Genome-wide DNA Methylation Profiling in Lyme Neuroborreliosis Reveals Altered Methylation Patterns of HLA Genes

Lyme neuroborreliosis (LNB) is a complex neuroinflammatory disorder caused by Borrelia burgdorferi, which is transmitted through tick bites. Epigenetic alterations, specifically DNA methylation (DNAm), could play a role in the host immune response during infection. In this study, we present the first genome-wide analysis of DNAm in peripheral blood mononuclear cells from patients with LNB and those without LNB. Using a network-based approach, we highlighted HLA genes at the core of these DNAm changes, which were found to be enriched in immune-related pathways. These findings shed light on the role of epigenetic modifications in the LNB pathogenesis that should be confirmed and further expanded upon in future studies.

Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis

Sensitive and reliable protein biomarkers are needed to predict disease trajectory and personalize treatment strategies for multiple sclerosis (MS). Here, we use the highly sensitive proximity-extension assay combined with next-generation sequencing (Olink Explore) to quantify 1463 proteins in cerebrospinal fluid (CSF) and plasma from 143 people with early-stage MS and 43 healthy controls. With longitudinally followed discovery and replication cohorts, we identify CSF proteins that consistently predicted both short- and long-term disease progression. Lower levels of neurofilament light chain (NfL) in CSF is superior in predicting the absence of disease activity two years after sampling (replication AUC = 0.77) compared to all other tested proteins. Importantly, we also identify a combination of 11 CSF proteins (CXCL13, LTA, FCN2, ICAM3, LY9, SLAMF7, TYMP, CHI3L1, FYB1, TNFRSF1B and NfL) that predict the severity of disability worsening according to the normalized age-related MS severity score (replication AUC = 0.90). The identification of these proteins may help elucidate pathogenetic processes and might aid decisions on treatment strategies for persons with MS.

Prominent epigenetic and transcriptomic changes in CD4+ and CD8+ T cells during and after pregnancy in women with multiple sclerosis and controls

BACKGROUND

Multiple sclerosis (MS) is a neuroinflammatory disease in which pregnancy leads to a temporary amelioration in disease activity as indicated by the profound decrease in relapses rate during the 3rd trimester of pregnancy. CD4⁺ and CD8⁺ T cells are implicated in MS pathogenesis as being key regulators of inflammation and brain lesion formation. Although Tcells are prime candidates for the pregnancy-associated improvement of MS, the precise mechanisms are yet unclear, and in particular, a deep characterization of the epigenetic and transcriptomic events that occur in peripheral T cells during pregnancy in MS is lacking.

METHODS

Women with MS and healthy controls were longitudinally sampled before, during (1st, 2nd and 3rd trimesters) and after pregnancy. DNA methylation array and RNA sequencing were performed on paired CD4⁺ and CD8⁺ T cells samples. Differential analysis and network-based approaches were used to analyze the global dynamics of epigenetic and transcriptomic changes.

RESULTS

Both DNA methylation and RNA sequencing revealed a prominent regulation, mostly peaking in the 3rd trimester and reversing post-partum, thus mirroring the clinical course with improvement followed by a worsening in disease activity. This rebound pattern was found to represent a general adaptation of the maternal immune system, with only minor differences between MS and controls. By using a network-based approach, we highlighted several genes at the core of this pregnancy-induced regulation, which were found to be enriched for genes and pathways previously reported to be involved in MS. Moreover, these pathways were enriched for in vitro stimulated genes and pregnancy hormones targets.

CONCLUSION

This study represents, to our knowledge, the first in-depth investigation of the methylation and expression changes in peripheral CD4⁺ and CD8⁺ T cells during pregnancy in MS. Our findings indicate that pregnancy induces profound changes in peripheral T cells, in both MS and healthy controls, which are associated with the modulation of inflammation and MS activity.

