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.

Prediction of estrogen receptor agonists and characterization of associated molecular descriptors by statistical learning methods

Specific estrogen receptor (ER) agonists have been used for hormone replacement therapy, contraception, osteoporosis prevention, and prostate cancer treatment. Some ER agonists and partial-agonists induce cancer and endocrine function disruption. Methods for predicting ER agonists are useful for facilitating drug discovery and chemical safety evaluation. Structure-activity relationships and rule-based decision forest models have been derived for predicting ER binders at impressive accuracies of 87.1-97.6% for ER binders and 80.2-96.0% for ER non-binders. However, these are not designed for identifying ER agonists and they were developed from a subset of known ER binders. This work explored several statistical learning methods (support vector machines, k-nearest neighbor, probabilistic neural network and C4.5 decision tree) for predicting ER agonists from comprehensive set of known ER agonists and other compounds. The corresponding prediction systems were developed and tested by using 243 ER agonists and 463 ER non-agonists, respectively, which are significantly larger in number and structural diversity than those in previous studies. A feature selection method was used for selecting molecular descriptors responsible for distinguishing ER agonists from non-agonists, some of which are consistent with those used in other studies and the findings from X-ray crystallography data. The prediction accuracies of these methods are comparable to those of earlier studies despite the use of significantly more diverse range of compounds. SVM gives the best accuracy of 88.9% for ER agonists and 98.1% for non-agonists. Our study suggests that statistical learning methods such as SVM are potentially useful for facilitating the prediction of ER agonists and for characterizing the molecular descriptors associated with ER agonists.

Expression of estrogen receptor (ER)-alpha and -beta immunoreactivity in hippocampal cell cultures with special attention to GABAergic neurons

This study investigated the expression patterns of estrogen receptor-alpha (ER alpha) and -beta (ER beta) in the cultured hippocampal cells of neonatal rats by combined application of cell culture and immunocytochemistry. The results revealed that the expression difference between ER alpha and ER beta seemed to be not obvious in the cultured hippocampal cells of neonatal rats. Moreover, immunoreactivity for either ER alpha or ER beta was observed to be localized in the majority of not only neurons but also astrocytes. The coexpression of both ER alpha and ER beta in the same individual cell was also demonstrated by the double-label immunocytochemistry. Western blot analysis showed that immunoreactivity for ER alpha in the neonatal hippocampal tissues was much higher than in the adult (became rather weak), although there was not such a great difference of immunoreactivity for ER beta. The data also provide direct evidence for the expression of ER subtypes within GABAergic neurons in hippocampal cell cultures and suggest that estrogen's effect on the hippocampus may be mediated at least in part by its ER-containing GABAergic neurons.

An amiloride-sensitive and voltage-dependent Na+ channel in an HLA-DR-restricted human T cell clone

We investigated changes in voltage-gated Na+ currents and effects of extracellular Na+ on proliferation in HLA-DR-restricted human CD4+ alphabeta T cells after stimulation with a non-self antigenic peptide, M12p54-68. In the absence of antigenic peptide, neither single (n = 80) nor APC-contacted (n = 71) T cells showed voltage-gated inward currents recording with whole-cell patch-clamp techniques, even with Ca2+ and Na+ ions present in the perfusion solution. However, with the same recording conditions, 31% (26 of 84) of APC-contacted T cells stimulated with the antigenic peptide showed voltage-dependent inward currents that were elicited from -60 mV. The inward currents were not inhibited in extracellular Ca2+-free conditions or in the presence of 1 mM NiCl2. However, they were completely inhibited in extracellular Na+-free conditions, which were made by replacing Na+ with iso-osmotic N-methyl-d -glucamine or choline. The Na+ currents were insensitive to tetrodotoxin, a classical blocker of Na+ channels, but were dose-dependently inhibited by amiloride, a potassium-sparing pyrazine diuretic. Furthermore, the Ag-specific proliferative response of T cells was completely inhibited in Na+-free Tyrode's solution and was suppressed by amiloride in a dose-dependent manner. Our findings suggest that activation of amiloride-sensitive and voltage-gated Na+ channels would be an important step to allow an adequate influx of Na+ and maintain a sustained high Ca2+ level during T cell activation.

