Determination of total calcium in plasma by flow injection analysis with tris(2,2 '-bipyridyl)ruthenium(II) electrochemiluminescent detection

We described here a new method for the determination of total calcium in plasma. The method is based on the precipitation of calcium with excess oxalate and the measurement of residual oxalate by flow injection analysis with Ru(bpy)(3)(2+) electrochemiluminescent detection. It has the advantages of extremely stable reagent, user-friendly instrument, high selectivity, good analytical recovery, wide dynamic range, and nice correlation with atomic absorption spectroscopy. The calibration plot for calcium is linear over a concentration range from 0.5 mmol L-1 to 4.8 mmol L-1, which is wider than those obtained by most other methods. The analytical recoveries for plasma calcium are 98.4-101.2% with coefficients of variation (CVs) of 1.96-2.52%. The within-day CVs range from 0.76% to 0.95%, and between-day CVs were from 1.12% to 1.46%. The time for each injection is one minute. Because the proposed method can be readily carried out on increasingly popular instruments for Ru(bpy)(3)(2+) ECL immunoassays and DNA probe assays, Ru(bpy)32+ ECL method is suitable for routine clinical analysis of calcium.

Determination of sulpiride by capillary electrophoresis with end-column electrogenerated chemiluminescence detection

Background: Capillary electrophoresis (CE) with tris(2,2'-bipyridyl)ruthenium(II) [Ru(bpy)(3)(2+)]-electro-generated chemiluminescence (ECL) detection is a promising method for clinical analysis. In this study, a method combining CE with Ru(bpy)(3)(2+) ECL (CE-ECL) detection that can be applied to amine-containing clinical species was developed, and the performance of CE-ECL as a quantitative method for determination of sulpiride in human plasma or urine was evaluated. Methods: Sulpiride was separated by capillary zone electrophoresis in uncoated fused-silica capillaries [510 cm x 25 mum (i.d.)] filled with phosphate buffer (pH 8.0 and a driving voltage of +15 kV, with end-column Ru(bpy)(3)(2+) ECL detection. A platinum disc electrode was used as working electrode. Sulpiride in human plasma or urine samples (100 muL) was extracted by a double-step liquid-liquid extraction procedure, dried under nitrogen at 35 degreesC in a water bath, and reconstituted with 100 muL of filtered water. The extraction solvent was ethyl acetate-dichloromethane (5:1 by volume). Results: Under optimum conditions (pH 8.0 phosphate buffer, injection for 6 s at 10 kV, and +1.2 V as detection potential), separation of sulpiride was accomplished within 4 min. The calibration curve was linear over a concentration range of 0.05-25.0 mumol/L, and the limit of detection was 2.9 x 10(-8) mol/L for sulpiride. Intra- and interday CVs for ECL intensities were <6%. Extraction recoveries of sulpiride were 95.6-101% with CVs of 2.9-6.0%. The method was,clinically validated for patient plasma and urine samples. Conclusions: CE combined with Ru(bpy)(3)(2+) ECL is reproducible, precise, selective, and enables the analysis of sulpiride in human plasma and urine. It thus is of value for rapid and efficient analysis of amine-containing analytes of clinical interest.

Peptidomics and genomics analysis of novel antimicrobial peptides from the frog, Rana nigrovittata

Much attention has been paid on amphibian peptides for their wide-ranging pharmacological properties, clinical potential, and gene-encoded origin. More than 300 antimicrobial peptides (AMPs) from amphibians have been studied. Peptidomics and genomics analysis combined with functional test including microorganism killing, histamine-releasing, and mast cell degranulation was used to investigate antimicrobial peptide diversity. Thirty-four novel AMPs from skin secretions of Rana nigrovittata were identified in current work, and they belong to 9 families, including 6 novel families. Other three families are classified into rugosin, gaegurin, and temporin family of amphibian AMP, respectively. These AMPs share highly conserved preproregions including signal peptides and spacer acidic peptides, while greatly diversified on mature peptides structures. In this work, peptidomics combined with genomics analysis was confirmed to be an effective way to identify amphibian AMPs, especially novel families. Some AMPs reported here will provide leading molecules for designing novel antimicrobial agents. (C) 2009 Elsevier Inc. All rights reserved

Genomic organization, gene duplication, and expression analysis of interleukin-1 beta in channel catfish (Ictalurus punctatus)

