PTEN hypermethylation profiles of Chinese Kazakh patients with esophageal squamous cell carcinoma

Aberrant DNA methylation of promoter region CpG islands may serve as an alternative mechanism to genetic defects in the inactivation of tumor suppressor genes (TSGs) in human malignancies. The aim of this study was to examine the promoter methylation status of the PTEN TSG and its association with esophageal squamous cell carcinoma (ESCC) carcinogenesis in a Chinese Kazakh population, which is known to have a relatively high ESCC incidence and mortality. The methylation status of the PTEN promoter region was determined in patients with ESCC (n = 95) and healthy individuals (n = 65) using highly sensitive Sequenom Epityper assays. The methylation level of the PTEN gene was significantly higher in patients with ESCC than in healthy controls. The median methylation level was 10.0% (interquartile range [IQR]: 7.0-11.0%) in patients with ESCC and 6.0% in controls (IQR: 4.0-9.0%; P = 0.001). PTEN methylation levels were higher in male patients with ESCC than in male controls, whereas a trend toward significance was observed between female patients with ESCC and female controls (P = 0.005 and P = 0.086, respectively). The PTEN methylation level was associated with histopathological grade and lymph node metastasis in patients with ESCC (P = 0.002 and P = 0.009, respectively). To our knowledge, this is the first report to show the presence of PTEN promoter CpG hypermethylation in ESCC and its association with tumor metastasis.

Virtual screening methods as tools for drug lead discovery from large chemical libraries

Virtual screening methods have been developed and explored as useful tools for searching drug lead compounds from chemical libraries, including large libraries that have become publically available. In this review, we discussed the new developments in exploring virtual screening methods for enhanced performance in searching large chemical libraries, their applications in screening libraries of ~ 1 million or more compounds in the last five years, the difficulties in their applications, and the strategies for further improving these methods.

Human papillomavirus type 16 infection may be involved in esophageal squamous cell carcinoma carcinogenesis in Chinese Kazakh patients

The aim of this study was to investigate human papillomavirus type 16 (HPV16) prevalence in esophageal squamous cell carcinoma (ESCC) in Xinjiang Kazakh patients and its role in ESCC carcinogenesis. One hundred and fifty cases of ESCC and 150 cases of corresponding normal esophageal mucosa (CNGM) samples were collected from north Xinjiang where the Kazakh ethnic group has lived since ancient times. HPV16 infection in ESCC and CNGM was detected by genotype-specific polymerase chain reaction. HPV16 DNA was detected in 55 of 150 ESCC samples (36.7%) and 24 of 150 corresponding normal esophageal mucosa samples (16%) with significant differences (P < 0.001, odds ratio = 3.039, 95% confidence interval: 1.756-5.260). No statistically significant correlations were found between HPV16 infection and the age or gender of patients, tumor site, tumor cell differentiation, or lymph node metastasis (P > 0.05). HPV16 infection is common in cases of ESCC in the Kazakh ethnic group in Xinjiang and may be involved in ESCC carcinogenesis.

Allergic Rhinitis and its Impact on Asthma (ARIA): achievements in 10 years and future needs

Allergic rhinitis (AR) and asthma represent global health problems for all age groups. Asthma and rhinitis frequently coexist in the same subjects. Allergic Rhinitis and its Impact on Asthma (ARIA) was initiated during a World Health Organization workshop in 1999 (published in 2001). ARIA has reclassified AR as mild/moderate-severe and intermittent/persistent. This classification closely reflects patients' needs and underlines the close relationship between rhinitis and asthma. Patients, clinicians, and other health care professionals are confronted with various treatment choices for the management of AR. This contributes to considerable variation in clinical practice, and worldwide, patients, clinicians, and other health care professionals are faced with uncertainty about the relative merits and downsides of the various treatment options. In its 2010 Revision, ARIA developed clinical practice guidelines for the management of AR and asthma comorbidities based on the Grading of Recommendation, Assessment, Development and Evaluation (GRADE) system. ARIA is disseminated and implemented in more than 50 countries of the world. Ten years after the publication of the ARIA World Health Organization workshop report, it is important to make a summary of its achievements and identify the still unmet clinical, research, and implementation needs to strengthen the 2011 European Union Priority on allergy and asthma in children.

