Bilateral remote ischemic conditioning in children: A two-center, double-blind, randomized controlled trial in young children undergoing cardiac surgery

Objective

The study objective was to determine whether adequately delivered bilateral remote ischemic preconditioning is cardioprotective in young children undergoing surgery for 2 common congenital heart defects with or without cyanosis.

Methods

We performed a prospective, double-blind, randomized controlled trial at 2 centers in the United Kingdom. Children aged 3 to 36 months undergoing tetralogy of Fallot repair or ventricular septal defect closure were randomized 1:1 to receive bilateral preconditioning or sham intervention. Participants were followed up until hospital discharge or 30 days. The primary outcome was area under the curve for high-sensitivity troponin-T in the first 24 hours after surgery, analyzed by intention-to-treat. Right atrial biopsies were obtained in selected participants.

Results

Between October 2016 and December 2020, 120 eligible children were randomized to receive bilateral preconditioning (n = 60) or sham intervention (n = 60). The primary outcome, area under the curve for high-sensitivity troponin-T, was higher in the preconditioning group (mean: 70.0 ± 50.9 μg/L/h, n = 56) than in controls (mean: 55.6 ± 30.1 μg/L/h, n = 58) (mean difference, 13.2 μg/L/h; 95% CI, 0.5-25.8; P = .04). Subgroup analyses did not show a differential treatment effect by oxygen saturations (pinteraction = .25), but there was evidence of a differential effect by underlying defect (pinteraction = .04). Secondary outcomes and myocardial metabolism, quantified in atrial biopsies, were not different between randomized groups.

Conclusions

Bilateral remote ischemic preconditioning does not attenuate myocardial injury in children undergoing surgical repair for congenital heart defects, and there was evidence of potential harm in unstented tetralogy of Fallot. The routine use of remote ischemic preconditioning cannot be recommended for myocardial protection during pediatric cardiac surgery.

Demonstrating the reliability of in vivo metabolomics based chemical grouping: towards best practice

While grouping/read-across is widely used to fill data gaps, chemical registration dossiers are often rejected due to weak category justifications based on structural similarity only. Metabolomics provides a route to robust chemical categories via evidence of shared molecular effects across source and target substances. To gain international acceptance, this approach must demonstrate high reliability, and best-practice guidance is required. The MetAbolomics ring Trial for CHemical groupING (MATCHING), comprising six industrial, government and academic ring-trial partners, evaluated inter-laboratory reproducibility and worked towards best-practice. An independent team selected eight substances (WY-14643, 4-chloro-3-nitroaniline, 17α-methyl-testosterone, trenbolone, aniline, dichlorprop-p, 2-chloroaniline, fenofibrate); ring-trial partners were blinded to their identities and modes-of-action. Plasma samples were derived from 28-day rat tests (two doses per substance), aliquoted, and distributed to partners. Each partner applied their preferred liquid chromatography-mass spectrometry (LC-MS) metabolomics workflows to acquire, process, quality assess, statistically analyze and report their grouping results to the European Chemicals Agency, to ensure the blinding conditions of the ring trial. Five of six partners, whose metabolomics datasets passed quality control, correctly identified the grouping of eight test substances into three categories, for both male and female rats. Strikingly, this was achieved even though a range of metabolomics approaches were used. Through assessing intrastudy quality-control samples, the sixth partner observed high technical variation and was unable to group the substances. By comparing workflows, we conclude that some heterogeneity in metabolomics methods is not detrimental to consistent grouping, and that assessing data quality prior to grouping is essential. We recommend development of international guidance for quality-control acceptance criteria. This study demonstrates the reliability of metabolomics for chemical grouping and works towards best-practice.

Lipidome characterisation and sex-specific differences in type 1 and type 2 diabetes mellitus

BACKGROUND

In this study, we evaluated the lipidome alterations caused by type 1 diabetes (T1D) and type 2 diabetes (T2D), by determining lipids significantly associated with diabetes overall and in both sexes, and lipids associated with the glycaemic state.

