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Biomedical subjects

M C Liu

Publications and source records attributed to M C Liu.

At least 19 recordsLinked to original sources
PubMed2006

Quantitative structure-toxicity relationships (QSTRs): a comparative study of various non linear methods. General regression neural network, radial basis function neural network and support vector machine in predicting toxicity of nitro- and cyano- aromatics to Tetrahymena pyriformis.

Prediction of toxicity of 203 nitro- and cyano-aromatic chemicals to Tetrahymena pyriformis was carried out by radial basis function neural network, general regression neural network and support vector machine, in non-linear response surface methodology. Toxicity was predicted from hydrophobicity parameter (log Kow) and maximum superdelocalizability (Amax). Special attention was drawn to prediction ability and robustness of the models, investigated both in a leave-one-out and 10-fold cross validation (CV) processes. The influence that the corresponding changes in the learning sets during these CV processes could have on a common external test set including 41 compounds was also examined. This allowed us to establish the stability of the models. The non linear results slightly outperform (as expected) multilinear relationships (MLR) and also favourably compete with various other non linear approaches recently proposed by Ren (J. Chem. Inf. Comput. Sci., 43 1679 (2003)).

Animals↗
PubMed2006

Spinal cord compression and dorsal root injury cause up-regulation of activating transcription factor-3 in large-diameter dorsal root ganglion neurons.

Spinal cord injury causes damage to ascending and descending tracts, as well as to local circuits, but relatively little is known about the effect of such injury on sensory neurons located within adjoining ganglia. We have therefore used immunocytochemistry for activating transcription factor-3 (ATF3), a sensitive marker of axonal damage, in order to examine the effects of spinal cord injury in rats on dorsal root ganglion (DRG) neurons. A 50-g static compression injury applied to the dorsal surface of the T12 thoracic spinal cord led to an up-regulation of ATF3 that was maximal at 1 day and affected 12-14% of DRG neurons in ganglia caudal to the injury (T13-L3). A similar response was seen after a T12 hemisection that transected the dorsal columns except that compression injury, but not hemisection, also evoked ATF3 expression in ganglia just rostral to the injury (T10, T11). ATF3 was up-regulated exclusively in DRG neurons that were of large diameter and immunoreactive for heavy neurofilament. Small-diameter cells, including the population that binds the lectin Grifffonia simplicifolia IB4, did not express ATF3 immunoreactivity. A similar pattern of ATF3 expression was induced by dorsal rhizotomy. The data show for the first time that ATF3 is up-regulated after spinal cord and dorsal root injury, but that this up-regulation is confined to the large-diameter cell population.

Activating Transcription Factor 3↗
PubMed2005

Prediction of the tissue/blood partition coefficients of organic compounds based on the molecular structure using least-squares support vector machines.

The accurate nonlinear model for predicting the tissue/blood partition coefficients (PC) of organic compounds in different tissues was firstly developed based on least-squares support vector machines (LS-SVM), as a novel machine learning technique, by using the compounds' molecular descriptors calculated from the structure alone and the composition features of tissues. The heuristic method (HM) was used to select the appropriate molecular descriptors and build the linear model. The prediction result of the LS-SVM model is much better than that obtained by HM method and the prediction values of tissue/blood partition coefficients based on the LS-SVM model are in good agreement with the experimental values, which proved that nonlinear model can simulate the relationship between the structural descriptors, the tissue composition and the tissue/blood partition coefficients more accurately as well as LS-SVM was a powerful and promising tool in the prediction of the tissue/blood partition behaviour of compounds. Furthermore, this paper provided a new and effective method for predicting the tissue/blood partition behaviour of the compounds in the different tissues from their structures and gave some insight into structural features related to the partition process of the organic compounds in different tissues.

Least-Squares Analysis↗
PubMed2005

Application of support vector machine (SVM) for prediction toxic activity of different data sets.

As a new method, support vector machine (SVM) were applied for prediction of toxicity of different data sets compared with other two common methods, multiple linear regression (MLR) and RBFNN. Quantitative structure-activity relationships (QSAR) models based on calculated molecular descriptors have been clearly established. Among them, SVM model gave the highest q(2) and correlation coefficient R. It indicates that the SVM performed better generalization ability than the MLR and RBFNN methods, especially in the test set and the whole data set. This eventually leads to better generalization than neural networks, which implement the empirical risk minimization principle and may not converge to global solutions. We would expect SVM method as a powerful tool for the prediction of molecular properties.

Algorithms↗
PubMed2005

Study of probabilistic neural networks to classify the active compounds in medicinal plants.