In cis autosomal dominant mutation of Senataxin associated with tremor/ataxia syndrome

Senataxin mutations are the molecular basis of two distinct syndromes: (1) ataxia oculomotor apraxia type 2 (AOA2) and (2) juvenile amyotrophic lateral sclerosis 4 (ALS4). The authors describe clinical and molecular genetic studies of mother and daughter who display symptoms of cerebellar ataxia/atrophy, oculomotor defects, and tremor. Both patients share Senataxin mutations N603D and Q653K in cis (N603D-Q653K), adjacent to an N-terminal domain thought to function in protein-protein interaction. The N-terminal and helicase domains appear to harbor missense mutation clusters associated with AOA2 and ALS4. Working synergistically, the N603D-Q653K mutations may confer a partial dominant negative effect, acting on the senataxin N-terminal, further expanding the phenotypic spectrum associated with Senataxin mutations.

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.

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.

Rhinitis associated with asthma is distinct from rhinitis alone: The ARIA-MeDALL hypothesis

Asthma, rhinitis and atopic dermatitis (AD) are interrelated clinical phenotypes that partly overlap in the human interactome. The concept of "one-airway-one-disease", coined over 20 years ago, is a simplistic approach of the links between upper- and lower-airway allergic diseases. With new data, it is time to reassess the concept. This article reviews (i) the clinical observations that led to Allergic Rhinitis and its Impact on Asthma (ARIA), (ii) new insights into polysensitisation and multimorbidity, (iii) advances in mHealth for novel phenotype definition, (iv) confirmation in canonical epidemiologic studies, (v) genomic findings, (vi) treatment approaches and (vii) novel concepts on the onset of rhinitis and multimorbidity. One recent concept, bringing together upper- and lower-airway allergic diseases with skin, gut and neuropsychiatric multimorbidities, is the "Epithelial Barrier Hypothesis". This review determined that the "one-airway-one-disease" concept does not always hold true and that several phenotypes of disease can be defined. These phenotypes include an extreme "allergic" (asthma) phenotype combining asthma, rhinitis and conjunctivitis. Rhinitis alone and rhinitis and asthma multimorbidity represent two distinct diseases with the following differences: (i) genomic and transcriptomic background (Toll-Like Receptors and IL-17 for rhinitis alone as a local disease; IL-33 and IL-5 for allergic and non-allergic multimorbidity as a systemic disease), (ii) allergen sensitisation patterns (mono- or pauci-sensitisation versus polysensitisation), (iii) severity of symptoms and (iv) treatment response. In conclusion, rhinitis alone (local disease) and rhinitis with asthma multimorbidity (systemic disease) should be considered as two distinct diseases, possibly modulated by the microbiome, and may be a model for understanding the epidemics of chronic and auto-immune diseases.

KDBI: Kinetic Data of Bio-molecular Interactions database

Understanding of cellular processes and underlying molecular events requires knowledge about different aspects of molecular interactions, networks of molecules and pathways in addition to the sequence, structure and function of individual molecules involved. Databases of interacting molecules, pathways and related chemical reaction equations have been developed. The kinetic data for these interactions, which is important for mechanistic investigation, quantitative study and simulation of cellular processes and events, is not provided in the existing databases. We introduce a new database of Kinetic Data of Bio-molecular Interactions (KDBI) aimed at providing experimentally determined kinetic data of protein-protein, protein-RNA, protein-DNA, protein-ligand, RNA-ligand, DNA-ligand binding or reaction events described in the literature. KDBI contains information about binding or reaction event, participating molecules (name, synonyms, molecular formula, classification, SWISS-PROT AC or CAS number), binding or reaction equation, kinetic data and related references. The kinetic data is in terms of one or a combination of the following quantities as given in the literature of a particular event: association/dissociation or on/off rate constant, first/second/third/. order rate constant, equilibrium rate constant, catalytic rate constant, equilibrium association/dissociation constant, inhibition constant and binding affinity constant. Each entry can be retrieved through protein or nucleic acid or ligand name, SWISS-PROT AC number, ligand CAS number and full-text search of a binding or reaction event. KDBI currently contains 8273 entries of biomolecular binding or reaction events involving 1380 proteins, 143 nucleic acids and 1395 small molecules. Hyperlinks are provided for accessing references in Medline and available 3D structures in PDB and NDB. This database can be accessed at http://xin.cz3.nus.edu.sg/group/kdbi/kdbi.asp.