METHODS

An untargeted lipidomic analysis was performed to measure the lipid profiles of 360 subjects (91 T1D, 91 T2D, 74 with prediabetes and 104 controls (CT)) without cardiovascular and/or chronic kidney disease. Ultra-high performance liquid chromatography-electrospray ionization mass spectrometry (UHPLC-ESI-MS) was conducted in two ion modes (positive and negative). We used multiple linear regression models to (1) assess the association between each lipid feature and each condition, (2) determine sex-specific differences related to diabetes, and (3) identify lipids associated with the glycaemic state by considering the prediabetes stage. The models were adjusted by sex, age, hypertension, dyslipidaemia, body mass index, glucose, smoking, systolic blood pressure, triglycerides, HDL cholesterol, LDL cholesterol, alternate Mediterranean diet score (aMED) and estimated glomerular filtration rate (eGFR); diabetes duration and glycated haemoglobin (HbA1c) were also included in the comparison between T1D and T2D.

RESULTS

A total of 54 unique lipid subspecies from 15 unique lipid classes were annotated. Lysophosphatidylcholines (LPC) and ceramides (Cer) showed opposite effects in subjects with T1D and subjects with T2D, LPCs being mainly up-regulated in T1D and down-regulated in T2D, and Cer being up-regulated in T2D and down-regulated in T1D. Also, Phosphatidylcholines were clearly down-regulated in subjects with T1D. Regarding sex-specific differences, ceramides and phosphatidylcholines exhibited important diabetes-associated differences due to sex. Concerning the glycaemic state, we found a gradual increase of a panel of 1-deoxyceramides from normoglycemia to prediabetes to T2D.

CONCLUSIONS

Our findings revealed an extensive disruption of lipid metabolism in both T1D and T2D. Additionally, we found sex-specific lipidome changes associated with diabetes, and lipids associated with the glycaemic state that can be linked to previously described molecular mechanisms in diabetes.

Simultaneously discovering the fate and biochemical effects of pharmaceuticals through untargeted metabolomics

Untargeted metabolomics is an established approach in toxicology for characterising endogenous metabolic responses to xenobiotic exposure. Detecting the xenobiotic and its biotransformation products as part of the metabolomics analysis provides an opportunity to simultaneously gain deep insights into its fate and metabolism, and to associate the internal relative dose directly with endogenous metabolic responses. This integration of untargeted exposure and response measurements into a single assay has yet to be fully demonstrated. Here we assemble a workflow to discover and analyse pharmaceutical-related measurements from routine untargeted UHPLC-MS metabolomics datasets, derived from in vivo (rat plasma and cardiac tissue, and human plasma) and in vitro (human cardiomyocytes) studies that were principally designed to investigate endogenous metabolic responses to drug exposure. Our findings clearly demonstrate how untargeted metabolomics can discover extensive biotransformation maps, temporally-changing relative systemic exposure, and direct associations of endogenous biochemical responses to the internal dose.

Suitability of Dried Blood Spots for Accelerating Veterinary Biobank Collections and Identifying Metabolomics Biomarkers With Minimal Resources

Biomarker discovery using biobank samples collected from veterinary clinics would deliver insights into the diverse population of pets and accelerate diagnostic development. The acquisition, preparation, processing, and storage of biofluid samples in sufficient volumes and at a quality suitable for later analysis with most suitable discovery methods remain challenging. Metabolomics analysis is a valuable approach to detect health/disease phenotypes. Pre-processing changes during preparation of plasma/serum samples may induce variability that may be overcome using dried blood spots (DBSs). We report a proof of principle study by metabolite fingerprinting applying UHPLC-MS of plasma and DBSs acquired from healthy adult dogs and cats (age range 1–9 years), representing each of 4 dog breeds (Labrador retriever, Beagle, Petit Basset Griffon Vendeen, and Norfolk terrier) and the British domestic shorthair cat (n = 10 per group). Blood samples (20 and 40 μL) for DBSs were loaded onto filter paper, air-dried at room temperature (3 h), and sealed and stored (4°C for ~72 h) prior to storage at −80°C. Plasma from the same blood draw (250 μL) was prepared and stored at −80°C within 1 h of sampling. Metabolite fingerprinting of the DBSs and plasma produced similar numbers of metabolite features that had similar abilities to discriminate between biological classes and correctly assign blinded samples. These provide evidence that DBSs, sampled in a manner amenable to application in in-clinic/in-field processing, are a suitable sample for biomarker discovery using UHPLC-MS metabolomics. Further, given appropriate owner consent, the volumes tested (20–40 μL) make the acquisition of remnant blood from blood samples drawn for other reasons available for biobanking and other research activities. Together, this makes possible large-scale biobanking of veterinary samples, gaining sufficient material sooner and enabling quicker identification of biomarkers of interest.

