Metabolomic analysis of molecular species of phospholipids from normotensive and preeclamptic human placenta electrospray ionization mass spectrometry

Integrative Placental Multi-Omics Analysis Reveals Perturbed Pathways and Potential Prognostic Biomarkers in Gestational Hypertension

BACKGROUND

Gestational hypertension (GH) is a severe complication that occurs after 20 weeks of pregnancy; however, its molecular mechanisms are not yet fully understood.

OBJECTIVE

Through this case-control discovery phase study, we aimed to find disease-specific candidate placental microRNAs (miRNAs) and metabolite markers for differentiating GH by integrating next-generation sequencing and metabolomics multi-omics analysis of placenta. Using small RNA sequencing and metabolomics of placental tissues of healthy pregnant (HP, n = 24) and GH subjects (n = 20), the transcriptome and metabolome were characterized in both groups.

RESULTS

The study identified a total of 44 downregulated placental miRNAs which includes three novel, three mature and 38 precursor miRNAs. Six miRNAs including three mature (hsa-miR-181a-5p, hsa-miR-498-5p, and hsa-miR-26b-5p) and three novel (NC_000016.10_1061, NC_000005.10_475, and NC_000001.11_53) were considered for final target prediction and functional annotation. Integrative analysis of differentially expressed miRNAs and metabolites yielded five pathways such as purine, glutathione, glycerophospholipid, inositol phosphate and β-alanine to be significantly perturbed in GH. We present fourteen genes (LPCAT1, LPCAT2, DGKH, PISD, GPAT2, PTEN, SACM1L, PGM2, AMPD3, AK7, AK3, CNDP1, IDH2, and ODC1) and eight metabolites (xanthosine, xanthine, spermine, glycine, CDP-Choline, glyceraldehyde 3-phosphate, β-alanine, and histidine) with potential to distinguish GH and HP.

CONCLUSION

The differential expression of miRNAs, their target genes, altered metabolites and metabolic pathways in GH patients were identified for the first time in our study. Further, the altered miRNAs and metabolites were integrated to build their inter-connectivity network. The findings obtained from our study may be used as a valuable source to further unravel the molecular pathways associated with GH and also for the evaluation of prognostic markers.

Identification of Biomarkers for Preeclampsia Based on Metabolomics

Background

Preeclampsia (PE) is a significant cause of maternal and neonatal morbidity and mortality worldwide. However, the pathogenesis of PE is unclear and reliable early diagnostic methods are still lacking. The purpose of this review is to summarize potential metabolic biomarkers and pathways of PE, which might facilitate risk prediction and clinical diagnosis, and obtain a better understanding of specific metabolic mechanisms of PE.

Methods

This review included human metabolomics studies related to PE in the PubMed, Google Scholar, and Web of Science databases from January 2000 to November 2021. The reported metabolic biomarkers were systematically examined and compared. Pathway analysis was conducted through the online software MetaboAnalyst 5.0.

Results

Forty-one human studies were included in this systematic review. Several metabolites, such as creatinine, glycine, L-isoleucine, and glucose and biomarkers with consistent trends (decanoylcarnitine, 3-hydroxyisovaleric acid, and octenoylcarnitine), were frequently reported. In addition, eight amino acid metabolism-related, three carbohydrate metabolism-related, one translation-related and one lipid metabolism-related pathways were identified. These biomarkers and pathways, closely related to renal dysfunction, insulin resistance, lipid metabolism disorder, activated inflammation, and impaired nitric oxide production, were very likely to contribute to the progression of PE.

Conclusion

This study summarized several metabolites and metabolic pathways, which may be associated with PE. These high-frequency differential metabolites are promising to be biomarkers of PE for early diagnosis, and the prominent metabolic pathway may provide new insights for the understanding of the pathogenesis of PE.