Intercomparison of dose enhancement ratio and secondary electron spectra for gold nanoparticles irradiated by X-rays calculated using multiple Monte Carlo simulation codes

PURPOSE

Targeted radiation therapy has seen an increased interest in the past decade. In vitro and in vivo experiments showed enhanced radiation doses due to gold nanoparticles (GNPs) to tumors in mice and demonstrated a high potential for clinical application. However, finding a functionalized molecular formulation for actively targeting GNPs in tumor cells is challenging. Furthermore, the enhanced energy deposition by secondary electrons around GNPs, particularly by short-ranged Auger electrons is difficult to measure. Computational models, such as Monte Carlo (MC) radiation transport codes, have been used to estimate the physical quantities and effects of GNPs. However, as these codes differ from one to another, the reliability of physical and dosimetric quantities needs to be established at cellular and molecular levels, so that the subsequent biological effects can be assessed quantitatively.

METHODS

In this work, irradiation of single GNPs of 50 nm and 100 nm diameter by X-ray spectra generated by 50 and 100 peak kilovoltages was simulated for a defined geometry setup, by applying multiple MC codes in the EURADOS framework.

RESULTS

The mean dose enhancement ratio of the first 10 nm-thick water shell around a 100 nm GNP ranges from 400 for 100 kVp X-rays to 600 for 50 kVp X-rays with large uncertainty factors up to 2.3.

CONCLUSIONS

It is concluded that the absolute dose enhancement effects have large uncertainties and need an inter-code intercomparison for a high quality assurance; relative properties may be a better measure until more experimental data is available to constrain the models.

Quantitative Structure-Pharmacokinetic Relationships for Drug Distribution Properties by Using General Regression Neural Network

Quantitative Structure-Pharmacokinetic Relationships (QSPkR) have increasingly been used for developing models for the prediction of the pharmacokinetic properties of drug leads. QSPkR models are primarily developed by means of statistical methods such as multiple linear regression (MLR). These methods often explore a linear relationship between the pharmacokinetic property of interest and the structural and physicochemical properties of the studied compounds, which are not applicable to those agents with nonlinear relationships. Hence, statistical methods capable of modeling nonlinear relationships need to be developed. In this work, a relatively new kind of nonlinear method, general regression neural network (GRNN), was explored for modeling three drug distribution properties based on diverse sets of drugs. The three properties are blood-brain barrier penetration, binding to human serum albumin, and milk-plasma distribution. The prediction capability of GRNN-developed models was compared to those developed using MLR and a nonlinear multilayer feedforward neural network (MLFN) method. For blood-brain barrier penetration, the computed r(2) and MSE values of the GRNN-, MLR-, and MLFN-developed models are 0.701 and 0.130, 0.649 and 0.154, and 0.662 and 0.147, respectively, by using an independent validation set. The corresponding values for human serum albumin binding are 0.851 and 0.041, 0.770 and 0.079, and 0.749 and 0.089, respectively, and that for milk-plasma distribution are 0.677 and 0.206, 0.224 and 0.647, and 0.201 and 0.587, respectively. These suggest that GRNN is potentially useful for predicting QSPkR properties of chemical agents.

