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PubMed2026

Discovery and validation of GNA12circle as a first-trimester plasma eccDNA marker for early-onset preeclampsia.

BACKGROUND: Early-onset preeclampsia (EOPE) is a major cause of maternal and perinatal morbidity and is characterized by placental dysfunction, systemic endothelial injury, and hypertensive vascular stress. Because hypertensive disorders of pregnancy may also signal later maternal cardiovascular and cerebrovascular vulnerability, effective biomarkers for first-trimester risk assessment remain clinically important. Extrachromosomal circular DNA (eccDNA), a stable form of circulating cell-free DNA, has emerged as a potential source of disease-associated biomarkers. This study aimed to characterize first-trimester plasma eccDNA alterations associated with subsequent EOPE and to identify and validate a candidate circulating eccDNA marker for early risk assessment. METHODS: A two-stage nested case-control study was conducted within a prospective birth cohort. In the discovery stage, plasma samples collected at 11-13 weeks of gestation from 5 women who subsequently developed EOPE and 5 matched normotensive controls were profiled by Circle-Seq to characterize genome-wide eccDNA alterations. Candidate eccDNAs were prioritized through differential abundance analysis and were further confirmed by outward PCR and Sanger sequencing. In the validation stage, the candidate selected marker was quantified by junction-specific qPCR in an independent cohort of 109 EOPE cases and 109 controls. Its potential predictive value was further evaluated alone and in combination with routine first-trimester clinical variables. RESULTS: In the exploratory discovery analysis, 410 nominally differentially abundant candidate eccDNAs were identified as a hypothesis-generating pool. Among these, GNA12circle (chr7:2876332-2,876,692) was prioritized and experimentally validated at the circular junction. In the independent validation cohort, plasma GNA12circle levels were significantly higher in women who later developed EOPE than in controls. When combined with routine first-trimester variables, GNA12circle improved predictive performance. The RF model showed the best overall cross-validated performance among the evaluated classifiers, with a mean held-out test-fold AUC of 0.843. CONCLUSION: First-trimester plasma eccDNA profiling revealed distinct alterations associated with subsequent EOPE, from which GNA12circle was identified and validated as a candidate circulating marker. These findings support further investigation of circulating eccDNA for early EOPE risk assessment in larger multicenter populations.

Humans↗

PubMed2004

Optimisation of a silicon/silicon dioxide substrate for a fluorescence DNA microarray.

This paper presents a comprehensive theory and experimental characterisation of the modulation of the fluorescence intensity by the construction of optical interferences on oxidised silicon substrates used for DNA microarrays. The model predicts a 90-fold variation of the fluorescence signal depending on the oxide thickness. For a Cy3 dye, the signal is maximal for a 90 nm oxide thickness corresponding to a 7.5-fold enhancement with respect to a standard glass substrate. For experimental validation of the model, we have prepared Si/SiO2 substrates with different parallel steps of decreasing oxide thicknesses on the same sample using a buffered oxide etch (BOE) etching process after thermal oxidation. The SiO2 surface has been functionalized by a silane monolayer before in situ synthesis of L185 oligonucleotide probes. After hybridisation with complementary targets, the variations of the fluorescence intensity versus oxide thickness are in very good accordance with the theoretical model. The experimental comparison against a glass substrate shows a 10-fold enhancement of the detection sensitivity. Our results demonstrate that a Si/SiO2 substrate is an attractive alternative to standard glass slides for the realisation of fluorescence DNA microarrays whenever detection sensitivity is an important issue.

Coated Materials, Biocompatible↗

PubMed1999

Optimization of the arthroscopic indentation instrument for the measurement of thin cartilage stiffness.

Structural alterations associated with early, mostly reversible, degeneration of articular cartilage induce tissue softening, generally preceding fibrillation and, thus, visible changes of the cartilage surface. We have already developed an indentation instrument for measuring arthroscopic stiffness of cartilage with typical thickness >2 mm. The aim of this study was to extend the applicability of the instrument for the measurement of thin (<2 mm) cartilage stiffness. Variations in cartilage thickness, which will not be known during arthroscopy, can nonetheless affect the indentation measurement, and therefore optimization of the indenter dimensions is necessary. First, we used theoretical and finite element models to compare plane-ended and spherical-ended indenters and, then, altered the dimensions to determine the optimal indenter for thin cartilage measurements. Finally, we experimentally validated the optimized indenter using bovine humeral head cartilage. Reference unconfined compression measurements were carried out with a material testing device. The spherical-ended indenter was more insensitive to the alterations in cartilage thickness (20% versus 39% in the thickness range 1.5-5 mm) than the plane-ended indenter. For thin cartilage, the optimal dimensions for the spherical-ended indenter were 0.5 mm for diameter and 0.1 mm for height. The experimental stiffness measurements with this indenter correlated well with the reference measurements (r = 0.811, n = 31, p < 0.0001) in the cartilage thickness range 0.7-1.8 mm. We conclude that the optimized indenter is reliable and well suited for the measurement of thin cartilage stiffness.

