Background: Meta-analyses of N-acetylcysteine (NAC) for preventing contrast-induced nephrotoxicity (CIN) have led to disparate conclusions. Here we examine and attempt to resolve the heterogeneity evident among these trials.

A shock canine pneumonia model that permitted relief of discomfort with the use of objective criteria was developed and validated. After intrabronchial Staphylococcus aureus challenge, mechanical ventilation, antibiotics, fluids, vasopressors, sedatives, and analgesics were titrated based on algorithms for 96 h. Increasing S. aureus (1 to 8 x 10(9) colony-forming units/kg) produced decreasing survival rates (P = 0.04). From 4 to 96 h, changes in arterial-alveolar oxygen gradients, mean pulmonary artery pressure, IL-1, serum sodium levels, mechanical ventilation, and vasopressor support were ordered based on survival time [acute nonsurvivors (< or =24 h until death, n = 8) > or = subacute nonsurvivors (>24 to 96 h until death, n = 8) > or = survivors (> or =96 h until death, n = 22) (all P < 0.05)]. In the first 12 h, increases in lactate and renal abnormalities were greatest in acute nonsurvivors (all P < 0.05). Compared with survivors, subacute nonsurvivors had greater rises in cytokines and liver enzymes and greater falls in platelets, white cell counts, pH, and urine output from 24 to 96 h (all P < 0.05). Importantly, these changes were not attributable to dosages of sedation, which decreased in nonsurvivors [survivors vs. nonsurvivors: 5.0 +/- 1.0 vs. 3.8 +/- 0.7 ml x h(-1) x (fentanyl/midazolam/ medetomidine)(-1); P = 0.02]. In this model, the pain control regimen did not mask changes in metabolic function and lung injury or the need for more hemodynamic and pulmonary support related to increasing severity of sepsis. The integration into this model of both specific and supportive titrated therapies routinely used in septic patients may provide a more realistic setting to evaluate therapies for sepsis.

Background: Prefractionation techniques such as serum albumin depletion are useful precursors to proteomic analysis, but they may introduce preanalytical bias if the depletion is not reproducible. We examined the reproducibility of albumin immunodepletion and describe a method of QC for this process. Methods: Depletion of albumin from pooled serum, performed using IgY immunoaffinity spin columns, was assessed for 21 runs on each of 4 columns. We measured albumin concentrations, after albumin depletion, by use of an immunoturbidimetric assay on the Beckman LX 20 analyzer and assessed mass spectra of albumin-depleted samples by use of SELDI-TOF mass spectrometry. Results: There was substantial run-to-run variation in efficiency of albumin depletion, with systematic decline in efficiency after multiple uses of the columns. Mean depletion efficiency was >95% for 15 of the 1st 17 runs and <90% for runs 18 to 21. We evaluated the 10 highest-intensity peaks present in all spectra from runs 1, 8, 17, and 21 and assessed the effect of albumin depletion on SELDI-TOF mass spectrometry reproducibility. Comparing the %CV of relative intensities for low and high m/z measurements revealed a significant difference of run 21 compared with runs 1, 8, and 17 (P <0.0001). Six-fold more peaks were found in albumindepleted than unfractionated serum at both high and low m/z.

We hypothesized that invasive pulmonary aspergillosis (IPA) may generate a distinctive proteomic signature in plasma and bronchoalveolar lavage (BAL). Proteins in plasma and BAL from two neutropenic rabbit models of IPA and Pseudomonas pneumonia were analyzed by SELDI-TOF MS. Hierarchical clustering analysis of plasma time course spectra demonstrated two clusters of peaks that were differentially regulated between IPA and Pseudomonas pneumonia (57 and 34 peaks, respectively, p<0.001). PCA of plasma proteins demonstrated a time-dependent separation of the two infections. A random forest analysis that ranked the top 30 spectral points distinguished between late Aspergillus and Pseudomonas pneumonias with 100% sensitivity and specificity. Based on spectral data analysis, three proteins were identified using SDS-PAGE and LC/MS and quantified using reverse phase arrays. Differences in the temporal sequence of plasma haptoglobin (p <0.001), apolipoprotein A1 (p<0.001) and transthyretin (p<0.038) were observed between IPA and Pseudomonas pneumonia, as was C-reactive protein (p<0.001). In summary, proteomic analysis of plasma and BAL proteins of experimental Aspergillus and Pseudomonas pneumonias demonstrates unique protein profiles with principal components and spectral regions that are shared in early infection and diverge at later stages of infection. Haptoglobin, apolipoprotein A1, transthyretin and C-reactive protein are differentially expressed in these infections suggesting important contributions to host defense against IPA.

Peak detection is a pivotal first step in biomarker discovery from mass spectrometry (MS) data and can significantly influence the results of downstream data analysis steps. We developed a novel automatic peak detection method for prOTOF MS data which does not require a priori knowledge of protein masses. Random noise is removed by an undecimated wavelet transform and chemical noise is attenuated by an adaptive short-time discrete Fourier transform. Isotopic peaks corresponding to a single protein are combined by extracting an envelope over them. Depending on the signal-to-noise ratio (SNR), the desired peaks in each individual spectrum are detected and those with the highest intensity among their peak clusters are recorded. The common peaks among all the spectra are identified by choosing an appropriate cut-off threshold in the complete linkage hierarchical clustering. To remove the 1Da shifting of the peaks, the peak corresponding to the same protein is determined as the detected peak with the largest number among its neighborhood. We validated this method using a dataset of serial peptide and protein calibration standards. Compared with MoverZ program, our new method detects more peaks and significantly enhances SNR of the peak after the chemical noise removal. We then successfully applied this method to a dataset from prOTOF MS spectra of albumin and albumin-bound proteins from serum samples of 59 patients with carotid artery disease to detect peaks with SNR ≥2. Our method is easily implemented and is highly effective to define peaks that will be used for disease classification or to highlight potential biomarkers.