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Liang Ji

Publications and source records attributed to Liang Ji.

13 recordsLinked to original sources

Automated neurite labeling and analysis in fluorescence microscopy images.

BACKGROUND: To investigate the intricate nervous processes involved in many biological activities by computerized image analysis, accurate and reproducible labeling and measurement of neurites are prerequisite. We have developed an automated neurite analysis method to assist this task. METHODS: Our approach can be considered as automated with certain user interaction in setting initial parameters. Single and connected centerlines along neurites are extracted. The computerized method can also generate branching and end points. Owing to its multi-scale flexibility, both thick and thin neurites are simultaneously detected. RESULTS: We employ the relative neurite length difference (defined as the difference between the lengths obtained by automated and manual analysis divided by the total length of the latter) and neurite centerline deviation (defined as the area of the regions enclosed by different paths between automated and manual analysis divided by the total length of the former) to evaluate the performance of our algorithm, which is of great interest in neurite analysis. The average of the relative length difference is about 0.02, while the average of the centerline deviation is about 2.8 pixels. The probabilities of the distributions being the same from the Kolmogorov-Smirnov (KS) test of the automatic and manual results are 99.79%. The KS test also shows no significant bias between different observers based on the proposed new validation scheme. CONCLUSIONS: With the accurate and automated extraction of neurite centerlines and measurement of neurite lengths, the proposed method, which greatly reduces human labor and improves efficiency, can serve as a candidate tool for large-scale neurite analysis beyond the capability of manual tracing methods.

Algorithms↗

[An association study between paranoid schizophrenia and four genes involved in dopamine metabolism].

Schizophrenia is a complex disease caused by interactions among multiple genes. Reports of one of its susceptibility genes, ethyltracatechol-O-mnsferase (COMT) have been conflicting. In the present study on paranoid schizophrenia, we have performed a multilocus association study to analyze the interactions among 4 genes that are involved in dopamine metabolism. Result supports the hypothesis that COMT-136-BclI regulates Val108/158Met. When the genotype of the former is CC, Met (A) is the genotype of susceptibility allele Val108/158Met; and when the genotype of the former is GG, Val (G) is the genotype of susceptibility allele Val108/158Met. This new hypothesis may explain the conflicting results about Val108/158Met (COMT) obtained by single-locus analyses. It also illustrates that multilocus analysis is necessary for the research of complex diseases.

Adult↗

Detection of chromosomal alterations in bladder transitional cell carcinomas from Northern China by comparative genomic hybridization.

To identify chromosome alterations in Chinese bladder cancer, forty-six transitional cell carcinomas of the bladder were analyzed by comparative genomic hybridization. Frequent gains of DNA copy number were observed on 1p (13/46), 1q (13/46), 5p (8/46), 6p (9/46), 7p (7/46), 8q (12/46), 11q (8/46), 17q (11/46), 19q (7/46), 20q (8/46) and Yq (8/46), with minimal overlapping regions at 1p32-pter (10/46), 1q21-q24 (12/46), 5p (8/46), 6p22-p23 (7/46), 7p11.2-p14 (7/46), 8q22-q24 (12/46), 11q13-q14 (8/46), 17q22-qter (11/46), 19q11-13.2 (7/46), 20q11-q13.2 (8/46) and Yq11 (8/46). Losses were predominantly found on 2q (16/46), 5q (8/46), 8p (7/46), 9p (8/46), 9q (13/46), 11p (7/46), 13q (7/46), 17p (12/46), 18q (7/46), Xp (18/46) and Xq (19/46), with smallest overlapping regions at 2q32-qter (16/46), 5q12-q31 (8/46), 8p12-pter (7/46), 9p21-pter (10/46), 9q (13/46), 11p (7/46), 13q13-q22 (7/46), 17p (12/46), 18q21-qter (7/46), Xp (18/46) and Xq (19/46). There were significantly higher frequencies of gains of 1q21-q24 and 17q22-qter in moderately differentiated tumors as compared with those in well-differentiated tumors, indicating a possible association of these two abnormalities with the dedifferentiation of tumor cells. Gains of 1p32-pter, 5p, 6p22-p23, 11q13-q14, 17q22-qter and losses of 2q32-qter, 9q, 17p were more frequent in pT1 as compared with those in pTa carcinomas. Gains at 1q21-q24, 7p11.2-p14, 8q22-q24, 19q, 20q11-q13.2 and losses at 5q12-q31, 8p12-pter, 9p21-pter, 11p, 13q13-q22 and 18q21-qter were unique to pT1 and higher stage tumors, suggesting that genes responsible for the invasion and progression of bladder cancer might be located at these chromosomal regions. In multiple tumors from the same patients, consistent alterations such as gains of 8q, 11q13-q14, 12q13-q15, 13q12, 20q and losses of 2q32-qter, 8p, 9, 11p, 11q21-qter, 13q13-qter, X were detected. These abnormalities were possibly earlier events, which might play a critical role during the genesis of the tumors. Further detailed studies to the recurrent aberration regions may lead to the identification of oncogenes and tumor suppressor genes involved in the development and progression of Chinese bladder cancer.