Metabolomics Applied to Cord Serum in Preeclampsia Newborns: Implications for Neonatal Outcomes

Preeclampsia (PE) is one of the leading causes of maternal and perinatal morbidity and mortality. However, it is still uncertain how PE affects neonate metabolism. We conducted an untargeted metabolomics analysis of cord blood to explore the metabolic changes in PE neonates. Umbilical cord serum samples from neonates with preeclampsia (n = 29) and non-preeclampsia (non-PE) (n = 32) pregnancies were analyzed using the UHPLC-QE-MS metabolomic platform. Different metabolites were screened, and pathway analysis was conducted. A subgroup analysis was performed among PE neonates to compare the metabolome between appropriate-for-gestational-age infants (n = 21) and small-for-gestational-age (SGA) infants (n = 8). A total of 159 different metabolites were detected in PE and non-PE neonates. Creatinine, N4-acetylcytidine, sphingomyelin (D18:1/16:0), pseudouridine, uric acid, and indolelactic acid were the most significant differential metabolites in the cord serum of PE neonates. Differential metabolite levels were elevated in PE neonates and were involved in the following metabolic pathways: glycine, serine, and threonine metabolism; sphingolipid, glyoxylate, and dicarboxylate metabolism; and arginine biosynthesis. In PE neonates, SGA neonates showed increased levels of hexacosanoyl carnitine and decreased abundance of 3-hydroxybutyric acid and 3-sulfinoalanine. Taurine-related metabolism and ketone body-related pathways were mainly affected. Based on the UHPLC-QE-MS metabolomics analysis, we identified the metabolic profiles of PE and SGA neonates. The abundance of metabolites related to certain amino acid, sphingolipid, and energy metabolism increased in the umbilical cord serum of PE neonates.

The value of coupling thin-layer chromatography to mass spectrometry in lipid research - a review

Mass spectrometry has emerged as an extremely powerful analytical tool, which is widely used in many fields. This broad application range became possible with the invention of MALDI and ESI as "soft ionization" techniques that keep fragmentation of the analyte to a minimum. However, when these techniques are applied to mixture analysis, less-sensitively detectable compounds may be suppressed by more sensitively detectable compounds, a process called "ion suppression". Thus, previous separation of the mixture into the individual lipid classes is necessary to be able to detect all compounds. This review summarizes the current knowledge in the field of combined TLC/MS and discusses the most important strengths and weaknesses of the different MS (particularly ionization) techniques with respect to phospholipids. This comprises techniques such as MALDI and ESI, but less established approaches such as plasma desorption will be also discussed.

Metabolomic biomarkers in midtrimester maternal plasma can accurately predict the development of preeclampsia

Early identification of patients at risk of developing preeclampsia (PE) would allow providers to tailor their prenatal management and adopt preventive strategies, such as low-dose aspirin. Nevertheless, no mid-trimester biomarkers have as yet been proven useful for prediction of PE. This study investigates the ability of metabolomic biomarkers in mid-trimester maternal plasma to predict PE. A case–control study was conducted including 33 pregnant women with mid-trimester maternal plasma (gestational age [GA], 16–24 weeks) who subsequently developed PE and 66 GA-matched controls with normal outcomes (mid-trimester cohort). Plasma samples were comprehensively profiled for primary metabolic and lipidomic signatures based on gas chromatography time-of-flight mass spectrometry (GC-TOF MS) and liquid chromatography Orbitrap mass spectrometry (LC-Orbitrap MS). A potential biomarker panel was computed based on binary logistic regression and evaluated using receiver operating characteristic (ROC) analysis. To evaluate whether this panel can be also used in late pregnancy, a retrospective cohort study was conducted using plasma collected from women who delivered in the late preterm period because of PE (n = 13) or other causes (n = 21) (at-delivery cohort). Metabolomic biomarkers were compared according to the indication for delivery. Performance of the metabolomic panel to identify patients with PE was compared also to a commonly used standard, the plasma soluble fms-like tyrosine kinase-1/placental growth factor (sFlt-1/PlGF) ratio. In the mid-trimester cohort, a total of 329 metabolites were identified and semi-quantified in maternal plasma using GC-TOF MS and LC-Orbitrap-MS. Binary logistic regression analysis proposed a mid-trimester biomarker panel for the prediction of PE with five metabolites (SM C28:1, SM C30:1, LysoPC C19:0, LysoPE C20:0, propane-1,3-diol). This metabolomic model predicted PE better than PlGF (AUC [95% CI]: 0.868 [0.844–0.891] vs 0.604 [0.485–0.723]) and sFlt-1/PlGF ratio. Analysis of plasma from the at-delivery cohort confirmed the ability of this biomarker panel to distinguish PE from non-PE, with comparable discrimination power to that of the sFlt-1/PlGF ratio. In conclusion, an integrative metabolomic biomarker panel in mid-trimester maternal plasma can accurately predict the development of PE and showed good discriminatory power in patients with PE at delivery.

