67 resultados para Recurrence quantification analysis


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OBJECTIVE The malignant potential of intraepithelial neoplasia of the vulva and vagina after treatment is not well defined. Our objective was to examine risk factors for recurrence and invasive disease. METHODS Four hundred sixty-four women with biopsy proven high-grade intraepithelial neoplasia of the vulva and vagina were identified in the electronic databases of four colposcopy clinics. Inclusion criteria were a follow-up of more than one year, no history of invasive cancer and no invasive cancer within the first year after initial treatment. We investigated the potential factors associated with recurrence and progression using a logistic regression analysis to estimate odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS Of the 411 eligible patients, 123 patients (29.9%) recurred later than one year after initial treatment and 24 patients (5.8%) progressed to invasive disease. According to multivariate analyses, the risk factors associated with recurrence were multifocality (OR, 3.33; 95% CI, 2.02 to 5.51), immunosuppression (OR, 2.51; 95% CI, 1.09 to 5.81), excision as initial treatment (vs. laser evaporation; OR, 1.79; 95% CI, 1.11 to 2.91) and smoking (OR, 1.61; 95% CI, 1.02 to 2.55). Risk factors for progression to invasive disease were immunosuppression (OR, 4.00; 95% CI, 1.30 to 12.25), multifocality (OR, 3.05; 95% CI, 1.25 to 7.43) and smoking (OR, 2.97; 95% CI, 1.16 to 7.60), but not treatment modality. CONCLUSION Laser evaporation combined with extensive biopsy is at least as efficacious as initial treatment of intraepithelial neoplasia with excision. Smoking is a risk factor for both recurrence and progression to invasive disease. Hence, smoking cessation should be advised and maintaining a long follow-up period due to late relapses is necessary.

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In this study, the development of a new sensitive method for the analysis of alpha-dicarbonyls glyoxal (G) and methylglyoxal (MG) in environmental ice and snow is presented. Stir bar sorptive extraction with in situ derivatization and liquid desorption (SBSE-LD) was used for sample extraction, enrichment, and derivatization. Measurements were carried out using high-performance liquid chromatography coupled to electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS). As part of the method development, SBSE-LD parameters such as extraction time, derivatization reagent, desorption time and solvent, and the effect of NaCl addition on the SBSE efficiency as well as measurement parameters of HPLC-ESI-MS/MS were evaluated. Calibration was performed in the range of 1–60 ng/mL using spiked ultrapure water samples, thus incorporating the complete SBSE and derivatization process. 4-Fluorobenzaldehyde was applied as internal standard. Inter-batch precision was <12 % RSD. Recoveries were determined by means of spiked snow samples and were 78.9 ± 5.6 % for G and 82.7 ± 7.5 % for MG, respectively. Instrumental detection limits of 0.242 and 0.213 ng/mL for G and MG were achieved using the multiple reaction monitoring mode. Relative detection limits referred to a sample volume of 15 mL were 0.016 ng/mL for G and 0.014 ng/mL for MG. The optimized method was applied for the analysis of snow samples from Mount Hohenpeissenberg (close to the Meteorological Observatory Hohenpeissenberg, Germany) and samples from an ice core from Upper Grenzgletscher (Monte Rosa massif, Switzerland). Resulting concentrations were 0.085–16.3 ng/mL for G and 0.126–3.6 ng/mL for MG. Concentrations of G and MG in snow were 1–2 orders of magnitude higher than in ice core samples. The described method represents a simple, green, and sensitive analytical approach to measure G and MG in aqueous environmental samples.

