Materials science. Molecular fuel tanks.
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Comment↗
Biomedical subjects
Michael D Ward
Publications and source records attributed to Michael D Ward.
Adhesion between molecules and calcium oxalate crystals: critical interactions in kidney stone formation.
Kidney stones are crystal aggregates, most commonly containing calcium oxalate monohydrate (COM) crystals as the primary constituent. Notably, in vitro studies have suggested that anionic molecules or macromolecules with substantial anionic functionality (e.g., carboxylate) play an important role in crystal aggregation and crystal attachment to renal epithelial cells. Furthermore, kidney stones contain measurable amounts of carboxylate-rich proteins that may serve as adhesives and promote aggregation of COM crystals. Atomic force microscopy (AFM) measurements of adhesion forces between tip-immobilized molecules and the COM (100) surface in aqueous media, described herein, reveal the effect of functional groups on adhesion and support an important role for the carboxylate group in processes responsible for kidney stone formation, specifically macromolecule-mediated adhesion of COM crystals to cells and crystal aggregation. The presence of poly(aspartic acid) during force measurements results in a reduction in the adhesion force measured for carboxylate-modified tips, consistent with the blocking of binding sites on the COM (100) surface by the carboxylate-rich polymer. This competitive binding behavior mimics the known reduction in attachment of COM crystals to renal epithelial cells in the presence of carboxylate-rich urinary macromolecules. These results suggest a feasible methodology for identifying the most important crystal surface-macromolecule combinations related to stone formation.
Calcium Oxalate↗
Interplay of light antenna and excitation "energy reservoir" effects in a bichromophoric system based on ruthenium-polypyridine and pyrene units linked by a long and flexible poly(ethylene glycol) chain.
Steady-state and time-resolved spectroscopic properties of bichromophoric species containing [Ru(bpy)(3)](2+) and pyrene (pyr) units linked together by flexible poly(ethylene glycol) chains of variable length, [Ru(bpy)(2)(bpy-pyr)](PF(6))(2) (1) and [Ru(bpy)(2)(bpy-O6-pyr)](PF(6))(2) (2), have been investigated in acetonitrile solvent. The complexes were designed with the aim of examining the intercomponent energy-transfer processes taking place after light absorption at the two chromophores and the influence of the distance separation between them; in the case of complex 2, the linking chain in the extended conformation is as long as 21 A. Direct excitation of the pyrene unit (lambda(exc) = 410 nm) results in singlet-to-singlet energy transfer (an antenna effect) to the Ru-based component, (1)pyr --> (1)MLCT, which we analyze in terms of the Förster mechanism taking place with unit efficiency. Analysis of the time-resolved pyrene fluorescence reveals that the actual center-to-center distance separation (d(cc)) between the photoactive centers changes according to a Gaussian distribution, with an average d(cc) = 13.6 A (distribution width, a = 2.8 A) and 12 A (a = 10.2 A), for 1 and 2, respectively; this is ascribed to folding of the poly(ethylene glycol) linking chain. In O(2)-free solvent at room temperature, after population of the (1)MLCT level (which takes place either because of direct excitation by using lambda(exc) > 355 nm or via the "antenna" effect) and subsequent intersystem crossing localized at the Ru center, (1)MLCT --> (3)MLCT, a triplet-triplet thermal equilibration is established which involves the physically separated centers, (3)MLCT <--> (3)pyr, with K(eq) = 11 (the energy gap between the two levels is 480 cm(-1), as determined from luminescence data obtained at 77 K). As a consequence of this equilibrium, the (3)MLCT luminescence lifetime becomes tau(Ru) approximately 9 micros both in 1 and 2, i.e., 1 order of magnitude longer than for the unsubstituted [Ru(bpy)(3)](2+) luminophore. In air-equilibrated solvent, diffusional quenching by O(2) effectively depletes the (3)pyr level and only the forward (3)MLCT --> (3)pyr energy transfer step is observed with k(en) = 4 x 10(8) and 2 x 10(8) s(-1) for 1 and 2, respectively. As briefly discussed, reasons for the high rate constants observed for the various triplet-triplet steps may be traced back to the folding properties of the linking chains.
