Enhanced thermal stability of monodispersed silver cluster arrays assembled on block copolymer scaffolds

Triblock copolymer poly(styrene-b-butadiene-b-styrene) (SBS) films with long-range ordered self-assembled nanopatterns are used as templates to selectively adsorb soft-landing silver clusters. Closely spaced cluster arrays with high monodispersity are formed through the confinement of the block copolymer scaffolds, and show a much enhanced thermal stability as compared with the cluster assemblies on the surfaces of covalent amorphous solids, or even on the disordered SBS films. Their morphologies are barely influenced by long time thermal annealing at a temperature as high as 180 degrees C, while in the latter case intense aggregations and coalescences of silver clusters are commonly observed upon annealing. The different thermal stabilities of the cluster assemblies also induce different evolutions of their optical extinction spectra under annealing. This promises a simple way to control the monodispersity and thermal stability of metal cluster assembly via self-assembled block copolymer template.

Video-assisted repair of cervical lung hernia

Lung hernia is an extremely rare condition and the treatments vary. We report a case of cervical lung hernia without any trauma. The patient underwent video-assisted repair with a satisfactory result.

Trends in the exploration of anticancer targets and strategies in enhancing the efficacy of drug targeting

A number of therapeutic targets have been explored for developing anticancer drugs. Continuous efforts have been directed at the discovery of new targets as well as the improvement of therapeutic efficacy of agents directed at explored targets. There are 84 and 488 targets of marketed and investigational drugs for the treatment of cancer or cancer related illness. Analysis of these targets, particularly those of drugs in clinical trials and US patents, provides useful information and perspectives about the trends, strategies and progresses in targeting key cancer-related processes and in overcoming the difficulties in developing efficacious drugs against these targets. The efficacy of anticancer drugs directed at these targets is frequently compromised by counteractive molecular interactions and network crosstalk, negative and adverse secondary effects of drugs, and undesired ADMET profiles. Multi-component therapies directed at multiple targets and improved drug targeting methods are being explored for alleviating these efficacy-reducing processes. Investigation of the modes of actions of these combinations and targeting methods offers clues to aid the development of more effective anticancer therapies.

Trends in the exploration of anticancer targets and strategies in enhancing the efficacy of drug targeting

A number of therapeutic targets have been explored for developing anticancer drugs. Continuous efforts have been directed at the discovery of new targets as well as the improvement of therapeutic efficacy of agents directed at explored targets. There are 84 and 488 targets of marketed and investigational drugs for the treatment of cancer or cancer related illness. Analysis of these targets, particularly those of drugs in clinical trials and US patents, provides useful information and perspectives about the trends, strategies and progresses in targeting key cancer-related processes and in overcoming the difficulties in developing efficacious drugs against these targets. The efficacy of anticancer drugs directed at these targets is frequently compromised by counteractive molecular interactions and network crosstalk, negative and adverse secondary effects of drugs, and undesired ADMET profiles. Multi-component therapies directed at multiple targets and improved drug targeting methods are being explored for alleviating these efficacy-reducing processes. Investigation of the modes of actions of these combinations and targeting methods offers clues to aid the development of more effective anticancer therapies.

Induction of tumoricidal activity in mouse peritoneal macrophages by ginseng polysaccharide

This study examined the effects of ginseng polysaccharide (GPS) on mouse peritoneal macrophage (PM)-mediated cytotoxicity towards K562, HL-60, or KG1alpha cells. GPS had no direct effect on killing of tumor cells. However, when mouse PMs were treated with GPS, cytotoxic activity against K562, HL-60, or KG1alpha cells was significantly induced. In addition, phagocytic activity was enhanced in GPS-treated mouse PMs compared to the control. The expressions of CD(68), ACP and alpha-ANE in mouse PMs were increased by the treatment with GPS. Moreover, the levels of cytokines, including tumor necrosis factor-alpha (TNF-alpha), interleukin-1 (IL-1), IL-6 were increased and the production of nitric oxide (NO) was enhanced. Taken together, these results suggest that GPS possess a potent antitumor activity by stimulating macrophage and a potentiality as an immunomodulator against diseases such as cancer.

Petrochemical wastewater odor treatment by biofiltration

The treatment of odorous pollutants by microorganisms on packed waste straw and cortex was investigated at the wastewater treatment plant of the Shanghai petrochemical factory. The removal efficiency of H(2)S, NH(3) and VOCs (volatile organic compounds) reached 98%, 91% and 90%, respectively after operation for one month at an empty bed retention time (EBRT) of 120s. The heterotrophic bacteria were found to be the dominant microorganism in the biofilter, while fungi and actinomycetes were also present. The bacteria were mostly identified as the members of the genus Bacillus (62.5% of cultured bacteria). The single strand conformation polymorphism (SSCP) results revealed that the genus Bacillus and Pseudomonas were the predominant bacteria. The microbial diversity gradually increased as the treatment progressed, which indicated that the microbial community in the biofilter became more stable upon pollutant removal. The scanning electron microscopy (SEM) was performed to evaluate the microorganism growth on the media. It was found that the waste straw and cortex were suitable for microorganism attachment and growth, and may have potential application in odor treatment.