Oxidative stress from DGAT1 oncoprotein inhibition in melanoma suppresses tumor growth when ROS defenses are also breached

Dysregulated cellular metabolism is a cancer hallmark for which few druggable oncoprotein targets have been identified. Increased fatty acid (FA) acquisition allows cancer cells to meet their heightened membrane biogenesis, bioenergy, and signaling needs. Excess FAs are toxic to non-transformed cells but surprisingly not to cancer cells. Molecules underlying this cancer adaptation may provide alternative drug targets. Here, we demonstrate that diacylglycerol O-acyltransferase 1 (DGAT1), an enzyme integral to triacylglyceride synthesis and lipid droplet formation, is frequently up-regulated in melanoma, allowing melanoma cells to tolerate excess FA. DGAT1 over-expression alone transforms p53-mutant zebrafish melanocytes and co-operates with oncogenic BRAF or NRAS for more rapid melanoma formation. Antagonism of DGAT1 induces oxidative stress in melanoma cells, which adapt by up-regulating cellular reactive oxygen species defenses. We show that inhibiting both DGAT1 and superoxide dismutase 1 profoundly suppress tumor growth through eliciting intolerable oxidative stress.

Automated Sample Preparation and Data Collection Workflow for High-Throughput In Vitro Metabolomics

Regulatory bodies have started to recognise the value of in vitro screening and metabolomics as two types of new approach methodologies (NAMs) for chemical risk assessments, yet few high-throughput in vitro toxicometabolomics studies have been reported. A significant challenge is to implement automated sample preparation of the low biomass samples typically used for in vitro screening. Building on previous work, we have developed, characterised and demonstrated an automated sample preparation and analysis workflow for in vitro metabolomics of HepaRG cells in 96-well microplates using a Biomek i7 Hybrid Workstation (Beckman Coulter) and Orbitrap Elite (Thermo Scientific) high-resolution nanoelectrospray direct infusion mass spectrometry (nESI-DIMS), across polar metabolites and lipids. The experimental conditions evaluated included the day of metabolite extraction, order of extraction of samples in 96-well microplates, position of the 96-well microplate on the instrument's deck and well location within a microplate. By using the median relative standard deviation (mRSD (%)) of spectral features, we have demonstrated good repeatability of the workflow (final mRSD < 30%) with a low percentage of features outside the threshold applied for statistical analysis. To improve the quality of the automated workflow further, small method modifications were made and then applied to a large cohort study (4860 sample infusions across three nESI-DIMS assays), which confirmed very high repeatability of the whole workflow from cell culturing to metabolite measurements, whilst providing a significant improvement in sample throughput. It is envisioned that the automated in vitro metabolomics workflow will help to advance the application of metabolomics (as a part of NAMs) in chemical safety, primarily as an approach for high throughput screening and prioritisation.

Rapid identification of human muscle disease with fibre optic Raman spectroscopy

We demonstrate the use of fibre optic Raman spectroscopy for the rapid identification of muscle disorders.

Infrared Spectroscopic Analysis in the Differentiation of Epithelial Misplacement From Adenocarcinoma in Sigmoid Colonic Adenomatous Polyps

Purpose

The differential diagnosis of epithelial misplacement from invasive cancer in the colon is a challenging endeavour, augmented by the introduction of bowel cancer population screening. The main aim of the work is to test, as a proof-of concept study, the ability of the infrared spectroscopic imaging approach to differentiate epithelial misplacement from adenocarcinoma in sigmoid colonic adenomatous polyps.

Methods

Ten samples from each of the four diagnostic groups, normal colonic mucosa, adenomatous polyps with low grade dysplasia, epithelial misplacement in adenomatous polyps and adenocarcinoma, were analysed using IR spectroscopic imaging and data processing methods. IR spectral images were subjected to data pre-processing and cluster analysis based segmentation to identify epithelial, connective tissue and stromal regions. Statistical analysis was carried out using principal component analysis and linear discriminant analysis based cross validation, to classify spectral features according to the pathology, and the diagnostic attributes were compared.

Results

The combined 4-group classification model on an average showed a sensitivity of 64%, a specificity of 88% and an accuracy of 76% for prediction based on a 'single spectrum', whilst a 'majority-vote' prediction on an average showed a sensitivity of 73%, a specificity of 90% and an accuracy of 82%. The 2-group model, for the differential diagnosis of epithelial misplacement versus adenocarcinoma, showed an average sensitivity and specificity of 82.5% for prediction based on a 'single spectrum' whilst a 'majority-vote' classification showed an average sensitivity and specificity of 90%. A 92% area under the curve (AUC) value was obtained when evaluating the classifier using the Receiver Operating Characteristics (ROC) curves.