Synthesis and antitumor activity of spin labeled derivatives of podophyllotoxin

Three new nitroxyl labeled derivatives of podophyllotoxin 4-6 have been synthesized and evaluated for their antitumor activity in vitro. Compounds 4-6 showed significant inhibitory activity against human nasopharyngeal carcinoma KB,lung cancer A549 and stomach carcinoma SGC-7901 cells, as well as mouse leukemia L1210 and P388 cells. Compounds 4 and 5 exhibited comparable or superior activity to clinically used etoposide (VP-16,2) in their inhibition of these cell lines.

Genomic structure and mutational analysis of the human KIF1B gene which is homozygously deleted in neuroblastoma at chromosome 1p36.2

In order to clone candidate tumor suppressor genes whose loss contributes to the pathogenesis of neuroblastoma (NB), we performed polymerase chain reaction (PCR) screening using a high-density sequence tagged site-content map within a commonly deleted region (chromosome band 1p36) in 24 NB cell lines. We found a approximately 480 kb homozygously deleted region at chromosome band 1p36.2 in one of the 24 NB cell lines, NB-1, and cloned the human homologue (KIF1B-beta) of the mouseKif1B-beta gene in this region. The KIF1B-beta gene had at least 47 exons, all of which had a classic exon-intron boundary structure. Mouse Kif1B is a microtubule-based putative anterograde motor protein for the transport of mitochondria in neural cells. We performed mutational analysis of the KIF1B-beta gene in 23 cell lines using 46 sets of primers and also an allelic imbalance (AI) analysis of KIF1B-beta in 50 fresh NB samples. A missense mutation at codon 1554, GTG (Gly) to ATG (Met), silent mutations at codon 409 (ACG to ACA) and codon 1721 (ACC to ACT), and polymorphisms at codon 170, GAT (Asp) to GAA (Glu), and at codon 1087, TAT (Tyr), to TGT (Cys), were all identified, although their functional significances remain to be determined. The AI for KIF1B-beta was slightly higher (38%) than those for the other two markers (D1S244, D1S1350) (35 and 32%) within the commonly deleted region (1p36). Reverse transcriptase-PCR analysis of the KIF1B-beta gene revealed obvious expression in all NB cell lines except NB-1, although decreased expression of the KIF1B-beta gene was found in a subset of early- and advanced-stage NBs. These results suggest that the KIF1B-beta gene may not be a candidate for tumor suppressor gene of NB.

The rapid inhibitory effect of glucocorticoid on cytosolic free Ca2+ increment induced by high extracellular K+ and its underlying mechanism in PC12 cells

The effect of glucocorticoid(GC) on peak cytosolic free calcium net increment (delta[Ca2+]i) induced by high-K+ was detected with MiraCal Image System. The main results were as follows: (1) Corticosterone(B) could inhibit delta[Ca2+]i in a time-dependent and concentration-dependent manner. (2) The inhibitory effect of B could be mimicked by bovine-serum albumin conjugated corticosterone (B-BSA) also in a dose-dependent manner. (3) G-protein inhibitor, either PTX or GDP beta S significantly reduced the inhibitory effect of B and B-BSA on delta[Ca2+]i (4) PMA, a stimulator for protein kinase C(PKC), could inhibit delta[Ca2+]i. (5) Although the inhibitors of PKC, chelerythrine chloride and bisindolylamide I per se had no influence on delta[Ca2+]i, but they significantly antagonized the inhibitory effect of B and B-BSA on delta[Ca2+]i. It is postulated that GC inhibit delta[Ca2+]i induced by high-K+ through a membrane mechanism and by a pathway involving G-protein and PKC.

The role of a minor groove spine of hydration in stabilizing poly(dA).poly(dT) against fluctuational interbase H-bond disruption in the premelting temperature regime

Experimental estimates of the premelting Adenine-Thymine base pair opening probability for some B-DNA sequences are two orders of magnitude smaller than those of other B-DNA sequences. The AT pairs in the sequence with smaller open probability seem to be those that have a well defined spine of hydration in the minor groove. We show that this spine of hydration can significantly enhance the thermal stability of the base pairs to which they are attached. The effect of this spine of hydration coupled with the possible stabilization effect contributed from neighboring GC pairs can explain the differences in the observed AT pair opening probability for different AT containing B-DNA sequences.