RNA-sequencing and mass-spectrometry proteomic time-series analysis of T-cell differentiation identified multiple splice variants models that predicted validated protein biomarkers in inflammatory diseases

Profiling of mRNA expression is an important method to identify biomarkers but complicated by limited correlations between mRNA expression and protein abundance. We hypothesised that these correlations could be improved by mathematical models based on measuring splice variants and time delay in protein translation. We characterised time-series of primary human naïve CD4+ T cells during early T helper type 1 differentiation with RNA-sequencing and mass-spectrometry proteomics. We performed computational time-series analysis in this system and in two other key human and murine immune cell types. Linear mathematical mixed time delayed splice variant models were used to predict protein abundances, and the models were validated using out-of-sample predictions. Lastly, we re-analysed RNA-seq datasets to evaluate biomarker discovery in five T-cell associated diseases, further validating the findings for multiple sclerosis (MS) and asthma. The new models significantly out-performing models not including the usage of multiple splice variants and time delays, as shown in cross-validation tests. Our mathematical models provided more differentially expressed proteins between patients and controls in all five diseases. Moreover, analysis of these proteins in asthma and MS supported their relevance. One marker, sCD27, was validated in MS using two independent cohorts for evaluating response to treatment and disease prognosis. In summary, our splice variant and time delay models substantially improved the prediction of protein abundance from mRNA expression in three different immune cell types. The models provided valuable biomarker candidates, which were further validated in MS and asthma.

Plasma protein profiling reveals dynamic immunomodulatory changes in multiple sclerosis patients during pregnancy

Multiple sclerosis (MS) is a chronic autoimmune neuroinflammatory and neurodegenerative disorder of the central nervous system. Pregnancy represents a natural modulation of the disease course, where the relapse rate decreases, especially in the 3^rd trimester, followed by a transient exacerbation after delivery. Although the exact mechanisms behind the pregnancy-induced modulation are yet to be deciphered, it is likely that the immune tolerance established during pregnancy is involved. In this study, we used the highly sensitive and specific proximity extension assay technology to perform protein profiling analysis of 92 inflammation-related proteins in MS patients (n=15) and healthy controls (n=10), longitudinally sampled before, during, and after pregnancy. Differential expression analysis was performed using linear models and p-values were adjusted for false discovery rate due to multiple comparisons. Our findings reveal gradual dynamic changes in plasma proteins that are most prominent during the 3^rd trimester while reverting post-partum. Thus, this pattern reflects the disease activity of MS during pregnancy. Among the differentially expressed proteins in pregnancy, several proteins with known immunoregulatory properties were upregulated, such as PD-L1, LIF-R, TGF-β1, and CCL28. On the other hand, inflammatory chemokines such as CCL8, CCL13, and CXCL5, as well as members of the tumor necrosis factor family, TRANCE and TWEAK, were downregulated. Further in-depth studies will reveal if these proteins can serve as biomarkers in MS and whether they are mechanistically involved in the disease amelioration and worsening. A deeper understanding of the mechanisms involved may identify new treatment strategies mimicking the pregnancy milieu.

Progesterone Inhibits the Establishment of Activation-Associated Chromatin During TH1 Differentiation

TH1-mediated diseases such as multiple sclerosis (MS) and rheumatoid arthritis (RA) improve during pregnancy, coinciding with increasing levels of the pregnancy hormone progesterone (P4), highlighting P4 as a potential mediator of this immunomodulation. Here, we performed detailed characterization of how P4 affects the chromatin and transcriptomic landscape during early human TH1 differentiation, utilizing both ATAC-seq and RNA-seq. Time series analysis of the earlier events (0.5-24 hrs) during TH1 differentiation revealed that P4 counteracted many of the changes induced during normal differentiation, mainly by downregulating key regulatory genes and their upstream transcription factors (TFs) involved in the initial T-cell activation. Members of the AP-1 complex such as FOSL1, FOSL2, JUN and JUNB were particularly affected, in both in promoters and in distal regulatory elements. Moreover, the changes induced by P4 were significantly enriched for disease-associated changes related to both MS and RA, revealing several shared upstream TFs, where again JUN was highlighted to be of central importance. Our findings support an immune regulatory role for P4 during pregnancy by impeding T-cell activation, a crucial checkpoint during pregnancy and in T-cell mediated diseases, and a central event prior to T-cell lineage commitment. Indeed, P4 is emerging as a likely candidate involved in disease modulation during pregnancy and further studies evaluating P4 as a potential treatment option are needed.