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Objective: Processes occurring in the course of psychotherapy are characterized by the simple fact that they unfold in time and that the multiple factors engaged in change processes vary highly between individuals (idiographic phenomena). Previous research, however, has neglected the temporal perspective by its traditional focus on static phenomena, which were mainly assessed at the group level (nomothetic phenomena). To support a temporal approach, the authors introduce time-series panel analysis (TSPA), a statistical methodology explicitly focusing on the quantification of temporal, session-to-session aspects of change in psychotherapy. TSPA-models are initially built at the level of individuals and are subsequently aggregated at the group level, thus allowing the exploration of prototypical models. Method: TSPA is based on vector auto-regression (VAR), an extension of univariate auto-regression models to multivariate time-series data. The application of TSPA is demonstrated in a sample of 87 outpatient psychotherapy patients who were monitored by postsession questionnaires. Prototypical mechanisms of change were derived from the aggregation of individual multivariate models of psychotherapy process. In a 2nd step, the associations between mechanisms of change (TSPA) and pre- to postsymptom change were explored. Results: TSPA allowed a prototypical process pattern to be identified, where patient's alliance and self-efficacy were linked by a temporal feedback-loop. Furthermore, therapist's stability over time in both mastery and clarification interventions was positively associated with better outcomes. Conclusions: TSPA is a statistical tool that sheds new light on temporal mechanisms of change. Through this approach, clinicians may gain insight into prototypical patterns of change in psychotherapy.

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An HPLC-DAD method for the quantitative analysis of Δ(9)-tetrahydrocannabinol (THC), Δ(9)-tetrahydrocannabinolic acid-A (THCA-A), cannabidiol (CBD), and cannabinol (CBN) in confiscated cannabis products has been developed, fully validated and applied to analyse seized cannabis products. For determination of the THC content of plant material, this method combines quantitation of THCA-A, which is the inactive precursor of THC, and free THC. Plant material was dried, homogenized and extracted with methanol by ultrasonication. Chromatographic separation was achieved with a Waters Alliance 2695 HPLC equipped with a Merck LiChrospher 60 RP-Select B (5μm) precolumn and a Merck LiChroCart 125-4 LiChrospher 60 RP-Select B (5μm) analytical column. Analytes were detected and quantified using a Waters 2996 photo diode array detector. This method has been accepted by the public authorities of Switzerland (Bundesamt für Gesundheit, Federal Office of Public Health), and has been used to analyse 9092 samples since 2000. Since no thermal decarboxylation of THCA-A occurs, the method is highly reproducible for different cannabis materials. Two calibration ranges are used, a lower one for THC, CBN and CBD, and a higher one for THCA-A, due to its dominant presence in fresh plant material. As provider of the Swiss proficiency test, the robustness of this method has been tested over several years, and homogeneity tests even in the low calibration range (1%) show high precision (RSD≤4.3%, except CBD) and accuracy (bias≤4.1%, except CBN).

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BACKGROUND Clinical prognostic groupings for localised prostate cancers are imprecise, with 30-50% of patients recurring after image-guided radiotherapy or radical prostatectomy. We aimed to test combined genomic and microenvironmental indices in prostate cancer to improve risk stratification and complement clinical prognostic factors. METHODS We used DNA-based indices alone or in combination with intra-prostatic hypoxia measurements to develop four prognostic indices in 126 low-risk to intermediate-risk patients (Toronto cohort) who will receive image-guided radiotherapy. We validated these indices in two independent cohorts of 154 (Memorial Sloan Kettering Cancer Center cohort [MSKCC] cohort) and 117 (Cambridge cohort) radical prostatectomy specimens from low-risk to high-risk patients. We applied unsupervised and supervised machine learning techniques to the copy-number profiles of 126 pre-image-guided radiotherapy diagnostic biopsies to develop prognostic signatures. Our primary endpoint was the development of a set of prognostic measures capable of stratifying patients for risk of biochemical relapse 5 years after primary treatment. FINDINGS Biochemical relapse was associated with indices of tumour hypoxia, genomic instability, and genomic subtypes based on multivariate analyses. We identified four genomic subtypes for prostate cancer, which had different 5-year biochemical relapse-free survival. Genomic instability is prognostic for relapse in both image-guided radiotherapy (multivariate analysis hazard ratio [HR] 4·5 [95% CI 2·1-9·8]; p=0·00013; area under the receiver operator curve [AUC] 0·70 [95% CI 0·65-0·76]) and radical prostatectomy (4·0 [1·6-9·7]; p=0·0024; AUC 0·57 [0·52-0·61]) patients with prostate cancer, and its effect is magnified by intratumoral hypoxia (3·8 [1·2-12]; p=0·019; AUC 0·67 [0·61-0·73]). A novel 100-loci DNA signature accurately classified treatment outcome in the MSKCC low-risk to intermediate-risk cohort (multivariate analysis HR 6·1 [95% CI 2·0-19]; p=0·0015; AUC 0·74 [95% CI 0·65-0·83]). In the independent MSKCC and Cambridge cohorts, this signature identified low-risk to high-risk patients who were most likely to fail treatment within 18 months (combined cohorts multivariate analysis HR 2·9 [95% CI 1·4-6·0]; p=0·0039; AUC 0·68 [95% CI 0·63-0·73]), and was better at predicting biochemical relapse than 23 previously published RNA signatures. INTERPRETATION This is the first study of cancer outcome to integrate DNA-based and microenvironment-based failure indices to predict patient outcome. Patients exhibiting these aggressive features after biopsy should be entered into treatment intensification trials. FUNDING Movember Foundation, Prostate Cancer Canada, Ontario Institute for Cancer Research, Canadian Institute for Health Research, NIHR Cambridge Biomedical Research Centre, The University of Cambridge, Cancer Research UK, Cambridge Cancer Charity, Prostate Cancer UK, Hutchison Whampoa Limited, Terry Fox Research Institute, Princess Margaret Cancer Centre Foundation, PMH-Radiation Medicine Program Academic Enrichment Fund, Motorcycle Ride for Dad (Durham), Canadian Cancer Society.