Adult↗

Classifying G-protein coupled receptors with bagging classification tree.

G-protein coupled receptors (GPCRs) play a key role in different biological processes, such as regulation of growth, death and metabolism of cells. They are major therapeutic targets of numerous prescribed drugs. However, the ligand specificity of many receptors is unknown and there is little structural information available. Bioinformatics may offer one approach to bridge the gap between sequence data and functional knowledge of a receptor. In this paper, we use a bagging classification tree algorithm to predict the type of the receptor based on its amino acid composition. The prediction is performed for GPCR at the sub-family and sub-sub-family level. In a cross-validation test, we achieved an overall predictive accuracy of 91.1% for GPCR sub-family classification, and 82.4% for sub-sub-family classification. These results demonstrate the applicability of this relative simple method and its potential for improving prediction accuracy.

Algorithms↗

Lead adsorption capacities of different components in natural surface coatings.

Pb adsorption capacities of Fe oxide, Mn oxide and organic materials in natural surface coatings( biofilms and associated minerals) collected in three lakes, two ponds and a river in Jilin Province, China and Cayuga Lake in US were studied. A novel extraction technique was employed to remove one or more component(s) from the surface coatings. Pb adsorption to surface coatings before and after extraction was performed to determine the adsorptive properties of the extracted component(s). The statistical analysis of observed Pb adsorption was carried out using nonlinear least squares fitting(NLSF) to estimate the Pb adsorption capacity of each component of surface coatings. For each body of water, the estimated Pb adsorption capacity of Mn oxide(mol Pb/mol Mn) was significantly higher than that of Fe oxide(mol Pb/ mol Fe). The value of estimated adsorption capacities of organic materials with the unit mol Pb per kg COD was similar to or less than that of Fe oxides with the unit mol Pb per mol Fe. Comparison of components of surface coatings in different waters showed that the estimated Pb adsorption capacities of components in surface coatings developed in different natural waters were different, especially for Mn oxides.

Adsorption↗

Systematically experimental investigation on carcinogenesis or tumorigenicity of VERO cell lines of different karyotypes in nude mice in vivo used for viral vaccine manufacture.

Many cell lines used for vaccine production have a potentially strong tumorigenic character. Some of those routinely used need to be checked at different passage numbers for this characteristic. Using HeLa cell cultures as positive controls, and primary canine kidney cell (CKC) or feline kidney cell (FKC) cultures purified in vitro on passage three as negative controls, the tumorigenicity of VERO cell sublines was tested in 219 nude mice. The master cell stocks (MCS) and working cell banks (WCB) of eight strains of VERO African green monkey kidney cell (AGMKC) line used for canine, feline and mink vaccine preparation were established in China. The hypo-tetra-ploid JA or hyper-diploid KA strain of VERO line was highly tumorigenic. These data showed a variable chromosome karyotype of VERO line, and contraindicated the use of JA or KA strain of VERO line for the preparation of attenuated viral vaccines. JA or KA strain of VERO line could be a substitute for HeLa line as a positive-control malignant tumor (MT) cell model. The non-carcinogenic YB, JC, M and JB strains of VERO line were therefore selected for the preparation of modified live rabies viral vaccine in place of BHK-21. The cell sub-lines are comparatively stable in terms of their heritable characters, and show little significant changes between passages. In summary, we have found that: 1) the tumorigenicity of cell line is different among different-karyotypic cells; 2) it is the genetic characteristics of chromosomes of cell lines that determines their tumorigenicity, but with species-specific carcinogenicity; 3) the chromosome number variation of cell lines has positive relationship with their carcinogenesis; 4) highly variable strains of tumor cell line can be selected quickly and successfully in nude mice by alternate cultivation in vitro and in vivo. Malignant rhabdoid tumor (MRT) was evolved in nude mice inoculated with violently variable HeLa or VERO cells. The importance of assessing the tumorigenicity in cell sublines used for vaccine production is emphasised.