CD4+ T-cell DNA methylation changes during pregnancy significantly correlate with disease-associated methylation changes in autoimmune diseases

Epigenetics may play a central, yet unexplored, role in the profound changes that the maternal immune system undergoes during pregnancy and could be involved in the pregnancy-induced modulation of several autoimmune diseases. We investigated changes in the methylome in isolated circulating CD4⁺ T-cells in non-pregnant and pregnant women, during the 1^st and 2^nd trimester, using the Illumina Infinium Human Methylation 450K array, and explored how these changes were related to autoimmune diseases that are known to be affected during pregnancy. Pregnancy was associated with several hundreds of methylation differences, particularly during the 2^nd trimester. A network-based modular approach identified several genes, e.g., CD28, FYN, VAV1 and pathways related to T-cell signalling and activation, highlighting T-cell regulation as a central component of the observed methylation alterations. The identified pregnancy module was significantly enriched for disease-associated methylation changes related to multiple sclerosis, rheumatoid arthritis and systemic lupus erythematosus. A negative correlation between pregnancy-associated methylation changes and disease-associated changes was found for multiple sclerosis and rheumatoid arthritis, diseases that are known to improve during pregnancy whereas a positive correlation was found for systemic lupus erythematosus, a disease that instead worsens during pregnancy. Thus, the directionality of the observed changes is in line with the previously observed effect of pregnancy on disease activity. Our systems medicine approach supports the importance of the methylome in immune regulation of T-cells during pregnancy. Our findings highlight the relevance of using pregnancy as a model for understanding and identifying disease-related mechanisms involved in the modulation of autoimmune diseases.Abbreviations: BMIQ: beta-mixture quantile dilation; DMGs: differentially methylated genes; DMPs: differentially methylated probes; FE: fold enrichment; FDR: false discovery rate; GO: gene ontology; GWAS: genome-wide association studies; MDS: multidimensional scaling; MS: multiple sclerosis; PBMC: peripheral blood mononuclear cells; PBS: phosphate buffered saline; PPI; protein-protein interaction; RA: rheumatoid arthritis; SD: standard deviation; SLE: systemic lupus erythematosus; SNP: single nucleotide polymorphism; T_H: CD4⁺ T helper cell; VIStA: diVIsive Shuffling Approach.

Differential effects of estradiol and progesterone on human T cell activation in vitro

Estradiol (E2) and progesterone (P4) are steroid hormones important for the regulation of immune responses during pregnancy. Their increasing levels coincide with an improvement of T cell-mediated diseases such as multiple sclerosis (MS). Although immune-endocrine interactions are involved in this phenomenon, the relative contribution of hormones is not known. We here report a direct comparison of E2- and P4-mediated effects on human CD4⁺ T cells, key cells in immune regulation. T cells were stimulated to obtain different activation levels and exposed to a broad range of hormone concentrations. Activation level was assessed by CD69/CD25 expression by flow cytometry, and secreted proteins (n = 196) were measured in culture supernatants using proximity extension assay and electrochemiluminescence immunoassay. We found that in low activated cells, pregnancy-relevant E2 concentrations increased activation and the secretion of several immune- and inflammation-related proteins. P4, on the other hand, showed a biphasic pattern, where serum-related concentrations upregulated activation and protein secretion while placenta-relevant concentrations induced a prominent dampening irrespective of the initial activation level. Our results demonstrate the importance of P4 as a major hormone in the immune modulation of T cells during pregnancy and emphasize the need to further evaluate its potency in the treatment of diseases like MS.