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In practical forensic casework, backspatter recovered from shooters' hands can be an indicator of self-inflicted gunshot wounds to the head. In such cases, backspatter retrieved from inside the barrel indicates that the weapon found at the death scene was involved in causing the injury to the head. However, systematic research on the aspects conditioning presence, amount and specific patterns of backspatter is lacking so far. Herein, a new concept of backspatter investigation is presented, comprising staining technique, weapon and target medium: the 'triple contrast method' was developed, tested and is introduced for experimental backspatter analysis. First, mixtures of various proportions of acrylic paint for optical detection, barium sulphate for radiocontrast imaging in computed tomography and fresh human blood for PCR-based DNA profiling were generated (triple mixture) and tested for DNA quantification and short tandem repeat (STR) typing success. All tested mixtures yielded sufficient DNA that produced full STR profiles suitable for forensic identification. Then, for backspatter analysis, sealed foil bags containing the triple mixture were attached to plastic bottles filled with 10 % ballistic gelatine and covered by a 2-3-mm layer of silicone. To simulate backspatter, close contact shots were fired at these models. Endoscopy of the barrel inside revealed coloured backspatter containing typable DNA and radiographic imaging showed a contrasted bullet path in the gelatine. Cross sections of the gelatine core exhibited cracks and fissures stained by the acrylic paint facilitating wound ballistic analysis.

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Quantification of protein expression based on immunohistochemistry (IHC) is an important step in clinical diagnoses and translational tissue-based research. Manual scoring systems are used in order to evaluate protein expression based on staining intensities and distribution patterns. However, visual scoring remains an inherently subjective approach. The aim of our study was to explore whether digital image analysis proves to be an alternative or even superior tool to quantify expression of membrane-bound proteins. We analyzed five membrane-binding biomarkers (HER2, EGFR, pEGFR, β-catenin, and E-cadherin) and performed IHC on tumor tissue microarrays from 153 esophageal adenocarcinomas patients from a single center study. The tissue cores were scored visually applying an established routine scoring system as well as by using digital image analysis obtaining a continuous spectrum of average staining intensity. Subsequently, we compared both assessments by survival analysis as an end point. There were no significant correlations with patient survival using visual scoring of β-catenin, E-cadherin, pEGFR, or HER2. In contrast, the results for digital image analysis approach indicated that there were significant associations with disease-free survival for β-catenin, E-cadherin, pEGFR, and HER2 (P = 0.0125, P = 0.0014, P = 0.0299, and P = 0.0096, respectively). For EGFR, there was a greater association with patient survival when digital image analysis was used compared to when visual scoring was (visual: P = 0.0045, image analysis: P < 0.0001). The results of this study indicated that digital image analysis was superior to visual scoring. Digital image analysis is more sensitive and, therefore, better able to detect biological differences within the tissues with greater accuracy. This increased sensitivity improves the quality of quantification.