Probabilistic neural networks (PNNs) were utilized for the classifications of 102 active compounds from diverse medicinal plants with anticancer activity against human rhinopharyngocele cell line KB. Molecular descriptors calculated from structure alone were used to represent molecular structures. A subset of the calculated descriptors selected using factor correlation analysis and forward stepwise regression was used to construct the prediction models. Linear discriminant analysis (LDA) was also utilized to construct the classification model to compare the results with those obtained by PNNs. The accuracy of the training set, the cross-validation set, and the test set given by PNNs and LDA were 100, 92.3, 90.9% and 71.8, 92.3, 54.5%, respectively, which indicated that the results obtained by PNNs agree well with the experimental values of these compounds and also revealed the superiority of PNNs over LDA approach for the classification of anticancer activities of compounds. The models built in this work would be of potential help in the design of novel and more potent anticancer agents.

Algorithms↗
PubMed2005

The prediction of human oral absorption for diffusion rate-limited drugs based on heuristic method and support vector machine.

Support vector machine (SVM), as a novel machine learning technique, was used for the prediction of the human oral absorption for a large and diverse data set using the five descriptors calculated from the molecular structure alone. The molecular descriptors were selected by heuristic method (HM) implemented in CODESSA. At the same time, in order to show the influence of different molecular descriptors on absorption and to well understand the absorption mechanism, HM was used to build several multivariable linear models using different numbers of molecular descriptors. Both the linear and non-linear model can give satisfactory prediction results: the square of correlation coefficient R(2) was 0.78 and 0.86 for the training set, and 0.70 and 0.73 for the test set respectively. In addition, this paper provides a new and effective method for predicting the absorption of the drugs from their structures and gives some insight into structural features related to the absorption of the drugs.

Administration, Oral↗
PubMed2005

QSAR study of natural, synthetic and environmental endocrine disrupting compounds for binding to the androgen receptor.

A large data set of 146 natural, synthetic and environmental chemicals belonging to a broad range of structural classes have been tested for their relative binding affinity (expressed as log (RBA)) to the androgen receptor (AR). These chemicals commonly termed endocrine disrupting compounds (EDCs) present a variety of adverse effects in humans and animals. As assays for binding affinity remains a time-consuming task, it is important to develop predictive methods. In this work, quantitative structure-activity relationships (QSARs) were determined using three methods, multiple linear regression (MLR), radical basis function neural network (RBFNN) and support vector machine (SVM). Five descriptors, accounting for hydrogen-bonding interaction, distribution of atomic charges and molecular branching degree, were selected from a heuristic method to build predictive QSAR models. Comparison of the results obtained from three models showed that the SVM method exhibited the best overall performances, with a RMS error of 0.54 log (RBA) units for the training set, 0.59 for the test set, and 0.55 for the whole set. Moreover, six linear QSAR models were constructed for some specific families based on their chemical structures. These predictive toxicology models, should be useful to rapidly identify potential androgenic endocrine disrupting compounds.

Algorithms↗
PubMed2004

QSAR and classification models of a novel series of COX-2 selective inhibitors: 1,5-diarylimidazoles based on support vector machines.

The support vector machine, which is a novel algorithm from the machine learning community, was used to develop quantitation and classification models which can be used as a potential screening mechanism for a novel series of COX-2 selective inhibitors. Each compound was represented by calculated structural descriptors that encode constitutional, topological, geometrical, electrostatic, and quantum-chemical features. The heuristic method was then used to search the descriptor space and select the descriptors responsible for activity. Quantitative modelling results in a nonlinear, seven-descriptor model based on SVMs with root mean-square errors of 0.107 and 0.136 for training and prediction sets, respectively. The best classification results are found using SVMs: the accuracy for training and test sets is 91.2% and 88.2%, respectively. This paper proposes a new and effective method for drug design and screening.

Algorithms↗
PubMed2004

3D QSAR studies on antimalarial alkoxylated and hydroxylated chalcones by CoMFA and CoMSIA.

The 3D QSAR analyses of antimalarial alkoxylated and hydroxylated chalcones were first conducted by Comparative molecular field analysis (CoMFA) and Comparative similarity indices analysis (CoMSIA) to determine the factors required for the activity of these compounds. Satisfactory results were obtained after performing a leave-one-out (LOO) cross-validation study with cross-validation q(2) and conventional r(2) values of 0.740 and 0.972 by the CoMFA model, 0.714 and 0.976 by the CoMSIA model, respectively. The results provided the tools for predicting the affinity of related compounds, and for guiding the design and synthesis of novel and more potent antimalarial agents.

Antimalarials↗
PubMed2004

Novel strategies in cancer therapeutics: targeting enzymes involved in cell cycle regulation and cellular proliferation.

