158 research outputs found

    Enhanced Recovery of Oil Mixtures from Calcite Nanopores Facilitated by CO<sub>2</sub> Injection

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    Slow production, preferential recovery of light hydrocarbons, and low recovery factors are common challenges in oil production from unconventional reservoirs dominated by nanopores. Gas injection-based techniques such as CO2 Huff-n-Puff have shown promise in addressing these challenges. However, a limited understanding of the recovery of oil mixtures on the nanopore scale hinders their effective optimization. Here, we use molecular dynamics simulations to study the recovery of an oil mixture (C10 + C19) from a single 4 nm-wide calcite dead-end pore, both with and without CO2 injection. Without CO2 injection, oil recovery is much faster than expected from oil vaporization and features an undesired selectivity, i.e., the preferential recovery of lighter C10. With CO2 injection, oil recovery is accelerated and its selectivity toward C10 is greatly mitigated. These recovery behaviors are understood by analyzing the spatiotemporal evolution of C10, C19, and CO2 distributions in the calcite pore. In particular, we show that interfacial phenomena (e.g., the strong adsorption of oil and CO2 on pore walls, their competition, and their modulation of transport behavior) and bulk phenomena (e.g., solubilization of oil by CO2 in the middle portion of the pore) play crucial roles in determining the oil recovery rate and selectivity

    Association between 1p11-rs11249433 Polymorphism and Breast Cancer Susceptibility: Evidence from 15 Case-Control Studies

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    <div><p>Genome-wide association studies have identified SNP rs11249433 at chromosome 1p11 as a new breast cancer (BC) susceptibility locus in populations of European descent. Since then, the relationship between 1p11- rs11249433 and breast cancer has been reported in various ethnic groups; however, these studies have yielded inconsistent results. To investigate this inconsistency, we performed a meta-analysis of 15 studies involving a total of 90,154 cases and 137,238 controls for 1p11-rs11249433 polymorphism to evaluate its effect on genetic susceptibility for breast cancer. An overall random effects odds ratio of 1.09 (95% CI: 1.06-1.12, P<10<sup>-5</sup>) was found for rs11249433-G variant. Significant results were also observed for heterozygous (OR=1.09, 95% CI: 1.05-1.12, P<10<sup>-5</sup>) and homozygote (OR=1.14, 95% CI: 1.08-1.21, P<10<sup>-5</sup>). There was strong evidence of heterogeneity, which largely disappeared after stratification by ethnicity. After stratiļ¬ed by ethnicity, significant associations were found among Caucasians. However, no significant associations were detected among East Asian and African populations. In addition, we found that rs11249433 polymorphism on 1p11 confer risk, exclusively for ER-positive tumors with per-allele OR of 1.13 (95% CI: 1.08-1.18; P <10<sup>-5</sup>) compared to ER-negative tumors of 1.01 (95% CI: 0.98-1.04; P=0.49). Similar results were also observed when stratified by PR status. Our findings demonstrated that rs11249433-G allele is a risk-conferring factor for the development of breast cancer, especially in Caucasians.</p></div

    Membrane fouling control in the integrated process of magnetic anion exchange and ultrafiltration

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    <p>Magnetic anion exchange (MIEX) has been increasingly concerned owing to its excellent performance for the removal of dissolved organic carbon in the treatment of drinking water. In this study, the ability of ultrafiltration (UF) membrane fouling control was analyzed by different combination processes of MIEX-UF. A single cycle and multi-cycle operations were conducted, and the separated and integrated processes of MIEX-UF were compared. Membrane filtration resistance, removal of organics, and morphologies of the membrane surface were analyzed. The results of the short-term operation did not show any obvious improvement in the membrane fouling control in the separated process (compared to UF alone); however, a marked improvement was obtained in the integrated process. The membrane filtration resistance analysis showed that the cake resistance (<i>R</i><sub>c</sub>) and pore blocking resistance (<i>R</i><sub>p</sub>) in the integrated process were only 52 and 24% of the values in the separated process. The multi-cycle operation demonstrated that the cumulative rate of hydraulically irreversible fouling was 0.0021 in the integrated process and was much lower than that in the separated process (0.0182). The mechanistic analysis shows that in the integrated process, a dynamic layer was formed on the membrane surface by the deposited MIEX beads, which markedly decreased the accumulation of the membrane foulants on the membrane surface and in the membrane pores.</p

    Representative plots of CD4+CD25+FoxP3+Tregs from individual subjects in the HIV-1-infected patients at week 0, week 60, healthy controls and LTNPs.

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    <p>Representative plots of CD4+CD25+FoxP3+Tregs from individual subjects in the HIV-1-infected patients at week 0, week 60, healthy controls and LTNPs.</p

    The association of DC subsets with viral loads and CD4+Tcells.

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    <p>(Aā€“B) Correlation between DC subsets counts and plasma viral loads, CD4+Tcells counts during ART. (Cā€“D) Correlation between change in counts of DC subsets at week 8 and the change in plasma viral loads, CD4+Tcells counts at week 60 post ART.</p

    Longitudinal changes in the percentage and counts of Tregs during ART (weeks).

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    <p>(Aā€“B) Longitudinal changes in the percentage and counts of Tregs in HIV-1-infected patients during ART. (Cā€“D) Comparisons of the percentage and counts of Tregs among HIV-1-infected patients at week 0, week 60, healthy controls and LTNPs. **<i>p</i><0.01, *<i>p</i><0.05.</p

    Longitudinal changes in DC subsets and IFN-a plasma levels during ART (weeks).

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    <p>(Aā€“C) Longitudinal changes in counts of mDCs, pDCs and IFN-a plasma levels in HIV-1-infected patients during ART. (Dā€“F) Comparisons of mDCs, pDCs and IFN-a plasma levels among HIV-1-infected patients at week 0, week 60, healthy controls and LTNPs. **<i>p</i><0.01, *<i>p</i><0.05.</p

    The association of DC subsets with Tregs percentage.

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    <p>(A) Correlation between mDCs counts and Tregs percentage during ART. (B) Correlation between pDCs counts and Tregs percentage during ART.</p
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