Animals↗

PubMed2026

Analysis and validation of abnormal signaling pathways and immune cell infiltration characteristics in digestive system cancers based on peroxisome-related genes.

BACKGROUND: Although emerging evidence suggests a role for peroxisomes in tumorigenesis, their functions in digestive cancers remain unclear. This study aims to investigate the association between peroxisomes and digestive tract tumors. METHODS: To systematically investigate peroxisomal functions in digestive cancers, we first constructed and validated tumor-specific prognostic signatures based on peroxisome-related genes (PRGs) through univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses. We then characterized the tumor immune microenvironment (TIME) with CIBERSORT, X-CELL, and EPIC algorithms, and identified tumor-specific and common signalings via Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA). Focusing on hepatocellular carcinoma (HCC), we experimentally validated peroxisome-related therapeutic responses by profiling signature genes in radioresistant cells and an orthotopic transarterial chemoembolization (TACE) rat model. PEX13 knockdown further assessed peroxisomal role in radiosensitivity and targeted therapy response. Clinical relevance of PEX13 was evaluated in HCC cohort. Single-cell RNA sequencing dataset and lipidomics further revealed peroxisomal mechanisms in HCC progression. Finally, peroxisomal function in colorectal cancer (CRC) was validated in vitro. RESULTS: Novel peroxisome-related prognostic signatures demonstrated strong predictive power in HCC, colon adenocarcinoma, rectal adenocarcinoma, pancreatic adenocarcinoma, gastric adenocarcinoma, esophageal adenocarcinoma, esophageal squamous cell carcinoma, and cholangiocarcinoma. High-risk patients displayed an immunosuppressive microenvironment, characterized by increased infiltration of regulatory T cells, M2 macrophages, Th2 cells, or cancer-associated fibroblasts, or Th1 cells' reduction. Peroxisomes engaged in several distinct yet convergent pathways, most notably "positive regulation of response to stimuli". HCC prognostic genes were dynamically regulated in response to therapeutic stimuli, including radiotherapy, targeted therapy, and TACE. Clinically, the expression of PEX13 was markedly upregulated in tumor tissues from therapy-resistant HCC patients. Mechanistically, peroxisomal dysfunction induced by silencing PEX13 in HCC or UBE2D2 in CRC may overcome therapeutic resistance (radiotherapy/ lenvatinib resistance in HCC, radioresistance in CRC) through reprogramming lipid metabolism. CONCLUSIONS: Peroxisomes act as pivotal regulators of digestive cancer progression by modulating signaling pathways, the TIME, therapeutic resistance, and lipid metabolism. Targeting peroxisomal function, particularly in high-risk subgroups of HCC and CRC, warrants further exploration as a promising therapeutic strategy.

Peroxisomes↗

PubMed2000

Integrated pressure-force-kinematics measuring system for the characterisation of plantar foot loading during locomotion.

Plantar pressure, ground reaction force and body-segment kinematics measurements are largely used in gait analysis to characterise normal and abnormal function of the human foot. The combination of all these data together provides a more exhaustive, detailed and accurate view of foot loading during activities than traditional measurement systems alone do. A prototype system is presented that integrates a pressure platform, a force platform and a 3D anatomical tracking system to acquire combined information about foot function and loading. A stereophotogrammetric system and an anatomically based protocol for foot segment kinematics is included in a previously devised piezo-dynamometric system that combines pressure and force measurements. Experimental validation tests are carried out to check for both spatial and time synchronisation. Misalignment of the three systems is found to be within 6.0, 5.0 and 1.5 mm for the stereophotogrammetric system, force platform and pressure platform, respectively. The combination of position and pressure data allows for a more accurate selection of plantar foot subareas on the footprint. Measurements are also taken on five healthy volunteers during level walking to verify the feasibility of the overall experimental protocol. Four main subareas are defined and identified, and the relevant vertical and shear force data are computed. The integrated system is effective when there is a need for loading measurements in specific plantar foot subareas. This is attractive both in clinical assessment and in biomechanics research.