Tumor development, growth, and progression depend on some combination of altered cell cycle regulation, excessive growth factor pathway activation, and decreased apoptosis. Understanding the complex molecular mechanisms that underlie these processes should therefore lead to the identification of potential targets for therapeutic intervention. The estrogen receptor and HER-2/neu were among the earliest targets investigated, ultimately leading to the widespread use of tamoxifen and trastuzumab, respectively, in the treatment of breast cancer. Major research advances have since led to other classes of targeted therapies, including cyclin-dependent kinase inhibitors, histone deactylase inhibitors, and receptor tyrosine kinase inhibitors. The following review provides a discussion of the molecular biology associated with each of these types of therapies as well as a detailed summary of the preclinical and clinical data published on selected compounds from each of these subgroups.

Animals↗
PubMed2003

In vitro antiviral activities of Caesalpinia pulcherrima and its related flavonoids.

The aim of this study was to search for new antiviral agents from Chinese herbal medicine. Pure flavonoids and aqueous extracts of Caesalpinia pulcherrima Swartz were used in experiments to test their influence on a series of viruses, namely herpesviruses (HSV-1, HSV-2) and adenoviruses (ADV-3, ADV-8, ADV-11). The EC50 was defined as the concentration required to achieve 50% protection against virus-induced cytopathic effects, and the selectivity index (SI) was determined as the ratio of CC50 (concentration of 50% cellular cytotoxicity) to EC50. Results showed that aqueous extracts of C. pulcherrima and its related quercetin possessed a broad-spectrum antiviral activity. Among them, the strongest activities against ADV-8 were fruit and seed (EC50 = 41.2 mg/l, SI = 83.2), stem and leaf (EC50 = 61.8 mg/l, SI = 52.1) and flower (EC50 = 177.9 mg/l, SI = 15.5), whereas quercetin possessed the strongest anti-ADV-3 activity (EC50 = 24.3 mg/l, SI = 20.4). In conclusion, some compounds of C. pulcherrima which possess antiviral activities may be derived from the flavonoid of quercetin. The mode of action of quercetin against HSV-1 and ADV-3 was found to be at the early stage of multiplication and with SI values greater than 20, suggesting the potential use of this compound for treatment of the infection caused by these two viruses.

Antiviral Agents↗
PubMed2003

Solid-phase microextraction from small volumes of sample in a glass capillary.

A new sampling method is proposed for solid-phase microextraction (SPME), in which the extraction is carried out in a glass capillary containing a few microliters of sample. When an adsorption-type fiber is used for SPME, the equilibrium between aqueous sample and coating can be described by a Langmuir isotherm. Since the total amount of analytes and coexisting substances stays at a low level in a small volume of sample, the linear concentration range of analytes will be extended for SPME to be applied in quantification and the interference caused by sample matrix will be reduced. In addition, sampling in a capillary has a short diffusion distance and extraction equilibrium is established in 5-10 min. It is important in clinical analysis and therapeutic drug monitoring to be able to analyse sample volumes of samples. The feasibility of the new sampling method is demonstrated by the extractions of p-hydroxybenzaldehyde and a synthetic solution containing 1-naphthol, paeonol and 1-naphthylamine.

Chromatography, Gas↗
PubMed2002

Toxicity of different industrial effluents in Taiwan: a comparison of the sensitivity of Daphnia similis and Microtox.

Industrial effluents are known to exhibit toxicity toward different aquatic organisms. In Taiwan management of these discharges still relies on chemical and physical and physical characteristics of water, although various standard method for assessing aquatic toxicity have been proposed by the Taiwan Environmental Protection Administration. In this study we examined the toxicity and compared the sensitivity of different types of industrial effluents using two proposed toxicity tests: the Daphnia similis acute toxicity test and the Microtox acute assay (Vibrio fischeri). Results showed that electroplating effluents were the most toxic of all the effluents tested, followed by acrylonitrile manufacturing, pulp/paper, and tannery effluents. The EC50 of an electroplating effluent for D. similis and V. fischeri (15 min) was as low as, respectively, 2.9% and 3.9% of the whole effluent. The other effluents were not acutely toxic to either organism tested. However, the tests exhibited different sensitivity toward various discharges. Only the electroplating and acrylonitrile manufacturing effluents had effects on both organisms. These results indicate the importance of the incorporation of aquatic toxicity tests into the management scheme for treated wastewaters.

Animals↗
PubMed2001

Effects and mechanisms of aloe-emodin on cell death in human lung squamous cell carcinoma.