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With the increasing production and use of engineered nanoparticles it is crucial that their interaction with biological systems is understood. Due to the small size of nanoparticles, their identification and localization within single cells is extremely challenging. Therefore, various cutting-edge techniques are required to detect and to quantify metals, metal oxides, magnetic, fluorescent, as well as electron-dense nanoparticles. Several techniques will be discussed in detail, such as inductively coupled plasma atomic emission spectroscopy, flow cytometry, laser scanning microscopy combined with digital image restoration, as well as quantitative analysis by means of stereology on transmission electron microscopy images. An overview will be given regarding the advantages of those visualization/quantification systems, including a thorough discussion about limitations and pitfalls.

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Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.

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One of the most promising applications for the restoration of small or moderately sized focal articular lesions is mosaicplasty (MP). Although recurrent hemarthrosis is a rare complication after MP, recently, various strategies have been designed to find an effective filling material to prevent postoperative bleeding from the donor site. The porous biodegradable polymer Polyactive (PA; a polyethylene glycol terephthalate - polybutylene terephthalate copolymer) represents a promising solution in this respect. A histological evaluation of the longterm PA-filled donor sites obtained from 10 experimental horses was performed. In this study, attention was primarily focused on the bone tissue developed in the plug. A computer-assisted image analysis and quantitative polarized light microscopic measurements of decalcified, longitudinally sectioned, dimethylmethylene blue (DMMB)- and picrosirius red (PS) stained sections revealed that the coverage area of the bone trabecules in the PA-filled donor tunnels was substantially (25%) enlarged compared to the neighboring cancellous bone. For this quantification, identical ROIs (regions of interest) were used and compared. The birefringence retardation values were also measured with a polarized light microscope using monochromatic light. Identical retardation values could be recorded from the bone trabeculae developed in the PA and in the neighboring bone, which indicates that the collagen orientation pattern does not differ significantly among these bone trabecules. Based on our new data, we speculate that PA promotes bone formation, and some of the currently identified degradation products of PA may enhance osteo-conduction and osteoinduction inside the donor canal.

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OBJECTIVE To evaluate possible predictive factors for recurrence after laparoscopic segmental bowel resection for bowel endometriosis. DESIGN Cohort study. SETTING Academic tertiary referral center. METHODS 95 symptomatic women with bowel endometriosis who underwent laparoscopic segmental bowel resection at the Endometriosis clinic, University of Berne, between 2002 and 2012 were enrolled. Since 14 women were lost to follow-up, 81 formed the final cohort. Clinical and histological characteristics were examined as possible predictive factors for disease recurrence. MAIN OUTCOME MEASURES Recurrence, defined as a subsequent operation due to recurrent endometriosis-associated pain with a histologically confirmed endometriotic lesion. RESULTS Recurrence was observed in 13 (16%) patients. Variables that were significantly associated to recurrence by the Cox regression analysis were positive bowel resection margins (hazard ratio 6.5, 95% confidence interval 1.8-23.5, p = 0.005), age <31 years (hazard ratio 5.6, 95% confidence interval 1.7-18.6, p = 0.005) and body mass index ≥23 kg/m(2) (hazard ratio 11.0, 95% confidence interval 2.7-44.6, p = 0.001). CONCLUSIONS Positive bowel resection margins as well as age <31 years and body mass index ≥23 kg/m(2) appear to be independent predictors of disease recurrence.

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The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them quantitatively. Over the past years, C. elegans' motility has been studied across a wide range of environments, including crawling on substrates, swimming in fluids, and locomoting through microfluidic substrates. However, each environment often requires customized image processing tools relying on heuristic parameter tuning. In the present study, we propose a novel Multi-Environment Model Estimation (MEME) framework for automated image segmentation that is versatile across various environments. The MEME platform is constructed around the concept of Mixture of Gaussian (MOG) models, where statistical models for both the background environment and the nematode appearance are explicitly learned and used to accurately segment a target nematode. Our method is designed to simplify the burden often imposed on users; here, only a single image which includes a nematode in its environment must be provided for model learning. In addition, our platform enables the extraction of nematode ‘skeletons’ for straightforward motility quantification. We test our algorithm on various locomotive environments and compare performances with an intensity-based thresholding method. Overall, MEME outperforms the threshold-based approach for the overwhelming majority of cases examined. Ultimately, MEME provides researchers with an attractive platform for C. elegans' segmentation and ‘skeletonizing’ across a wide range of motility assays.