Conclusions

IR spectroscopy shows promise in its ability to differentiate epithelial misplacement from adenocarcinoma in tissue sections, considered as one of the most challenging endeavours in population-wide diagnostic histopathology. Further studies with larger series, including cases with challenging diagnostic features are required to ascertain the capability of this modern digital pathology approach. In the long-term, IR spectroscopy based pathology which is relatively low-cost and rapid, could be a promising endeavour to consider for integration into the existing histopathology pathway, in particular for population based screening programmes where large number of samples are scrutinised.

An Extensive Metabolomics Workflow to Discover Cardiotoxin-Induced Molecular Perturbations in Microtissues

Discovering modes of action and predictive biomarkers of drug-induced structural cardiotoxicity offers the potential to improve cardiac safety assessment of lead compounds and enhance preclinical to clinical translation during drug development. Cardiac microtissues are a promising, physiologically relevant, in vitro model, each composed of ca. 500 cells. While untargeted metabolomics is capable of generating hypotheses on toxicological modes of action and discovering metabolic biomarkers, applying this technology to low-biomass microtissues in suspension is experimentally challenging. Thus, we first evaluated a filtration-based approach for harvesting microtissues and assessed the sensitivity and reproducibility of nanoelectrospray direct infusion mass spectrometry (nESI-DIMS) measurements of intracellular extracts, revealing samples consisting of 28 pooled microtissues, harvested by filtration, are suitable for profiling the intracellular metabolome and lipidome. Subsequently, an extensive workflow combining nESI-DIMS untargeted metabolomics and lipidomics of intracellular extracts with ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS/MS) analysis of spent culture medium, to profile the metabolic footprint and quantify drug exposure concentrations, was implemented. Using the synthetic drug and model cardiotoxin sunitinib, time-resolved metabolic and lipid perturbations in cardiac microtissues were investigated, providing valuable data for generating hypotheses on toxicological modes of action and identifying putative biomarkers such as disruption of purine metabolism and perturbation of polyunsaturated fatty acid levels.

In Vivo Fiber Optic Raman Spectroscopy of Muscle in Preclinical Models of Amyotrophic Lateral Sclerosis and Duchenne Muscular Dystrophy

Neuromuscular diseases result in muscle weakness, disability, and, in many instances, death. Preclinical models form the bedrock of research into these disorders, and the development of in vivo and potentially translational biomarkers for the accurate identification of disease is crucial. Spontaneous Raman spectroscopy can provide a rapid, label-free, and highly specific molecular fingerprint of tissue, making it an attractive potential biomarker. In this study, we have developed and tested an in vivo intramuscular fiber optic Raman technique in two mouse models of devastating human neuromuscular diseases, amyotrophic lateral sclerosis, and Duchenne muscular dystrophy (SOD1G93A and mdx, respectively). The method identified diseased and healthy muscle with high classification accuracies (area under the receiver operating characteristic curves (AUROC): 0.76-0.92). In addition, changes in diseased muscle over time were also identified (AUROCs 0.89-0.97). Key spectral changes related to proteins and the loss of α-helix protein structure. Importantly, in vivo recording did not cause functional motor impairment and only a limited, resolving tissue injury was seen on high-resolution magnetic resonance imaging. Lastly, we demonstrate that ex vivo muscle from human patients with these conditions produced similar spectra to those observed in mice. We conclude that spontaneous Raman spectroscopy of muscle shows promise as a translational research tool.

Rapid infrared mapping for highly accurate automated histology in Barrett's oesophagus

Barrett's oesophagus (BE) is a premalignant condition that can progress to oesophageal adenocarcinoma. Endoscopic surveillance aims to identify potential progression at an early, treatable stage, but generates large numbers of tissue biopsies. Fourier transform infrared (FTIR) mapping was used to develop an automated histology tool for detection of BE and Barrett's neoplasia in tissue biopsies. 22 oesophageal tissue samples were collected from 19 patients. Contiguous frozen tissue sections were taken for pathology review and FTIR imaging. 45 mid-IR images were measured on an Agilent 620 FTIR microscope with an Agilent 670 spectrometer. Each image covering a 140 μm × 140 μm region was measured in 5 minutes, using a 1.1 μm² pixel size and 64 scans per pixel. Principal component fed linear discriminant analysis was used to build classification models based on spectral differences, which were then tested using leave-one-sample-out cross validation. Key biochemical differences were identified by their spectral signatures: high glycogen content was seen in normal squamous (NSQ) tissue, high glycoprotein content was observed in glandular BE tissue, and high DNA content in dysplasia/adenocarcinoma samples. Classification of normal squamous samples versus 'abnormal' samples (any stage of Barrett's) was performed with 100% sensitivity and specificity. Neoplastic Barrett's (dysplasia or adenocarcinoma) was identified with 95.6% sensitivity and 86.4% specificity. Highly accurate pathology classification can be achieved with FTIR measurement of frozen tissue sections in a clinically applicable timeframe.