Application of metabolomics to preeclampsia diagnosis

Preeclampsia is a multifactorial disorder defined by hypertension and increased urinary protein excretion during pregnancy. It is a significant cause of maternal and neonatal deaths worldwide. Despite various research efforts to clarify pathogenies of preeclampsia and predict this disease before beginning of symptoms, the pathogenesis of preeclampsia is unclear. Early prediction and diagnosis of women at risk of preeclampsia has not markedly improved. Therefore, the objective of this study was to perform a review on metabolomic articles assessing predictive and diagnostic biomarkers of preeclampsia. Four electronic databases including PubMed/Medline, Web of Science, Sciencedirect, and Scopus were searched to identify studies of preeclampsia in humans using metabolomics from inception to March 2018. Twenty-one articles in a variety of biological specimens and analytical platforms were included in the present review. Metabolite profiles may assist in the diagnosis of preeclampsia and discrimination of its subtypes. Lipids and their related metabolites were the most generally detected metabolites. Although metabolomic biomarkers of preeclampsia are not routinely used, this review suggests that metabolomics has the potential to be developed into a clinical tool for preeclampsia diagnosis and could contribute to an improved understanding of disease mechanisms.

ABBREVIATIONS

PE: preeclampsia; sFlt-1: soluble FMS-like tyrosine kinase-1; PlGF: placental growth factor; GC-MS: gas chromatography-mass spectrometry; LC-MS: liquid chromatography-mass spectrometry; NMR: nuclear magnetic resonance spectroscopy; HMDB: human metabolome database; RCT: randomized control trial; e-PE: early-onset PE; l-PE: late-onset PE; PLS-DA: partial least-squares-discriminant analysis; CRL: crown-rump length; UtPI: uterine artery Doppler pulsatility index; BMI: body mass index; MAP: mean arterial pressure; OS: oxidative stress; PAPPA: plasma protein A; FTIR: Fourier transform infrared; BCAA: branched chain amino acids; Arg: arginine; NO: nitric oxide.

Applications of Metabolomics in the Study and Management of Preeclampsia; A Review of the Literature

Introduction

Preeclampsia represents a major public health burden worldwide, but predictive and diagnostic biomarkers are lacking. Metabolomics is emerging as a valuable approach to generating novel biomarkers whilst increasing the mechanistic understanding of this complex condition.

Objectives

To summarize the published literature on the use of metabolomics as a tool to study preeclampsia.

Methods

PubMed and Web of Science were searched for articles that performed metabolomic profiling of human biosamples using either Mass-spectrometry or Nuclear Magnetic Resonance based approaches and which included preeclampsia as a primary endpoint.

Results

Twenty-eight studies investigating the metabolome of preeclampsia in a variety of biospecimens were identified. Individual metabolite and metabolite profiles were reported to have discriminatory ability to distinguish preeclamptic from normal pregnancies, both prior to and post diagnosis. Lipids and carnitines were among the most commonly reported metabolites. Further work and validation studies are required to demonstrate the utility of such metabolites as preeclampsia biomarkers.

Conclusion

Metabolomic-based biomarkers of preeclampsia have yet to be integrated into routine clinical practice. However, metabolomic profiling is becoming increasingly popular in the study of preeclampsia and is likely to be a valuable tool to better understand the pathophysiology of this disorder and to better classify its subtypes, particularly when integrated with other omic data.

Placental dimethyl acetal fatty acid derivatives are elevated in preeclampsia

Preeclampsia (PE) was shown to affect the placental content and the transfer of polyunsaturated fatty acids (PUFA) to the fetus. Plasmalogens, a type of phospholipids with a vinyl-ether link at the sn-1 position, play an antioxidant role and are specifically enriched in PUFA at the sn-2 position. In this study, we characterized plasmalogen-derived dimethyl acetal (DMA) fatty acid derivatives, 16:0 DMA, 18:0 DMA, 9c-/11c-18:1 DMA and PUFA in the placenta of normotensive (n = 20) and PE (n = 20) pregnancies, according to the sampling site: peri-insertion or periphery. Phospholipid fatty acids from the placenta and maternal erythrocytes were identified by gas chromatography mass spectrometry and quantified by flame ionization detection. We found elevated total DMA in the PE placenta by 18% when compared to normotensive controls (p = 0.026). Moreover, the 16:0 DMA account for more than 55% of DMA fatty acids measured in the placenta, and its level is significantly higher in PE than controls (p = 0.018). Also, we found elevated placental PUFA, 20:5(n-3), 22:5(n-3) and a low level of 20:4(n-3) in PE compared to controls. Placental DMA was highly correlated with n-6 and n-3 PUFA in both, normotensive and PE pregnancies. In sum, elevated DMA fatty acids in the PE placenta could be an indirect defensive mechanism against oxidative stress and poor placental fatty acid transfer in PE.