In vitro culture and differentiation of buffalo (Bubalus bubalis) spermatogonia

The objective of this study was to develop a culture system which could support buffalo spermatogonia differentiation into spermatids in vitro. Testes from 3- to 5-month-old buffaloes were decapsulated and seminiferous tubules were enzymatically dissociated to recover spermatogonia and sertoli cells. The cells were cultured in modified Dulbecco modified Eagle medium supplemented with different concentrations of foetal bovine serum, retinol, testosterone for 2 months at 37 degrees C. Spermatogonia and sertoli cells were identified with an antibody against c-kit or GATA4, respectively. The viability of spermatogonia in the media supplemented with different concentrations of serum was all significantly higher (p < 0.05) compared with that in the medium without serum. A-paired or A-aligned spermatogonia and spermatogonial colonies (AP-positive) were observed after 7-10 days of culture and spermatid-like cells with a flagellum (6-8 microm) appeared after 30 days of culture. For cultured conditions, retinol could not significantly promote the formation of spermatid-like cells (p > 0.05), whereas supplementation of testosterone could significantly promote (p < 0.05) the formation of spermatid-like cells after 41 days of culture. The expression of the spermatid-specific marker gene (PRM2) was identified after 30 days of culture by RT-PCR. Yet, the transition protein 1 (TP1, a haploid makers) was not detected. Meanwhile, spermatids developed in vitro were also confirmed by Raman spectroscopy. These results suggest that buffalo spermatogonia could differentiate into spermatids in vitro based on the analysis of their morphology, PRM2 expression and Raman spectroscopy. Yet, the normality of the spermatid-like cells was not supported by TP1 expression.

Prediction of biodegradation rate constants of hydroxylated polychlorinated biphenyls by fungal laccases from Trametes versicolor and Pleurotus ostreatus

Quantitative structure-activity relationship (QSAR) models for fungal laccase-catalyzed degradation of different hydroxylated polychlorinated biphenyls (OH-PCBs) were developed using some fundamental quantum chemical descriptors. The cross-validated Q(2)(cum )values for the two optimal QSAR models are as high as 0.958 and 0.961 for laccases from Trametes versicolor and Pleurotus ostreatus, respectively, indicating good predictive abilities for laccase-catalyzed degradation of OH-PCBs. Results from this study show that increasing heat of formation (DeltaH(f)) and frontier molecular orbital energy (i.e. E(LUMO) + E(HOMO)) values or decreasing frontier molecular orbital energy (i.e. E(HOMO-1)) and core-core repulsion energy (CCR) values leads to the increase of OH-PCB degradation rates by laccases.

Homology-free prediction of functional class of proteins and peptides by support vector machines

Protein and peptide sequences contain clues for functional prediction. A challenge is to predict sequences that show low or no homology to proteins or peptides of known function. A machine learning method, support vector machines (SVM), has recently been explored for predicting functional class of proteins and peptides from sequence-derived properties irrespective of sequence similarity, which has shown impressive performance for predicting a wide range of protein and peptide classes including certain low- and non- homologous sequences. This method serves as a new and valuable addition to complement the extensively-used alignment-based, clustering-based, and structure-based functional prediction methods. This article evaluates the strategies, current progresses, reported prediction performances, available software tools, and underlying difficulties in using SVM for predicting the functional class of proteins and peptides.

Trends in the exploration of therapeutic targets for the treatment of endocrine, metabolic and immune disorders

A number of therapeutic targets have been explored for developing drugs in the treatment of endocrine, metabolic and immune disorders. Continuous efforts and increasing interest have been directed at the search of new targets. Data from the therapeutic target database at http://bidd.nus.edu.sg/group/cjttd/ttd.asp, shows that there are 26, 24, and 22 targets of marketed drugs for the treatment of these three classes of diseases, respectively. The number of targets of investigational agents has reached 98, 124, and 72, respectively. An analysis of these targets, particularly those of recently approved drugs and patented investigational agents, provides useful hint about the general trends of target exploration, with current focus on drug discovery and the difficulties encountered in developing drugs against these targets. Multiple profiles of these targets have been analyzed to probe the sequence, structural, physicochemical and systems-related features contributing to the successful exploration of a target against these diseases.

