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Background: Glucocorticoids (GCs) play a key role in the treatment of seasonal allergic rhinitis (SAR). However, some patients show a low response to GC treatment. We hypothesized that proteins that correlated to discrimination between symptomatic high and low responders (HR and LR) to GC treatment might be regulated by GCs and therefore suitable as biomarkers for GC treatment., Methodology/principal Findings: We identified 953 nasal fluid proteins in symptomatic HR and LR with a LC MS/MS based-quantitative proteomics analysis and performed multivariate analysis to identify a combination of proteins that best separated symptomatic HR and LR. Pathway analysis showed that those proteins were most enriched in the acute phase response pathway. We prioritized candidate biomarkers for GC treatment based on the multivariate and pathway analysis. Next, we tested if those candidate biomarkers differed before and after GC treatment in nasal fluids from 40 patients with SAR using ELISA. Several proteins including ORM (P<0.0001), APOH (P<0.0001), FGA (P<0.01), CTSD (P<0.05) and SERPINB3 (P<0.05) differed significantly before and after GC treatment. Particularly, ORM (P<0.01), FGA (P<0.05) and APOH (P<0.01) that belonged to the acute phase response pathway decreased significantly in HR but not LR before and after GC treatment., Conclusions/significance: We identified several novel biomarkers for GC treatment response in SAR with combined proteomics, multivariate and pathway analysis. The analytical principles may be generally applicable to identify biomarkers in clinical studies of complex diseases.

A new set of amino acid descriptor scales was recently introduced. The new scales relate to amino acid side chain (i) rigidity and (ii) flexibility. These two properties were found to be orthogonal to each other. In this study, (i) the understanding of their meaning is improved, (ii) their utility further corroborated, and (iii) the scope of their applicability is broadened. Notably, the rigidity and flexibility scales are benchmarked against previous amino acid description precedence and found to contribute (1) new information, and (2) direct interpretation. The suggested description extensions were tested using empirical data from peptide description and in quantitative structure-activity relationships (QSAR).

A set of compounds designed to bind to the S2-S3 pockets of thrombin was prepared. These compounds included examples with no interactions in the S1 pocket. Proline, a common P2 in many thrombin inhibitors, was combined with known P3 residues and P1 substituents of varying size and lipophilicity. Binding constants were determined using surface plasmon resonance (SPR) biosensor technology and were found to be in good agreement with results from an enzyme assay. A dramatic increase in affinity (100-1000 times) was seen for compounds incorporating an amino group capable of forming a hydrogen bond with gly216 in the protein backbone. The ligand efficiency was increased by including substituents that form stronger hydrophobic interactions with the P1 pocket. The binding mode was confirmed by X-ray analysis, which revealed the anticipated binding motif that included hydrogen bonds as well as a tightly bound water molecule. A QSAR model indicated that hydrogen bonding and lipophilicity were important for the prediction of binding constants. The results described here may have implications for how directed compound libraries for shallow protein pockets, like S2 and S3 in serine proteases, can be designed.

Natural products (NPs) are a rich source of novel compound classes and new drugs. In the present study we have used the chemical space navigation tool ChemGPS-NP to evaluate the chemical space occupancy by NPs and bioactive medicinal chemistry compounds from the database WOMBAT. The two sets differ notably in coverage of chemical space, and tangible leadlike NPs were found to cover regions of chemical space that lack representation in WOMBAT. Property based similarity calculations were performed to identify NP neighbors of approved drugs. Several of the NPs revealed by this method were confirmed to exhibit the same activity as their drug neighbors. The identification of leads from a NP starting point may prove a useful strategy for drug discovery in the search for novel leads with unique properties.

Internet has become a central source for information, tools, and services facilitating the work for medicinal chemists and drug discoverers worldwide. In this paper we introduce a web-based public tool, ChemGPS-NP(Web) (http://chemgps.bmc.uu.se), for comprehensive chemical space navigation and exploration in terms of global mapping onto a consistent, eight dimensional map over structure derived physico-chemical characteristics. ChemGPS-NP(Web) can assist in compound selection and prioritization; property description and interpretation; cluster analysis and neighbourhood mapping; as well as comparison and characterization of large compound datasets. By using ChemGPS-NP(Web), researchers can analyze and compare chemical libraries in a consistent manner. In this study it is demonstrated how ChemGPS-NP(Web) can assist in interpreting results from two large datasets tested for activity in biological assays for pyruvate kinase and Bcl-2 family related protein interactions, respectively. Furthermore, a more than 30-year-old suggestion of "chemical similarity" between the natural pigments betalains and muscaflavins is tested.