Biomechanical Phenomena↗

PubMed2006

A supervised hidden markov model framework for efficiently segmenting tiling array data in transcriptional and chIP-chip experiments: systematically incorporating validated biological knowledge.

MOTIVATION: Large-scale tiling array experiments are becoming increasingly common in genomics. In particular, the ENCODE project requires the consistent segmentation of many different tiling array datasets into 'active regions' (e.g. finding transfrags from transcriptional data and putative binding sites from ChIP-chip experiments). Previously, such segmentation was done in an unsupervised fashion mainly based on characteristics of the signal distribution in the tiling array data itself. Here we propose a supervised framework for doing this. It has the advantage of explicitly incorporating validated biological knowledge into the model and allowing for formal training and testing. METHODOLOGY: In particular, we use a hidden Markov model (HMM) framework, which is capable of explicitly modeling the dependency between neighboring probes and whose extended version (the generalized HMM) also allows explicit description of state duration density. We introduce a formal definition of the tiling-array analysis problem, and explain how we can use this to describe sampling small genomic regions for experimental validation to build up a gold-standard set for training and testing. We then describe various ideal and practical sampling strategies (e.g. maximizing signal entropy within a selected region versus using gene annotation or known promoters as positives for transcription or ChIP-chip data, respectively). RESULTS: For the practical sampling and training strategies, we show how the size and noise in the validated training data affects the performance of an HMM applied to the ENCODE transcriptional and ChIP-chip experiments. In particular, we show that the HMM framework is able to efficiently process tiling array data as well as or better than previous approaches. For the idealized sampling strategies, we show how we can assess their performance in a simulation framework and how a maximum entropy approach, which samples sub-regions with very different signal intensities, gives the maximally performing gold-standard. This latter result has strong implications for the optimum way medium-scale validation experiments should be carried out to verify the results of the genome-scale tiling array experiments.

Artificial Intelligence↗

PubMed2005

Estimating non-isothermal bacterial growth in foods from isothermal experimental data.

AIM: To develop a mathematical method to estimate non-isothermal microbial growth curves in foods from experiments performed under isothermal conditions and demonstrate the method's applicability with published growth data. METHODS AND RESULTS: Published isothermal growth curves of Pseudomonas spp. in refrigerated fish at 0-8 degrees C and Escherichia coli 1952 in a nutritional broth at 27.6-36 degrees C were fitted with two different three-parameter 'primary models' and the temperature dependence of their parameters was fitted by ad hoc empirical 'secondary models'. These were used to generate non-isothermal growth curves by solving, numerically, a differential equation derived on the premise that the momentary non-isothermal growth rate is the isothermal rate at the momentary temperature, at a time that corresponds to the momentary growth level of the population. The predicted non-isothermal growth curves were in agreement with the reported experimental ones and, as expected, the quality of the predictions did not depend on the 'primary model' chosen for the calculation. CONCLUSIONS: A common type of sigmoid growth curve can be adequately described by three-parameter 'primary models'. At least in the two systems examined, these could be used to predict growth patterns under a variety of continuous and discontinuous non-isothermal temperature profiles. SIGNIFICANCE AND IMPACT OF THE STUDY: The described mathematical method whenever validated experimentally will enable the simulation of the microbial quality of stored and transported foods under a large variety of existing or contemplated commercial temperature histories.

Animals↗

PubMed2003

Multiple roles of the tuberous sclerosis complex genes.

Soon after proposing the "two-hit" hypothesis for tumorigenesis, Knudson pursued further experimental validation of the concept by using a rat model of dominantly inherited renal tumor. Today, the Eker rat is one of the best characterized models of tuberous sclerosis complex (TSC) and has been used extensively for study of the function of the TSC2 tumor suppressor gene. Along with TSC1, these two genes behave as expected for tumor suppressor genes with evidence for loss of heterozygosity in tumors and suppression of growth when expressed in proliferating cells. Despite much experimental work, the mechanisms of these genes have remained elusive until recently. This review summarizes some of the current concepts in our understanding of the biological and biochemical function of the TSC genes.

Animals↗

PubMed2003

Validation of a pencil beam model-based treatment planning system for fast neutron therapy.

