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author:("Shi, jindong")
1.  Cortical Endogenic Neural Regeneration of Adult Rat after Traumatic Brain Injury 
PLoS ONE  2013;8(7):e70306.
Focal and diffuse neuronal loss happened after traumatic brain injury (TBI). With little in the way of effective repair, recent interest has focused on endogenic neural progenitor cells (NPCs) as a potential method for regeneration. Whether endogenic neural regeneration happened in the cortex of adult rat after TBI remains to be determined. In this study, rats were divided into a sham group and a TBI group, and the rat model of medium TBI was induced by controlled cortical impact. Rats were injected with BrdU at 1 to 7 days post-injury (dpi) to allow identification of differentiated cells and sacrificed at 1, 3, 7, 14 and 28 dpi for immunofluorescence. Results showed nestin+/sox-2+ NPCs and GFAP+/sox-2+ radial glial (RG)-like cells emerged in peri-injured cortex at 1, 3, 7, 14 dpi and peaked at 3 dpi. The number of GFAP+/sox-2+ cells was less than that of nestin+/sox-2+ cells. Nestin+/sox-2+ cells from posterior periventricle (pPV) immigrated into peri-injured cortex through corpus callosum (CC) were found. DCX+/BrdU+ newborn immature neurons in peri-injured cortex were found only at 3, 7, 14 dpi. A few MAP-2+/BrdU+ newborn neurons in peri-injured cortex were found only at 7 and 14 dpi. NeuN+/BrdU+ mature neurons were not found in peri-injured cortex at 1, 3, 7, 14 and 28 dpi. While GFAP+/BrdU+ astrocytes emerged in peri-injured cortex at 1, 3, 7, 14, 28 dpi and peaked at 7 dpi then kept in a stable state. In the corresponding time point, the percentage of GFAP+/BrdU+ astrocytes in BrdU+ cells was more than that of NPCs or newborn neurons. No CNP+/BrdU+ oligodendrocytes were found in peri-injured cortex. These findings suggest that NPCs from pPV and reactive RG–like cells emerge in peri-injured cortex of adult rats after TBI. It can differentiate into immature neurons and astrocytes, but the former fail to grow up to mature neurons.
PMCID: PMC3726380  PMID: 23922973
2.  A feedback framework for protein inference with peptides identified from tandem mass spectra 
Proteome Science  2012;10:68.
Protein inference is an important computational step in proteomics. There exists a natural nest relationship between protein inference and peptide identification, but these two steps are usually performed separately in existing methods. We believe that both peptide identification and protein inference can be improved by exploring such nest relationship.
In this study, a feedback framework is proposed to process peptide identification reports from search engines, and an iterative method is implemented to exemplify the processing of Sequest peptide identification reports according to the framework. The iterative method is verified on two datasets with known validity of proteins and peptides, and compared with ProteinProphet and PeptideProphet. The results have shown that not only can the iterative method infer more true positive and less false positive proteins than ProteinProphet, but also identify more true positive and less false positive peptides than PeptideProphet.
The proposed iterative method implemented according to the feedback framework can unify and improve the results of peptide identification and protein inference.
PMCID: PMC3776439  PMID: 23164319
3.  Features-Based Deisotoping Method for Tandem Mass Spectra 
Advances in Bioinformatics  2012;2011:210805.
For high-resolution tandem mass spectra, the determination of monoisotopic masses of fragment ions plays a key role in the subsequent peptide and protein identification. In this paper, we present a new algorithm for deisotoping the bottom-up spectra. Isotopic-cluster graphs are constructed to describe the relationship between all possible isotopic clusters. Based on the relationship in isotopic-cluster graphs, each possible isotopic cluster is assessed with a score function, which is built by combining nonintensity and intensity features of fragment ions. The non-intensity features are used to prevent fragment ions with low intensity from being removed. Dynamic programming is adopted to find the highest score path with the most reliable isotopic clusters. The experimental results have shown that the average Mascot scores and F-scores of identified peptides from spectra processed by our deisotoping method are greater than those by YADA and MS-Deconv software.
PMCID: PMC3259476  PMID: 22262971
4.  Peptide charge state determination of tandem mass spectra from low-resolution collision induced dissociation 
Proteome Science  2011;9(Suppl 1):S3.
Charge states of tandem mass spectra from low-resolution collision induced dissociation can not be determined by mass spectrometry. As a result, such spectra with multiple charges are usually searched multiple times by assuming each possible charge state. Not only does this strategy increase the overall database search time, but also yields more false positives. Hence, it is advantageous to determine charge states of such spectra before database search.
We propose a new approach capable of determining the charge states of low-resolution tandem mass spectra. Four novel and discriminant features are introduced to describe tandem mass spectra and used in Gaussian mixture model to distinguish doubly and triply charged peptides. By testing on three independent datasets with known validity, the results have shown that this method can assign charge states to low-resolution tandem mass spectra more accurately than existing methods.
The proposed method can be used to improve the speed and reliability of peptide identification.
PMCID: PMC3289082  PMID: 22166140
5.  A novel approach to denoising ion trap tandem mass spectra 
Proteome Science  2009;7:9.
Mass spectrometers can produce a large number of tandem mass spectra. They are unfortunately noise-contaminated. Noises can affect the quality of tandem mass spectra and thus increase the false positives and false negatives in the peptide identification. Therefore, it is appealing to develop an approach to denoising tandem mass spectra.
We propose a novel approach to denoising tandem mass spectra. The proposed approach consists of two modules: spectral peak intensity adjustment and intensity local maximum extraction. In the spectral peak intensity adjustment module, we introduce five features to describe the quality of each peak. Based on these features, a score is calculated for each peak and is used to adjust its intensity. As a result, the intensity will be adjusted to a local maximum if a peak is a signal peak, and it will be decreased if the peak is a noisy one. The second module uses a morphological reconstruction filter to remove the peaks whose intensities are not the local maxima of the spectrum. Experiments have been conducted on two ion trap tandem mass spectral datasets: ISB and TOV. Experimental results show that our algorithm can remove about 69% of the peaks of a spectrum. At the same time, the number of spectra that can be identified by Mascot algorithm increases by 31.23% and 14.12% for the two tandem mass spectra datasets, respectively.
The proposed denoising algorithm can be integrated into current popular peptide identification algorithms such as Mascot to improve the reliability of assigning peptides to spectra.
Availability of the software
The software created from this work is available upon request.
PMCID: PMC2670284  PMID: 19292921

Results 1-5 (5)