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Biomedical subjects

H X Liu

Publications and source records attributed to H X Liu.

At least 55 records · Page 3Linked to original sources
PubMed1992

[Synthesis and radiosensitizing activity of nitro-arylimino-diethyl-sodium thiosulfate and nitro phenylalanine derivatives].

A series of compounds was synthesized, these compounds were tested for Hela-S3 cells in vitro for radiosensitizing activity. Five of them are 2,2'-(arylimino)-diethyl-sodium thiosulfate and two of them are phenylalanine derivatives. Most of them showed various degrees of radiosensitizing activity. Among them, SER of L07 was 1.89 at 3 mmol, and had low cytotoxicity to Hela-S3 cells, ID50 was 18.8 mmol. The relationship between radiosensitizing effects and chemical structure was discussed. It offers a base for further exploration of selectively hypoxic cell radiosensitizers.

HeLa Cells↗
PubMed1991

Recombinant human and rat ciliary neurotrophic factors.

The human ciliary neurotrophic factor (CNTF) gene was identified and cloned, based on homology with the recently cloned rat cDNA. The gene encodes a protein of 200 amino acids, which shares about 80% sequence identity with rat and rabbit CNTF and, like these homologues, lacks an apparent secretion signal sequence. The human CNTF gene, like the rat gene, appears to contain a single intron separating two protein coding exons. An intronless human CNTF gene was constructed by the use of polymerase chain reactions and introduced into vectors designed for expression of foreign proteins in E. coli. The rat CNTF gene was also introduced into similar vectors. Both the human and rat proteins were expressed at exceptionally high levels, at 20-40% and 60-70% of total protein, respectively. Extraction of the recombinant proteins from inclusion bodies by guanidinium chloride, followed by two column chromatography steps, produced high yields of pure CNTF that supported survival and neurite outgrowth from embryonic chick ciliary neurons in culture. The biological activity of both recombinant proteins was comparable to that of native rat CNTF.

Amino Acid Sequence↗
PubMed1991

[Promotion of intestinal drug absorption by milk fat globule membrane].

A soybean oil emulsion was prepared by using milk fat globule membrane (MFGM) materials as an emulsifier. Its stability and effect on the intestinal absorption of vitamin D3, amphotericin B and kanamycin were studied. The MFGM emulsion was as highly stable as a Tween 80 emulsion. When the MFGM emulsion was sonicated with ultrasonic disrupter, the emulsion became more stable. Quantification of vitamin D3 in the intestinal lymph indicated that the MFGM emulsion enhanced lymphatic absorption of vitamin D3. The recovered percentage of vitamin D3 emulsified with MFGM in the lymph was 1.4 times that by Tween 80, and 2.5 times that of oil-in-water suspension. Statistically significant difference was found among them (p less than 0.05). The volumes of an oil phase in the emulsion affected the absorption of vitamin D3. The recovered percentage of vitamin D3 from the lymph increased with reducing the volume of the oil phase. Sonication of the emulsion did not affect the intestinal drug absorption. Furthermore, the MFGM emulsion had no effect on the intestinal absorption of amphotericin B and kanamycin.

Amphotericin B↗
PubMed1991

Compatibility between Oncomelania hupensis and different isolates of Schistosoma japonicum in China.

Oncomelania hupensis from six localities were used for infection with different isolates of Schistosoma japonicum in the mainland of China, ie Anhui in the east, Hubei in the center, Guangxi in the south, Sichuan in the West, Yunnan in the southwest and Fujian in the southeast. Snails from Anhui and Hubei were readily infected with the local isolate of S. japonicum and cross infection also took place readily between the snails and the schistosomes from these two places. Snails from Sichuan and Yunnan were refractory to infection with schistosome isolates from Hubei and Anhui, but the isolates from Sichuan and Yunnan were able to develop in snails from Hubei and Anhui. Though the Guangxi isolate developed readily in both Anhui and Guangxi snails, the average precercarial period in the former was significantly longer than in the latter. None of the other snails from Sichuan, Yunnan and Fujian became infected. On the other hand, snails from Guangxi infected with Anhui parasites also had a longer precercarial period than that in Anhui snails. Snails from Fujian were readily infected with the isolates from Anhui and Yunnan. The present results suggest that there might be different geographic strains of S. japonicum and their Oncomelania snail hosts in the mainland of China.

Animals↗
PubMed1990

[Studies on the strain differences of Schistosoma japonicum in the mainland of China. I. Compatibility between schistosomes and their snail hosts].

