Abstract:To explore the application of protein fingerprint technique and differential diagnosis in bacteriological negative pulmonary tuberculosis and pneumonia, 60 patients with bacteriological negative pulmonary tuberculosis, 60 patients with pneumonia, and 60 healthy volunteers were selected from known clinical cases. Surface strengthening laser desorption ionization time of flight mass spectrometry (SELDI ToF Ms) and protein chip technology were applied to detect serum proteins, and analyze their protein peaks by Ciphergen protein chip 3.1.1 software. Comparison of the serum protein fingerprinting data from the pool of 180 patients and healthy volunteers showed significant difference in 5 protein peaks (1 028.49, 4 796.56, 7 564.77, 8 048.02, and 11 526.75 m/z) identified between pulmonary tuberculosis and pneumonia (P<0.01). The total effective rate of the 5 protein peaks as a diagnosis model for differential diagnosis of bacteriological negative pulmonary tuberculosis and pneumonia was 84.2% (101/120), the specificity was 82.5% (52/63), the sensitivity was 85.9% (49/57), the positive predictive value was 86.7% (52/60), and the negative predictive value was 81.7% (49/60). The total effective rate of the diagnosis model for differential diagnosis of bacteriological negative pulmonary tuberculosis, pneumonia and healthy volunteers was 89.4% (161/180). The specificity was 100% (60/60), the sensitivity was 84.2% (101/120), the positive predictive value was 100% (101/101), and the negative predictive value was 75.9% (60/79). Protein fingerprinting technology is advantageous of being a simple method, quick detection, and requires less amount of sample. It is an effective means to screening the tuberculosis specific markers. We found the good diagnosis model through the detection of serum protein by protein fingerprinting technology.
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