Effects of Large Blood Vessel Locations during High Intensity Focused Ultrasound Therapy for Hepatic Tumors: a finite element study

High-Intensity Focused Ultrasound (HIFU) has become a viable alternative for treatment of primary and metastatic liver tumors. We evaluated the effects of presence of a large blood vessel and its distance to the tumor on lesion size during HIFU heating. A finite element method (FEM) was used to obtain the temperature distribution for a transfer equation based on large blood vessels convection effect. In 3-D FEM simulation, a 4-mm diameter, 10-mm height cylindrical tumor tissue was heated by different heating schemes with a large blood vessel (10-mm diameter) located at different positions nearby. The distance between the vessel and the tumor tissue varied from 1 mm to 3 mm. For HIFU therapy, the large blood vessel of different locations do not have significant effect on temperature distribution and thermal dose profile, when the heating duration is short (~2s) or the distance of the large blood vessel from the tumor is larger than 2 mm. The domain of thermal lesion can effectively cover the desired therapeutic region with short ultrasound exposure duration (~2s).

Severe chronic allergic (and related) diseases: a uniform approach--a MeDALL--GA2LEN--ARIA position paper

Concepts of disease severity, activity, control and responsiveness to treatment are linked but different. Severity refers to the loss of function of the organs induced by the disease process or to the occurrence of severe acute exacerbations. Severity may vary over time and needs regular follow-up. Control is the degree to which therapy goals are currently met. These concepts have evolved over time for asthma in guidelines, task forces or consensus meetings. The aim of this paper is to generalize the approach of the uniform definition of severe asthma presented to WHO for chronic allergic and associated diseases (rhinitis, chronic rhinosinusitis, chronic urticaria and atopic dermatitis) in order to have a uniform definition of severity, control and risk, usable in most situations. It is based on the appropriate diagnosis, availability and accessibility of treatments, treatment responsiveness and associated factors such as comorbidities and risk factors. This uniform definition will allow a better definition of the phenotypes of severe allergic (and related) diseases for clinical practice, research (including epidemiology), public health purposes, education and the discovery of novel therapies.

International consensus on (ICON) pediatric asthma

Asthma is the most common chronic lower respiratory disease in childhood throughout the world. Several guidelines and/or consensus documents are available to support medical decisions on pediatric asthma. Although there is no doubt that the use of common systematic approaches for management can considerably improve outcomes, dissemination and implementation of these are still major challenges. Consequently, the International Collaboration in Asthma, Allergy and Immunology (iCAALL), recently formed by the EAACI, AAAAI, ACAAI, and WAO, has decided to propose an International Consensus on (ICON) Pediatric Asthma. The purpose of this document is to highlight the key messages that are common to many of the existing guidelines, while critically reviewing and commenting on any differences, thus providing a concise reference. The principles of pediatric asthma management are generally accepted. Overall, the treatment goal is disease control. To achieve this, patients and their parents should be educated to optimally manage the disease, in collaboration with healthcare professionals. Identification and avoidance of triggers is also of significant importance. Assessment and monitoring should be performed regularly to re-evaluate and fine-tune treatment. Pharmacotherapy is the cornerstone of treatment. The optimal use of medication can, in most cases, help patients control symptoms and reduce the risk for future morbidity. The management of exacerbations is a major consideration, independent of chronic treatment. There is a trend toward considering phenotype-specific treatment choices; however, this goal has not yet been achieved.

[ARIA (Allergic Rhinitis and its Impact on Asthma) achievements in 10 years and future needs]

Allergic rhinitis and asthma represent global health problems for all age groups. Asthma and rhinitis frequently co-exist in the same subjects. Allergic Rhinitis and its Impact on Asthma (ARIA) was initiated during a World Health Organization (WHO) workshop in 1999 and was published in 2001. ARIA has reclassified allergic rhinitis as mild/moderate-severe and intermittent/persistent. This classification schema closely reflects the impact of allergic rhinitis on patients. In its 2010 Revision, ARIA developed clinical practice guidelines for the management of allergic rhinitis and asthma co-morbidities based on GRADE (Grading of Recommendation, Assessment, Development and Evaluation). ARIA has been disseminated and implemented in over 50 countries of the world. In Turkey, it is important to make a record of ARIA achievements and to identify the still unmet clinical, research and implementation needs in order to strengthen the 2011 EU Priority on allergy and asthma in children.

