A model for SOS-lesion-targeted mutations in Escherichia coli

The UmuD'2C protein complex (Escherichia coli pol V) is a low-fidelity DNA polymerase (pol) that copies damaged DNA in the presence of RecA, single-stranded-DNA binding protein (SSB) and the beta,gamma-processivity complex of E. coli pol III (ref. 4). Here we propose a model to explain SOS-lesion-targeted mutagenesis, assigning specific biochemical functions for each protein during translesion synthesis. (SOS lesion-targeted mutagenesis occurs when pol V is induced as part of the SOS response to DNA damage and incorrectly incorporates nucleotides opposite template lesions.) Pol V plus SSB catalyses RecA filament disassembly in the 3' to 5' direction on the template, ahead of the polymerase, in a reaction that does not involve ATP hydrolysis. Concurrent ATP-hydrolysis-driven filament disassembly in the 5' to 3' direction results in a bidirectional stripping of RecA from the template strand. The bidirectional collapse of the RecA filament restricts DNA synthesis by pol V to template sites that are proximal to the lesion, thereby minimizing the occurrence of untargeted mutations at undamaged template sites.     

A hybrid neural network model for consciousness

A new framework for consciousness is introduced based upon traditional artificial neural network models. This framework reflects explicit connections between two parts of the brain: one global working memory and distributed modular cerebral networks relating to specific brain functions. Accordingly this framework is composed of three layers, physical mnemonic layer and abstract thinking layer, which cooperate together through a recognition layer to accomplish information storage and cognition using algorithms of how these interactions contribute to consciousness: (1) the reception process whereby cerebral subsystems group distributed signals into coherent object patterns; (2) the partial recognition process whereby patterns from particular subsystems are compared or stored as knowledge; and (3) the resonant learning process whereby global workspace stably adjusts its structure to adapt to patterns' changes. Using this framework, various sorts of human actions can be explained, leading to a general approach for analyzing brain functions.