Treatment planning systems (TPSs) are used to compute dose delivered to the patient. In the case of fast neutron therapy, TPSs are mostly not of general purpose but are dedicated to one facility. This is due to the few fast neutron facilities worldwide and due to the high variation in the neutron energy distributions. Efforts have been undertaken to develop a new TPS that could be applied to all the existing fast neutron facilities. The University Hospital of Essen operates a d (14 MeV) + Be fast neutron beam and the TPS used is based on an empirical model. In a previous study, the empirical model has been evolved to a pencil beam model of 35 monoenergetic neutron beams. Monte Carlo techniques have been utilized to compute distributions of the energy deposition due to primary and scattered neutrons in a simple geometry water phantom. The experimental validation of the method is now presented. Depth dose curves in water of monoenergetic neutrons have been derived from the distributions of energy deposition. The resultant depth dose curves have been utilized in order to determine the depth dose curves of the fast neutron beam of the Essen facility for the 14 radiation field sizes available in this facility. This determination requires the initial neutron spectrum. As this spectrum could not be measured at the Essen facility, the initial neutron spectrum of the Physikalisch Technische Bundesanstalt, Braunschweig, Germany, which operates the same cyclotron, was used. The calculated depth dose curves were compared to experimental depth dose curves that have been obtained in water at the University Hospital of Essen. The comparison between calculated and experimental depth dose curves showed significant deviations in the case of large radiation fields and of depth less than 5 cm. In the case of radiation field areas less than 150 cm2 and depth more than 5 cm (usual clinical situation), the measured and calculated values are in a good agreement. In the case of clinical situation, the dependence on the radiation field size is relatively well taken into account by the model presented here.

Computer Simulation↗

PubMed2003

Dynamic flavor release from sucrose solutions.

The initial dynamic flavor release from sucrose solutions was modeled. Modeling was based on the theoretical hydration behavior of sucrose, theoretical physicochemical data of flavor volatiles, and process parameters of a headspace apparatus used for model validation. The rate-limiting factor determining the initial flavor release was the hydration of sucrose, which in turn depends on the molarity of sucrose in the solution and, therefore, on the actual amount of nonbound water. Improved solubility of the more hydrophilic compounds due to their orientation toward the hydration shells of the sugar molecules was considered. The viscosity of nonassociated water forming the microregion for mass transfer of volatiles was considered instead of the bulk solution viscosity. Experimental validation of the model by real-time measurements of dynamic flavor release using foodlike flavor concentrations confirmed the above theory. Increasing sucrose concentrations resulted predominantly in increased flavor release, and bulk solution viscosity showed no effect.

Chemical Phenomena↗

PubMed2000

Modelling individual temperature profiles from an isolated perfused bovine tongue.

To predict the temperature distribution during hyperthermia treatments a thermal model that accounts for the thermal effect of blood flow is mandatory. The DIscrete VAsculature (DIVA) thermal model developed at our department is able to do so; geometrically described vessels are handled individually and the remaining vasculature is modelled collectively. The goal of this paper is to experimentally validate the DIVA model by comparing measured with modelled temperature profiles on an individual basis. Temperature profiles in an isolated bovine tongue heated with three hot water tubes were measured at three controlled perfusion levels, 0, 6 and 24 ml (100 g)(-1) min(-1). The geometries of the tongue, the hot water tubes, thermocouples and discrete vasculature down to 0.5 mm diameter were reconstructed by using cryo-microtome slices at 0.1 mm cubic resolution. This reconstruction of the experimental set-up is used for the modelling of individual profiles. In a no-flow agar-agar phantom, DIVA showed nearly perfect correspondence between measurements and simulations. In the isolated bovine tongue the correspondence at no flow was slightly disturbed due to geometrical distortion in the reconstruction of the experimental set-up. Measurements showed decreasing temperature profiles with increasing perfusion. DIVA correctly predicted this decrease in temperature as well as the thermal impact of a large vessel close to a thermocouple. Blood flow was modelled using discrete vasculature and using a heat sink model. Although at 24 ml (100 g)(-1) min(-1) correspondence between heat sink simulations and measurements was reasonable, modelling discrete vasculature yielded the best correspondence at both 6 and 24 ml (100 g)(-1) min(-1). The results strongly suggest that with accurate data acquisition DIVA can predict temperature profiles on an individual basis. For this kind of patient-specific treatment planning in the clinic, geometrical reconstruction of the anatomy, vasculature and the heating implant is necessary. MRI is capable of providing these data. Further research will be done on thermal simulations of actual clinical hyperthermia treatments.

Agar↗

PubMed2026

CLASPP: A unified model for predicting post-translational modifications.

