Simultaneous determination of iron, cadmium, zinc, copper, nickel, lead, and uranium in sea water by stable isotope dilution spark source mass spectrometry

Surfactant-mediated complex formation for determination of traces amounts of zinc, cadmium, and lead with 4-(2-thiazolylazo) resorcinol and chemometric methods

The partial least squares modeling is a powerful multivariate statistical tool applied to the spectrophotometric simultaneous determination of the divalent ions of zinc, cadmium, and lead based on the formation of their complexes with 4-(2-thiazolylazo) resorcinol in surfactant media. The linear concentration range for zinc, cadmium, and lead were 0.10-1.31, 0.148-1.92, and 0.148-3.70 mg L( -1), respectively. The experimental calibration set was composed of 36 sample solutions using a mixture design for three component mixtures. The absorption spectra were recorded from 380 through 650 nm. The effect of pH on the sensitivity in determination of zinc, cadmium, and lead was studied in order to choose the optimum pH (pH = 8) for determination. The root-mean-square errors of predictions for zinc, cadmium, and lead were 0.0466, 0.0282, and 0.050, respectively. The proposed method was successfully applied for the determination of zinc, cadmium, and lead in water samples.

Mass spectrometry-based clinical proteomics: head-and-neck cancer biomarkers and drug-targets discovery

Mass spectrometry (MS)-based proteomics is a rapidly developing technology for both qualitative and quantitative analyses of proteins, and investigations into protein posttranslational modifications, subcellular localization, and interactions. Recent advancements in MS have made tremendous impact on the throughput and comprehensiveness of cancer proteomics, paving the way to unraveling deregulated cellular pathway networks in human malignancies. In turn, this knowledge is rapidly being translated into the discovery of novel potential cancer markers (PCMs) and targets for molecular therapeutics. Head-and-neck cancer is one of the most morbid human malignancies with an overall poor prognosis and severely compromised quality of life. Early detection and novel therapeutic strategies are urgently needed for more effective disease management. The characterizations of protein profiles of head-and-neck cancers and non-malignant tissues, with unprecedented sensitivity and precision, are providing technology platforms for identification of novel PCMs and drug targets. Importantly, low-abundance proteins are being identified and characterized, not only from the tumor tissues, but also from bodily fluids (plasma, saliva, and urine) in a high-throughput and unbiased manner. This review is a critical appraisal of recent advances in MS-based proteomic technologies and platforms for facilitating the discovery of biomarkers and novel drug targets in head-and-neck cancer. A major challenge in the discovery and verification of these cancer biomarkers is the typically limited availability of well-characterized and adequately stored clinical samples in tumor and sera banks, collected using recommended procedures, and with detailed information on clinical, pathological parameters, and follow-up. Most biomarker discovery studies use limited number of clinical samples and verification of cancer markers in large number of samples is beyond the scope of a single laboratory. The validation of these potential markers in large sample cohorts in multicentric studies is needed for their translation from the bench to the bedside.

Structural insights into protein–uranyl interaction: towards an in silico detection method

Documenting the modes of interaction of uranyl (UO(2)2+) with large biomolecules, and particularly with proteins, is instrumental for the interpretation of its behavior in vitro and in vivo. The gathering of three-dimensional information concerning uranyl-first shell atoms from two structural databases, the Cambridge Structural Databank and the Protein Data Bank (PDB) allowed a screening of corresponding topologies in proteins of known structure. In the computer-aided procedure, all potentially bound residues from the template structure were granted full flexibility using a rotamer library. The Amber force-field was used to loosen constraints and score each predicted site. Our algorithm was validated as a first stage through the recognition of existing experimental data in the PDB. The coherent localization of missing atoms in the density map of an ambiguous uranium/uranyl-protein complex exemplified the efficiency of our approach, which is currently suggesting the experimental investigation of uranyl-protein binding site.

Effects of heavy metals on sea urchin embryo development. 1. Tracing the cause by the effects

The toxicity of the polluted waters originating from a disused lead mine was evaluated using both sea urchin bioassays and heavy metal analysis. Samples from three polluted waters (a seawater and two freshwaters) were collected from the mine area and one seawater sample was taken from a non-contaminated reference site. The test waters contained higher concentrations of heavy metals such as manganese, lead, cadmium, zinc, chromium, nickel, iron, and copper than did ambient seawater. The three test waters had inhibitory effects, in a dose-dependent manner, on the first cleavage of sea urchin embryos and on pluteus formation during the development. Some malformations, such as a radialized pluteus, exo-gastrula, and spaceship Apollo-like embryos were induced by the test waters without dilution. Zinc alone also induced the same anomaly. Zinc in the test seawater was ascertained as one of the metals that caused the anomalies, but not all of the toxicity was caused by zinc. It was speculated that interactive effects, involving zinc and possibly manganese and nickel, were occurring.