Interleukin-1 beta (IL-1 beta) is one of the pivotal early response pro-inflammatory cytokines that enables organisms to respond to infection and induces a cascade of reactions leading to inflammation. In spite of its importance and two decades of studies in the mammalian species, genes encoding IL-1 beta were not identified from non-mammalian species until recently. Recent research, particularly with genomic approaches, has led to sequencing of IL-1 beta from many species. Clinical studies also Suggested IL-1 beta as an immunoreagulatory molecule potentially useful for enhancing vaccination. However, no IL-1 beta genes have been identified from channel catfish, the primary aquaculture species from the United States. In this study, we identified two distinct cDNAs encoding catfish IL-1 beta. Their encoding genes were identified, sequenced, and characterized. The catfish IL-1 beta genes were assigned to bacterial artificial chromosome (BAC) clones. Genomic studies indicated that the IL-1 beta genes were tandemly duplicated on the same chromosome. Phylogenetic analysis of various IL-1 beta genes indicated the possibility of recent species-specific gene duplications in channel catfish, and perhaps also in swine and carp. Expression analysis indicated that both IL-1 beta genes were expressed, but exhibited distinct expression profiles in various catfish tissues, and after bacterial infection with Edwardsiella ictaluri. (c) 2005 Elsevier Ltd. All rights reserved.

Application of probabilistic neural network in the clinical diagnosis of cancers based on clinical chemistry data

As a recently developed and powerful classification tool, probabilistic neural network was used to distinguish cancer patients from healthy persons according to the levels of nucleosides in human urine. Two datasets (containing 32 and 50 patterns, respectively) were investigated and the total consistency rate obtained was 100% for dataset 1 and 94% for dataset 2. To evaluate the performance of probabilistic neural network, linear discriminant analysis and learning vector quantization network, were also applied to the classification problem. The results showed that the predictive ability of the probabilistic neural network is stronger than the others in this study. Moreover, the recognition rate for dataset 2 can achieve to 100% if combining, these three methods together, which indicated the promising potential of clinical diagnosis by combining different methods. (C) 2002 Elsevier Science B.V. All rights reserved.

Artificial neural network classification based on high-performance liquid chromatography of urinary and serum nucleosides for the clinical diagnosis of cancer

Nucleosides in human urine and serum have frequently been studied as a possible biomedical marker for cancer, acquired immune deficiency syndrome (AIDS) and the whole-body turnover of RNAs. Fifteen normal and modified nucleosides were determined in 69 urine and 42 serum samples using high-performance liquid chromatography (HPLC). Artificial neural networks have been used as a powerful pattern recognition tool to distinguish cancer patients from healthy persons. The recognition rate for the training set reached 100%. In the validating set, 95.8 and 92.9% of people were correctly classified into cancer patients and healthy persons when urine and serum were used as the sample for measuring the nucleosides. The results show that the artificial neural network technique is better than principal component analysis for the classification of healthy persons and cancer patients based on nucleoside data. (C) 2002 Elsevier Science B.V. All rights reserved.

Evaluation of a combined wavelet and a combined principal component analysis classification system for BCG diagnostic problem

Heart disease is one of the main factor causing death in the developed countries. Over several decades, variety of electronic and computer technology have been developed to assist clinical practices for cardiac performance monitoring and heart disease diagnosis. Among these methods, Ballistocardiography (BCG) has an interesting feature that no electrodes are needed to be attached to the body during the measurement. Thus, it is provides a potential application to asses the patients heart condition in the home. In this paper, a comparison is made for two neural networks based BCG signal classification models. One system uses a principal component analysis (PCA) method, and the other a discrete wavelet transform, to reduce the input dimensionality. It is indicated that the combined wavelet transform and neural network has a more reliable performance than the combined PCA and neural network system. Moreover, the wavelet transform requires no prior knowledge of the statistical distribution of data samples and the computation complexity and training time are reduced.

Rapid identification of pathogenic bacteria by capillary electrophoretic analysis of rRNA genes

Molecular diagnosis is playing an increasingly important role in the rapid detection and identification of pathogenic organisms in clinical samples. The genetic variation of ribosomal genes in bacteria offers an alternative to culturing for the detection and identification of these organisms. Here 16S rRNA and 16S-23S rRNA spacer region genes were chosen as the amplified targets for single-strand conformation polymorphism (SSCP) and restriction fragment length polymorphism (RFLP) capillary electrophoresis analysis and bacterial identification. The multiple fluorescence based SSCP method for the 16S rRNA gene and the RFLP method for the 16S-23S rRNA spacer region gene were developed and applied to the identification of pathogenic bacteria in clinical samples, in which home-made short-chained linear polyacrylamide (LPA) was used as a sieving matrix; a higher sieving capability and shorter analysis time were achieved than with a commercial sieving matrix because of the simplified template preparation procedure. A set of 270 pathogenic bacteria representing 34 species in 14 genera were analyzed, and a total of 34 unique SSCP patterns representing 34 different pathogenic bacterial species were determined. Based on the use of machine code to represent peak patterns developed in this paper, the identification of bacterial species becomes much easier.

Clinical significance and prognostic value of urinary nucleosides in breast cancer patients

Objective: Thirteen urinary nucleosides, primarily degradation products of tRNA, were evaluated as potential tumor markers for breast cancer patients.