Near infrared spectroscopy (NIR) was developed primarily for applications such as the quantitative determination of nutrients in the agricultural and food industries. Examples include the determination of water, protein, and fat within complex samples such as grain and milk. Because of its useful properties, NIR analysis has spread to other areas such as chemistry and pharmaceutical production. NIR spectra consist of infrared overtones and combinations thereof, making interpretation of the results complicated. It can be very difficult to assign peaks to known constituents in the sample. Thus, multivariate analysis (MVA) has been crucial in translating spectral data into information, mainly for predictive purposes. Orthogonal partial least squares (OPLS), a new MVA method, has prediction and modeling properties similar to those of other MVA techniques, e.g., partial least squares (PLS), a method with a long history of use for the analysis of NIR data. OPLS provides an intrinsic algorithmic improvement for the interpretation of NIR data. In this report, four sets of NIR data were analyzed to demonstrate the improved interpretation provided by OPLS. The first two sets included simulated data to demonstrate the overall principles; the third set comprised a statistically replicated design of experiments (DoE), to demonstrate how instrumental difference could be accurately visualized and correctly attributed to Wood's anomaly phenomena; the fourth set was chosen to challenge the MVA by using data relating to powder mixing, a crucial step in the pharmaceutical industry prior to tabletting. Improved interpretation by OPLS was demonstrated for all four examples, as compared to alternative MVA approaches. It is expected that OPLS will be used mostly in applications where improved interpretation is crucial; one such area is process analytical technology (PAT). PAT involves fewer independent samples, i.e., batches, than would be associated with agricultural applications; in addition, the Food and Drug Administration (FDA) demands "process understanding" in PAT. Both these issues make OPLS the ideal tool for a multitude of NIR calibrations. In conclusion, OPLS leads to better interpretation of spectrometry data (e.g., NIR) and improved understanding facilitates cross-scientific communication. Such improved knowledge will decrease risk, with respect to both accuracy and precision, when using NIR for PAT applications.

We have previously demonstrated that the prototypical GABA B receptor agonist baclofen inhibits transient lower esophageal sphincter relaxations (TLESRs), the most important mechanism for gastroesophageal reflux. Thus, GABA B agonists could be exploited for the treatment of gastroesophageal reflux disease. However, baclofen, which is used as an antispastic agent, and other previously known GABA B agonists can produce CNS side effects such as sedation, dizziness, nausea, and vomiting at higher doses. We now report the discovery of atypical GABA B agonists devoid of classical GABA B agonist related CNS side effects at therapeutic doses and the optimization of this type of compound for inhibition of TLESRs, which has resulted in a candidate drug ( R)- 7 (AZD3355) that is presently being evaluated in man.

The authors present fragment screening data obtained using a label-free parallel analysis approach where the binding of fragment library compounds to 4 different target proteins can be screened simultaneously using surface plasmon resonance detection. They suggest this method as a first step in fragment screening to identify and select binders, reducing the demanding requirements on subsequent X-ray or nuclear magnetic resonance studies, and as a valuable "clean-up" tool to eliminate unwanted promiscuous binders from libraries. A small directed fragment library of known thrombin binders and a general 500-compound fragment library were used in this study. Thrombin, blocked thrombin, carbonic anhydrase, and glutathione-S-transferase were immobilized on the sensor chip surface, and the direct binding of the fragments was studied in real time. Only 12 microg of each protein is needed for screening of a 3000-compound fragment library. For screening, a binding site-blocked target as reference facilitates the identification of binding site-selective hits and the signals from other reference proteins for the elimination of false positives. The scope and limitations of this screening approach are discussed for both target-directed and general fragment libraries.