A Computer Method for Validating Traditional Chinese Medicine Herbal Prescriptions

Traditional Chinese medicine (TCM) has been widely practiced and is considered as an alternative to conventional medicine. TCM herbal prescriptions contain a mixture of herbs that collectively exert therapeutic actions and modulating effects. Traditionally defined herbal properties, related to the pharmacodynamic, pharmacokinetic and toxicological, as well as physicochemical properties of their principal ingredients, have been used as the basis for formulating TCM multi-herb prescriptions. These properties are used in this work to develop a computer program for predicting whether a multi-herb recipe is a valid TCM prescription. This program is based on a statistical learning method, support vector machine (SVM), and it is trained by using 575 well-known TCM prescriptions and 1961 non-TCM recipes generated by random combination of TCM herbs. Testing results by using 72 well-known TCM prescriptions and 5039 non-TCM recipes showed that 73.6% of the TCM prescriptions and 99.9% of non-TCM recipes are correctly classified by this system. A further test by using 48 TCM prescriptions published in recent years found that 68.7% of these are correctly classified. These accuracies are comparable to those of SVM classification of other biological systems. Our study indicates the potential of SVM for facilitating the analysis of TCM prescriptions.

An integrated mathematical model of thrombin-, histamine-and VEGF-mediated signalling in endothelial permeability

BACKGROUND

Endothelial permeability is involved in injury, inflammation, diabetes and cancer. It is partly regulated by the thrombin-, histamine-, and VEGF-mediated myosin-light-chain (MLC) activation pathways. While these pathways have been investigated, questions such as temporal effects and the dynamics of multi-mediator regulation remain to be fully studied. Mathematical modeling of these pathways facilitates such studies. Based on the published ordinary differential equation models of the pathway components, we developed an integrated model of thrombin-, histamine-, and VEGF-mediated MLC activation pathways.

RESULTS

Our model was validated against experimental data for calcium release and thrombin-, histamine-, and VEGF-mediated MLC activation. The simulated effects of PAR-1, Rho GTPase, ROCK, VEGF and VEGFR2 over-expression on MLC activation, and the collective modulation by thrombin and histamine are consistent with experimental findings. Our model was used to predict enhanced MLC activation by CPI-17 over-expression and by synergistic action of thrombin and VEGF at low mediator levels. These may have impact in endothelial permeability and metastasis in cancer patients with blood coagulation.

CONCLUSION

Our model was validated against a number of experimental findings and the observed synergistic effects of low concentrations of thrombin and histamine in mediating the activation of MLC. It can be used to predict the effects of altered pathway components, collective actions of multiple mediators and the potential impact to various diseases. Similar to the published models of other pathways, our model can potentially be used to identify important disease genes through sensitivity analysis of signalling components.

Update of PROFEAT: a web server for computing structural and physicochemical features of proteins and peptides from amino acid sequence

Sequence-derived structural and physicochemical features have been extensively used for analyzing and predicting structural, functional, expression and interaction profiles of proteins and peptides. PROFEAT has been developed as a web server for computing commonly used features of proteins and peptides from amino acid sequence. To facilitate more extensive studies of protein and peptides, numerous improvements and updates have been made to PROFEAT. We added new functions for computing descriptors of protein–protein and protein–small molecule interactions, segment descriptors for local properties of protein sequences, topological descriptors for peptide sequences and small molecule structures. We also added new feature groups for proteins and peptides (pseudo-amino acid composition, amphiphilic pseudo-amino acid composition, total amino acid properties and atomic-level topological descriptors) as well as for small molecules (atomic-level topological descriptors). Overall, PROFEAT computes 11 feature groups of descriptors for proteins and peptides, and a feature group of more than 400 descriptors for small molecules plus the derived features for protein–protein and protein–small molecule interactions. Our computational algorithms have been extensively tested and used in a number of published works for predicting proteins of specific structural or functional classes, protein–protein interactions, peptides of specific functions and quantitative structure activity relationships of small molecules. PROFEAT is accessible free of charge at http://bidd.cz3.nus.edu.sg/cgi-bin/prof/protein/profnew.cgi.