Progesterone Dampens Immune Responses in In Vitro Activated CD4+ T Cells and Affects Genes Associated With Autoimmune Diseases That Improve During Pregnancy

The changes in progesterone (P4) levels during and after pregnancy coincide with the temporary improvement and worsening of several autoimmune diseases like multiple sclerosis (MS) and rheumatoid arthritis (RA). Most likely immune-endocrine interactions play a major role in these pregnancy-induced effects. In this study, we used next generation sequencing to investigate the direct effects of P4 on CD4⁺ T cell activation, key event in pregnancy and disease. We report profound dampening effects of P4 on T cell activation, altering the gene and protein expression profile and reversing many of the changes induced during the activation. The transcriptomic changes induced by P4 were significantly enriched for genes associated with diseases known to be modulated during pregnancy such as MS, RA and psoriasis. STAT1 and STAT3 were significantly downregulated by P4 and their downstream targets were significantly enriched among the disease-associated genes. Several of these genes included well-known and disease-relevant cytokines, such as IL-12β, CXCL10 and OSM, which were further validated also at the protein level using proximity extension assay. Our results extend the previous knowledge of P4 as an immune regulatory hormone and support its importance during pregnancy for regulating potentially detrimental immune responses towards the semi-allogenic fetus. Further, our results also point toward a potential role for P4 in the pregnancy-induced disease immunomodulation and highlight the need for further studies evaluating P4 as a future treatment option.

Immunomodulating Effects Depend on Prolactin Levels in Patients with Hyperprolactinemia

Prolactin is known to have immune modulatory effects acting through the prolactin receptor, which is present on a variety of immune cells. Certain chemokines contribute to form the type of T helper (Th) preponderance in the immune response. The objective of this work was to assess if hyperprolactinemia not related to pregnancy is associated with changes in circulating levels of chemokines and other immunological markers. In this cross sectional study, 35 patients with hyperprolactinemia (5 men), and 102 healthy blood donors (19 men) were included. Serum levels of Th1- Th2- and Th17-associated chemokines, C-reactive protein, immunoglobulins, and the B cell attracting chemokine CXCL13 were assessed. The hyperprolactinemic group had significantly higher levels of Th2 associated CCL22 (p=0.022), Th17 associated CXCL1 (p=0.001), B cell attracting CXCL13 (p=0.003), and C-reactive protein (p<0.001) compared to controls, and these proteins were also positively correlated with prolactin levels. While differences in CCL22, CXCL1, CXCL13, and C-reactive protein were present in patients with low or moderate hyperprolactinemia, no differences were observed at high (>3600 mU/l) prolactin levels. To evaluate a possible dose-associated response to prolactin, an in vitro model was used, showing prolactin-induced increase in T-helper cell activation at moderate levels, while activation decreased at higher levels. Hyperprolactinemia seems to have several immunomodulatory effects and was associated with increased levels of chemokines associated with Th2 and Th17 responses and B cell attraction. However, patients with greatly increased prolactin had normal levels of chemokines, and in vitro, high levels of prolactin decreased T-helper cell activation.

Dynamic Response Genes in CD4+ T Cells Reveal a Network of Interactive Proteins that Classifies Disease Activity in Multiple Sclerosis

Multiple sclerosis (MS) is a chronic inflammatory disease of the CNS and has a varying disease course as well as variable response to treatment. Biomarkers may therefore aid personalized treatment. We tested whether in vitro activation of MS patient-derived CD4+ T cells could reveal potential biomarkers. The dynamic gene expression response to activation was dysregulated in patient-derived CD4+ T cells. By integrating our findings with genome-wide association studies, we constructed a highly connected MS gene module, disclosing cell activation and chemotaxis as central components. Changes in several module genes were associated with differences in protein levels, which were measurable in cerebrospinal fluid and were used to classify patients from control individuals. In addition, these measurements could predict disease activity after 2 years and distinguish low and high responders to treatment in two additional, independent cohorts. While further validation is needed in larger cohorts prior to clinical implementation, we have uncovered a set of potentially promising biomarkers.