Cause and pre-alarm control of bulking and foaming by Microthrix parvicella--a case study in triple oxidation ditch at a wastewater treatment plant

The cause and control of foaming and bulking in triple oxidation ditch at a wastewater treatment plant (WWTP) were investigated. The results showed that the foaming and bulking was mainly caused by the excessive propagation of Microthrix parvicella, and mostly occurred in the cold winter and spring. Batch and continuous flow experiments indicated that biological techniques such as reducing sludge retention time (SRT) and increasing F/M ratio, chemical methods such as addition of chlorine (NaOCl), quaternary ammonium salt (QAS), or cationic polyacrylamide flocculants (PAM), polyaluminum salt (PAC) could decrease Sludge Volume Index (SVI) and control foaming and bulking at different levels. In practical application, the shorter SRT was effective to control foaming and bulking in initial stage, although it took longer time. Addition of 10gClkgMLSSd(-1) could gradually change the activated sludge with serious foaming and bulking to normal state within a week. Pre-alert control strategies should be established for the control of filamentous foaming and bulking.

Prediction of the functional class of metal-binding proteins from sequence derived physicochemical properties by support vector machine approach

Metal-binding proteins play important roles in structural stability, signaling, regulation, transport, immune response, metabolism control, and metal homeostasis. Because of their functional and sequence diversity, it is desirable to explore additional methods for predicting metal-binding proteins irrespective of sequence similarity. This work explores support vector machines (SVM) as such a method. SVM prediction systems were developed by using 53,333 metal-binding and 147,347 non-metal-binding proteins, and evaluated by an independent set of 31,448 metal-binding and 79,051 non-metal-binding proteins. The computed prediction accuracy is 86.3%, 81.6%, 83.5%, 94.0%, 81.2%, 85.4%, 77.6%, 90.4%, 90.9%, 74.9% and 78.1% for calcium-binding, cobalt-binding, copper-binding, iron-binding, magnesium-binding, manganese-binding, nickel-binding, potassium-binding, sodium-binding, zinc-binding, and all metal-binding proteins respectively. The accuracy for the non-member proteins of each class is 88.2%, 99.9%, 98.1%, 91.4%, 87.9%, 94.5%, 99.2%, 99.9%, 99.9%, 98.0%, and 88.0% respectively. Comparable accuracies were obtained by using a different SVM kernel function. Our method predicts 67% of the 87 metal-binding proteins non-homologous to any protein in the Swissprot database and 85.3% of the 333 proteins of known metal-binding domains as metal-binding. These suggest the usefulness of SVM for facilitating the prediction of metal-binding proteins. Our software can be accessed at the SVMProt server http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi.

PharmGED: Pharmacogenetic Effect Database

Prediction and elucidation of pharmacogenetic effects is important for facilitating the development of personalized medicines. Knowledge of polymorphism-induced and other types of drug-response variations is needed for facilitating such studies. Although databases of pharmacogenetic knowledge, polymorphism and toxicogenomic information have appeared, some of the relevant data are provided in separate web-pages and in terms of relatively long descriptions quoted from literatures. To facilitate easy and quick assessment of the relevant information, it is helpful to develop databases that provide all of the information related to a pharmacogenetic effect in the same web-page and in brief descriptions. We developed a database, Pharmacogenetic Effect Database (PharmGED), for providing sequence, function, polymorphism, affected drugs and pharmacogenetic effects. PharmGED can be accessed at free of charge for academic use. It currently contains 1825 entries covering 108 disease conditions, 266 distinct proteins, 693 polymorphisms, 414 drugs/ligands cited from 856 references.

Prediction of the functional class of lipid binding proteins from sequence-derived properties irrespective of sequence similarity

Lipid binding proteins play important roles in signaling, regulation, membrane trafficking, immune response, lipid metabolism, and transport. Because of their functional and sequence diversity, it is desirable to explore additional methods for predicting lipid binding proteins irrespective of sequence similarity. This work explores the use of support vector machines (SVMs) as such a method. SVM prediction systems are developed using 14,776 lipid binding and 133,441 nonlipid binding proteins and are evaluated by an independent set of 6,768 lipid binding and 64,761 nonlipid binding proteins. The computed prediction accuracy is 78.9, 79.5, 82.2, 79.5, 84.4, 76.6, 90.6, 79.0, and 89.9% for lipid degradation, lipid metabolism, lipid synthesis, lipid transport, lipid binding, lipopolysaccharide biosynthesis, lipoprotein, lipoyl, and all lipid binding proteins, respectively. The accuracy for the nonmember proteins of each class is 99.9, 99.2, 99.6, 99.8, 99.9, 99.8, 98.5, 99.9, and 97.0%, respectively. Comparable accuracies are obtained when homologous proteins are considered as one, or by using a different SVM kernel function. Our method predicts 86.8% of the 76 lipid binding proteins nonhomologous to any protein in the Swiss-Prot database and 89.0% of the 73 known lipid binding domains as lipid binding. These findings suggest the usefulness of SVMs for facilitating the prediction of lipid binding proteins. Our software can be accessed at the SVMProt server (http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi).