Animals↗

[Analysis, identification and correction of some errors of model refseqs appeared in NCBI Human Gene Database by in silico cloning and experimental verification of novel human genes].

We found that human genome coding regions annotated by computers have different kinds of many errors in public domain through homologous BLAST of our cloned genes in non-redundant (nr) database, including insertions, deletions or mutations of one base pair or a segment in sequences at the cDNA level, or different permutation and combination of these errors. Basically, we use the three means for validating and identifying some errors of the model genes appeared in NCBI GENOME ANNOTATION PROJECT REFSEQS: (I) Evaluating the support degree of human EST clustering and draft human genome BLAST. (2) Preparation of chromosomal mapping of our verified genes and analysis of genomic organization of the genes. All of the exon/intron boundaries should be consistent with the GT/AG rule, and consensuses surrounding the splice boundaries should be found as well. (3) Experimental verification by RT-PCR of the in silico cloning genes and further by cDNA sequencing. And then we use the three means as reference: (1) Web searching or in silico cloning of the genes of different species, especially mouse and rat homologous genes, and thus judging the gene existence by ontology. (2) By using the released genes in public domain as standard, which should be highly homologous to our verified genes, especially the released human genes appeared in NCBI GENOME ANNOTATION PROJECT REFSEQS, we try to clone each a highly homologous complete gene similar to the released genes in public domain according to the strategy we developed in this paper. If we can not get it, our verified gene may be correct and the released gene in public domain may be wrong. (3) To find more evidence, we verified our cloned genes by RT-PCR or hybrid technique. Here we list some errors we found from NCBI GENOME ANNOTATION PROJECT REFSEQs: (1) Insert a base in the ORF by mistake which causes the frame shift of the coding amino acid. In detail, abase in the ORF of a gene is a redundant insertion, which causes a reading frame shift in the translation of an alternative protein, such as LOC124919 is wrong form of C17 orf32 (with mouse and rat orthologs determined by us). (2) Put together by mistake (with force). This is a wrong assembly of non-relating cDNA segment, such as LOC147007 is wrong form of C17orf32. (3) Mistakenly insert a base or one section of cDNA in the ORF which causes it ending beforehand, only coding cDNA sequence of N-terminal amino acids, incomplete. For example, LOC123722 is wrong form of SPRYD1, and even the human hypothetical gene LOC126250 or PDCD5 is wrong form of our PDCD5 (TFAR19). (4) Incomplete, only coding cDNA sequence of C-terminal amino acids. For example, human LOC149076 and mouse LOC230761 are wrong form of our verified human ZNF362 and mouse Zfp362, respectively. (5) Incomplete, only coding one section of coding protein cDNA sequence of correct gene ORF, lacking N-terminal and C-terminal amino acids sequence, and at the same time, mistakenly anticipates the first non-initiation codon amino acid of the incomplete protein amino acid as the initiation codon, e.g. anticipating L as M. For example, LOC200084 is wrong form of ZNF362. (6) Mistakenly insert a base or one section of cDNA in the ORF, wrongly causing unwanted termination codon before the insertion, so the coding protein lacks the first part of the amino acids. For example, the GenBank Acc. No. AL096883 ( LOCUS No. HS323M22B) is wrong form of an experimentally verified human NM_012263 with mouse ortholog of BC010510 determined. (7) It may regard the polluted genomic sequence as complete gene cDNA sequence and anticipate the so-called single exon gene, even the real one, only a small ORF in the very long single exon mRNA, while there really exists termination code in the same phase of the upper part of the ORF initiation code, no other characters accord with the gene's condition. For example, LOC91126 is wrong form of ZNF362. (8) The anticipated genes only have ORF which has no EST proofs on both terminal sides. Depending on this ORF, a complete gene cDNA with double support of EST and human genome (there are termination codes at the same phase of the upper part of ORF) which indicates the anticipated ORF reference sequence may be incorrect. For example, LOC164395 may be wrong form of novel human gene bankit4590055. (9) A similar but smaller protein-coding gene is anticipated in the range of the human genome sequence that has the support of EST experimental proof, so other new anticipated gene may be incorrect. For example, LOC167563 may be wrong form of CMYA5. However,these errors can be corrected or avoided by using our strategy. Here we give one example in detail: Comparision of the sequence SPRYD1 with human hypothetical gene LOC123722. The TAA bases in the position of 478-480 in LOC123722 cDNA is redundant, which causes a reading frame shift in the translation of an alternative protein. The redundancy of GTAAA