Metabolomics studies generate increasingly complex data tables, which are hard to summarize and visualize without appropriate tools. The use of chemometrics tools, e.g., principal component analysis (PCA), partial least-squares to latent structures (PLS), and orthogonal PLS (OPLS), is therefore of great importance as these include efficient, validated, and robust methods for modeling information-rich chemical and biological data. Here the S-plot is proposed as a tool for visualization and interpretation of multivariate classification models, e.g., OPLS discriminate analysis, having two or more classes. The S-plot visualizes both the covariance and correlation between the metabolites and the modeled class designation. Thereby the S-plot helps identifying statistically significant and potentially biochemically significant metabolites, based both on contributions to the model and their reliability. An extension of the S-plot, the SUS-plot (shared and unique structure), is applied to compare the outcome of multiple classification models compared to a common reference, e.g., control. The used example is a gas chromatography coupled mass spectroscopy based metabolomics study in plant biology where two different transgenic poplar lines are compared to wild type. By using OPLS, an improved visualization and discrimination of interesting metabolites could be demonstrated.

Natural compounds are evolutionary selected and prevalidated by Nature, displaying a unique chemical diversity and a corresponding diversity of biological activities. These features make them highly interesting for studies of chemical biology, and in the pharmaceutical industry for development of new leads. Of utmost importance, for the discovery of new biologically active compounds, is the identification and charting of the corresponding biologically relevant chemical space. The primary key to this is the coverage of the natural products' chemical space. Here we introduce ChemGPS-NP, a new tool tuned for handling the chemical diversity encountered in natural products research, in contrast to previous tools focused on the much more restricted drug-like chemical space. The aim is to provide a framework for making compound classification and comparison more efficient and stringent, to identify volumes of chemical space related to particular biological activities, and to track changes in chemical properties due to, for example, evolutionary traits and modifications in biosynthesis. Physical-chemical properties not directly discernible from structural data can be discovered, making selection more efficient and increasing the probability of hit generation when screening natural compounds and analogues.

This investigation describes the discovery of novel possible cerebrospinal fluid (CSF) biomarkers for frontotemporal dementia (FTD) using surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS). Sixteen clinically diagnosed FTD patients and 12 non-demented controls were included in the study. CSF was collected and analyzed for protein expression by SELDI-TOF MS. The samples were analyzed on four different array surfaces using two different energy-absorbing molecules as matrices. In total each sample was subjected to eight different surface/matrix conditions. About 2000 protein peaks (mass/charge ratios) were detected. Forty-two peaks were differentially expressed in FTD (P < 0.01). After exclusion of peaks with low signal-to-noise ratio and/or poor resolution and peaks representing differentially charged proteins, 10 peaks remained, five of which were increased and five decreased in FTD cases compared to controls. Using partial least square discriminant analysis (PLS-DA), the combination of these biomarkers discriminated FTD from non-demented controls with a sensitivity of 94%, a specificity of 83% and an accuracy of 89%. Five of the peaks were purified further and identified by tandem MS as a fragment of neurosecretory protein VGF, transthyretin, S-cysteinylated transthyretin, truncated cystatin C and a fragment of chromogranin B. With use of these potential biomarkers, FTD can be distinguished from control subjects with high accuracy in this pilot study.

Recently various attempts have been made to increase the efficacy and precision of chemical libraries used in high-throughput screening (HTS) drug discovery approaches. One such approach is ChemGPS, which provides a defined chemical space for prescreening evaluation of chemical compound properties or virtual dereplication. In the present study, ChemGPS has been applied to a set of natural products shown to exhibit cyclooxygenase-1 and/or -2 (COX-1/2) inhibition. With the purpose of defining chemical properties and linking these to the observed mode of enzyme inhibition, this resulted in two lines of reasoning. On one hand several specific features of these compounds have been identified and discussed. Overall COX inhibition was frequently correlated with the presence of at least one ring in the structure, fragments exhibiting structural rigidity, and a relatively large molecular size. The concept "size" includes several parameters, e.g., molecular volume, weight, and number of bonds. On the other hand, and possibly even more important, was the unexpected finding that the natural products studied to a large extent fell outside the defined ChemGPS chemical space. Therefore, we also propose an expanded space for natural products: ChemGPS-NP.