Post-Translational Modifications (PTMs) are a fundamental mechanism for regulating cellular pathways and increasing the functional diversity of the proteome. Accurately predicting the PTM types that are likely to occur at a given site in the primary sequence is a key challenge in functional proteomics. Existing PTM prediction models predominantly focus on either single PTM types or employ ensemble methods that combine multiple models to predict different PTM types. This fragmentation is largely driven by the vast imbalance in data availability across PTM types, making it difficult to predict multiple PTM types with a single model. To address this limitation, we present the Contrastively Learned Attention-based Stratified PTM Predictor (CLASPP), a unified PTM prediction model. CLASPP addresses imbalance challenges by leveraging unsupervised clustering-based undersampling and a novel contrastive learning framework tailored to PTM data. Additionally, our hierarchical data organization and curation are shown to improve CLASPP's performance by balancing the representation of individual PTM types and provides a standardized dataset to train and validate future model designs. Drawing inspiration from advancements in image and natural language processing, the CLASPP model employs a multi-stage training strategy and a high-quality, curated training dataset to improve PTM prediction performance. To uncover what is learned during the contrastive learning stage, the CLASPP model is shown to distinguish known protein kinase substrate specificity profiles as a form of explainability. Finally, we evaluate the application of CLASPP in predicting PTMs in different model organisms and experimentally validated ubiquitination sites in the understudied DCLK3 kinase. Overall, CLASPP represents a unified model for PTM prediction that addresses key bottlenecks in data imbalance and offers new strategies for biological data curation, thereby improving PTM-type prediction performance across diverse organisms.

Protein Processing, Post-Translational↗

PubMed1999

Engineering a thermostable protein via optimization of charge-charge interactions on the protein surface.

A simple theoretical model for increasing the protein stability by adequately redesigning the distribution of charged residues on the surface of the native protein was tested experimentally. Using the molecule of ubiquitin as a model system, we predicted possible amino acid substitutions on the surface of this protein which would lead to an increase in its stability. Experimental validation for this prediction was achieved by measuring the stabilities of single-site-substituted ubiquitin variants using urea-induced unfolding monitored by far-UV CD spectroscopy. We show that the generated variants of ubiquitin are indeed more stable than the wild-type protein, in qualitative agreement with the theoretical prediction. As a positive control, theoretical predictions for destabilizing amino acid substitutions on the surface of the ubiquitin molecule were considered as well. These predictions were also tested experimentally using correspondingly designed variants of ubiquitin. We found that these variants are less stable than the wild-type protein, again in agreement with the theoretical prediction. These observations provide guidelines for rational design of more stable proteins and suggest a possible mechanism of structural stability of proteins from thermophilic organisms.

Amino Acid Substitution↗

PubMed1976

[Herpes therapy and prophylaxis. I. A critical review (author's transl)].

This critical review is based upon controlled experimental and clinical data. Dendritic keratitis initially should be treated by debridement of the diseased epithelium followed by antiviral medication. The advantages and disadvantages of different debridement techniques and different synthetic antivirals are discussed. Rational treatment of other forms of herpetic eye disease with antivirals, steroids, therapeutic soft lenses, collagenase inhibitors etc. necessitates first of all an exact diagnosis (disciform edema, interstitial herpetic keratitis, herpetic (kerato-)uveitis, metaherpetic erosion, metaherpetic ulcer). Therapeutic or prophylactic measures which as yet have found no valid experimental or clinical basis are discussed as well as further developments. Special interest is laid upon the application of human interferon.

Animals↗

PubMedDate not supplied

[Development and study of immunoglobulins against Lassa fever].

The authors validate the use of horses as producers of immune antiserum to Lassa virus. Specific immunoglobulin with at least 1:512 titer of virus neutralizing antibodies to Lassa virus was obtained from the serum of immunized horses by Kohn's alcohol method. The resultant preparation does not differ from the heterologous commercial immunoglobulins. Preclinical studies of immunoglobulin against Lassa virus demonstrated its safety and high specific activity. The strategy of treating with the immunoglobulin alone and in combination with virasol has been experimentally validated.

Animals↗

PubMed2005

Simulated bioprosthetic heart valve deformation under quasi-static loading.