of LOC123722 is not supported by our experimental clone,and is almost fully rejected by human EST alignment, and is shown as the next intron sequence by genomic GT/AG organization analysis. The verification of cDNA or genomic DNA sequence of SPRYD1 implies that LOC123722 has a wrong stop codon within its ORF because of the prediction program, thus being not complete cds. To sum up, by combining bioinformatics analyses with experimental verification, we have found that there are many errors of at least nine kinds appeared in NCBI GENOME ANNOTATION PROJECT REFSEQs through BLAST of our cloned genes in non-redundant database, and our strategy is helpful in correcting them, such as LOC14907, LOC200084 and LOC91126 (all of them should be ZNF362, but are three different kinds of wrong forms of ZNF362), three model reference sequences predicted from NCBI contig NT_004511 by automated computational analysis using gene prediction method, or such as LOC124919 and LOC147007 (both should be C17orf32, but are two different kinds of wrong forms of C17orf32), two model reference sequences predicted from NCBI contig NT_010808 by automated computational analysis using gene prediction method. Therefore, the correct identification and annotation of novel human genes may be still a heavy task, which can be finished within a long period of time. So human genome coding regions annotated by computer should be used with caution. The articles published in the past did not clearly point out the existence of mistakes in the NCBI human gene mode reference sequence. At the Seventh International Human Genome Conference held in April 2002, we first published the researching result on this aspect in the communication form of Posterly insert a base or one section of cDNA in the ORF, wrongly causing unwanted termination codon before the insertion, so the coding protein lacks the first part of the amino acids. For example, the GenBank Acc. No. AL096883 ( LOCUS No. HS323M22B) is wrong form of an experimentally verified human NM_012263 with mouse ortholog of BC010510 determined. (7) It may regard the polluted genomic sequence as complete gene cDNA sequence and anticipate the so-called single exon gene, even the real one, only a small ORF in the very long single exon mRNA, while there really exists termination code in the same phase of the upper part of the ORF initiation code, no other characters accord with the gene's condition. For example, LOC91126 is wrong form of ZNF362. (8) The anticipated genes only have ORF which has no EST proofs on both terminal sides. Depending on this ORF, a complete gene cDNA with double support of EST and human genome (there are termination codes at the same phase of the upper part of ORF) which indicates the anticipated ORF reference sequence may be incorrect. For example, LOC164395 may be wrong form of novel human gene bankit4590055. (9) A similar but smaller protein-coding gene is anticipated in the range of the human genome sequence that has the support of EST experimental proof, so other new anticipated gene may be incorrect. For example, LOC167563 may be wrong form of CMYA5. However, these errors can be corrected or avoided by using our strategy. Here we give one example in detail: Comparision of the sequence SPRYD1 with human hypothetical gene LOC123722. The TAA bases in the position of 478-480 in LOC123722 cDNA is redundant, which causes a reading frame shift in the translation of an alternative protein. The redundancy of GTAAA of LOC123722 is not supported by our experimental clone, and is almost fully rejected by human EST alignment, and is shown as the next intron sequence by genomic GT/AG organization analysis. The verification of cDNA or genomic DNA sequence of SPRYD1 implies that LOC123722 has a wrong stop codon within its ORF because of the prediction program, thus being not complete cds. To sum up, by combining bioinformatics analyses with experimental verification, we have found that there are many errors of at least nine kinds appeared in NCBI GENOME ANNOTATION PROJECT REFSEQs through BLAST of our cloned genes in non-redundant database, and our strategy is helpful in correcting them, such as LOC14907, LOC200084 and LOC91126 (all of them should be ZNF362, but are three different kinds of wrong forms of ZNF362), three model reference sequences predicted from NCBI contig NT_004511 by automated computational analysis using gene prediction method, or such as LOC124919 and LOC147007 (both should be C17orf32, but are two different kinds of wrong forms of C17orf32), two model reference sequences predicted from NCBI contig NT_010808 by automated computational analysis using gene prediction method. Therefore, the correct identification and annotation of novel human genes may be still a heavy task, which can be finished within a long period of time. So human genome coding regions annotated by computer should be used with caution. (ABSTRACT TRUNCATED)

Amino Acid Sequence↗

[Correction of five different types of errors of model REFSEQs appeared in NCBI human gene database only by using two novel human genes C17orf32 and ZNF362].

