proteins from minute samples of biological materials. Here, we review recent progress in the development and application of mass spectrometry-based techniques for the qualitative and quantitative analysis of global proteome samples derived from whole cells, tissues, or organisms. Techniques such as multidimensional peptide and protein separations coupled with mass spectrometry, accurate mass measurement of peptides from global proteome digests, and mass spectrometric characterization of intact proteins hold great promise for characterization of highly complex protein mixtures. Advances in chemical tagging and isotope labeling techniques have enabled quantitative analysis of proteomes, and highly specific isolation strategies have been developed aimed at selective analysis of posttranslationally modified proteins.

Chromatography, Affinity↗
PubMed2003

Construction of the contingent valuation market in health care: a critical assessment.

Contingent valuation (CV) has been criticised for being too hypothetical, with expressed values bearing little relation to actual values. The magnitude of this divergence, however, depends upon how realistic and believable the contingent market is. This paper presents an overview of five key aspects in the construction of the contingent market: (i) scenario development and presentation; (ii) payment vehicle; (iii) expression of risk; (iv) time period of valuation; and (v) survey administration. CV studies in health care since 1985, totalling 111, are critically reviewed with respect to these five aspects. It is concluded that CV studies in health care have performed poorly in the construction, specification and presentation of the contingent market, and that there has been little, if any, improvement in this respect over the last 15 years. Suggestions are made concerning why this may be the case, and how the construction of the contingent market may be improved in future.

Attitude to Health↗
PubMed2003

Willingness to pay and size of health benefit: an integrated model to test for 'sensitivity to scale'.

A key theoretical prediction concerning willingness to pay is that it is positively correlated with benefit size and is assessed by testing the 'sensitivity to scale (scope)'. 'External' (between-sample) sensitivity tests are usually regarded as less powerful than 'internal' (within-subject) tests. However, the latter may suffer from 'anchoring' effects. This paper studies the statistical power of these tests by questioning the distributional assumption of empirical data. We present an integrated model to capture both internal and external variations, while controlling for sample heterogeneity, applied to data from a survey estimating the value of reducing symptom-days. Results indicate that once data is properly transformed, WTP becomes 'scale sensitive' and consistent with diminishing marginal utility theory.

Adult↗
PubMed2003

Identification of tryptic peptides from large databases using multiplexed tandem mass spectrometry: simulations and experimental results.

Multiplexed tandem mass spectrometry (MS/MS) has recently been demonstrated as a means to increase the throughput of peptide identification in liquid chromatography (LC) MS/MS experiments. In this approach, a set of parent species is dissociated simultaneously and measured in a single spectrum (in the same manner that a single parent ion is conventionally studied), providing a gain in sensitivity and throughput proportional to the number of species that can be simultaneously addressed. In the present work, simulations performed using the Caenorhabditis elegans predicted proteins database show that multiplexed MS/MS data allow the identification of tryptic peptides from mixtures of up to ten peptides from a single dataset with only three "y" or "b" fragments per peptide and a mass accuracy of 2.5 to 5 ppm. At this level of database and data complexity, 98% of the 500 peptides considered in the simulation were correctly identified. This compares favorably with the rates obtained for classical MS/MS at more modest mass measurement accuracy. LC multiplexed Fourier transform-ion cyclotron resonance MS/MS data obtained from a 66 kDa protein (bovine serum albumin) tryptic digest sample are presented to illustrate the approach, and confirm that peptides can be effectively identified from the C. elegans database to which the protein sequence had been appended.

Algorithms↗
PubMed2003

Detection of in situ labeled cell surface proteins by mass spectrometry: application to the membrane subproteome of human mammary epithelial cells.

Characterization of the surface exposed membrane subproteome of human mammary epithelial cells (strain 184 A1L5) implemented lysine specific in situ labeling of the proteins using sulfosuccinimidyl-6-(biotinamido)hexanoate, followed by enrichment of the biotinylated, tryptically digested peptides, and then liquid chromatography-tandem mass spectrometry analysis of the labeled peptides. Probing the membrane subproteome in this manner yielded unambiguous identification of proteins situated on the cell surface. The method reported can be adapted to include stable isotope labeling of proteins for quantitation of changes occurring on the cell surface in response to specific perturbations.

Amino Acid Sequence↗
PubMed2003

Initial implementation of external accumulation liquid chromatography/electrospray ionization Fourier transform ion cyclotron resonance with automated gain control.

Capillary liquid chromatography (LC) separation coupled with external accumulation Fourier transform ion cyclotron resonance (FTICR) mass spectrometry has recently been demonstrated to have significant potential for proteomics research. Accumulation of an excessive space charge external to the FTICR cell ion trap has been shown to result in increased mass measurement error, undesirable ion discrimination and/or fragmentation, potentially causing misrepresentation or incorrect assignments of lower abundance peptides in the acquired mass spectra. In this work we report on the capability of data-dependent adjustment of ion accumulation times in the course of LC separations, further referred to as automated gain control (AGC). Three different AGC approaches were evaluated based on the number of putative peptides from a tryptic digest of four casein proteins detected in the course of LC/FTICR separations. When compared with the conventional technique, AGC was found to increase, up to a factor of 3, the total number of peptides identified.

Automation↗
PubMed2003

Stable isotope-coded proteomic mass spectrometry.

Developing the ability to quantify changes in protein abundance between cells subjected to a variety of physiological and environmental conditions is an extremely active area of proteome research. Although advances in chromatography, mass spectrometry instrumentation, and bioinformatics have contributed to producing a viable method for comparative proteome-wide analyses, the highest precision of quantitation is based, in part, upon improved methods for chemical and metabolic stable isotope labeling of proteins and peptides. The ability to quantify differences in protein expression and post-translational modifications using stable isotope labeling has been achieved, but insights into the biochemical mechanisms that will contribute to the development of new biotechnologies have yet to be realized.

Affinity Labels↗