Multi-centre Raman spectral mapping of oesophageal cancer tissues: a study to assess system transferability

The potential for Raman spectroscopy to provide early and improved diagnosis on a wide range of tissue and biopsy samples in situ is well documented. The standard histopathology diagnostic methods of reviewing H&E and/or immunohistochemical (IHC) stained tissue sections provides valuable clinical information, but requires both logistics (review, analysis and interpretation by an expert) and costly processing and reagents. Vibrational spectroscopy offers a complimentary diagnostic tool providing specific and multiplexed information relating to molecular structure and composition, but is not yet used to a significant extent in a clinical setting. One of the challenges for clinical implementation is that each Raman spectrometer system will have different characteristics and therefore spectra are not readily compatible between systems. This is essential for clinical implementation where classification models are used to compare measured biochemical or tissue spectra against a library training dataset. In this study, we demonstrate the development and validation of a classification model to discriminate between adenocarcinoma (AC) and non-cancerous intraepithelial metaplasia (IM) oesophageal tissue samples, measured on three different Raman instruments across three different locations. Spectra were corrected using system transfer spectral correction algorithms including wavenumber shift (offset) correction, instrument response correction and baseline removal. The results from this study indicate that the combined correction methods do minimize the instrument and sample quality variations within and between the instrument sites. However, more tissue samples of varying pathology states and greater tissue area coverage (per sample) are needed to properly assess the ability of Raman spectroscopy and system transferability algorithms over multiple instrument sites.

Developing Raman spectroscopy as a diagnostic tool for label-free antigen detection

For several decades, a multitude of studies have documented the ability of Raman spectroscopy (RS) to differentiate between tissue types and identify pathological changes to tissues in a range of diseases. Furthermore, spectroscopists have illustrated that the technique is capable of detecting disease-specific alterations to tissue before morphological changes become apparent to the pathologist. This study draws comparisons between the information that is obtainable using RS alongside immunohistochemistry (IHC), since histological examination is the current GOLD standard for diagnosing a wide range of diseases. Here, Raman spectral maps were generated using formalin-fixed, paraffin-embedded colonic tissue sections from healthy patients and spectral signatures from principal components analysis (PCA) were compared with several IHC markers to confirm the validity of their localizations. PCA loadings identified a number of signatures that could be assigned to muscle, DNA and mucin glycoproteins and their distributions were confirmed with antibodies raised against anti-Desmin, anti-Ki67 and anti-MUC2, respectively. The comparison confirms that there is excellent correlation between RS and the IHC markers used, demonstrating that the technique is capable of detecting compositional changes in tissue in a label-free manner, eliminating the need for antibodies.

Mirrored stainless steel substrate provides improved signal for Raman spectroscopy of tissue and cells

Raman spectroscopy (RS) is a powerful technique that permits the non-destructive chemical analysis of cells and tissues without the need for expensive and complex sample preparation. To date, samples have been routinely mounted onto calcium fluoride (CaF₂) as this material possesses the desired mechanical and optical properties for analysis, but CaF₂ is both expensive and brittle and this prevents the technique from being routinely adopted. Furthermore, Raman scattering is a weak phenomenon and CaF₂ provides no means of increasing signal. For RS to be widely adopted, particularly in the clinical field, it is crucial that spectroscopists identify an alternative, low-cost substrate capable of providing high spectral signal to noise ratios with good spatial resolution. Results show that these desired properties are attainable when using mirrored stainless steel as a Raman substrate. When compared with CaF₂, data show that stainless steel has a low background signal and provides an average signal increase of 1.43 times during tissue analysis and 1.64 times when analyzing cells. This result is attributed to a double-pass of the laser beam through the sample where the photons from the source laser and the forward scattered Raman signal are backreflected and retroreflected from the mirrored steel surface and focused towards collection optics. The spatial resolution on stainless steel is at least comparable to that on CaF₂ and it is not compromised by the reflection of the laser. Steel is a fraction of the cost of CaF₂ and the reflection and focusing of photons improve signal to noise ratios permitting more rapid mapping. The low cost of steel coupled with its Raman signal increasing properties and robust durability indicates that steel is an ideal substrate for biological and clinical RS as it possesses key advantages over routinely used CaF₂. © 2016 The Authors. Journal of Raman Spectroscopy Published by John Wiley & Sons Ltd.