PEARLS: Program for Energetic Analysis of Receptor−Ligand System

Analysis of the energetics of small molecule ligand-protein, ligand-nucleic acid, and protein-nucleic acid interactions facilitates the quantitative understanding of molecular interactions that regulate the function and conformation of proteins. It has also been extensively used for ranking potential new ligands in virtual drug screening. We developed a Web-based software, PEARLS (Program for Energetic Analysis of Ligand-Receptor Systems), for computing interaction energies of ligand-protein, ligand-nucleic acid, protein-nucleic acid, and ligand-protein-nucleic acid complexes from their 3D structures. AMBER molecular force field, Morse potential, and empirical energy functions are used to compute the van der Waals, electrostatic, hydrogen bond, metal-ligand bonding, and water-mediated hydrogen bond energies between the binding molecules. The change in the solvation free energy of molecular binding is estimated by using an empirical solvation free energy model. Contribution from ligand conformational entropy change is also estimated by a simple model. The computed free energy for a number of PDB ligand-receptor complexes were studied and compared to experimental binding affinity. A substantial degree of correlation between the computed free energy and experimental binding affinity was found, which suggests that PEARLS may be useful in facilitating energetic analysis of ligand-protein, ligand-nucleic acid, and protein-nucleic acid interactions. PEARLS can be accessed at http://ang.cz3.nus.edu.sg/cgi-bin/prog/rune.pl.

Effects of perceived peer isolation and social support availability on the relationship between body mass index and depressive symptoms

OBJECTIVE

To examine relationships between body mass index (BMI) and psychological correlates in Chinese school adolescents during the period of economic transition.

DESIGN

Baseline data of 1655 Chinese adolescents aged 11-15 y were retrieved from a longitudinal smoking cessation and health promotion program in Wuhan, China. Assessments of body weight and height, depressive symptoms, perceived peer isolation (PPI) and perceived availability of social support (PASS) were collected.

RESULTS

Based on the International Obesity Task Force (IOTF) age-and sex-specific BMI cutoffs, 12.5% of boys and 9.2% of girls were overweight. In girls, high BMI was significantly related to higher self-reported depressive symptoms, and was dominantly mediated by PPI. On the contrary, high BMI boys reported significantly lower levels of PPI although high PPI level aggravated depressive symptoms. For both girls and boys, the observed effect of PPI on the relationship between BMI and depressive symptoms was sustained only in low PASS boys and girls.

CONCLUSIONS

The present study revealed different effects of PPI on the association of BMI and depressive symptoms between boys and girls, which were buffered by levels of PASS. The findings of this study may contribute to our understanding of the influences of psychological correlates in pediatric overweight in the Eastern cultural environment.

Trends in exploration of therapeutic targets

Lead discovery against a preselected therapeutic target is a key component in modern drug development. Continuous effort and increasing interest has been directed at the search for new targets, which has led to the identification of a growing number of them. Data from the therapeutic target database, at http://bidd.nus.edu.sg/group/cjttd/ttd.asp, show that, as of July 2004, the number of documented targets of marketed and investigational drugs has reached 1,174 distinct proteins (including subtypes) and 27 nucleic acids, 239 of which are targets of the marketed drugs. Analysis of these targets, particularly those of recently approved drugs and patented investigational agents, provide useful hints about general trends of target exploration and current focus in drug discovery for the treatment of high impact diseases needing effective or more treatment options.

MoViES: molecular vibrations evaluation server for analysis of fluctuational dynamics of proteins and nucleic acids

Analysis of vibrational motions and thermal fluctuational dynamics is a widely used approach for studying structural, dynamic and functional properties of proteins and nucleic acids. Development of a freely accessible web server for computation of vibrational and thermal fluctuational dynamics of biomolecules is thus useful for facilitating the relevant studies. We have developed a computer program for computing vibrational normal modes and thermal fluctuational properties of proteins and nucleic acids and applied it in several studies. In our program, vibrational normal modes are computed by using modified AMBER molecular mechanics force fields, and thermal fluctuational properties are computed by means of a self-consistent harmonic approximation method. A web version of our program, MoViES (Molecular Vibrations Evaluation Server), was set up to facilitate the use of our program to study vibrational dynamics of proteins and nucleic acids. This software was tested on selected proteins, which show that the computed normal modes and thermal fluctuational bond disruption probabilities are consistent with experimental findings and other normal mode computations. MoViES can be accessed at http://ang.cz3.nus.edu.sg/cgi-bin/prog/norm.pl.