A validated gene regulatory network and GWAS identifies early regulators of T cell-associated diseases

Early regulators of disease may increase understanding of disease mechanisms and serve as markers for presymptomatic diagnosis and treatment. However, early regulators are difficult to identify because patients generally present after they are symptomatic. We hypothesized that early regulators of T cell-associated diseases could be found by identifying upstream transcription factors (TFs) in T cell differentiation and by prioritizing hub TFs that were enriched for disease-associated polymorphisms. A gene regulatory network (GRN) was constructed by time series profiling of the transcriptomes and methylomes of human CD4(+) T cells during in vitro differentiation into four helper T cell lineages, in combination with sequence-based TF binding predictions. The TFs GATA3, MAF, and MYB were identified as early regulators and validated by ChIP-seq (chromatin immunoprecipitation sequencing) and small interfering RNA knockdowns. Differential mRNA expression of the TFs and their targets in T cell-associated diseases supports their clinical relevance. To directly test if the TFs were altered early in disease, T cells from patients with two T cell-mediated diseases, multiple sclerosis and seasonal allergic rhinitis, were analyzed. Strikingly, the TFs were differentially expressed during asymptomatic stages of both diseases, whereas their targets showed altered expression during symptomatic stages. This analytical strategy to identify early regulators of disease by combining GRNs with genome-wide association studies may be generally applicable for functional and clinical studies of early disease development.

Coccygectomy: an effective treatment option for chronic coccydynia: retrospective results in 41 consecutive patients

Between 1993 and 2008, 41 patients underwent total coccygectomy for coccydynia which had failed to respond to six months of conservative management. Of these, 40 patients were available for clinical review and 39 completed a questionnaire giving their evaluation of the effect of the operation. Excellent or good results were obtained in 33 of the 41 patients, comprising 18 of the 21 patients with coccydynia due to trauma, five of the eight patients with symptoms following childbirth and ten of 12 idiopathic onset. In eight patients the results were moderate or poor, although none described worse pain after the operation. The only post-operative complication was superficial wound infection which occurred in five patients and which settled fully with antibiotic treatment. One patient required re-operation for excision of the distal cornua of the sacrum. Total coccygectomy offered satisfactory relief of pain in the majority of patients regardless of the cause of their symptoms.

Computer methods for the assessment of toxicity

The prediction of the biological activity of chemical compounds by means of mathematical models is discussed. Biological activity of chemicals, including their toxicity on man and other biological organisms and systems, involves too complex phenomena to presently be predictable by fundamental models such as ab initio quantum mechanical models or statistical mechanical models. Hence one takes recourse to semi-empirical and empirical models which relate the variation in chemical structure of chemical compounds to the variation in their measured biological activity, e.g. toxicity in one or several test systems. These models are "calibrated" on series of similar compounds with "known" toxicity, the training set. Thereafter the models can--in fortunate cases--be used to predict the toxicity of compounds which are structurally similar to the training set compounds. The formulation and applicability of semi-empirical and empirical models relating chemical structure to biological activity is discussed. Causes and remedies for commonly encountered fallacies are presented.

Similar regulatory mechanisms despite differences in membrane lipid composition in Acholeplasma laidlawii strains A-EF22 and B-PG9. A multivariate data analysis

Mycoplasmas are small, cell wall-deficient bacteria. The metabolic regulation of the lipid composition in the membrane of the species Acholeplasma laidlawii, strains A-EF22 and B-JU, is governed mainly by the balance between the potential formation of lamellar and nonlamellar phase structures. However, the regulatory features have not been consistently observed in the B-PG9 strain. A comparison has been performed between the membrane lipid composition for strains A-EF22 and B-PG9, simultaneously changing eight experimental conditions known to affect the regulation and packing properties of the A-EF22 lipids. Multiple regression and partial least-square discriminant analyses of many variables showed: (i) quantitative differences in membrane lipid and protein composition, and in membrane protein molecular masses of the two strains; (ii) different molar fractions of the major polar lipids monoglucosyldiacylglycerol (nonlamellar) and diglucosyldiacylglycerol (lamellar), which were caused by differences in lipid acyl chain length and unsaturation inherent in the strains and by the type of growth medium used; and (iii) similar regulatory mechanisms for changes in the lipid composition under most conditions, responding to the experimentally varied bilayer and nonbilayer properties of the lipid matrix. These regulatory principles are probably valid in other bacteria as well.