Evaluation of a confocal Raman probe for pathological diagnosis during colonoscopy

AIM

Raman spectroscopy of human tissue can provide a unique biochemical 'fingerprint' that alters with disease progression. Light incident on tissue is scattered and may be altered in wavelength, which can be represented as a Raman spectrum. A confocal fibreoptic Raman probe designed to fit down the accessory channel of a colonoscope has been constructed. This in-vitro study evaluated the accuracy of pathological diagnosis in the colon using probe-based Raman spectroscopy.

METHOD

Biopsy samples were collected at colonoscopy, snap frozen and stored at -80 °C. Raman spectra with 10-s and 1-s acquisition periods were measured with the probe tip in contact with the mucosal surface of thawed specimens. Mathematical modelling using principal component analysis followed by linear discriminant analysis was used to correlate Raman spectra with histopathological diagnoses.

RESULTS

Three-hundred and seventy-five Raman spectra were measured from a total of 356 colon biopsies (81 of normal colon mucosa, 79 of hyperplastic polyps, 92 of adenomatous polyps, 64 of adenocarcinoma and 40 of ulcerative colitis) from 177 patients. Spectral classification accuracies comparing pathology pairs ranged from 72.1 to 95.9% for 10-s acquisitions and from 61.5 to 95.1% for 1-s acquisitions. For a three-group model of normal, adenomatous and adenocarcinoma tissue, accuracies were 74.1% for 10-s acquisitions and 63.5% for 1-s acquisitions.

CONCLUSION

The confocal Raman probe system can distinguish between different colorectal pathologies. The probe has potential to establish Raman spectroscopy as a clinical tool for instant diagnosis at colonoscopy.

Assessment of a custom-built Raman spectroscopic probe for diagnosis of early oesophageal neoplasia

We evaluate the potential of a custom-built fiber-optic Raman probe, suitable for in vivo use, to differentiate between benign, metaplastic (Barrett's oesophagus), and neoplastic (dysplastic and malignant) oesophageal tissue ex vivo on short timescales. We measured 337 Raman spectra (λ(ex)=830 nm; P(ex)=60 mW; t=1 s) using a confocal probe from fresh (298) and snap-frozen (39) oesophageal tissue collected during surgery or endoscopy from 28 patients. Spectra were correlated with histopathology and used to construct a multivariate classification model which was tested using leave one tissue site out cross-validation in order to evaluate the diagnostic accuracy of the probe system. The Raman probe system was able to differentiate, when tested with leave one site out cross-validation, between normal squamous oesophagus, Barrett's oesophagus and neoplasia with sensitivities of (838% to 6%) and specificities of (89% to 99%). Analysis of a two group model to differentiate Barrett's oesophagus and neoplasia demonstrated a sensitivity of 88% and a specificity of 87% for classification of neoplastic disease. This fiber-optic Raman system can provide rapid, objective, and accurate diagnosis of oesophageal pathology ex vivo. The confocal design of this probe enables superficial mucosal abnormalities (metaplasia and dysplasia) to be classified in clinically applicable timescales paving the way for an in vivo trial.

Support vector machines for classification and regression

The increasing interest in Support Vector Machines (SVMs) over the past 15 years is described. Methods are illustrated using simulated case studies, and 4 experimental case studies, namely mass spectrometry for studying pollution, near infrared analysis of food, thermal analysis of polymers and UV/visible spectroscopy of polyaromatic hydrocarbons. The basis of SVMs as two-class classifiers is shown with extensive visualisation, including learning machines, kernels and penalty functions. The influence of the penalty error and radial basis function radius on the model is illustrated. Multiclass implementations including one vs. all, one vs. one, fuzzy rules and Directed Acyclic Graph (DAG) trees are described. One-class Support Vector Domain Description (SVDD) is described and contrasted to conventional two- or multi-class classifiers. The use of Support Vector Regression (SVR) is illustrated including its application to multivariate calibration, and why it is useful when there are outliers and non-linearities.