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The effects of tetrahydrocannabinol (THC) and endogenous cannabinoids (endocannabinoids, ECs) are both mediated by activation of the cannabinoid receptors CB1 and CB2. Exogenous activation of these receptors by THC could therefore alter EC levels. We tested this hypothesis in healthy volunteers (n = 25) who received a large intravenous dose of THC (0.10 mg/kg). Effects on the EC system were quantified by serial measurements of plasma ECs after THC administration. Eleven blood samples were drawn during the first 5 h after THC administration and two more samples after 24 and 48 h. THC, its metabolites THC-OH (biologically active) and THC-COOH (non-active), and the ECs anandamide and 2-arachidonoylglycerol (2-AG) were quantified by liquid chromatography-mass spectrometry. EC-plasma levels showed a biphasic response after THC injection reaching maximal values at 30 min. Anandamide increased slightly from 0.58 ± 0.21 ng/ml at baseline to 0.64 ± 0.24 ng/ml (p < 0.05) and 2-AG from 7.60 ± 4.30 ng/ml to 9.50 ± 5.90 ng/ml (p < 0.05). After reaching maximal concentrations, EC plasma levels decreased markedly to a nadir of 300 min after THC administration (to 0.32 ± 0.15 ng/ml for anandamide and to 5.50 ± 3.01 ng/ml for 2-AG, p < 0.05). EC plasma concentrations returned to near baseline levels until 48 h after the experiment. THC (0.76 ± 0.16 ng/ml) and THC-OH (0.36 ± 0.17 ng/ml) were still measurable at 24 h and remained detectible until 48 h after THC administration. Although the underlying mechanism is not clear, high doses of intravenous THC appear to influence endogenous cannabinoid concentrations and presumably EC-signalling.

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Purpose: Traditionally, the proximal isovelocity surface area (PISA) is based on the assumption of a single hemisphere (hemispheric PISA), but this technique has not been validated for the quantification of mitral regurgitation (MR) with multiple jets. Methods: The left heart simulator was actuated by a pulsatile pump at various stroke amplitudes. The regurgitant volume (Rvol) passing through the mitral valve phantoms with single and double regurgitant orifices of varying size and interspace was quantified by a flowmeter as reference technique. Color Doppler 3-D full-volumes were obtained, and Rvol were derived from 2-D PISA surfaces on the basis of hemispheric and hemicylindric assumption with one base (partial hemicylindric PISA) or 2 bases (total hemicylindric PISA). Results: 72 regurgitant volumes (Rvol range: 8 to 76 ml/beat) were obtained. Hemispheric PISA Rvol correlated well with reference Rvol by one orifice (R²=0.97; bias -2.7±3.2ml), but less by ≥ one orifice (R²=0.89). When a fusion of two PISAs occured, addition of two hemispheric PISA overestimated Rvol (bias 9.1±12.2ml, fig.1), and single hemispheric PISA underestimated Rvol (bias -12.4±4.9ml). If an integrated approach was used (hemispheric in single orifice, total hemicylindric in two non-fused PISAs and partial hemicylindric in two fused PISAs), the correlation was R²=0.95, bias -1.6±5.6ml (fig.2). In the ROC analysis, the cutoff to detect ≥ moderate-to-severe Rvol (≥45ml) was 42ml (AUC 0.99, sens. 100%, spec. 93%). Conclusions: In MR with two regurgitant jets, the 2-D hemicylindric assumption of the PISA offers a better quantification of Rvol than the hemispheric assumption. Quantification of MR using 2-D PISA requires an integrated approach that considers number of regurgitant orifices and fusion of the PISAs.