Found that there exist many mistakes in the REFSEQ issued in the genome annotation project of NCBI, the result of which indicates that people be cautious in using REFSEQ database in NCBI. By adopting the technical route combining bioinformatics analysis and experimental verification, through the comparison of the cloned genes in the non-redundant database, we found that there were many mistakes in the computer annotation human genome coding sequences that were issued on the internet. First we quoted nine wrong types of novel human genes anticipated by NCBI GENOME Annotation Project. Here we give one example in detail: (1) Comparison of the sequences between novel human gene C17orf32 and hypothetical human gene LOC124919. LOC123722 is a modified sequence of C17orf32 cDNA with an inserted G between 406 -407 nucleotides. The base G in the 401 position of LOC123722 cDNA is a redundant insert, which causes a reading frame shift in the translation of an alternative protein. This inserted G has not been found in our experimental clone, and is fully rejected by human EST alignment, and is shown as a redundance by genomic GT/AG organization analysis. (2) Comparison of the sequences between novel human gene C17orf32 and hypothetical human gene LOC147007. C17orf32 gene (ORF from 31 to 657 nucleotides) is located on human chromosome 17(Accession No. NT_010808.7), and is only linked with a hypothetical human gene LOC147007 (ORF from 55 to 435 nucleotides) at present. This hypothetical human gene sequence has not been verified by experiment, and is a wrong form of our verified C17orf32 gene. The full-length 1 679 bp cDNA sequence of C17orf32 exhibits overall homology to that of LOC147007 of 625 bp mRNA, with matching percentage of 37% in 36% of total window over the full-length nucleotide, especially 121 approximately 366 bp of LOC147007 is just the same as 316 approximately 561 bp of C17orf32. Thus, the 126 aa protein encoded by XP_097165 of LOC147007 exhibits overall homology to the 208 aa protein encoded by C17orf32, with matching percentage of 50% in 48% of total window over the full-length protein, especially 23 approximately 104 aa of XP_097165 is just the same as 96 approximately 177 aa of C17orf32 protein. Both flanking regions of LOC147007 outside the same ORF central part are wrong assembly of non-relative cDNA. In addition, we have in silico cloned a novel mouse gene, ORF32 (open reading frame 32) with TPA accession number of BK000258, which is the mouse ortholog of human C17orf32. Our strategy is helpful in both finding out more novel human genes and correcting the mistakes in the REFSEQs issued by NCBI genome annnotation project. For example, we adopted the gene anticipating method, through automatic calculation and analysis, anticipated two modes reference sequences (LOC124919 and LOC147007) from NCBI contig NT_ 010808. Both of them should be C17orf32, but the fact is that both of them are various wrong forms of C17orf32, respectively are the first type and second type of mistakes. Another example, we adopted gene anticipation method, through automatic calculation and analysis, anticipated three modes reference sequences (LOC14907, LOC200084 and LOC91126) from NCBI contig NT_004511 which really are one type of gene of ZNF362, but submitted three different wrong forms of ZNF362, respectively are: the fourth, fifth, and seventh type of mistakes. We can correct or avoid the currently wrong human genome coding sequence by using in silico clone and combining experimental verification. People should be cautious in treating the computer's annotation which may exist all type of wrong human genome coding sequences. The correct identification and annotation of the novel human genes still remain to be a long and arduous task.

Amino Acid Sequence↗

Reconstruction of deforming aortas in two-photon autofluorescence image sequences.

Information loss may occur frequently in the imaging of living tissues by using two-photon fluorescence microscopy due to the intensive deformation of the tissue. A landmark-based optical flow interpolation scheme is proposed for image reconstruction of living aorta walls in two-photon autofluorescence image sequences. Landmarks are extracted and evaluated by an active contour-based aorta model, and are aligned and reconstructed by use of a hierarchical algorithm. The accuracy of the calculation of optical flow is improved by applying landmark-based image warping. Experimental results show that the proposed scheme outperforms commonly used optical flow interpolation techniques for the reconstruction of intensively deforming tissues.

Aorta↗

Cytogenetic studies of esophageal squamous cell carcinomas in the northern Chinese population by comparative genomic hybridization.