Pattern recognition of inductively coupled plasma atomic emission spectroscopy of human scalp hair for discriminating between healthy and hepatitis C patients

Inductively Coupled Plasma Atomic Emission Spectroscopy measurements of six trace elements were performed on the scalp hair of 155 donors, 73 of which have been diagnosed with Hepatitis C and 82 Controls. Principal Components Analysis (PCA) was employed to visualise the separation between groups and show the relationship between the elements and the diseased state. Pattern recognition methods for classification involving Quadratic Discriminant Analysis and Partial Least Squares Discriminant Analysis (PLS-DA) were applied to the data. The number of significant components for both PCA and PLS were determined using the bootstrap. The stability of training set models were determined by repeatedly splitting the data into training and test sets and employing visualisation for two components models: the percent classification ability (CC), predictive ability (PA) and model stability (MS) were computed for test and training sets.

Learning Vector Quantization for Multiclass Classification: Application to Characterization of Plastics

Learning vector quantization (LVQ) is described, with both the LVQ1 and LVQ3 algorithms detailed. This approach involves finding boundaries between classes based on codebook vectors that are created for each class using an iterative neural network. LVQ has an advantage over traditional boundary methods such as support vector machines in the ability to model many classes simultaneously. The performance of the algorithm is tested on a data set of the thermal properties of 293 commercial polymers, grouped into nine classes: each class in turn consists of several grades. The method is compared to the Mahalanobis distance method, which can also be applied to a multiclass problem. Validation of the classification ability is via iterative splits of the data into test and training sets. For the data in this paper, LVQ is shown to perform better than the Mahalanobis distance as the latter method performs best when data are distributed in an ellipsoidal manner, while LVQ makes no such assumption and is primarily used to find boundaries. Confusion matrices are obtained of the misclassification of polymer grades and can be interpreted in terms of the chemical similarity of samples.

Ionization of H2 Rydberg molecules at a metal surface

The ionization of a beam of H2 Rydberg molecules in collision with a metal surface (evaporated Au or Al) is studied. The Rydberg states are excited in an ultraviolet-vacuum ultraviolet double-resonant process and are state selected with a core rotational quantum number N+=0 or 2 and principal quantum numbers n=17-22 (N+=2) or n=41-45 (N+=0). It is found that the N+=0 states behave in a very similar manner to previous studies with atomic xenon Rydberg states, the distance of ionization from the surface scaling with n2. The N+=2 states, however, undergo a process of surface-induced rotational autoionization in which the core rotational energy transfers to the Rydberg electron. In this case the ionization distance scales approximately with nu0(2), the effective principal quantum number with respect to the adiabatic threshold. This process illustrates the close similarity between field ionization in the gas phase and the surface ionization process which is induced by the field due to image charges in the metal surface. The surface ionization rate is enhanced at certain specific values of the field, which is applied in the time interval between excitation and surface interaction. It is proposed here that these fields correspond to level crossings between the N+=0 and N+=2 Stark manifolds. The population of individual states of the N+=2, n=18 Stark manifold in the presence of a field shows that the surface-induced rotational autoionization is more facile for the blueshifted states, whose wave function is oriented away from the surface, than for the redshifted states. The observed processes appear to show little dependence on the chemical nature of the metallic surface, but a significant change occurs when the surface roughness becomes comparable to the Rydberg orbit dimensions.

Factors influencing the contamination of UK banknotes with drugs of abuse

Bank of England banknotes sampled from different locations in the UK have been analysed for the presence of cocaine, diamorphine (DAM), Delta(9)-tetrahydrocannabinol (THC) and 3,4-methylenedioxymethamphetamine (MDMA). A database of the contamination detected is routinely used as a benchmark against which the contamination detected on seized banknotes can be compared. Evidence presented at court details how banknotes seized from a suspect may differ from banknotes in general circulation in terms of their contamination with controlled drugs. A question arising from such evidence is whether seized banknotes could have become contaminated through being in circulation in drug "hot spots". In order to address this issue, a Plackett-Burman experimental design was used to investigate the influence of source location and other factors on banknote contamination with drugs of abuse. Banknotes were drawn from banks in eight regions throughout the UK. Each location could be described by a unique combination of the factors under investigation, namely whether the location was rural or urban, in the North or South of the UK, and whether it was a port of entry. The socio-economic class and the proportion of drug offenders in the area and the denomination of the banknotes were also considered as potentially influential factors. Indices were calculated to describe the degree to which samples were contaminated with different drugs, and normal probability plots were used to identify the factors that could account for the contamination observed. Whilst some factors were more influential than others, it was shown that, at the 95% confidence level, none of the proposed factors were significant influences on the contamination. Cocaine contamination on banknotes has been shown to follow a log-normal distribution. It was, therefore, possible to calculate F- and t-statistics to compare the cocaine contamination on the entire sample set with that detected on a second sample set consisting of banknotes all drawn from a single bank branch. It was shown that both inter-bank samples and intra-bank samples had similar variance and similar contamination levels at the 95% confidence level. This suggests that there are no significant regional trends in the contamination of banknotes with drugs of abuse across the UK.