Capillary electrophoresis (CE) was evaluated as an in-vitro format for experimental modelling of membrane permeability using only nanogram quantities of drug compounds. The rationale for the CE technique emanates from emulation of a lipid-like pseudo-stationary phase that governs separations mainly as a result of differences in molecular size, lipophilicity, hydrogen bonding and charge, all of which also have a strong influence on in-vivo drug absorption. By means of micellar, microemulsion and liposome electrolytes, the migration behaviour was studied at 37 degrees C for 22 model drug compounds. The generated CE retention factor data were then compared with membrane permeability reference data. Both simple log D and more common Caco-2 cell parameters were evaluated. In addition, permeation through intestinal segments of rat ileum and rat colon was included. An improved correlation was obtained in the order: micellar < microemulsion < liposome systems. Although the correlation for the best liposome CE system was only R(2)=0.77, the evaluation results for all emphasized the strength and flexibility of CE for assessing specific drug-membrane interaction through tailor-made lipophilic media.

Diagnosing clinical dementia is based on an assessment of different variables, such as the patient's medical history, known risk factors, and biochemical features. Partial least squares discriminant analysis was used to evaluate variables of importance for diagnosing dementia in a clinical dementia population. Polymorphism for genotypes of glutathione S-transferase (GST) and sulfotransferase 1A1, hypothetically of importance in dementia disorders, was also included in the analysis. The study population consisted of 73 patients with Alzheimer's disease (AD), 14 with mixed dementia, 75 patients with vascular dementia, and 28 control cases. We found that several of the variables, such as the presence of ApoE4 allele, high cerebrospinal fluid levels of total tau protein, low levels of beta-amyloid((1-42)), and a low score on the Mini-Mental State Examination, facilitated a discrimination between the diagnoses compared with the controls. The different diagnoses overlapped. There were indications that genotypes of GSTs contributed to a subgrouping within AD.

This article describes the applicability of multivariate projection techniques, such as principal-component analysis (PCA) and partial least-squares (PLS) projections to latent structures, to the large-volume high-density data structures obtained within genomics, proteomics, and metabonomics. PCA and PLS, and their extensions, derive their usefulness from their ability to analyze data with many, noisy, collinear, and even incomplete variables in both X and Y. Three examples are used as illustrations: the first example is a genomics data set and involves modeling of microarray data of cell cycle-regulated genes in the microorganism Saccharomyces cerevisiae. The second example contains NMR-metabonomics data, measured on urine samples of male rats treated with either of the drugs chloroquine or amiodarone. The third and last data set describes sequence-function classification studies in a set of G-protein-coupled receptors using hierarchical PCA.

OMEGA is a rule-based program which rapidly generates conformational ensembles of small molecules. We have varied the parameters which control the nature of the ensembles generated by OMEGA in a statistical fashion (D-optimal) with the aim of increasing the probability of generating bioactive conformations. Thirty-six drug-like ligands from different ligand-protein complexes determined by high-resolution (< or =2.0A) X-ray crystallography have been analyzed. Statistically significant models (Q(2)> or =0.75) confirm that one can increase the performance of OMEGA by modifying the parameters. Twenty-eight of the bioactive conformations were retrieved when using a low-energy cut-off (5 kcal/mol), a low RMSD value (0.6A) for duplicate removal, and a maximum of 1000 output conformations. All of those that were not retrieved had eight or more rotatable bonds. The duplicate removal parameter was found to have the largest impact on retrieval of bioactive conformations, and the maximum number of conformations also affected the results considerably. The input conformation was found to influence the results largely because certain bond angles can prevent the bioactive conformation from being generated as a low-energy conformation. Pre-optimizing the input structures with MMFF94s improved the results significantly. We also investigated the performance of OMEGA in connection with database searching. The shape-matching program Rapid Overlay of Chemical Structures (ROCS) was used as search tool. Two multi-conformational databases were built from the MDDR database plus the 36 compounds; one large (maximum 1000 conformations/mol) and one small (maximum 100 conformations/mol). Both databases provided satisfactory results in terms of retrieval. ROCS was able to rank 35 out of 36 X-ray structures among the top 500 hits from the large database.