A strategy for ranking environmentally occurring chemicals. Part VI. QSARs for the mutagenic effects of halogenated aliphatics

A strategy for the systematic analysis and priority ranking of environmental chemicals has been applied to a class of 58 halogenated aliphatic hydrocarbons. A training set of ten compounds representing this class, was selected by statistical design. The training set compounds were then subjected to biological testing in the Salmonella typhimurium reverse mutation assay (Ames test). The measured biological data, recorded as dose-response curves, were analyzed to determine the mutagenic potency (slope of the initial portion) and the mutagen dose (MD 50) required to increase the number of revertants above the background by 50%. For each compound, four mutagenic potency estimates and four MD 50 values were determined, all originating from the tester strains TA 100 and TA 1535 with and without metabolic activation. The obtained responses were analyzed with multivariate techniques to give QSAR models relating the mutagenic potency data to the physico-chemical properties of the compounds. Finally, the derived QSARs were used to predict the mutagenic potencies and the MD 50S for the non-tested compounds in the class.

Minimum analogue peptide sets (MAPS) for quantitative structure-activity relationships

The information contents in previously published peptide sets was compared with smaller sets of peptides selected according to statistical designs. It was found that minimum analogue peptide sets (MAPS) constructed by factorial or fractional factorial designs in physiochemical properties contained substantial structure-activity information. Although five to six times smaller than the originally published peptide sets the MAPS resulted in QSAR models able to predict biological activity. The QSARs derived from a MAPS of nine dipeptides, and from a set of 58 dipeptides inhibiting angiotensin converting enzyme were compared and found to be of equal strength. Furthermore, for a set of bitter tasting dipeptides it was found that an incomplete MAPS of 10 dipeptides gave just as good a model as the model based on a set of 48 dipeptides. By comparison other non-designed sets of peptides gave QSARs with poor predictive power. It was also demonstrated how MAPS centered on a lead peptide can be constructed as to specifically explore the physiochemical and biological properties in the vicinity of the lead. It was concluded that small information-rich peptide sets MAPS can be constructed on the basis of statistical designs with principal properties of amino acids as design variables.

A multivariate representation and analysis of DNA sequence data

A new way to represent and analyze DNA sequence data is described. This approach complements methods currently used, in that it allows the systematic part of the variation between different sequences to be modeled. This can prove as informative as absence of variation (homology), which is the most widely used criterion for comparing sequence data. A multivariate sequence-activity model (SAM), for DNA-promoter sequences is presented, by which the relative promoter strength is modeled in terms of the primary DNA-sequence. The model is shown to have a good predictive capability. The coefficients from the model are interpreted, and used to design new structures predicted to be strong promoters in the system investigated. The approach described is also applicable to other kinds of sequence data, e.g. RNAs, proteins or peptides.

Quantitative structure-activity relationships for sea anemone polypeptide toxins

Sea anemone polypeptides vary considerably in their affinities for sodium channels occurring in different excitable cells. The amino acid sequence variation in a set of six sea anemone type I polypeptide toxins (46-49 residues long), was parameterized using descriptor scales z1, z2, and z3, derived from a large number of amino acid physicochemical properties. The pharmacological properties of the toxins were represented by the results from four bioassays on crab, mouse, and rat brain and from rat heart. By means of the descriptor scales and the multivariate data analytical method PLS (partial least squares projections to latent structures), it was possible to develop quantitative structure-activity relationships (QSAR). Using the QSARs derived from the set of six polypeptide toxins the pharmacological properties of two homologous sea anemone polypeptide toxins were predicted. Thus it is shown that QSARs may be formulated for relatively long bioactive polypeptides. The QSARs indicate that 11 different amino acid positions may be of importance, but that positions no. 5, 21, 28, 34, 37, and 40 were of main importance in modeling the relative toxicities of the six polypeptides.