For more than 40 years, the replacement of diseased natural heart valves with prosthetic devices has dramatically extended the quality and length of the lives of millions of patients worldwide. However, bioprosthetic heart valves (BHV) continue to fail due to structural failure resulting from poor tissue durability and faulty design. Clearly, an in-depth understanding of the biomechanical behavior of BHV at both the tissue and functional prosthesis levels is essential to improving BHV design and to reduce rates of failure. In this study, we simulated quasi-static BHV leaflet deformation under 40, 80, and 120 mm Hg quasi-static transvalvular pressures. A Fung-elastic material model was used that incorporated material parameters and axes derived from actual leaflet biaxial tests and measured leaflet collagen fiber structure. Rigorous experimental validation of predicted leaflet strain field was used to validate the model results. An overall maximum discrepancy of 2.36% strain between the finite element (FE) results and experiment measurements was obtained, indicating good agreement between computed and measured major principal strains. Parametric studies utilizing the material parameter set from one leaflet for all three leaflets resulted in substantial variations in leaflet stress and strain distributions. This result suggests that utilization of actual leaflet material properties is essential for accurate BHV FE simulations. The present study also underscores the need for rigorous experimentation and accurate constitutive models in simulating BHV function and design.

Animals↗

PubMed2026

AI-Driven Multi-Omics Integration of Synthetic Colon Adenocarcinoma for Cluster-Guided PROTAC Candidate Design Targeting KRASG12D.

Colorectal cancer is a leading cause of cancer death, yet its molecular heterogeneity remains poorly translated into individualized treatment. We present a reproducible artificial intelligence (AI) framework that integrates multi-omics benchmarking, sample-level drug prioritization, E3 ubiquitin ligase selection, and shape-anchored Proteolysis Targeting Chimera (PROTAC) design for KRASG12D in colon adenocarcinoma (COAD). A controlled synthetic benchmark comprising 425 tumor and 41 simulated normal profiles, parameterized to match The Cancer Genome Atlas (TCGA) distributions, was used for pipeline verification. Among sixteen methods, the Balanced Latent Integration with Stability Selection (BLISS) model achieved the highest silhouette width (0.86) and competitive agreement (Adjusted Rand Index, ARI, 0.90). The pipeline was validated on real data: a TCGA COAD cohort (186 tumors) with independent Consensus Molecular Subtype (CMS) labels and a CPTAC cohort (104 tumors). Integration modestly recovered CMS (ARI 0.28), and stage, not molecular cluster, drove survival (log-rank p = 0.005 versus 0.81). Sample-level prioritization differed from cluster-level ranking in 82.6% of profiles, below chance (p < 0.0001), without indicating efficacy. Candidate NOVEL00489 showed a good MM-GBSA estimate, matching the reference ASP3082. Compounds are computational candidates requiring experimental validation. This establishes a transparent benchmark for in silico degrader generation in precision oncology.

Humans↗

PubMed2003

Optimization of accelerated solvent extraction for polyhalogenated dibenzo-p-dioxins and benzo-p-furans in mineral and environmental matrixes using experimental designs.

This paper deals with the optimization of accelerated solvent extraction (ASE) for the analysis of the polychlorinated dibenzo-p-dioxins, benzo-p-furans (PCDD/Fs), mixed bromine/chlorine-dibenzo-p-dioxins, and benzo-p-furans (so-called MXDD/Fs) in solid samples. Previous theoretical studies have shown that these compounds exhibit similar electronic properties. It is reasonable to assume that there is little difference in the behavior, formation, and toxicity of PCDD/Fs and MXDD/Fs. Indeed, for most of the cases, the affinity is defined by these weak interactions. Only eight native standards are available for the MXDD/Fs; hence, the use of similar compounds (native and (13)C(12)-labeled), such as PCDD/Fs, is required to optimize and to validate experimental methods. This would allow conclusions to be applied for the MXDD/Fs without extended studies involving complex synthesis methods. Experimental design methodology was used to evaluate the influence of five parameters (temperature, pressure, static time, number of cycles, and solvent nature) on the polyhalogenated dibenzodioxin and -furan (PXDD/Fs) extractions in different materials. The extraction profiles and the optimal operating conditions were determined for each matrix from the modeling of extraction performance. The two following effects, the relative peak area and the co-extracted matrix (CEM), were screened in this study. The temperature of extraction was found to be the most important parameter. ASE offers automation and appears to be as efficient as Soxhlet or Soxtet; however, a major benefit was that a 4-fold decrease in extraction time was obtained. Results suggest that extraction efficiency was quantitative with extraction times as low as 15 min for all congeners at 130 degrees C with a mixed solvent (n-hexane/acetone (1/1)). Under these operating conditions, the CEM and the degradation of the highly brominated compounds were minimized. The analysis of some real life samples from municipal solid waste incinerators showed significant amounts of PXDD/Fs.

Journal Article↗