Journal Article↗
Assembly of a truncated-tetrahedral chiral [M12(mu-L)18]24+ cage.
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Journal Article↗
Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men.
The prostate-specific antigen test has been a major factor in increasing awareness and better patient management of prostate cancer (PCA), but its lack of specificity limits its use in diagnosis and makes for poor early detection of PCA. The objective of our studies is to identify better biomarkers for early detection of PCA using protein profiling technologies that can simultaneously resolve and analyze multiple proteins. Evaluating multiple proteins will be essential to establishing signature proteomic patterns that distinguish cancer from noncancer as well as identify all genetic subtypes of the cancer and their biological activity. In this study, we used a protein biochip surface enhanced laser desorption/ionization mass spectrometry approach coupled with an artificial intelligence learning algorithm to differentiate PCA from noncancer cohorts. Surface enhanced laser desorption/ionization mass spectrometry protein profiles of serum from 167 PCA patients, 77 patients with benign prostate hyperplasia, and 82 age-matched unaffected healthy men were used to train and develop a decision tree classification algorithm that used a nine-protein mass pattern that correctly classified 96% of the samples. A blinded test set, separated from the training set by a stratified random sampling before the analysis, was used to determine the sensitivity and specificity of the classification system. A sensitivity of 83%, a specificity of 97%, and a positive predictive value of 96% for the study population and 91% for the general population were obtained when comparing the PCA versus noncancer (benign prostate hyperplasia/healthy men) groups. This high-throughput proteomic classification system will provide a highly accurate and innovative approach for the early detection/diagnosis of PCA.
Aged↗
Anion-templated self-assembly of tetrahedral cage complexes of cobalt(II) with bridging ligands containing two bidentate pyrazolyl-pyridine binding sites.
The bridging ligands L(1) and L(2) contain two N,N-bidentate pyrazolyl-pyridine units linked to a central aromatic spacer unit (1,2-phenyl or 2,3-naphthyl, respectively). Reaction with Ni(II) salts and treatment with the anions tetrafluoroborate or perchlorate result in formation of dinuclear complexes having a 2:3 metal:ligand ratio, with one bridging and two terminal tetradentate ligands. In contrast, reaction of L(1) and L(2) with Co(II) salts, followed by treatment with tetrafluoroborate or perchlorate, results in assembly of cage complexes having a 4:6 metal:ligand ratio; these complexes have a metal ion at each corner of an approximate tetrahedron, and a bis-bidentate bridging ligand spanning each edge. The central cavity is occupied by a tetrahedral counterion that forms multiple hydrogen-bonding interactions with the methylene protons of the bridging ligands. The anionic guest fits tightly into the central cavity of the cage to which it is ideally complementary in terms of shape, size, and charge. Solution NMR experiments show that the central anion acts as a template for cage formation, with a mixture of Co(II) and the appropriate bridging ligand alone giving no assembly into a cage until the tetrahedral anion is added, at which point cage assembly is fast and quantitative. The difference between the structures of the complexes with Ni(II) and Co(II) illustrate how the uncoordinated anions can exert a profound influence on the course of the assembly process.
Anions↗
Tumor-associated zinc finger mutations in the CTCF transcription factor selectively alter tts DNA-binding specificity.
CTCF is a widely expressed 11-zinc finger (ZF) transcription factor that is involved in different aspects of gene regulation including promoter activation or repression, hormone-responsive gene silencing, methylation-dependent chromatin insulation, and genomic imprinting. Because CTCF targets include oncogenes and tumor suppressor genes, we screened over 100 human tumor samples for mutations that might disrupt CTCF activity. We did not observe any CTCF mutations leading to truncations/premature stops. Rather, in breast, prostate, and Wilms' tumors, we observed four different CTCF somatic missense mutations involving amino acids within the ZF domain. Each ZF mutation abrogated CTCF binding to a subset of target sites within the promoters/insulators of certain genes involved in regulating cell proliferation but did not alter binding to the regulatory sequences of other genes. These observations suggest that CTCF may represent a novel tumor suppressor gene that displays tumor-specific "change of function" rather than complete "loss of function."