The two most frequently examined biomarkers in the diagnosis of dementia are cerebrospinal fluid (CSF) tau and beta-amyloid(1-42) (Abeta(1-42)). An assay for tau phosphorylated at threonine 181 (phospho-tau) has recently been developed. We studied these three markers in patients with possible Alzheimer's disease (AD; n = 23), probable AD (n = 50), AD with relevant cerebrovascular disease (AD with CVD; n = 14), possible vascular dementia (VaD; n = 39), probable VaD (n = 36), cognitively impaired (n = 13) and 27 neurologically healthy controls. Compared with the controls, tau levels were significantly increased in possible AD, probable AD, AD with CVD and probable VaD. Abeta(1-42) was decreased in all dementia groups compared with the controls. In contrast, phospho-tau levels were increased only in probable AD compared with the controls. From the results of the present study, it is concluded that neither measurement of phospho-tau, tau nor Abeta(1-42) in CSF can discriminate entirely between dementia and cognitively non-disturbed controls or between dementia of different aetiologies in the clinical diagnostic procedure., (Copyright 2002 S. Karger AG, Basel)

Cerebrospinal fluid (CSF) levels of tau (total tau), growth-associated protein-43 (GAP-43), soluble amyloid precursor protein (sAPP; i.e. total sAPP), and beta-amyloid(42) (Abeta(42)) were studied in patients with frontotemporal dementia (FTD; n = 14), Alzheimer's disease (AD; n = 47) and vascular dementia (VAD; n = 16), and in age-matched controls (n = 12). CSF-tau was increased in AD compared to controls and FTD (p < 0.001 for both). CSF-GAP-43 was increased in AD compared to controls (p < 0.05), and both CSF-GAP-43 and CSF-sAPP were increased in AD compared to FTD (p < 0.01). Positive and highly significant correlations were found between CSF-tau and CSF-GAP-43 in all groups and between CSF-tau, CSF-GAP-43 and CSF-sAPP in AD. The correlations found may reflect a common pathophysiologic process such as axonal degeneration., (Copyright 2001 S. Karger AG, Basel)

There is considerable enthusiasm for the prospect of using common polymorphisms (primarily single nucleotide polymorphisms; SNPs) in candidate genes to unravel the genetics of complex disease. This approach has generated a number of findings of loci which are significantly associated with sporadic Alzheimer's disease (AD). In the present study, a total of 15 genes of interest were chosen from among the previously published reports of significant association in AD. Genotyping was performed on polymorphisms within those genes (14 SNPs and one deletion) using Dynamic Allele Specific Hybridization (DASH) in 204 Swedish patients with sporadic late-onset AD and 186 Swedish control subjects. The genes chosen for analysis were; low-density lipoprotein receptor-related protein (LRP1), angiotensin converting enzyme (DCP1), alpha-2-macroglobulin (A2M), bleomycin hydrolase (BLMH), dihydrolipoyl S-succinyltransferase (DLST), tumour necrosis factor receptor superfamily member 6 (TNFRSF6), nitric oxide synthase (NOS3), presenilin 1 (PSEN1), presenilin 2 (PSEN2), butyrylcholinesterase (BCHE), Fe65 (APBB1), oestrogen receptor alpha (ESR1), cathepsin D (CTSD), methylenetetrahydrofolate reductase (MTHFR), and interleukin 1A (IL1A). We found no strong evidence of association for any of these loci with AD in this population. While the possibility exists that the genes analysed are involved in AD (ie they have weak effects and/or are population specific), results reinforce the need for extensive replication studies if we are to be successful in defining true risk factors in complex diseases.

Structure-property relationships, central to many of today's drug discovery strategies, are not straightforward to deal with when trying to predict drug efficacy, that is, the combined outcome of target affinity, pharmacodynamic behavior, pharmacokinetic properties, and metabolic fate. In this article, we discuss the handling of chemical property information in reagents-for-synthesis selection, enumeration, and virtual library construction. We describe the use of diversity assessment and/or experimental design in selection of compound-libraries-to-be-synthesized. Our overall objective was to identify good-quality drug candidates through reliable structure-activity relationship data, with the minimum number of compounds synthesized and tested. Chemical filters, property filters, scoring functions, and utilization of interactive visualization tools are discussed. The concept of chemical diversity and aspects of chemical space navigation employing a proprietary tool, Chemical Global Positioning System (ChemGPS), for mapping the drug-related chemical space are examined. Guidelines and workflow recommendations for the practicing medicinal chemist are proposed.