HIT: linking herbal active ingredients to targets

The information of protein targets and small molecule has been highly valued by biomedical and pharmaceutical research. Several protein target databases are available online for FDA-approved drugs as well as the promising precursors that have largely facilitated the mechanistic study and subsequent research for drug discovery. However, those related resources regarding to herbal active ingredients, although being unusually valued as a precious resource for new drug development, is rarely found. In this article, a comprehensive and fully curated database for Herb Ingredients' Targets (HIT, http://lifecenter.sgst.cn/hit/) has been constructed to complement above resources. Those herbal ingredients with protein target information were carefully curated. The molecular target information involves those proteins being directly/indirectly activated/inhibited, protein binders and enzymes whose substrates or products are those compounds. Those up/down regulated genes are also included under the treatment of individual ingredients. In addition, the experimental condition, observed bioactivity and various references are provided as well for user's reference. Derived from more than 3250 literatures, it currently contains 5208 entries about 1301 known protein targets (221 of them are described as direct targets) affected by 586 herbal compounds from more than 1300 reputable Chinese herbs, overlapping with 280 therapeutic targets from Therapeutic Targets Database (TTD), and 445 protein targets from DrugBank corresponding to 1488 drug agents. The database can be queried via keyword search or similarity search. Crosslinks have been made to TTD, DrugBank, KEGG, PDB, Uniprot, Pfam, NCBI, TCM-ID and other databases.

Virtual screening of selective multitarget kinase inhibitors by combinatorial support vector machines

Multitarget agents have been increasingly explored for enhancing efficacy and reducing countertarget activities and toxicities. Efficient virtual screening (VS) tools for searching selective multitarget agents are desired. Combinatorial support vector machines (C-SVM) were tested as VS tools for searching dual-inhibitors of 11 combinations of 9 anticancer kinase targets (EGFR, VEGFR, PDGFR, Src, FGFR, Lck, CDK1, CDK2, GSK3). C-SVM trained on 233-1,316 non-dual-inhibitors correctly identified 26.8%-57.3% (majority >36%) of the 56-230 intra-kinase-group dual-inhibitors (equivalent to the 50-70% yields of two independent individual target VS tools), and 12.2% of the 41 inter-kinase-group dual-inhibitors. C-SVM were fairly selective in misidentifying as dual-inhibitors 3.7%-48.1% (majority <20%) of the 233-1,316 non-dual-inhibitors of the same kinase pairs and 0.98%-4.77% of the 3,971-5,180 inhibitors of other kinases. C-SVM produced low false-hit rates in misidentifying as dual-inhibitors 1,746-4,817 (0.013%-0.036%) of the 13.56 M PubChem compounds, 12-175 (0.007%-0.104%) of the 168 K MDDR compounds, and 0-84 (0.0%-2.9%) of the 19,495-38,483 MDDR compounds similar to the known dual-inhibitors. C-SVM was compared to other VS methods Surflex-Dock, DOCK Blaster, kNN and PNN against the same sets of kinase inhibitors and the full set or subset of the 1.02 M Zinc clean-leads data set. C-SVM produced comparable dual-inhibitor yields, slightly better false-hit rates for kinase inhibitors, and significantly lower false-hit rates for the Zinc clean-leads data set. Combinatorial SVM showed promising potential for searching selective multitarget agents against intra-kinase-group kinases without explicit knowledge of multitarget agents.

Salt dependent premelting base pair opening probabilities of B and Z DNA Poly [d(G-C)] and significance for the B-Z transition

We calculate room temperature thermal fluctuational base pair opening probabilities of B and Z DNA Poly[d(G-C)] at various salt concentrations and discuss the significance of thermal fluctuation in facilitating base pair disruption during B to Z transition. Our calculated base pair opening probability of the B DNA at lower salt concentrations and the probability of the Z DNA at high salt concentrations are in agreement with observations. The salt dependence of the probabilities indicates a B to Z transition at a salt concentration close to the observed concentration.