Amino Acid Sequence↗
Normal, benign, preneoplastic, and malignant prostate cells have distinct protein expression profiles resolved by surface enhanced laser desorption/ionization mass spectrometry.
PURPOSE: The objective of this study was to discover protein biomarkers that differentiate malignant from nonmalignant cell populations, especially early protein alterations that signal the initiation of a developing cancer. We hypothesized that Surface Enhanced Laser Desorption/Ionization-time of flight-mass spectrometry-assisted protein profiling could detect these protein alterations. EXPERIMENTAL DESIGN: Epithelial cell populations [benign prostatic hyperplasia (BPH), prostate intraepithelial neoplasia (PIN), and prostate cancer (PCA)] were procured from nine prostatectomy specimens using laser capture microdissection. Surface Enhanced Laser Desorption/Ionization-time of flight-mass spectrometry analysis was performed on cell lysates, and the relative intensity levels of each protein or peptide in the mass spectra was calculated and compared for each cell type. RESULTS: Several small molecular mass peptides or proteins (3000-5000 Da) were found in greater abundance in PIN and PCA cell lysates. Another peak, with an average mass of 5666 Da, was observed to be up-regulated in 86% of the BPH cell lysates. Higher levels of this same peak were found in only 22% of the PIN lysates and none of the PCA lysates. Expression differences were also found for intracellular levels of prostate-specific antigen, which were reduced in PIN and PCA cells when compared with matched normals. Although no single protein alteration was observed in all PIN/PCA samples, combining two or more of the markers was effective in distinguishing the benign cell types (normal/BPH) from diseased cell types (PIN/PCA). Logistic regression analysis using seven differentially expressed proteins resulted in a predictive equation that correctly distinguished the diseased lysates with a sensitivity and specificity of 93.3 and 93.8%, respectively. CONCLUSIONS: We have shown that the protein profiles from prostate cells with different disease states have discriminating differences. These differentially regulated proteins are potential markers for early detection and/or risk factors for development of prostate cancer. Studies are under way to identify these protein/peptides, with the goal of developing a diagnostic test for the early detection of prostate cancer.
Adult↗
Boosted decision tree analysis of surface-enhanced laser desorption/ionization mass spectral serum profiles discriminates prostate cancer from noncancer patients.
BACKGROUND: The low specificity of the prostate-specific antigen (PSA) test makes it a poor biomarker for early detection of prostate cancer (PCA). Because single biomarkers most likely will not be found that are expressed by all genetic forms of PCA, we evaluated and developed a proteomic approach for the simultaneous detection and analysis of multiple proteins for the differentiation of PCA from noncancer patients. METHODS: Serum samples from 386 men [197 with PCA, 92 with benign prostatic hyperplasia (BPH), and 96 healthy individuals], randomly divided into training (n = 326) and test (n = 60) sets, were analyzed by surface-enhanced laser desorption/ionization (SELDI) mass spectrometry. The 124 peaks detected by computer analyses were analyzed in the training set by a boosting tree algorithm to develop a classifier for separating PCA from the noncancer groups. The classifier was then challenged with the test set (30 PCA samples, 15 BPH samples, 15 samples from healthy men) to determine the validity and accuracy of the classification system. RESULTS: Two classifiers were developed. The AdaBoost classifier completely separated the PCA from the noncancer samples, achieving 100% sensitivity and specificity. The second classifier, the Boosted Decision Stump Feature Selection classifier, was easier to interpret and used only 21 (compared with 74) peaks and a combination of 21 (vs 500) base classifiers to achieve a sensitivity and specificity of 97% for the test set. CONCLUSIONS: The high sensitivity and specificity achieved in this study provides support of the potential for SELDI, coupled with a bioinformatics learning algorithm, to improve the early detection/diagnosis of PCA.
Algorithms↗