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Deep geological storage of radioactive waste foresees cementitious materials as reinforcement of tunnels and as backfill. Bentonite is proposed to enclose spent fuel canisters and as drift seals. Sand/bentonite (s/b) is foreseen as backfill material of access galleries or as drift seals. The emplacement of cementitious material next to clay material generates an enormous chemical gradient in pore-water composition that drives diffusive solute transport. Laboratory studies and reactive transport modeling predicted significant mineral alteration at and near interfaces, mainly resulting in a decrease of porosity in bentonite. The goal of this thesis was to characterize and quantify the cement/bentonite interactions both spatially and temporally in laboratory experiments. A newly developed mobile X-ray transparent core infiltration device was used to perform X-ray computed tomography (CT) scans without interruption of running experiments. CT scans allowed tracking the evolution of the reaction plume and changes in core volume/diameter/density during the experiments. In total 4 core infiltration experiments were carried out for this study with the compacted and saturated cores consisting of MX-80 bentonite and sand/MX-80 bentonite mixture (s/b; 65/35%). Two different high-pH cementitious pore-fluids were infiltrated: a young (early) ordinary Portland cement pore-fluid (APWOPC; K+–Na+–OH-; pH 13.4; ionic strength 0.28 mol/kg) and a young ‘low-pH’ ESDRED shotcrete pore-fluid (APWESDRED; Ca2+–Na+–K+–formate; pH 11.4; ionic strength 0.11 mol/kg). The experiments lasted between 1 and 2 years. In both bentonite experiments, the hydraulic conductivity was strongly reduced after switching to high-pH fluids, changing eventually from an advective to a diffusion-dominated transport regime. The reduction was mainly induced by mineral precipitation and possibly partly also by high ionic strength pore-fluids. Both bentonite cores showed a volume reduction and a resulting transient flow in which pore-water was squeezed out during high-pH infiltration. The outflow chemistry was characterized by a high ionic strength, while chloride in the initial pore water got replaced as main anionic charge carrier by sulfate, originating from gypsum dissolution. The chemistry of the high-pH fluids got strongly buffered by the bentonite, consuming hydroxide and in case of APWESDRED also formate. Hydroxide got consumed by mineral reactions (saponite and possibly talc and brucite precipitation), while formate being affected by bacterial degradation. Post-mortem analysis showed reaction zones near the inlet of the bentonite core, characterized by calcium and magnesium enrichment, consisting predominately of calcite and saponite, respectively. Silica got enriched in the outflow, indicating dissolution of silicate-minerals, identified as preferentially cristobalite. In s/b, infiltration of APWOPC reduced the hydraulic conductivity strongly, while APWESDRED infiltration had no effect. The reduction was mainly induced by mineral precipitation and probably partly also by high ionic strength pore-fluids. Not clear is why the observed mineral precipitates in the APWESDRED experiment had no effect on the fluid flow. Both s/b cores showed a volume expansion along with decreasing ionic strengths of the outflow, due to mineral reactions or in case of APWESDRED infiltration also mediated by microbiological activity, consuming hydroxide and formate, respectively. The chemistry of the high-pH fluids got strongly buffered by the s/b. In the case of APWESDRED infiltration, formate reached the outflow only for a short time, followed by enrichment in acetate, indicating most likely biological activity. This was in agreement to post-mortem analysis of the core, observing black spots on the inflow surface, while the sample had a rotten-egg smell indicative of some sulfate reduction. Post-mortem analysis showed further in both cores a Ca-enrichment in the first 10 mm of the core due to calcite precipitation. Mg-enrichment was only observed in the APWOPC experiment, originating from newly formed saponite. Silica got enriched in the outflow of both experiments, indicating dissolution of silicate-minerals, identified in the OPC experiment as cristobalite. The experiments attested an effective buffering capacity for bentonite and s/b, a progressing coupled hydraulic-chemical sealing process and also the preservation of the physical integrity of the interface region in this setup with a total pressure boundary condition on the core sample. No complete pore-clogging was observed but the hydraulic conductivity got rather strongly reduced in 3 experiments, explained by clogging of the intergranular porosity (macroporosity). Such a drop in hydraulic conductivity may impact the saturation time of the buffer in a nuclear waste repository, although the processes and geometry will be more complex in repository situation.