Photo-initiated enhanced antibacterial therapy using a non-covalent functionalized graphene oxide nanoplatform

This study describes a novel antibacterial phototherapeutic platform for highly efficient healing of bacteria-infected wounds. It is based on the photodynamic and physical actions of a zinc tetraaminophthalocyanine-modified graphene oxide nanocomposite produced via non-covalent functionalization. The nanocomposite is positively charged and can easily capture negatively charged bacteria via electrostatic interactions. The antibacterial action is two-fold: (1) reactive oxygen species are produced by the phthalocyanine photosensitizer after short-term exposure to 680 nm light and (2) the graphene oxide can physically cut bacterial cell membranes. These enhanced activities can kill Gram-positive and Gram-negative bacteria at very low dosages. An ultrastructural examination indicates that this nanocomposite causes enormous damage to bacterial morphology and leakage of intracellular substances that lead to bacterial death. A rat wound model is used to demonstrate that the proposed phototherapeutic platform has low cytotoxicity and can promote rapid healing in bacteria-infected wounds. These results suggest that the integration of different antibacterial methods into a single nanotherapeutic platform is a promising strategy for anti-infective treatment.

Learning a Local-Variable Model of Aromatic and Conjugated Systems

A collection of new approaches to building and training neural networks, collectively referred to as deep learning, are attracting attention in theoretical chemistry. Several groups aim to replace computationally expensive ab initio quantum mechanics calculations with learned estimators. This raises questions about the representability of complex quantum chemical systems with neural networks. Can local-variable models efficiently approximate nonlocal quantum chemical features? Here, we find that convolutional architectures, those that only aggregate information locally, cannot efficiently represent aromaticity and conjugation in large systems. They cannot represent long-range nonlocality known to be important in quantum chemistry. This study uses aromatic and conjugated systems computed from molecule graphs, though reproducing quantum simulations is the ultimate goal. This task, by definition, is both computable and known to be important to chemistry. The failure of convolutional architectures on this focused task calls into question their use in modeling quantum mechanics. To remedy this heretofore unrecognized deficiency, we introduce a new architecture that propagates information back and forth in waves of nonlinear computation. This architecture is still a local-variable model, and it is both computationally and representationally efficient, processing molecules in sublinear time with far fewer parameters than convolutional networks. Wave-like propagation models aromatic and conjugated systems with high accuracy, and even models the impact of small structural changes on large molecules. This new architecture demonstrates that some nonlocal features of quantum chemistry can be efficiently represented in local variable models.

Aromaticity and antiaromaticity of substituted fulvene derivatives: perspectives from the information-theoretic approach in density functional reactivity theory

Strong correlations among aromaticity descriptors and information-theoretic quantities are unveiled, providing novel insights about aromaticity and antiaromaticity from different perspectives.

Electron Density Analysis of Hyperconjugation

Hyperconjugation is analyzed through the electron density of orbitals responsible for hyperconjugative interactions, which cannot be detected by means of conventional electron-density-based calculations. This interaction is detected through the π electron density topology, by excluding σ electron density from the total. As the presence of the hyperconjugation phenomenon in carbocation systems is well understood, several carbocations are benchmarked, and the results show that the positive carbon atom establishes a hyperconjugative critical point with the adjacent methyl group(s). Also, π localization and delocalization indices are employed to support the conclusions made by the topological analysis.