Coccygodynia treated by resection of the coccyx

Sixty-five patients suffering from coccygodynia resistant to conservative treatment had total or partial coccygectomy, all without serious complications. Eight reoperations were performed. After an average of 15 years, 46 of the 55 patients seen at follow-up were satisfied. A normal radiograph of the coccyx does not exclude a good result from coccygectomy. We recommend total coccygectomy using a longitudinal incision in carefully selected and well-informed patients.

Peptide QSAR on substance P analogues, enkephalins and bradykinins containing L- and D-amino acids

Peptide QSARs are constructed for substance P analogues, enkephalins (two examples) and bradykinins containing both L- and D-amino acids. As descriptors in the QSARs, the previously developed descriptors z1 (hydrophobicity), z2 (bulk) and z3 (electronic effect) are used together with a qualitative variable coding for variation in chirality. Two parametrizations of the peptide sequences are tested. In the first no chiral description is used at all, and in the second chirality is described by the qualitative variable. It is concluded that for the current series of peptides, the biological response to variation in amino acid sequence and chirality can be modelled.

MEIC--a new international multicenter project to evaluate the relevance to human toxicity of in vitro cytotoxicity tests

A new international project to evaluate the relevance for human systemic and local toxicity of in vitro tests of general toxicity of chemicals has been organized by the Scandinavian Society of Cell Toxicology under the title Multicenter Evaluation of In Vitro Cytotoxicity (MEIC). The basic assumptions underlying the project, as well as the practical goals and the design of the program are outlined. The list of the first 50 reference chemicals is presented. The chemicals are an otherwise unbiased selection of compounds with known human acutely lethal dosage and blood concentrations, including LD50-values in the rat or mouse. Most agents also have other data on human toxicity and toxicokinetics, including more extensive animal toxicity data. International laboratories already using or developing in vitro tests of various partial aspects of general toxicity are invited to test the substances, the results of which will be evaluated by us. The predictivity of the in vitro results for both partial and gross human toxicity data will be determined with combined use of univariate regression analysis and soft multivariate modeling. The predictivity of the in vitro results will be compared with the predictivity of conventional animal tests for the same chemicals. Finally, batteries of tests with optimal prediction power for various types of human toxicity will be selected. The need for and possible uses of such batteries are discussed.

A multivariate approach to saccharide quantitative structure-activity relationships exemplified by two series of 9-hydroxyellipticine glycosides

Multivariate saccharide quantitative structure-activity relationships (QSARs) have been developed for two series of 9-hydroxyellipticine glycosides. In order to describe the structural variation of the glycoside moieties, thirteen chromatographic variables were used. Eleven D-glycosides and seven L-glycosides were used in separate QSARs to model 9-hydroxyellipticine glycoside antitumour activity against L 1210 leukemia. The multivariate partial least squares (PLS) method was used to establish the QSARs.

[Alpine skiing--a hand injury despite safety hand grips]

During a fall, a skier sustained two fractures of the metacarpal bones despite special safety hand grips on the ski-sticks. Altered design of these grips is recommended as a prophylactic measure.

Gait with light and heavy fracture bandages on the lower leg

Using an instrumented treadmill which measured ground reaction forces, ten normal subjects were tested wearing conventional plaster-of-Paris bandages on the lower leg and lightweight crus-plastic bandages. Two different types of heels were also tested. From calculation of gait parameters it was found that the free walking speed was lowest with a conventional bandage with heel. The external work of gait was lowest with the lightweight bandage. Ataxia was least while wearing the lightweight bandage. The lightweight bandage is preferable from a biomechanical point of view, in accordance with the opinion of the subjects.