Analysis of in vitro oxidized human LDL phospholipids by solid-phase extraction and micellar electrokinetic capillary chromatography

Phospholipids of in vitro oxidized human low-density lipoproteins (LDL) were separated by two different solid-phase extraction (SPE) methods. One of the two methods was designed to test the effects of gradient elution. This SPE method isolated more phospholipids from in vitro oxidized LDL than the other one according to the results of liquid chromatography and electrospray ionization mass spectrometry (LC ESI-MS) analysis. A micellar electrokinetic capillary chromatography (MEKC) method was also used to analyze phospholipids separated by SPE. The results of MEKC and LC ESI-MS were consistent for the major phospholipid classes, including PC, lysoPC, PE, PI and PS. The MEKC profiles showed significant differences for native and oxidized LDL phospholipids. Therefore, the unique combination of SPE and MEKC methods showed dramatic distinctions between native and in vitro oxidized human LDL phospholipids. The combination also shows great potential for rapid analysis of in vivo oxidized human LDL phospholipids in the future.

Review: The effects of oxygen on normal and pre-eclamptic placental tissue--insights from metabolomics

Placental dysfunction is central to many complications of human pregnancy including pre-eclampsia (PE), intra-uterine growth restriction (IUGR) and stillbirth. The precise molecular pathophysiology of placental dysfunction in these conditions is not known, although oxidative and nitrative stresses have been implicated. Metabolites are low molecular weight chemicals which play an important role in biological function, primarily through metabolism and regulation of biological processes. The holistic study of metabolites, defined as metabolomics or metabolic profiling, has the objective to detect and identify all, or a large complement of all metabolites. Metabolomics is applied to discover new knowledge regarding biological processes and systems. We hypothesised that a metabolomic strategy could (1) provide a reproducible technique to investigate the intracellular metabolism of placental tissue and also metabolites consumed from or secreted in to the extracellular 'metabolic footprint' of in vitro culture systems (2) identify metabolic related differences in placental tissue culture systems subjected to perturbations in oxygen tension and from pregnancies complicated by PE. We review our early studies which demonstrate that a reproducible experimental protocol is required, including the preparation of culture medium and the site of the placenta applied for sampling tissue. We have detected changes in the intracellular metabolome and metabolic footprint of placental tissue in response to altered oxygen tension and PE. We have demonstrated that placental tissue from uncomplicated pregnancies cultured in 1% oxygen (hypoxia) had metabolic similarities to explants from PE pregnancies cultured at 6% oxygen (normoxia). Metabolites requiring further study include lipids, glutamate and glutamine and metabolites related to tryptophan, leukotriene and prostaglandin metabolism. Metabolomics has the potential to identify changes in clinical conditions, such as PE, that are associated with placental molecular pathophysiology.

Fine mapping the spatial distribution and concentration of unlabeled drugs within tissue micro-compartments using imaging mass spectrometry

Readouts that define the physiological distributions of drugs in tissues are an unmet challenge and at best imprecise, but are needed in order to understand both the pharmacokinetic and pharmacodynamic properties associated with efficacy. Here we demonstrate that it is feasible to follow the in vivo transport of unlabeled drugs within specific organ and tissue compartments on a platform that applies MALDI imaging mass spectrometry to tissue sections characterized with high definition histology. We have tracked and quantified the distribution of an inhaled reference compound, tiotropium, within the lungs of dosed rats, using systematic point by point MS and MS/MS sampling at 200 µm intervals. By comparing drug ion distribution patterns in adjacent tissue sections, we observed that within 15 min following exposure, tiotropium parent MS ions (mass-to-charge; m/z 392.1) and fragmented daughter MS/MS ions (m/z 170.1 and 152.1) were dispersed in a concentration gradient (80 fmol-5 pmol) away from the central airways into the lung parenchyma and pleura. These drug levels agreed well with amounts detected in lung compartments by chemical extraction. Moreover, the simultaneous global definition of molecular ion signatures localized within 2-D tissue space provides accurate assignment of ion identities within histological landmarks, providing context to dynamic biological processes occurring at sites of drug presence. Our results highlight an important emerging technology allowing specific high resolution identification of unlabeled drugs at sites of in vivo uptake and retention.