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).

Expression of estrogen receptor -alpha and -beta immunoreactivity in the cultured neonatal suprachiasmatic nucleus: with special attention to GABAergic neurons

This study investigated the expression patterns of estrogen receptor -alpha (ERalpha) and -beta (ERbeta) in cultured cells of the suprachiasmatic nucleus (SCN) in neonatal rats by combined application of cell culture and double-label immunocytochemistry. The results revealed that the immunoreactivity for either ERalpha or ERbeta (with predominance of ERbeta) was localized in not only neurons but also astrocytes. The co-expression of both ERalpha and ERbeta in the same individual cell was also demonstrated by the double-label immunocytochemistry. The observations also provide a direct evidence for the differential expression of ER subtypes within GABAergic SCN neurons in vitro and suggest that estrogen's effect on the SCN may be mediated at least in part by its ER-containing GABAergic neurons.

Computer automated prediction of potential therapeutic and toxicity protein targets of bioactive compounds from Chinese medicinal plants

Understanding the molecular mechanism and pharmacology of bioactive compounds from Chinese medicinal plants (CMP) is important in facilitating scientific evaluation of novel therapeutic approaches in traditional Chinese medicine. It is also of significance in new drug development based on the mechanism of Chinese medicine. A key step towards this task is the determination of the therapeutic and toxicity protein targets of CMP compounds. In this work, newly developed computer software INVDOCK is used for automated identification of potential therapeutic and toxicity targets of several bioactive compounds isolated from Chinese medicinal plants. This software searches a protein database to find proteins to which a CMP compound can bind or weakly bind. INVDOCK results on three CMP compounds (allicin, catechin and camptotecin) show that 60% of computer-identified potential therapeutic protein targets and 27% of computer-identified potential toxicity targets have been implicated or confirmed by experiments. This software may potentially be used as a relatively fast-speed and low-cost tool for facilitating the study of molecular mechanism and pharmacology of bioactive compounds from Chinese medicinal plants and natural products from other sources.

Some lifestyle factors in human lung cancer: a case-control study of 792 lung cancer cases

In order to investigate the relationship between some lifestyle factors and lung cancer, a case-control study involving all lung cancer deaths registered in 1986 was performed. The results show that among males, 92.5% of the cases and 75.5% of controls were smokers, implying that cigarette smoking is a primary risk factor for lung cancer in males. By contrast, among females only 60.6% of the cases and 30.8% of the controls were smokers, implying factors other than cigarette smoking must be involved in the development of lung cancer in females. The risk of lung cancer in nonsmoking females was found to be unaffected by exposure to environmental tobacco smoke (ETS). A study of diet and eating habits showed that in males the risk of lung cancer was reduced by the intake of vegetables and fruits, but was significantly increased by a frequent intake of fried foods. The positive association between the intake of fried food and the risk of lung cancer could result from cooking practices and from inappropriate methods used in food preparation. No association can be demonstrated between the consumption of high protein or high fat diets, salty and smoked food items and the incidence of lung cancer. Thus, it is not likely that sufficient lung cancer inducing carcinogens can be generated through the intake of food. In addition, the positive association found to exist between the living index and the risk of lung cancer in females is consistent with the notion that coal smoke or cooking practices may generate sufficient indoor air pollutants to significantly increase the risk of lung cancer in females.