Peptide quantitative structure-activity relationships, a multivariate approach

The variation in amino acid sequence within sets of peptides is described by three principal properties, z1, z2, and z3, per varied amino acid position. These principal properties are derived from a principal components analysis of a matrix of 29 physicochemical variables for the 20 coded (in mRNA) amino acids. The scales z1, z2, and z3 are used to construct informative sets of analogues for exploring and developing quantitative structure-activity relationships (QSAR) of peptides. For the QSARs, the multivariate partial least squares (PLS) method is used. Multivariate QSARs are developed for four families of peptides, and it is shown how these QSARs can predict the activity of new peptide analogues.

Relationships between induction of anesthesia and mitotic spindle disturbances studied by means of principal component analysis

A dataset comprising the activity of 30 compounds in 4 biological tests--anesthesia of tadpoles, anesthesia of frog heart, abnormal growth and spindle disturbances in Allium root tips--was re-evaluated by means of principal component analysis. A two-component model is required to explain the variation in biological activity of the compounds. It is found that abnormal growth is different from the other biological responses. When this test is excluded, as much as 90% of the variation is explained by a one-component model, the determining factor most probably being the lipophilic character of the compounds. Mammalian mitotic cells respond in a similar way to mitotic cells of Allium root tips. It is suggested that possible regularities in the dose-response relationships for anesthesia, teratogenic effects and generation of abnormal chromosome numbers require further exploration.

The prediction of bradykinin potentiating potency of pentapeptides. An example of a peptide quantitative structure-activity relationship

The variation in amino acid sequence, in a set of bradykinin potentiating pentapeptides, is described by three variables per amino acid position. The variables were derived from a principal components analysis of a property matrix for the 20 coded amino acids. The resulting structure descriptor matrix describes the observed activity of the peptides to 97% by means of a multivariate partial least squares (PLS) model. It is demonstrated that this quantitative structure-activity relationship (QSAR) can be used to predict the activity of new peptide analogs.

Toxicity modeling and prediction with pattern recognition

Empirical models can be constructed relating the change in toxicity to the change in chemical structure for series of similar compounds or mixtures. The first step is to translate the variation in structure to quantitative numbers. This gives a data table, a data matrix denoted by X, which then is analyzed. The same type of the models can be used to relate the variation of in vivo data to the variation of a battery of in vitro tests. A single data analytical model cannot be applied to a set of compounds of diverse chemical structure. For such data sets, separate models must be developed for each subgroup of compounds. The data analytical problem then partly is one of classification, pattern recognition (PARC). The assumption of structural and biological similarity within each subset of modeled compounds is then essential for empirical models to apply. PARC is often used to classify compounds as active (toxic) or inactive. The data structure is then often asymmetric which puts special demands on the data analysis, making the traditional PARC methods inapplicable. Depending on the desired information from the data analysis and on the type of available data, four levels of PARC can be distinguished: (I) the data X are used to develop rules for classifying future compounds into one of the classes represented in X; (II) same as I, but the possibility of future compounds belonging to "unknown" classes not represented in X is taken into account; (III) same as II, plus the quantitative prediction of one activity variable (here toxicity) in some classes; (IV) same as III, but several quantitative activity (toxicity) variables are predicted.

Normal gait of young and old men and women. Ground reaction force measurement on a treadmill

Forty normal persons had their gait tested using an instrumented treadmill. All were tested at the same speed of gait. The temporal factors of gait, the ataxia, and the external work of the gait were all calculated from the ground reaction forces. Ten women and ten men 20-29 years and ten women and ten men aged 60-69 were tested. The study demonstrated a constant pattern of gait independent of age and sex.

Displaced supracondylar fractures of the humerus in children

In a 3-year period, 101 children were admitted to hospital with supracondylar fractures of the humerus. Eight-six were examined an average of 3.7 years after the injury. Forty-seven cases were treated with closed reduction and plaster bandage. After an unsuccessful attempt at closed reduction, 39 cases were treated with percutaneous K-wire pinning and plaster. The cases treated with percutaneous pinning thus include the most severe fractures. Nevertheless, the results at follow-up in these cases easily equalled those obtained by closed reduction for the less displaced fractures. They were also comparable with reported results of extension treatment and, in contrast, required only a few days of hospitalisation.