Identifying Novel Type ZBGs and Nonhydroxamate HDAC Inhibitors Through a SVM Based Virtual Screening Approach

Histone deacetylase inhibitors (HDACi) have been successfully used for the treatment of cancers and other diseases. Search for novel type ZBGs and development of non-hydroxamate HDACi has become a focus in current research. To complement this, it is desirable to explore a virtual screening (VS) tool capable of identifying different types of potential inhibitors from large compound libraries with high yields and low false-hit rates similar to HTS. This work explored the use of support vector machines (SVM) combined with our newly developed putative non-inhibitor generation method as such a tool. SVM trained by 702 pre-2008 hydroxamate HDACi and 64334 putative non-HDACi showed good yields and low false-hit rates in cross-validation test and independent test using 220 diverse types of HDACi reported since 2008. The SVM hit rates in scanning 13.56 M PubChem and 168K MDDR compounds are comparable to HTS rates. Further structural analysis of SVM virtual hits suggests its potential for identification of non-hydroxamate HDACi. From this analysis, a series of novel ZBG and cap groups were proposed for HDACi design.

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.

A laser-Compton scattering prototype experiment at 100 MeV linac of Shanghai Institute of Applied Physics

As a prototype of the Shanghai Laser Electron Gamma Source in the Shanghai Synchrotron Radiation Facility, an x-ray source based on laser-Compton scattering (LCS) has been installed at the terminal of the 100 MeV linac of the Shanghai Institute of Applied Physics. LCS x-rays are generated by interactions between Q-switched Nd:yttrium aluminum garnet laser pulses [with wavelength of 1064 nm and pulse width of 21 ns (full width at half maximum)] and electron bunches [with energy of 108 MeV and pulse width of 0.95 ns (rms)] at an angle of 42 degrees between laser and electron beam. In order to measure the energy spectrum of LCS x-rays, a Si(Li) detector along the electron beam line axis is positioned at 9.8 m away from a LCS chamber. After background subtraction, the LCS x-ray spectrum with the peak energy of 29.1+/-4.4|(stat)+/-2.1|(syst) keV and the peak width (rms) of 7.8+/-2.8|(stat)+/-0.4|(syst) keV is observed. Normally the 100 MeV linac operates with the electron macropulse charge of 1.0 nC/pulse, and the electron and laser collision repetition rate of 20 Hz. Therefore, the total LCS x-ray flux of (5.2+/-2.0) x 10(2) Hz can be achieved.

Virtual screening of Abl inhibitors from large compound libraries by support vector machines

Abl promotes cancers by regulating cell morphogenesis, motility, growth, and survival. Successes of several marketed and clinical trial Abl inhibitors against leukemia and other cancers and appearances of reduced efficacies and drug resistances have led to significant interest in and efforts for developing new Abl inhibitors. In silico methods of pharmacophore, fragment, and molecular docking have been used in some of these efforts. It is desirable to explore other in silico methods capable of searching large compound libraries at high yields and reduced false-hit rates. We evaluated support vector machines (SVM) as a virtual screening tool for searching Abl inhibitors from large compound libraries. SVM trained and tested by 708 inhibitors and 65,494 putative noninhibitors correctly identified 84.4 to 92.3% inhibitors and 99.96 to 99.99% noninhibitors in 5-fold cross validation studies. SVM trained by 708 pre-2008 inhibitors and 65 494 putative noninhibitors correctly identified 50.5% of the 91 inhibitors reported since 2008 and predicted as inhibitors 29,072 (0.21%) of 13.56M PubChem, 659 (0.39%) of 168K MDDR, and 330 (5.0%) of 6638 MDDR compounds similar to the known inhibitors. SVM showed comparable yields and substantially reduced false-hit rates against two similarity based and another machine learning VS methods based on the same training and testing data sets and molecular descriptors. These suggest that SVM is capable of searching Abl inhibitors from large compound libraries at low false-hit rates.

Large anisotropy in colossal magnetoresistance of charge orbital ordered epitaxial Sm(0.5)Ca(0.5)MnO(3) films

We investigated the structure and magnetotransport properties of Sm(0.5)Ca(0.5)MnO(3) (SCMO) films epitaxially grown on (011)-oriented SrTiO(3) substrates, which exhibited clear charge/orbital ordering transition. A significant anisotropy of ∼1000 in the colossal magnetoresistance (CMR) effect was observed in the films with a thickness between 50 and 80 nm, which was distinctly different from the basically isotropic CMR effect in bulk SCMO. The large anisotropy in the CMR can be ascribed to the intrinsic asymmetric strain in the film, which plays an important role in tuning the spin-orbit coupling in manganite films. The origin of the peculiar CMR effect is discussed.