The inhaled Steroid Treatment as Regular Therapy in early asthma (START) study: rationale and design

Although the beneficial effects of treatment with inhaled steroids in asthma are widely accepted, the role of early intervention in patients with mild asthma remains unsettled. Conventional efficacy trials are often of short duration and involve highly selected patient populations that exclude many patients typical of those encountered in routine clinical practice. Hence, a large "real-world" effectiveness study is needed to evaluate the benefits of early intervention with inhaled steroids in patients with mild, persistent asthma. In the START (inhaled Steroid Treatment As Regular Therapy in early asthma) study, patients ages 6-60 years, from 31 countries and districts worldwide with mild persistent asthma, have been randomized to once-daily treatment with budesonide, 200 microg (for patients < 11 years) or 400 microg (for patients > or = 11 years), or placebo via Turbuhaler for 3 years. The double-blind treatment period will be followed by a 2-year period of open budesonide treatment. Throughout the study, other asthma medication including glucocorticosteroids can be given as judged appropriate by the investigator. Lung function will be measured by spirometry using standardized techniques at 3-month intervals throughout the study, and bronchodilator reversibility will be measured annually. The primary outcome measures are the time to the first severe asthma-related event during the first 3 years of the study and the change in postbronchodilator forced expiratory volume in 1 second (FEV(1)) from baseline during the entire 5-year study period. These measures have been chosen to reflect the progression of mild asthma toward more severe asthma and the extent of irreversible airflow limitation, which should reflect the degree of airway remodeling.

Tea and premenstrual syndrome in the People's Republic of China

We evaluated the hypothesis that tea consumption causes premenstrual syndrome by studying 188 nursing students and tea factory workers in the People's Republic of China via questionnaires distributed in classes (nursing students) or during routine physical examinations (tea factory workers). Analysis of the data revealed that tea consumption is strongly related to the prevalence of premenstrual syndrome and that the effects are dose-dependent.

Specificity of human anti-variable heavy (VH ) chain autoantibodies and impact on the design and clinical testing of a VH domain antibody antagonist of tumour necrosis factor-α receptor 1

During clinical trials of a tumour necrosis factor (TNF)-R1 domain antibody (dAb™) antagonist (GSK1995057), infusion reactions consistent with cytokine release were observed in healthy subjects with high levels of a novel, pre-existing human anti-VH (HAVH) autoantibody. In the presence of HAVH autoantibodies, GSK1995057 induced cytokine release in vitro due to binding of HAVH autoantibodies to a framework region of the dAb. The epitope on GSK1995057 was characterized and dAbs with reduced binding to HAVH autoantibodies were generated; pharmacological comparability was determined in human in-vitro systems and in-vivo animal experiments. A Phase I clinical trial was conducted to investigate the safety and tolerability of the modified dAb (GSK2862277). A significant reduction in HAVH binding was achieved by adding a single alanine residue at the C-terminus to create GSK2862277. Screening a pool of healthy donors demonstrated a reduced frequency of pre-existing autoantibodies from 51% to 7%; in all other respects, GSK2862277 and the parent dAb were comparable. In the Phase I trial, GSK2862277 was well tolerated by both the inhaled and intravenous routes. One subject experienced a mild infusion reaction with cytokine release following intravenous dosing. Subsequently, this subject was found to have high levels of a novel pre-existing antibody specific to the extended C-terminus of GSK2862277. Despite the reduced binding of GSK2862277 to pre-existing HAVH autoantibodies, adverse effects associated with the presence of a novel pre-existing antibody response specific to the modified dAb framework were identified and highlight the challenge of developing biological antagonists to this class of receptor.

Triterpenoid saponins from Clematis tangutica

Two new triterpenoid saponins, tanguticoside A and B along with seven known saponins vitalboside B, alpha-hederin, saponin PK, beta-hederin, saponin PJ3, saponin PE, and ciwujianoside A were isolated from aerial part of Clematis tangutica. By chemical and spectral evidences methods, the structures of tanguticoside A and B were elucidated as 3-O-beta-D-glucopyranosylhederagenin 28-O-alpha-L-rhamnopyranosyl-(1-->4)-beta-D-glucopyranosyl-(1-->6)-beta-D-glucopyranoside and 3-O-beta-D-glucopyranosyl-(1-->2)-beta-D-glucopyranosylhederagenin 28-O-alpha-D-rhamnopyranosyl-(1-->4)-beta-D-glucopyranosyl-(1-->6)-beta-D-glucopyranoside, respectively.