Oncomelania hupensis hupensis from six localities were used in this study, i.e. Guichi of Anhui in the east, Jianli of Hubei in the middle, Guiping of Guangxi in the south, Tianquan of Sichuan and Eryuan of Yunnan in the southwest and Fuqing of Fujian in the southeast. Snails from each locality were individually cross-exposed to 20 miracidia of the different isolates of S. japonicum from the above-named places, with the exception of Fujian Province where no snail could be found naturally infected with S. japonicum. The results showed that snails from one locality were readily infected with the local isolate of S. japonicum. Besides, cross infection also took place readily between the snails and the schistosomes from Hubei and Anhui with snail infection rates of 43.8% and 40.9% respectively. Snails from Sichuan and Yunnan were refractory to infection with schistosome isolates from Hubei and Anhui, but the isolate from Sichuan was able to develop in Oncomelania snails from Hubei and Anhui, resulting in infection rates of 10.2% and 4.5% while that from Yunnan, in snails from Hubei and Anhui in infection rates of 33.6% and 10.8% respectively. Though the Guangxi isolate of S. japonicum developed readily in both Anhui (30.7%) and Guangxi snails (9.4%), the average precercarial period was 100.9 days in the former which was significantly longer than 76.9 days in the latter. None of the other snails from Sichuan, Yunnan and Fujian became infected. On the other hand, snails from Guangxi infected with Anhui parasites also had a longer precercarial period of 92.7 days compared with that of 81.6 days in Anhui snail.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗
PubMed1988

Establishment and biological properties of mouse granulocytic leukemic cell line-L833.

A granulocytic leukemic cell line, called L833 has been established through culturing in vitro from mouse bone marrow of transplantable granulocytic leukemia. More than 280 passages have been performed in 3 years. Cell growth has been rapid and stable. Incidence of tumour formation was 100% with various routes of inoculation. The nature of granulocytic leukemia was confirmed by examination of cytology, cytochemistry, pathology and ultrastructural changes. Analysis proved chromosomes to be hypodiploid with model number of 39, loss of chromosomes, and presence of a marker. Besides the chromosomal change as mentioned above, both L883-A and L833-B derived from colonies formed from the L833 cells cultured in semi-solid agar medium, have their own marker. The cell line was sensitive to various types of antitumour agents in varying degrees. It was also sensitive to ionizing radiation. D0 values of L833 and L883-A cells were 98.8 and 104.9 rad, respectively. The results were similar to that of L801. Establishment of this cell line is of important significance for studying leukemia and screening anti-tumour agents, as well as provides a useful direct, economic and precisely quantitative tool for other relative studies.

Animals↗
PubMed1988

[Flow cytometry in analysis of precancerous lesions of the esophagus].

DNA content of the severe dysplasia cells in the esophageal epithelium was quantitatively analysed using flow cytometry and compared with those of the normal, mild dysplasia and cancer cells. The results showed that DNA index of the severe dysplasia cells was 1.27 +/- 0.11 and there was a significant difference between its value and those of the normal (1.0 +/- 0.02), mild dysplasia (1.01 +/- 0.03) and cancer cells (1.73 +/- 0.35). The DNA content of severe dysplasia cells lies between the normal and cancer cells. The hyperplasia degree of the severe dysplasia cells parallels their DNA contents. This study indicates that flow cytometry is a useful supplementary tool for diagnosis of the tumor.

DNA↗
PubMedDate not supplied

Comparison of high performance capillary electrophoresis and liquid chromatography for the determination of acyclovir and guanine in pharmaceuticals and urine.

High-performance capillary electrophoresis (HPCE) and high-performance liquid chromatography (HPLC) were developed and applied to the determination of acyclovir (ACV) and guanine (G) in pharmaceuticals. The comparison study showed that two methods gave comparable results in linear range, recovery and reproducibility. HPCE was used for the determination of ACV and G in urine; the recovery was better than 81.3% and the RSD was less than 4.4%.

Acyclovir↗
PubMedDate not supplied

Diagnosing breast cancer based on support vector machines.

The Support Vector Machine (SVM) classification algorithm, recently developed from the machine learning community, was used to diagnose breast cancer. At the same time, the SVM was compared to several machine learning techniques currently used in this field. The classification task involves predicting the state of diseases, using data obtained from the UCI machine learning repository. SVM outperformed k-means cluster and two artificial neural networks on the whole. It can be concluded that nine samples could be mislabeled from the comparison of several machine learning techniques.

Algorithms↗
PubMedDate not supplied

QSAR study of ethyl 2-[(3-methyl-2,5-dioxo(3-pyrrolinyl))amino]-4-(trifluoromethyl) pyrimidine-5-carboxylate: an inhibitor of AP-1 and NF-kappa B mediated gene expression based on support vector machines.

The support vector machine, as a novel type of learning machine, for the first time, was used to develop a QSAR model of 57 analogues of ethyl 2-[(3-methyl-2,5-dioxo(3-pyrrolinyl))amino]-4-(trifluoromethyl)pyrimidine-5-carboxylate (EPC), an inhibitor of AP-1 and NF-kappa B mediated gene expression, based on calculated quantum chemical parameters. The quantum chemical parameters involved in the model are Kier and Hall index (order3) (KHI3), Information content (order 0) (IC0), YZ Shadow (YZS) and Max partial charge for an N atom (MaxPCN), Min partial charge for an N atom (MinPCN). The mean relative error of the training set, the validation set, and the testing set is 1.35%, 1.52%, and 2.23%, respectively, and the maximum relative error is less than 5.00%.