Metabolomics in premature labor: a novel approach to identify patients at risk for preterm delivery

OBJECTIVE

Biomarkers for preterm labor (PTL) and delivery can be discovered through the analysis of the transcriptome (transcriptomics) and protein composition (proteomics). Characterization of the global changes in low-molecular weight compounds which constitute the 'metabolic network' of cells (metabolome) is now possible by using a 'metabolomics' approach. Metabolomic profiling has special advantages over transcriptomics and proteomics since the metabolic network is downstream from gene expression and protein synthesis, and thus more closely reflects cell activity at a functional level. This study was conducted to determine if metabolomic profiling of the amniotic fluid can identify women with spontaneous PTL at risk for preterm delivery, regardless of the presence or absence of intraamniotic infection/inflammation (IAI).

STUDY DESIGN

Two retrospective cross-sectional studies were conducted, including three groups of pregnant women with spontaneous PTL and intact membranes: (1) PTL who delivered at term; (2) PTL without IAI who delivered preterm; and (3) PTL with IAI who delivered preterm. The first was an exploratory study that included 16, 19, and 20 patients in groups 1, 2, and 3, respectively. The second study included 40, 33, and 40 patients in groups 1, 2, and 3, respectively. Amniotic fluid metabolic profiling was performed by combining chemical separation (with gas and liquid chromatography) and mass spectrometry. Compounds were identified using authentic standards. The data were analyzed using discriminant analysis for the first study and Random Forest for the second.

RESULTS

(1) In the first study, metabolomic profiling of the amniotic fluid was able to identify patients as belonging to the correct clinical group with an overall 96.3% (53/55) accuracy; 15 of 16 patients with PTL who delivered at term were correctly classified; all patients with PTL without IAI who delivered preterm neonates were correctly identified as such (19/19), while 19/20 patients with PTL and IAI were correctly classified. (2) In the second study, metabolomic profiling was able to identify patients as belonging to the correct clinical group with an accuracy of 88.5% (100/113); 39 of 40 patients with PTL who delivered at term were correctly classified; 29 of 33 patients with PTL without IAI who delivered preterm neonates were correctly classified. Among patients with PTL and IAI, 32/40 were correctly classified. The metabolites responsible for the classification of patients in different clinical groups were identified. A preliminary draft of the human amniotic fluid metabolome was generated and found to contain products of the intermediate metabolism of mammalian cells and xenobiotic compounds (e.g. bacterial products and Salicylamide).

CONCLUSION

Among patients with spontaneous PTL with intact membranes, metabolic profiling of the amniotic fluid can be used to assess the risk of preterm delivery in the presence or absence of infection/inflammation.

Profiling and biomarker identification in plasma from different Zucker rat strains via high mass accuracy multistage mass spectrometric analysis using liquid chromatography/mass spectrometry with a quadrupole ion trap-time of flight mass spectrometer

High mass accuracy electrospray ionisation multistage tandem mass spectrometry (MS(n)) was applied to metabolite profiling studies on plasma samples derived from two strains of rat (the Zucker (fa/fa) obese strain and the normal wild type). Using a quadrupole ion trap time-of-flight (QIT-TOF) mass spectrometer, metabolite profiling software was applied to locate components of biological significance that could account for the differences between the two strains of rat and a formula prediction software tool was used to help identify individual components. The primary factor discriminating between the two populations was the concentration of endogenous lipids. In the Zucker (fa/fa) obese strain, the dominant ion signals and MS(n) spectra were in agreement with lysoglycerophosphocholine components such as palmitoyllysophosphatidylcholine, 1-oleoylglycerophosphocholine, 1-octadecyl-sn-glycero-3-phosphocholine and 1-stearoylglycerophosphocholine and these were found in relatively higher concentrations compared to the normal wild type. Components were identified using high mass accuracy MS(n) data, formula prediction software and by agreement with published mass spectra through internet databases, rather than using a conventional approach with authentic standards. This application shows that the use of high mass accuracy electrospray ionisation MS(n) together with a software tool can be used effectively to detect and characterise unknown analytes in complex matrices, and represents a promising approach for future profiling studies.