Ionization of hydrogen Rydberg molecules at a metal surface

The interaction of a beam of Rydberg molecules with a metal surface is investigated for the first time. Hydrogen molecules in a supersonic expansion are excited to Rydberg states with principal quantum number n, in the range 17-22 and are directed at a small angle onto a flat surface of either aluminum or gold. Detection of ions produced when Rydberg electrons tunnel into the metal surface provides information on the interaction between the Rydberg molecules and the surface potential. The experimental results suggest that, when close to the metal surface, the Rydberg molecules undergo a process of surface-induced rotational autoionization. It is found that the surface-ionization cross section shows strong resonances as a function of the applied electric field, which are independent of the metal studied.

A calorimetric investigation into the interaction between paracetamol and polyethlene glycol 4000 in physical mixes and solid dispersions

The solubility, heat of solution and dissolution rate of paracetamol and polyethyelene glycol 4000 (PEG 4000) systems have been studied in order to clarify the nature of the interaction between the two components during dissolution of solid dispersions. The logarithmic solubility of paracetamol demonstrated a non-linear increase with concentration of PEG 4000, while linear relationships between heat of solution in water and concentration were seen for both individual components. However, the heat of solution of paracetamol was found to decrease with increasing concentrations of PEG 4000. Similarly, the heats of solution in water of physical mixes and solid dispersions prepared using two manufacturing protocols were found to be lower than the theoretical values calculated from those corresponding to the individual components. Drug release studies showed a marked increase in paracetamol dissolution rate when prepared as a solid dispersion, with behaviour consistent with carrier controlled dissolution observed at low drug contents which was ascribed to enhanced dissolution of the drug into the diffusion layer of the PEG 4000. The implications of the understanding of this mechanism for the choice of carrier and manufacturing protocol for solid dispersion products is discussed.

An investigation into the melting behavior of binary mixes and solid dispersions of paracetamol and PEG 4000

The melting behavior of paracetamol and polyethylene glycol (PEG) 4000, both individually and as binary systems, has been studied using differential scanning calorimetry. The appearance of the PEG peaks was shown to be highly dependent on scanning rate, with evidence for the existence of once-folded and extended chain forms being noted at slower scanning speeds. The melting peak of paracetamol was found to be profoundly influenced by the presence of the PEG 4000; when observed at all, the endotherm became broader and occurred at a lower temperature on mixing with the polymer. The thermal behavior of the binary mixes was again highly dependent on scanning rate, with faster rates leading to the appearance of the paracetamol peak at lower concentrations. The mixes were then thermally cycled to mimic production of solid dispersions, showing that the temperature cycling of the PEG 4000 could result in binary melting with the paracetamol peak disappearing. The interpretation of these results in terms of the characterization of PEG solid dispersions is discussed.

The case of the missing vault: a "cold" bone lesion following electrical burn

Osteonecrosis of the skull produced by an electrical burn presented as a dramatic "cold" bone lesion on an MDP bone scan, despite normal skull radiographs. Four months later the skull radiograph showed marked bone resorption, and the three-phase bone scan confirmed healing and new osteoblastic activity. The pathophysiology of high-voltage injuries is outlined.

A miniaturized counting technique for anaerobic bacteria

A miniaturized counting technique gave results as good as the pour-plate and Most Probable Number (MPN) techniques for enumeration of clostridia spp. and anaerobic isolates from the gut. Highest counts were obtained when ascorbic acid (1%) and dithiothreitol (0.015%) were added to the reinforced clostridial medium used for counting. This minimized the effect of exposure to air before incubation. The miniature technique allowed up to 40 samples to be plated and incubated in one McIntosh-Filde's-type anaerobic jar, compared with 3 or 4 by the normal pour plate.