Esophageal cancer is the fourth most prevalent malignancy in China. So far, the genetic events involved in esophageal cancer remain largely unknown. To identify chromosomal alterations in this disease, comparative genomic hybridization was performed on 25 primary tumors of esophageal squamous cell carcinomas. Results exhibited nonrandom copy number changes in chromosome DNA, with higher incidence in gain than in loss. The average gains and losses per patient were 7.76 and 4, respectively. The most common gains were 3q (20/25), 1q (15/25), 8q (15/25), 20p (12/25), 20q (11/25), 5p (10/25), 15q (8/25), and 9q (8/25) with two minimal amplification loci mapped to chromosomal regions of 8q24 (2 cases) and 11q13 (7 cases). High-level amplification was observed at 3q (8 cases), 5p (4 cases), and 8q (4 cases). Losses at 3p (10/25), 13q (8/25), 18q (7/25), Xp (7/25), 4 (6/25), 9p (6/25), 14q (6/25), 18p (6/25), and 21q (6/25) were identified. Remarkably, ten cases showed both loss of the entire 3p and overrepresentation of almost the whole 3q. No significant differences in stage or grade of tumor were found for DNA copy number changes. The results provided candidate regions for potential oncogenes and tumor suppressor genes related to Chinese esophageal cancer, to which further molecular studies should be addressed.

Asian People↗

Karyotyping of comparative genomic hybridization human metaphases using kernel nearest-neighbor algorithm.

BACKGROUND: Comparative genomic hybridization (CGH) is a relatively new molecular cytogenetic method that detects chromosomal imbalances. Automatic karyotyping is an important step in CGH analysis because the precise position of the chromosome abnormality must be located and manual karyotyping is tedious and time-consuming. In the past, computer-aided karyotyping was done by using the 4',6-diamidino-2-phenylindole, dihydrochloride (DAPI)-inverse images, which required complex image enhancement procedures. METHODS: An innovative method, kernel nearest-neighbor (K-NN) algorithm, is proposed to accomplish automatic karyotyping. The algorithm is an application of the "kernel approach," which offers an alternative solution to linear learning machines by mapping data into a high dimensional feature space. By implicitly calculating Euclidean or Mahalanobis distance in a high dimensional image feature space, two kinds of K-NN algorithms are obtained. New feature extraction methods concerning multicolor information in CGH images are used for the first time. RESULTS: Experiment results show that the feature extraction method of using multicolor information in CGH images improves greatly the classification success rate. A high success rate of about 91.5% has been achieved, which shows that the K-NN classifier efficiently accomplishes automatic chromosome classification from relatively few samples. CONCLUSIONS: The feature extraction method proposed here and K-NN classifiers offer a promising computerized intelligent system for automatic karyotyping of CGH human chromosomes.

Algorithms↗

Karyotyping of comparative genomic hybridization human metaphases by using support vector machines.

BACKGROUND: Comparative genomic hybridization (CGH) is a relatively new molecular cytogenetic method for detecting chromosomal imbalance. Karyotyping of human metaphases is an important step to assign each chromosome to one of 23 or 24 classes (22 autosomes and two sex chromosomes). Automatic karyotyping in CGH analysis is needed. However, conventional karyotyping approaches based on DAPI images require complex image enhancement procedures. METHODS: This paper proposes a simple feature extraction method, one that generates density profiles from original true color CGH images and uses normalized profiles as feature vectors without quantization. A classifier is developed by using support vector machine (SVM). It has good generalization ability and needs only limited training samples. RESULTS: Experiment results show that the feature extraction method of using color information in CGH images can improve greatly the classification success rate. The SVM classifier is able to acquire knowledge about human chromosomes from relatively few samples and has good generalization ability. A success rate of moe than 90% has been achieved and the time for training and testing is very short. CONCLUSIONS: The feature extraction method proposed here and the SVM-based classifier offer a promising computerized intelligent system for automatic karyotyping of CGH human chromosomes.

Chromosomes, Human↗

Tracking deforming aortas in two-photon autofluorescence images and its application on quantitative evaluation of aorta-related drugs.

This paper describes a novel approach to an objective measurement of aorta samples of rats and a quantitative evaluation of aorta-related drugs. Two-photon fluorescence microscopy is used for recording image sequences of deforming aorta. Time sequence snake models are used to track the structural deformations of aorta walls caused by drug stimulation of the elastic lamina in the aorta. Several objective and quantitative biomarkers extracted from these models are used as diagnostic indicators. In a preliminary study, the technique was successfully used for evaluating the effect of a newly developed drug-human erythrocyte-derived depressing factor quantitatively and objectively.

Animals↗