The use of high-dimensional biology (genomics, transcriptomics, proteomics, and metabolomics) to understand the preterm parturition syndrome

High-dimensional biology (HDB) refers to the simultaneous study of the genetic variants (DNA variation), transcription (messenger RNA [mRNA]), peptides and proteins, and metabolites of an organ, tissue, or an organism in health and disease. The fundamental premise is that the evolutionary complexity of biological systems renders them difficult to comprehensively understand using only a reductionist approach. Such complexity can become tractable with the use of "omics" research. This term refers to the study of entities in aggregate. The current nomenclature of "omics" sciences includes genomics for DNA variants, transcriptomics for mRNA, proteomics for proteins, and metabolomics for intermediate products of metabolism. Another discipline relevant to medicine is pharmacogenomics. The two major advances that have made HDB possible are technological breakthroughs that allow simultaneous examination of thousands of genes, transcripts, and proteins, etc., with high-throughput techniques and analytical tools to extract information. What is conventionally considered hypothesis-driven research and discovery-driven research (through "omic" methodologies) are complementary and synergistic. Here we review data which have been derived from: 1) genomics to examine predisposing factors for preterm birth; 2) transcriptomics to determine changes in mRNA in reproductive tissues associated with preterm labour and preterm prelabour rupture of membranes; 3) proteomics to identify differentially expressed proteins in amniotic fluid of women with preterm labour; and 4) metabolomics to identify the metabolic footprints of women with preterm labour likely to deliver preterm and those who will deliver at term. The complementary nature of discovery science and HDB is emphasised.

Diet and Cancer: Facts and Controversies

Evidence continues to mount that dietary components are important determinants of cancer risk and tumor behavior. Although these linkages are fascinating, numerous inconsistencies are also evident in the literature. Although multifactorial, these discrepancies likely reflect variation in the ability of food constituents to reach and/or modify critical molecular targets. Genetic polymorphisms can alter the response to dietary components (nutrigenetic effect) by influencing the absorption, metabolism, or site of action. Likewise, variation in DNA methylation patterns and other epigenomic events that influence overall gene expression can influence the biological response to food components and vice versa. Fluctuations in the ability of food components to increase or depress gene expression (nutritional transcriptomic effect) may also account for some of the inconsistencies in the response to foods. Functional proteomic studies that capture all of the proteins produced by a species and link them to physiological significance within the cell will be fundamental to understanding the relationship between dietary interventions, proteome changes, and cancer. Although a bioactive food component may influence a number of key molecular events that are involved with cancer prevention, to do so it must achieve an effective concentration within the target site, be in the correct metabolic form, and bring about a change in one or more small molecular weight signals in the cellular milleau (metabolomic effects). Fundamental to assessing and evaluating the significance of the interrelationships among bioactive food components with nutrigenetics, nutritional epigenomics, nutritional transcriptomics, proteomics, and metabolomics is knowledge about the appropriate tissue/cell or surrogate to evaluate and validated biomarkers that reflect changes in each. As the era of molecular nutrition grows, a greater understanding about the role of foods and their components on cancer risk and tumor behavior will surely unfold. Such information will be critical in the development of effective preemptive approaches to reduce the cancer burden.

Current literature in mass spectrometry

In order to keep subscribers up-to-date with the latest developments in their field, John Wiley & Sons are providing a current awareness service in each issue of the journal. The bibliography contains newly published material in the field of mass spectrometry. Each bibliography is divided into 11 sections: 1 Books, Reviews & Symposia; 2 Instrumental Techniques & Methods; 3 Gas Phase Ion Chemistry; 4 Biology/Biochemistry: Amino Acids, Peptides & Proteins; Carbohydrates; Lipids; Nucleic Acids; 5 Pharmacology/Toxicology; 6 Natural Products; 7 Analysis of Organic Compounds; 8 Analysis of Inorganics/Organometallics; 9 Surface Analysis; 10 Environmental Analysis; 11 Elemental Analysis. Within each section, articles are listed in alphabetical order with respect to author (4 Weeks journals - Search completed at 12th. Jan. 2005).