A method is described which enables real-time analysis of film coating on pharmaceutical pellets during an industrial manufacturing process. Measurements were conducted on the solid particulate material by near-infrared (NIR) spectrometry utilizing a diffuse reflectance fiber-optic probe positioned inside a fluidized bed process vessel. Time series of NIR spectra from 11 batches generated a three-way data matrix that was unfolded and modeled by partial least squares (PLS) in a multivariate batch calibration. The process conditions were deliberately varied according to an experimental design. This yielded good predictability of the coating thickness with a best model fit, R2 = 0.97, for one PLS-projection, and a root-mean-square error of calibration = 2.2 microm (range tested 0-50 microm). The regression vector was shown to be highly influenced by responses that are both direct (aliphatic C-H stretch overtones) and indirect (aromatic C-H stretch overtones), from film component and core material, respectively. The impact of different data pre-treatment methods on the normalization of the regression vector is reported. Justification of the process calibration approach is emphasized by good correlation between values predicted from NIR data and reference image analysis data on dissected pellets and a theoretical nonlinear coating thickness growth model. General aspects of in-line NIR on solids and multivariate batch calibration are discussed.

Twenty patients with Alzheimer's disease (AD), 34 with senile dementia of the Alzheimer type (SDAT) and 12 with vascular dementia (VAD) were carefully investigated. The diagnoses were made according to the DSM-III-R criteria and for AD/SDAT also according to the NINCDS-ADRDA criteria. The data set consisted of 29 descriptor variables obtained at the examination, and the data were fitted to a partial least squares model using dummy variables for the response variables (i.e. clinical diagnoses). The distribution of the scores over the descriptor variable space revealed adequate classification regarding all three diagnoses, with some overlap between SDAT and AD and between VAD and SDAT. The study demonstrates a clear difference in symptomatology between AD and SDAT with no influence of age per se or the severity of dementia.

The ganglioside concentration and composition were determined in 42 human fetal brains from gestational week 10 to 22, a period that is morphologically characterized by rapid neuroblast proliferation and migration. The ganglioside concentration was constant during this period, approximately 1 mumol of ganglioside sialic acid/g of fresh tissue weight. At gestational week 10 the ganglioside pattern was dominated by gangliosides of the ganglio b series, with the major ganglioside being GT1b, contributing 40% of total ganglioside sialic acid, whereas GD1b and GD3 contributed only 15 and 10%, respectively. The proportion of b series ganglioside decreased to gestational week 22, with the most pronounced relative reduction affecting GD3, but also GT1b and GD1b to a lesser extent. The ganglioside GQ1b increased in content from gestational week 10 and peaked around week 16. The proportion of GD1a increased markedly between gestational week 12 and 14 and slowly between week 14 and 18 and then increased rapidly from week 20. Ganglioside GM1 underwent a similar change. Gangliosides of the lacto series contributed 6-10% of ganglioside sialic acid between gestational week 10 and 15, and thereafter the proportion slowly decreased. 3'-isoLM1 decreased rapidly in content from gestational week 10 (20 nmol/g of fresh weight) to week 22 (less than 0.5 nmol/g of fresh weight), whereas the gangliosides of the neolacto series (3'-LM1 and 3',8'-LD1) showed a slower and less marked decline in level. The biological significance of the ganglioside changes is discussed.

The developmental pattern of gangliosides in human fetal brain should reflect the activities of the respective glycosyltransferases. LA2-synthase activity, along with that of GM3-, GD3-, GM2-, and GM1-synthases, was determined in human fetal brain at 10-22 weeks of gestation. LA2-synthase is the pivotal enzyme in lacto series ganglioside formation. LA2-synthase activity decreased during the study period, mirroring a similar temporal decline in levels of the lacto series gangliosides, particularly 3'-isoLM1. The developmental profiles of the ganglio series glycosyltransferase activities demonstrate distinct changes that correspond to the ganglioside pattern between fetal weeks 10 and 22. In particular, the marked increase in GM2-synthase activity at 20 and 22 weeks of gestation and the decline in GD3-synthase activity after 15 weeks could explain the prominent expression of the a series gangliosides in this period of rapid neuronal outgrowth. However, a similar decline (two- to 2.5-fold) in GM3-synthase activity suggests a more likely conclusion, namely, that the two sialyltransferase activities are derived mainly from astroglial cells, which show a marked proliferation during the 10-15th fetal weeks. The data do not negate the hypothesis that GM3- and GD3-synthase are the critical enzymes in the regulation of ganglioside biosynthesis but do indicate a need to reevaluate the significance of GM2-synthase in expression of the a series gangliosides.

