Presymptomatic prediction of sepsis in intensive care unit patients.

Postoperative or posttraumatic sepsis remains one of the leading causes of morbidity and mortality in hospital populations, especially in populations in intensive care units (ICUs). Central to the successful control of sepsis-associated infections is the ability to rapidly diagnose and treat disease. The ability to identify sepsis patients before they show any symptoms would have major benefits for the health care of ICU patients. For this study, 92 ICU patients who had undergone procedures that increased the risk of developing sepsis were recruited upon admission. Blood samples were taken daily until either a clinical diagnosis of sepsis was made or until the patient was discharged from the ICU. In addition to standard clinical and laboratory parameter testing, the levels of expression of interleukin-1beta (IL-1beta), IL-6, IL-8, and IL-10, tumor necrosis factor-alpha, FasL, and CCL2 mRNA were also measured by real-time reverse transcriptase PCR. The results of the analysis of the data using a nonlinear technique (neural network analysis) demonstrated discernible differences prior to the onset of overt sepsis. Neural networks using cytokine and chemokine data were able to correctly predict patient outcomes in an average of 83.09% of patient cases between 4 and 1 days before clinical diagnosis with high sensitivity and selectivity (91.43% and 80.20%, respectively). The neural network also had a predictive accuracy of 94.55% when data from 22 healthy volunteers was analyzed in conjunction with the ICU patient data. Our observations from this pilot study indicate that it may be possible to predict the onset of sepsis in a mixed patient population by using a panel of just seven biomarkers.

The optimisation of a murine TNF-alpha ELISA and the application of the method to other murine cytokines.

Cytokines occur in biological systems at low levels of concentration, therefore assays developed to measure them must be very sensitive. Enzyme linked immunosorbent assays (ELISA's) developed using manufacturers recommended end points can detect cytokines to picogram levels but the lower parts of their standard curves can be unreliable. In this study the relative merits of different substrate systems - 2,2'-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) and 2 forms of tetramethyl benzidine (TMB), were investigated with regard to assay sensitivity. Further, a signal amplification method involving biotinylated tyramine has been used to increase the absorbance signal and thus the assay sensitivity and to achieve a sigmoidal standard curve. The amplified assay approach has been applied successfully to achieve more sensitive detection of TNF-alpha and improve the sensitivity of assays for a wide range of other cytokines. The optimised amplification method is the same for all the cytokine ELISA's performed in this work and this enables them to be performed

A comparison of the leakage of a monoclonal antibody from various immunoaffinity chromatography matrices.

Antibody leakage from immunoaffinity chromatography (IAC) matrices could reduce the working life of the IAC matrix and/or contaminate parenteral products, purified by IAC. There is therefore a need to measure the leakage of antibody from IAC matrices and to reduce such leakage. Using sensitive ELISAs it was found that the type of activated matrix, the buffer, the presence of proteases in the feedstock and the storage of IAC matrices between runs could all effect antibody leakage.

Development of enzyme-linked immunosorbent assays (ELISAs) for the detection of monoclonal antibody leakage from immunoaffinity chromatography matrices.

Antibodies can leak from immunoaffinity chromatography (IAC) matrices, reducing the working life of the IAC matrix and/or compromising the purity of the product, purified by IAC, for therapeutic use. There is therefore a need to monitor the leakage of antibody from IAC matrices. Antibody leakage from a model IAC system was measured using two-site 'non-competitive' ELISAs. Two assays were developed to measure the leakage of intact and fragmented antibody from the IAC matrix. By measuring the leakage of intact and fragmented antibody the mechanisms underlying antibody leakage from solid-supports could be elucidated.

Stishovite at the cretaceous-tertiary boundary, raton, new Mexico.

Stishovite, a dense phase of silica, has become widely accepted as an indicator of terrestrial impact events. Stishovite occurs at several impact structures but has not been found at volcanic sites. Solid-state silicon-29 magic-angle spinning nuclear magnetic resonance (silicon-29 MAS NMR) and X-ray diffraction of samples from the Cretaceous-Tertiary boundary layer at Raton, New Mexico, indicate that stishovite occurs in crystalline mineral grains. Stishovite was indicated by a single, sharp resonance with a chemical shift value of -191.3 ppm, characteristic of silicon in octahedral coordination, that disappeared after heating the sample at 850 degrees Celsius for 30 minutes. An X-ray diffraction pattern of HF residuals from the unheated sample displayed more than 120 peaks, most of which correspond to quartz, zircon, rutile, and anatase. Eight unambiguous weak to moderate reflections could be ascribed to d-spacings characteristic of stishovite.