Composition-based statistics and translated nucleotide searches: Improving the TBLASTN module of BLAST

BACKGROUND: TBLASTN is a mode of operation for BLAST that aligns protein sequences to a nucleotide database translated in all six frames. We present the first description of the modern implementation of TBLASTN, focusing on new techniques that were used to implement composition-based statistics for translated nucleotide searches. Composition-based statistics use the composition of the sequences being aligned to generate more accurate E-values, which allows for a more accurate distinction between true and false matches. Until recently, composition-based statistics were available only for protein-protein searches. They are now available as a command line option for recent versions of TBLASTN and as an option for TBLASTN on the NCBI BLAST web server. RESULTS: We evaluate the statistical and retrieval accuracy of the E-values reported by a baseline version of TBLASTN and by two variants that use different types of composition-based statistics. To test the statistical accuracy of TBLASTN, we ran 1000 searches using scrambled proteins from the mouse genome and a database of human chromosomes. To test retrieval accuracy, we modernize and adapt to translated searches a test set previously used to evaluate the retrieval accuracy of protein-protein searches. We show that composition-based statistics greatly improve the statistical accuracy of TBLASTN, at a small cost to the retrieval accuracy. CONCLUSION: TBLASTN is widely used, as it is common to wish to compare proteins to chromosomes or to libraries of mRNAs. Composition-based statistics improve the statistical accuracy, and therefore the reliability, of TBLASTN results. The algorithms used by TBLASTN are not widely known, and some of the most important are reported here. The data used to test TBLASTN are available for download and may be useful in other studies of translated search algorithms

Detection of amyloid beta aggregates in the brain of BALB/c mice after Chlamydia pneumoniae infection

Neuroinflammation, initiated by cerebral infection, is increasingly postulated as an aetiological factor in neurodegenerative diseases such as Alzheimer’s disease (AD). We investigated whether Chlamydia pneumoniae (Cpn) infection results in extracellular aggregation of amyloid beta (Aβ) in BALB/c mice. At 1 week post intranasal infection (p.i.), Cpn DNA was detected predominantly in the olfactory bulbs by PCR, whereas brains at 1 and 3 months p.i. were Cpn negative. At 1 and 3 months p.i., extracellular Aβ immunoreactivity was detected in the brain of Cpn-infected mice but also in the brain of mock-infected mice and mice that were neither Cpn infected nor mock infected. However, these extracellular Aβ aggregates showed morphological differences compared to extracellular Aβ aggregates detected in the brain of transgenic APP751SL/PS1M146L mice. These data do not unequivocally support the hypothesis that Cpn infection induces the formation of AD-like Aβ plaques in the brain of BALB/c mice, as suggested before. However, future studies are required to resolve these differences and to investigate whether Cpn is indeed an etiological factor in AD pathogenesis

Oxidants, antioxidants, and respiratory tract lining fluids.

Respiratory tract lining fluids (RTLFs) are a heterogeneous group of substances covering the respiratory tract epithelial cells (RTECs) from nasal mucosa to alveoli. Antioxidant contained in the RTLFs can be expected to provide an initial defense against inhaled environmental toxins. The major antioxidants in RTLF include mucin, uric acid, protein (largely albumin), ascorbic acid, and reduced glutathione (GSH). RTLF antioxidants can be augmented by such processes as transudation/exudation of plasma constituents; RTEC secretory processes, including glandular mucus secretion; and cellular antioxidants derived from lysis of RTECs and of inflammatory cells. The antioxidant composition of RTLFs and their role in modulating normal and pathophysiologic RTEC functions under conditions of oxidative stress are yet to be fully characterized

Role of Mesenchymal Stem Cells on Cornea Wound Healing Induced by Acute Alkali Burn