Medulloblastoma biopsies are heterogenous and might contain normal brain tissue, which limits the usefulness of such tumor material for biochemical analyses. We have, therefore, examined the gangliosides and their metabolism using the medulloblastoma cell lines. Daoy and D341 Med, cultured both in vitro and as xenografts in nude mice. The ganglioside patterns in the Daoy showed a switch from a high GM2, 70% (mol% of total ganglioside sialic acid) and low lactoseries gangliosides (2%) content in monolayer cultures, to a high proportion of lactoseries gangliosides (50%) and virtually no GM2 (1%) in xenografts, but an increased proportion of other a-series gangliosides. The D341 Med showed a similar change regarding the lacto-series gangliosides from 1% in suspension culture to 10% in xenografts. The activity of five glycosyltransferases, GM3, GD3, GM2, GM1 and LA2 synthases, did not parallel the ganglioside patterns and could not account for the noted variations therein. In the Daoy cell line the LA2 synthase as well as the GM2 synthase activity was relatively high in both culture systems, despite the marked difference in the expression of GM2 and the lactoseries gangliosides. These results suggest that environmental factors play a crucial role for the in vivo activity of the glycosyltransferases.

The ganglioside composition of six human medulloblastomas was analyzed. The characterization was performed by thin-layer chromatography, sialidase hydrolysis, and immunological staining with a panel of characterized antiganglioside monoclonal antibodies. The total ganglioside content ranged from 60 to 1,130 nmol of ganglioside sialic acid/g wet weight. Neuronal gangliosides (gangliotetraose series) were found in varying amounts in all medulloblastomas. Gangliosides of the neolactotetraose series (3'-LM1 and LD1) were present in all specimens, and the lactotetraose series ganglioside 3'-isoLM1 was found in all cases showing astrocytic differentiation. This supports our previous findings that 3'-isoLM1 is a marker for proliferating astroglial cells.

Utilizing reversed-phase high-performance liquid chromatography (HPLC) with electrochemical detection and optimization of the mobile phase using factorial designs and a constructed computer program to predict chromatograms, it has been possible to obtain a satisfactory resolution of seventeen of the major monoamine neurotransmitters, precursors and metabolites. A rapid (less than 25 min) isocratic system for the simultaneous determination of 3,4-dihydroxyphenylalanine, dopamine, dihydroxyphenylacetic acid, 3-methoxytyramine, homovanillic acid, norepinephrine, normetanephrine, 3,4-dihydroxyphenylethylene glycol, 3-methoxy-4-hydroxyphenylethylene glycol, epinephrine, metanephrine, vanillylmandelic acid, 5-hydroxytryptophan, serotonin, 5-hydroxytryptophol and 5-hydroxyindoleacetic acid in addition to the internal standard isoproterenol is presented. The optimization strategy included selection of variables to optimize by a reduced factorial design a detailed study of these variables by a complete factorial design, theoretical predictions of chromatograms by a constructed computer program and test on the HPLC system. This optimization strategy can easily be applied to any problem of solute separation by liquid chromatography.

The optimized chromatographic method procedure presented in Part I was employed for the assessment of human brain and cerebrospinal fluid neurotransmitters levels. The optimized sample preparation and chromatographic conditions permitted a rapid (less than 25 min), sensitive and semi-automated high-performance liquid chromatographic analysis which measures all major monoamine neurotransmitters, precursors and metabolites in human brain and cerebrospinal fluid. The brain specimen was deproteinized with perchloric acid (containing Na2EDTA and sodium sulphite), the internal standard and heparin were added and the samples were sonicated, centrifuged, filtered and injected directly into the chromatographic system. Cerebrospinal fluid was handled in a similar manner except that sonication was excluded. The regional distribution of monoamine neurotransmitter concentrations in human brain and cerebrospinal fluid is presented.

The biogenic amines, dopamine, serotonin, and noradrenaline, and their respective metabolites, homovanillic acid, 5-hydroxyindoleacetic acid, and hydroxymethoxyphenylglycol, were measured in selected brain regions obtained at postmortem examination from 4 patients, ages 12-30 years, with typical features of Rett syndrome. A 50% or greater reduction in each compound, except hydroxymethoxyphenylglycol, was observed in the substantia nigra from the 2 older patients, while the youngest patient had normal or nearly normal levels. These results correspond with the most consistent neuropathologic finding in Rett syndrome, reduced melanin content in neurons of the substantia nigra.