NMR studies of the relationship between the changes of membrane lipids and the cisplatin-resistance of A549/DDP cells

Changes of membrane lipids in cisplatin-sensitive A549 and cisplatin-resistant A549/DDP cells during the apoptotic process induced by a clinical dose of cisplatin (30 μM) were detected by (1)H and (31)P-NMR spectroscopy and by membrane fluidity measurement. The apoptotic phenotypes of the two cell lines were monitored with flow cytometry. The assays of apoptosis showed that significant apoptotic characteristics of the A549 cells were induced when the cells were cultured for 24 hours after treatment with cisplatin, while no apoptotic characteristic could be detected for the resistant A549/DDP cells even after 48 hours. The results of (1)H-NMR spectroscopy demonstrated that the CH(2)/CH(3 )and Glu/Ct ratios of the membrane of A549 cells increased significantly, but those in A549/DDP cell membranes decreased. In addition, the Chol/CH(3 )and Eth/Ct ratios decreased for the former but increased for the latter cells under the same conditions. (31)P-NMR spectroscopy indicated levels of phosphomonoesters (PME) and ATP decreased in A549 but increased in A549/DDP cells after being treated with cisplatin. These results were supported with the data obtained from (1)H-NMR measurements. The results clearly indicated that components and properties of membrane phospholipids of the two cell lines were significantly different during the apoptotic process when they were treated with a clinical dose of cisplatin. Plasma membrane fluidity changes during cisplatin treatment as detected with the fluorescence probe TMA-DPH also indicate marked difference between the two cell lines. We provided evidence that there are significant differences in plasma membrane changes during treatment of cisplatin sensitive A549 and resistant A549/DDP cells

Reaction mechanism and kinetics for CO₂ reduction on nickel single atom catalysts from quantum mechanics

Experiments have shown that graphene-supported Ni-single atom catalysts (Ni-SACs) provide a promising strategy for the electrochemical reduction of CO₂ to CO, but the nature of the Ni sites (Ni-N₂C₂, Ni-N₃C₁, Ni-N₄) in Ni-SACs has not been determined experimentally. Here, we apply the recently developed grand canonical potential kinetics (GCP-K) formulation of quantum mechanics to predict the kinetics as a function of applied potential (U) to determine faradic efficiency, turn over frequency, and Tafel slope for CO and H₂ production for all three sites. We predict an onset potential (at 10 mA cm⁻²) U_(onset) = −0.84 V (vs. RHE) for Ni-N₂C₂ site and U_(onset) = −0.92 V for Ni-N₃C₁ site in agreement with experiments, and U_(onset) = −1.03 V for Ni-N₄. We predict that the highest current is for Ni-N₄, leading to 700 mA cm⁻² at U = −1.12 V. To help determine the actual sites in the experiments, we predict the XPS binding energy shift and CO vibrational frequency for each site

Computational Heterogeneous Electrochemistry – From Quantum Mechanics to Machine Learning

Because of coulomb interactions and complex surface morphologies, rigorous methods for heterogeneous electrochemical catalysis were not well-established. Thus, for different types of electrochemical systems, a specific strategy must be adapted. In this thesis, we first used the cluster model to study the chemistry on a 1D chain of MoS2 edges. Then, a rigorous grand canonical potential kinetics (GCP-K) method was developed for general crystalline systems. Starting from quantum mechanical calculations, the method gave rise to a different picture from the traditional description given by the Butler-Volmer kinetics. Next, we studied the chemical selectivity of CO2 reduction on polycrystalline copper nanoparticles. Because of the complexity of the reaction sites, we combined the reactive force field, density functional theory, and machine learning method to predict the reactive sites on 20,000 sites on a roughly 200,000-atom nanoparticle. Such a strategy opens up new way to understand chemistries on a much wider range of complex structures that were impossible to study theoretically. Lastly, we formulated a machine learning force field strategy using atomic energies for amorphous systems. We have shown that such a method can be used to reproduce quantum mechanical accuracies for molecular dynamics. This method will enable the accurate study of the dynamics of heterogeneous systems during electrochemical reactions. In summary, we have developed quantum chemical methods and machine learning strategies to reformulate rigorous ways to study a wide range of heterogeneous electrochemical catalysts.</p

Many-Electron Effects on Optical Absorption Spectra of Strained Graphene

We employ the first-principles GW+Bethe Salpeter equation approach to study the electronic structure and optical absorption spectra of uniaxial strained graphene with many-electron effects included. Applied strain not only induces an anisotropic Fermi velocity but also tilts the axis of the Dirac cone. As a result, the optical response of strained graphene is dramatically changed; the optical absorption is anisotropic, strongly depending on the polarization direction of the incident light and the strain orientation; the characteristic single optical absorption peak from {\pi}-{\pi}* transitions of pristine graphene is split into two peaks and both display enhanced excitonic effects. Within the infrared regime, the optical absorbance of uniaxial strained graphene is no longer a constant because of the broken symmetry and associated anisotropic excitonic effects. Within the visible-light regime, we observe a prominent optical absorption peak due to a significant red shift by electron-hole interactions, enabling us to change the visible color and transparency of stretched graphene. Finally, we also reveal enhanced excitonic effects within the ultraviolet regime (8 to 15 eV), where a few nearly bound excitons are identified.Comment: 13 pages, 7 figures and 1 tabl

Effects of Surface Roughness on the Electrochemical Reduction of CO₂ over Cu

We have investigated the role of surface roughening on the CO₂ reduction reaction (CO₂RR) over Cu. The activity and product selectivity of Cu surfaces roughened by plasma pretreatment in Ar, O₂, or N₂ were compared with that of electrochemically polished Cu samples. Differences in total and product current densities, the ratio of current densities for HER (the hydrogen evolution reaction) to CO₂RR, and the ratio of current densities for C₂₊ to C₁ products depend on the electrochemically active surface and are nearly independent of plasma composition. Theoretical analysis of an electropolished and roughened Cu surface reveals a higher fraction of undercoordinated Cu sites on the roughened surface, sites that bind CO preferentially. Roughened surfaces also contain square sites similar to those on a Cu(100) surface but with neighboring step sites, which adsorb OC–COH, a precursor to C₂₊ products. These findings explain the increases in the formation of oxygenates and hydrocarbons relative to CO and the ratio of oxygenates to hydrocarbons observed with increasing surface roughness