The aim of this study was to investigate the effects of subconjunctivally administered mesenchymal stem cells (MSCs) on corneal wound healing in the acute stage of an alkali burn. A corneal alkali burn model was generated by placing a piece of 3-mm diameter filter paper soaked in NaOH on the right eye of 48 Sprague-Dawley female rats. 24 rats were administered a subconjunctival injection of a suspension of 2×106 MSCs in 0.1 ml phosphate-buffered saline (PBS) on day 0 and day 3 after the corneal alkali burn. The other 24 rats were administered a subconjunctival injection of an equal amount of PBS as a control. Deficiencies of the corneal epithelium and the area of corneal neovascularization (CNV) were evaluated on days 3 and 7 after the corneal alkali burn. Infiltrated CD68+ cells were detected by immunofluorescence staining. The mRNA expression levels of macrophage inflammatory protein-1 alpha (MIP-1α), tumor necrosis factor-alpha (TNF-α), monocyte chemotactic protein-1 (MCP-1) and vascular endothelial growth factor (VEGF) were analyzed using real-time polymerase chain reaction (real-time PCR). In addition, VEGF protein levels were analyzed using an enzyme-linked immunosorbent assay (ELISA). MSCs significantly enhanced the recovery of the corneal epithelium and decreased the CNV area compared with the control group. On day 7, the quantity of infiltrated CD68+ cells was significantly lower in the MSC group and the mRNA levels of MIP-1α, TNF-α, and VEGF and the protein levels of VEGF were also down-regulated. However, the expression of MCP-1 was not different between the two groups. Our results suggest that subconjunctival injection of MSCs significantly accelerates corneal wound healing, attenuates inflammation and reduces CNV in alkaline-burned corneas; these effects were found to be related to a reduction of infiltrated CD68+ cells and the down-regulation of MIP-1α, TNF-α and VEGF

High Mortality of Pneumonia in Cirrhotic Patients with Ascites

[[abstract]]Background Cirrhotic patients with ascites are prone to develop various infectious diseases. This study aimed to evaluate the occurrence and effect of major infectious diseases on the mortality of cirrhotic patients with ascites. Methods We reviewed de-identified patient data from the National Health Insurance Database, derived from the Taiwan National Health Insurance Program, to enroll 4,576 cirrhotic patients with ascites, who were discharged from Taiwan hospitals between January 1, 2004 and June 30, 2004. We collected patients’ demographic and clinical data, and reviewed diagnostic codes to determine infectious diseases and comorbid disorders of their hospitalizations. Patients were divided into an infection group and non-infection group and hazard ratios (HR) were determined for specific infectious diseases. Results Of the total 4,576 cirrhotic patients with ascites, 1,294 (28.2%) were diagnosed with infectious diseases during hospitalization. The major infectious diseases were spontaneous bacterial peritonitis (SBP) (645, 49.8%), urinary tract infection (151, 11.7%), and pneumonia (100, 7.7%). After adjusting for patients’ age, gender, and other comorbid disorders, the HRs of infectious diseases for 30-day and 90-day mortality of cirrhotic patients with ascites were 1.81 (1.54-2.11) and 1.60 (1.43-1.80) respectively, compared to those in the non-infection group. The adjusted HRs of pneumonia, urinary tract infection (UTI), spontaneous bacterial peritonitis (SBP), and sepsis without specific focus (SWSF) were 2.95 (2.05-4.25), 1.32 (0.86-2.05), 1.77 (1.45-2.17), and 2.19 (1.62-2.96) for 30-day mortality, and 2.57 (1.93-3.42), 1.36 (1.01-1.82), 1.51 (1.29-1.75), and 2.13 (1.70-2.66) for 90-day mortality, compared to those in the non-infection group. Conclusion Infectious diseases increased 30-day and 90-day mortality of cirrhotic patients with ascites. Among all infectious diseases identified, pneumonia carried the highest risk for mortality.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]電子

Predicting Transcriptional Activity of Multiple Site p53 Mutants Based on Hybrid Properties

As an important tumor suppressor protein, reactivate mutated p53 was found in many kinds of human cancers and that restoring active p53 would lead to tumor regression. In this work, we developed a new computational method to predict the transcriptional activity for one-, two-, three- and four-site p53 mutants, respectively. With the approach from the general form of pseudo amino acid composition, we used eight types of features to represent the mutation and then selected the optimal prediction features based on the maximum relevance, minimum redundancy, and incremental feature selection methods. The Mathew's correlation coefficients (MCC) obtained by using nearest neighbor algorithm and jackknife cross validation for one-, two-, three- and four-site p53 mutants were 0.678, 0.314, 0.705, and 0.907, respectively. It was revealed by the further optimal feature set analysis that the 2D (two-dimensional) structure features composed the largest part of the optimal feature set and maybe played the most important roles in all four types of p53 mutant active status prediction. It was also demonstrated by the optimal feature sets, especially those at the top level, that the 3D structure features, conservation, physicochemical and biochemical properties of amino acid near the mutation site, also played quite important roles for p53 mutant active status prediction. Our study has provided a new and promising approach for finding functionally important sites and the relevant features for in-depth study of p53 protein and its action mechanism