Though with constraints imposed by endosymbiosis, preferential attachment is still a plausible mechanism responsible for the evolution of the chloroplast metabolic network

Chloroplasts evolved as a result of endosymbiosis, during which sophisticated mechanisms evolved to translocate nucleus-encoded plastid-targeted enzymes into the chloroplast to form the chloroplast metabolic network. Given the constraints and complexity of endosymbiosis, will preferential attachment still be a plausible mechanism for chloroplast metabolic network evolution? We answer this question by analysing the metabolic network properties of the chloroplast and a cyanobacterium, Synechococcus sp. WH8102 (syw). First, we found that enzymes related to more ancient pathways are more connected, and synthetases have the highest connectivity. Most of the enzymes shared by the two densest cores between the chloroplast and syw are synthetases. Second, the highly conserved functional modules mainly consist of highly connected enzymes. Finally, isozymes and enzymes from endosymbiotic gene transfer (EGT) were distributed mainly in conserved modules and showed higher connectivity than nonisozymes or non-EGT enzymes. These results suggest that even with severe evolutionary constraints imposed by endosymbiosis, preferential attachment is still a plausible mechanism responsible for the evolution of the chloroplast metabolic network. However, the current analysis may not completely differentiate whether the chloroplast network properties reflect the evolution of the chloroplast network through preferential attachment or has been inherited from its cyanobacterial ancestor. To fully differentiate these two possibilities, further analyses of the metabolic network structure properties of organisms at various intermediate evolutionary stages between cyanobacteria and the chloroplast are needed.

Characterization and Optical Properties of the Single Crystalline SnS Nanowire Arrays

The SnS nanowire arrays have been successfully synthesized by the template-assisted pulsed electrochemical deposition in the porous anodized aluminum oxide template. The investigation results showed that the as-synthesized nanowires are single crystalline structures and they have a highly preferential orientation. The ordered SnS nanowire arrays are uniform with a diameter of 50 nm and a length up to several tens of micrometers. The synthesized SnS nanowires exhibit strong absorption in visible and near-infrared spectral region and the direct energy gap E(g) of SnS nanowires is 1.59 eV.

Evaluation of virtual screening performance of support vector machines trained by sparsely distributed active compounds

Virtual screening performance of support vector machines (SVM) depends on the diversity of training active and inactive compounds. While diverse inactive compounds can be routinely generated, the number and diversity of known actives are typically low. We evaluated the performance of SVM trained by sparsely distributed actives in six MDDR biological target classes composed of a high number of known actives (983-1645) of high, intermediate, and low structural diversity (muscarinic M1 receptor agonists, NMDA receptor antagonists, thrombin inhibitors, HIV protease inhibitors, cephalosporins, and renin inhibitors). SVM trained by regularly sparse data sets of 100 actives show improved yields at substantially reduced false-hit rates compared to those of published studies and those of Tanimoto-based similarity searching method based on the same data sets and molecular descriptors. SVM trained by very sparse data sets of 40 actives (2.4%-4.1% of the known actives) predicted 17.5-39.5%, 23.0-48.1%, and 70.2-92.4% of the remaining 943-1605 actives in the high, intermediate, and low diversity classes, respectively, 13.8-68.7% of which are outside the training compound families. SVM predicted 99.97% and 97.1% of the 9.997 M PUBCHEM and 167K remaining MDDR compounds as inactive and 2.6%-8.3% of the 19,495-38,483 MDDR compounds similar to the known actives as active. These suggest that SVM has substantial capability in identifying novel active compounds from sparse active data sets at low false-hit rates.

Finite-size effect on magnetic properties in iron sulfide nanowire arrays

We report the size effect on the magnetic properties in Fe(7)S(8) nanowire arrays. Samples with diameters in the range of 50-200 nm have been prepared by electrodeposition with AAO films. The Mössbauer measurement results show that four parameters (hyperfine fields, isomer shift, quadrupole splitting, full width at half-maximum) increased with decreasing the diameter of the nanowires. The magnetic properties were investigated. The hysteresis loop shape and the magnetization are dependent on the diameter of the nanowires. The thermomagnetic measurements on the as-synthesized nanowire samples and the corresponding bulk display a mixed-type curve and a Weiss-type curve, respectively.