Aloe-emodin (1,8-dihydroxy-3-(hydroxymethyl)-anthraquinone) is an active component from the root and rhizome of Rheum palmatum. The study investigated the effects and mechanisms of aloe-emodin-induced cell death in human lung squamous cell carcinoma cell line CH27. Aloe-emodin (40 microM)-induced CH27 cell apoptosis was confirmed by DNA fragmentation (DNA ladders and sub-G(1) formation). Aloe-emodin-induced apoptosis of CH27 cells involved modulation of the expression of Bcl-2 family proteins, such as BclX(L), Bag-1, and Bak, and was associated with the translocation of Bak and Bax from cytosolic to particulate fractions. Aloe-emodin-treated CH27 cells had an increased relative abundance of cytochrome c in the cytosolic fraction. Results demonstrated that the activation of caspase-3, caspase-8, and caspase-9 is an important determinant of apoptotic death induced by aloe-emodin. These results suggest that aloe-emodin induces CH27 cell death by the Bax and Fas death pathway.

Anthraquinones↗
PubMed2001

Results on single cell PCR for Huntington's gene and WAVE product analysis for preimplantation genetic diagnosis.

Triple repeat base pair amplification is the basis for a number of prevalent genetic diseases such as Huntington's, Fragile X, Myotonic Dystrophy and others. We have chosen to investigate the use of PCR to amplify a portion of the Huntington's gene in single cells in order to develop a clinical test system for preimplantation genetic diagnosis (PGD). Amplification of CAG triple repeat sequences poses difficulties due to resistance of GC melting for amplification. Special PCR modifications are necessary to carry out the amplification of GC rich areas found in most triple base pair expansions. We have used a modified polymerase chain reaction (PCR) protocol to amplify the expanded repeat sequence of the Huntington's gene with satisfactory efficiency. Detection of the amplified expanded CAG repeats is shown to be possible using both agarose gel electrophoresis and high definition denaturing high pressure liquid (DHPLC) chromatography. The incidence of allele dropout (ADO) is documented.

Cells, Cultured↗
PubMed2001

Identification of a novel cytokine, ML-1, and its expression in subjects with asthma.

A novel gene, designated ML-1, was identified from a human genomic DNA clone and human T cell cDNA sequences. The second exon of ML-1 gene shares significant sequence identity with the gene encoding IL-17 (IL-17). ML-1 gene expression was up-regulated in activated PBMCs, CD4(+) T cells, allergen-specific Th0, Th1, and Th2 clones, activated basophils, and mast cells. Increased expression of the ML-1 gene, but not IL-17, was seen following allergen challenge in four asthmatic subjects, suggesting its role in allergic inflammatory responses. ML-1 from transiently transfected COS-7 cells was able to induce gene expression and protein production for IL-6 and IL-8 (at 10 ng/ml of ML-1: for IL-6, 599.6 +/- 19.1 pg/ml; for IL-8, 1724.2 +/- 132.9 pg/ml; and at 100 ng/ml of ML-1: for IL-6, 1005.3 +/- 55.6 pg/ml; for IL-8, 4371.4 +/- 280.5 pg/ml; p < 0.05 for both doses vs baseline) in primary bronchial epithelial (PBE) cells. Furthermore, increased expression of ICAM-1 was found in ML-1-stimulated PBE cells (mean fluorescence intensity (MFI) = 31.42 +/- 4.39 vs baseline, MFI = 12.26 +/- 1.77, p < 0.05), a functional feature distinct from IL-17 (MFI = 11.07 +/- 1.22). This effect was not inhibited by a saturating amount of IL-17. These findings demonstrate that ML-1 is a novel cytokine with a distinct function, and suggest a different receptor for ML-1 on PBE cells.

Amino Acid Sequence↗
PubMed2001

Repetitive ozone exposure of young adults: evidence of persistent small airway dysfunction.

Earlier, we found that acute ozone (O3) exposure caused, along with inflammation, greater, more protracted changes in small airway function (isovolumetric V max at intermediate to low lung volumes) than in FVC or FEV1. To test if this distinction prevailed with repetitive O3 exposure, we exposed eight healthy adults on four consecutive days alternatively to filtered air (FA) and O3 (0.25 ppm x 2 h). Isovolumetric FEF25-75, Vmax50, and Vmax75, were grouped into a single value representing small airway function (SAW(grp)); respiratory frequency (f) and tidal volume (VT) were monitored during exercise. On Day 5, peripheral airway resistance (Rp) was measured followed by lavage. All daily spirometric and ventilatory changes declined in magnitude (adapted) after one or more days of O3 exposure. In addition, SAW(grp), f, and VT showed persistent changes beginning with Day 2, denoted either by depression of the preexposure baseline (SAW(grp)) or exaggerated tachypnea during exercise. O3-induced neutrophilia (p = 0.04) was present in lavage fluid. The possible relationship between these persistent changes in small airway function, measured in days, and the likelihood of cumulative injury in the same region if exposure is long term, is unknown.

Adult↗