Carboxylic Acids↗
PubMedDate not supplied

Prediction of the isoelectric point of an amino acid based on GA-PLS and SVMs.

The support vector machine (SVM), as a novel type of a learning machine, for the first time, was used to develop a QSPR model that relates the structures of 35 amino acids to their isoelectric point. Molecular descriptors calculated from the structure alone were used to represent molecular structures. The seven descriptors selected using GA-PLS, which is a sophisticated hybrid approach that combines GA as a powerful optimization method with PLS as a robust statistical method for variable selection, were used as inputs of RBFNNs and SVM to predict the isoelectric point of an amino acid. The optimal QSPR model developed was based on support vector machines, which showed the following results: the root-mean-square error of 0.2383 and the prediction correlation coefficient R=0.9702 were obtained for the whole data set. Satisfactory results indicated that the GA-PLS approach is a very effective method for variable selection, and the support vector machine is a very promising tool for the nonlinear approximation.

Amino Acids↗
PubMedDate not supplied

An accurate QSPR study of O-H bond dissociation energy in substituted phenols based on support vector machines.

The support vector machine (SVM), as a novel type of learning machine, was used to develop a Quantitative Structure-Property Relationship (QSPR) model of the O-H bond dissociation energy (BDE) of 78 substituted phenols. The six descriptors calculated solely from the molecular structures of compounds selected by forward stepwise regression were used as inputs for the SVM model. The root-mean-square (rms) errors in BDE predictions for the training, test, and overall data sets were 3.808, 3.320, and 3.713 BDE units (kJ mol(-1)), respectively. The results obtained by Gaussian-kernel SVM were much better than those obtained by multiple linear regression, radial basis function neural networks, linear-kernel SVM, and other QSPR approaches.

Journal Article↗
PubMedDate not supplied

QSAR models for the prediction of binding affinities to human serum albumin using the heuristic method and a support vector machine.

The binding affinities to human serum albumin for 94 diverse drugs and drug-like compounds were modeled with the descriptors calculated from the molecular structure alone using a quantitative structure-activity relationship (QSAR) technique. The heuristic method (HM) and support vector machine (SVM) were utilized to construct the linear and nonlinear prediction models, leading to a good correlation coefficient (R2) of 0.86 and 0.94 and root-mean-square errors (rms) of 0.212 and 0.134 albumin drug binding affinity units, respectively. Furthermore, the models were evaluated by a 10 compound external test set, yielding R2 of 0.71 and 0.89 and rms error of 0.430 and 0.222. The specific information described by the heuristic linear model could give some insights into the factors that are likely to govern the binding affinity of the compounds and be used as an aid to the drug design process; however, the prediction results of the nonlinear SVM model seem to be better than that of the HM.

Humans↗
PubMedDate not supplied

Diagnosing anorexia based on partial least squares, back propagation neural network, and support vector machines.

Support vector machine (SVM), as a novel type of learning machine, for the first time, was used to develop a predictive model for early diagnosis of anorexia. It was based on the concentration of six elements (Zn, Fe, Mg, Cu, Ca, and Mn) and the age extracted from 90 cases. Compared with the results obtained from two other classifiers, partial least squares (PLS) and back-propagation neural network (BPNN), the SVM method exhibited the best whole performance. The accuracies for the test set by PLS, BPNN, and SVM methods were 52%, 65%, and 87%, respectively. Moreover, the models we proposed could also provide some insight into what factors were related to anorexia.

Anorexia↗
PubMedDate not supplied

Quantitative prediction of logk of peptides in high-performance liquid chromatography based on molecular descriptors by using the heuristic method and support vector machine.

A new method support vector machine (SVM) and the heuristic method (HM) were used to develop the nonlinear and linear models between the capacity factor (logk) and seven molecular descriptors of 75 peptides for the first time. The molecular descriptors representing the structural features of the compounds only included the constitutional and topological descriptors, which can be obtained easily without optimizing the structure of the molecule. The seven molecular descriptors selected by the heuristic method in CODESSA were used as inputs for SVM. The results obtained by SVM were compared with those obtained by the heuristic method. The prediction result of the SVM model is better than that of heuristic method. For the test set, a predictive correlation coefficient R = 0.9801 and root-mean-square error of 0.1523 were obtained. The prediction results are in very good agreement with the experimental values. But the linear model of the heuristic method is easier to understand and ready to use for a chemist. This paper provided a new and effective method for predicting the chromatography retention of peptides and some insight into the structural features which are related to the capacity factor of peptides.

Artificial Intelligence↗