Geochemical detection of carbon dioxide in dilute aquifers

<p>Abstract</p> <p>Background</p> <p>Carbon storage in deep saline reservoirs has the potential to lower the amount of CO₂emitted to the atmosphere and to mitigate global warming. Leakage back to the atmosphere through abandoned wells and along faults would reduce the efficiency of carbon storage, possibly leading to health and ecological hazards at the ground surface, and possibly impacting water quality of near-surface dilute aquifers. We use static equilibrium and reactive transport simulations to test the hypothesis that perturbations in water chemistry associated with a CO₂gas leak into dilute groundwater are important measures for the potential release of CO₂to the atmosphere. Simulation parameters are constrained by groundwater chemistry, flow, and lithology from the High Plains aquifer. The High Plains aquifer is used to represent a typical sedimentary aquifer overlying a deep CO₂storage reservoir. Specifically, we address the relationships between CO₂flux, groundwater flow, detection time and distance. The CO₂flux ranges from 10³to 2 × 10⁶t/yr (0.63 to 1250 t/m²/yr) to assess chemical perturbations resulting from relatively small leaks that may compromise long-term storage, water quality, and surface ecology, and larger leaks characteristic of short-term well failure.</p> <p>Results</p> <p>For the scenarios we studied, our simulations show pH and carbonate chemistry are good indicators for leakage of stored CO₂into an overlying aquifer because elevated CO₂yields a more acid pH than the ambient groundwater. CO₂leakage into a dilute groundwater creates a slightly acid plume that can be detected at some distance from the leak source due to groundwater flow and CO₂buoyancy. pH breakthrough curves demonstrate that CO₂leaks can be easily detected for CO₂flux ≥ 10⁴t/yr within a 15-month time period at a monitoring well screened within a permeable layer 500 m downstream from the vertical gas trace. At lower flux rates, the CO₂dissolves in the aqueous phase in the lower most permeable unit and does not reach the monitoring well. Sustained pumping in a developed aquifer mixes the CO₂-affected water with the ambient water and enhances pH signal for small leaks (10³t/yr) and reduces pH signal for larger leaks (≥ 10⁴t/yr).</p> <p>Conclusion</p> <p>The ability to detect CO₂leakage from a storage reservoir to overlying dilute groundwater is dependent on CO₂solubility, leak flux, CO₂buoyancy, and groundwater flow. Our simulations show that the most likely places to detect CO₂are at the base of the confining layer near the water table where CO₂gas accumulates and is transported laterally in all directions, and downstream of the vertical gas trace where groundwater flow is great enough to transport dissolved CO₂laterally. Our simulations show that CO₂may not rise high enough in the aquifer to be detected because aqueous solubility and lateral groundwater transport within the lower aquifer unit exceeds gas pressure build-up and buoyancy needed to drive the CO₂gas upwards.</p

Comparison of immunohistochemistry with PCR for assessment of ER, PR, and Ki-67 and prediction of pathological complete response in breast cancer

Background: Proliferation may predict response to neoadjuvant therapy of breast cancer and is commonly assessed by manual scoring of slides stained by immunohistochemistry (IHC) for Ki-67 similar to ER and PgR. This method carries significant intra- and inter-observer variability. Automatic scoring of Ki-67 with digital image analysis (qIHC) or assessment of MKI67 gene expression with RT-qPCR may improve diagnostic accuracy. Methods: Ki-67 IHC visual assessment was compared to the IHC nuclear tool (AperioTM) on core biopsies from a randomized neoadjuvant clinical trial. Expression of ESR1, PGR and MKI67 by RT-qPCR was performed on RNA extracted from the same formalin-fixed paraffin-embedded tissue. Concordance between the three methods (vIHC, qIHC and RT-qPCR) was assessed for all 3 markers. The potential of Ki-67 IHC and RT-qPCR to predict pathological complete response (pCR) was evaluated using ROC analysis and non-parametric Mann-Whitney Test. Results: Correlation between methods (qIHC versus RT-qPCR) was high for ER and PgR (spearman´s r = 0.82, p < 0.0001 and r = 0.86, p < 0.0001, respectively) resulting in high levels of concordance using predefined cut-offs. When comparing qIHC of ER and PgR with RT-qPCR of ESR1 and PGR the overall agreement was 96.6 and 91.4%, respectively, while overall agreement of visual IHC with RT-qPCR was slightly lower for ER/ESR1 and PR/PGR (91.2 and 92.9%, respectively). In contrast, only a moderate correlation was observed between qIHC and RT-qPCR continuous data for Ki-67/MKI67 (Spearman’s r = 0.50, p = 0.0001). Up to now no predictive cut-off for Ki-67 assessment by IHC has been established to predict response to neoadjuvant chemotherapy. Setting the desired sensitivity at 100%, specificity for the prediction of pCR (ypT0ypN0) was significantly higher for mRNA than for protein (68.9% vs. 22.2%). Moreover, the proliferation levels in patients achieving a pCR versus not differed significantly using MKI67 RNA expression (Mann-Whitney p = 0.002), but not with qIHC of Ki-67 (Mann-Whitney p = 0.097) or vIHC of Ki-67 (p = 0.131). Conclusion: Digital image analysis can successfully be implemented for assessing ER, PR and Ki-67. IHC for ER and PR reveals high concordance with RT-qPCR. However, RT-qPCR displays a broader dynamic range and higher sensitivity than IHC. Moreover, correlation between Ki-67 qIHC and RT-qPCR is only moderate and RT-qPCR with MammaTyper® outperforms qIHC in predicting pCR. Both methods yield improvements to error-prone manual scoring of Ki-67. However, RT-qPCR was significantly more specific