Prediction of Ligand Binding Using an Approach Designed to Accommodate Diversity in Protein-Ligand Interactions

Computational determination of protein-ligand interaction potential is important for many biological applications including virtual screening for therapeutic drugs. The novel internal consensus scoring strategy is an empirical approach with an extended set of 9 binding terms combined with a neural network capable of analysis of diverse complexes. Like conventional consensus methods, internal consensus is capable of maintaining multiple distinct representations of protein-ligand interactions. In a typical use the method was trained using ligand classification data (binding/no binding) for a single receptor. The internal consensus analyses successfully distinguished protein-ligand complexes from decoys (r2, 0.895 for a series of typical proteins). Results are superior to other tested empirical methods. In virtual screening experiments, internal consensus analyses provide consistent enrichment as determined by ROC-AUC and pROC metrics

The activation of eco-driving mental models: can text messages prime drivers to use their existing knowledge and skills?

Eco-driving campaigns have traditionally assumed that drivers lack the necessary knowledge and skills and that this is something that needs rectifying. Therefore, many support systems have been designed to closely guide drivers and fine-tune their proficiency. However, research suggests that drivers already possess a substantial amount of the necessary knowledge and skills regarding eco-driving. In previous studies, participants used these effectively when they were explicitly asked to drive fuel-efficiently. In contrast, they used their safe driving skills when they were instructed to drive as they would normally. Hence, it is assumed that many drivers choose not to engage purposefully in eco-driving in their everyday lives. The aim of the current study was to investigate the effect of simple, periodic text messages (nine messages in 2 weeks) on drivers’ eco- and safe driving performance. It was hypothesised that provision of eco-driving primes and advice would encourage the activation of their eco-driving mental models and that comparable safety primes increase driving safety. For this purpose, a driving simulator experiment was conducted. All participants performed a pre-test drive and were then randomly divided into four groups, which received different interventions. For a period of 2 weeks, one group received text messages with eco-driving primes and another group received safety primes. A third group received advice messages on how to eco-drive. The fourth group were instructed by the experimenter to drive fuel-efficiently, immediately before driving, with no text message intervention. A post-test drive measured behavioural changes in scenarios deemed relevant to eco- and safe driving. The results suggest that the eco-driving prime and advice text messages did not have the desired effect. In comparison, asking drivers to drive fuel-efficiently led to eco-driving behaviours. These outcomes demonstrate the difficulty in changing ingrained habits. Future research is needed to strengthen such messages or activate existing knowledge and skills in other ways, so driver behaviour can be changed in cost-efficient ways

Towards neuro-inspired symbolic models of cognition: linking neural dynamics to behaviors through asynchronous communications

A computational architecture modeling the relation between perception and action is proposed. Basic brain processes representing synaptic plasticity are first abstracted through asynchronous communication protocols and implemented as virtual microcircuits. These are used in turn to build mesoscale circuits embodying parallel cognitive processes. Encoding these circuits into symbolic expressions gives finally rise to neuro-inspired programs that are compiled into pseudo-code to be interpreted by a virtual machine. Quantitative evaluation measures are given by the modification of synapse weights over time. This approach is illustrated by models of simple forms of behaviors exhibiting cognition up to the third level of animal awareness. As a potential benefit, symbolic models of emergent psychological mechanisms could lead to the discovery of the learning processes involved in the development of cognition. The executable specifications of an experimental platform allowing for the reproduction of simulated experiments are given in “Appendix”

A New Method for Species Identification via Protein-Coding and Non-Coding DNA Barcodes by Combining Machine Learning with Bioinformatic Methods

Species identification via DNA barcodes is contributing greatly to current bioinventory efforts. The initial, and widely accepted, proposal was to use the protein-coding cytochrome c oxidase subunit I (COI) region as the standard barcode for animals, but recently non-coding internal transcribed spacer (ITS) genes have been proposed as candidate barcodes for both animals and plants. However, achieving a robust alignment for non-coding regions can be problematic. Here we propose two new methods (DV-RBF and FJ-RBF) to address this issue for species assignment by both coding and non-coding sequences that take advantage of the power of machine learning and bioinformatics. We demonstrate the value of the new methods with four empirical datasets, two representing typical protein-coding COI barcode datasets (neotropical bats and marine fish) and two representing non-coding ITS barcodes (rust fungi and brown algae). Using two random sub-sampling approaches, we demonstrate that the new methods significantly outperformed existing Neighbor-joining (NJ) and Maximum likelihood (ML) methods for both coding and non-coding barcodes when there was complete species coverage in the reference dataset. The new methods also out-performed NJ and ML methods for non-coding sequences in circumstances of potentially incomplete species coverage, although then the NJ and ML methods performed slightly better than the new methods for protein-coding barcodes. A 100% success rate of species identification was achieved with the two new methods for 4,122 bat queries and 5,134 fish queries using COI barcodes, with 95% confidence intervals (CI) of 99.75–100%. The new methods also obtained a 96.29% success rate (95%CI: 91.62–98.40%) for 484 rust fungi queries and a 98.50% success rate (95%CI: 96.60–99.37%) for 1094 brown algae queries, both using ITS barcodes

A thalamic reticular networking model of consciousness

<p>Abstract</p> <p>[Background]</p> <p>It is reasonable to consider the thalamus a primary candidate for the location of consciousness, given that the thalamus has been referred to as the gateway of nearly all sensory inputs to the corresponding cortical areas. Interestingly, in an early stage of brain development, communicative innervations between the dorsal thalamus and telencephalon must pass through the ventral thalamus, the major derivative of which is the thalamic reticular nucleus (TRN). The TRN occupies a striking control position in the brain, sending inhibitory axons back to the thalamus, roughly to the same region where they receive afferents.</p> <p>[Hypotheses]</p> <p>The present study hypothesizes that the TRN plays a pivotal role in dynamic attention by controlling thalamocortical synchronization. The TRN is thus viewed as a functional networking filter to regulate conscious perception, which is possibly embedded in thalamocortical networks. Based on the anatomical structures and connections, modality-specific sectors of the TRN and the thalamus appear to be responsible for modality-specific perceptual representation. Furthermore, the coarsely overlapped topographic maps of the TRN appear to be associated with cross-modal or unitary conscious awareness. Throughout the latticework structure of the TRN, conscious perception could be accomplished and elaborated through accumulating intercommunicative processing across the first-order input signal and the higher-order signals from its functionally associated cortices. As the higher-order relay signals run cumulatively through the relevant thalamocortical loops, conscious awareness becomes more refined and sophisticated.</p> <p>[Conclusions]</p> <p>I propose that the thalamocortical integrative communication across first- and higher-order information circuits and repeated feedback looping may account for our conscious awareness. This TRN-modulation hypothesis for conscious awareness provides a comprehensive rationale regarding previously reported psychological phenomena and neurological symptoms such as blindsight, neglect, the priming effect, the threshold/duration problem, and TRN-impairment resembling coma. This hypothesis can be tested by neurosurgical investigations of thalamocortical loops via the TRN, while simultaneously evaluating the degree to which conscious perception depends on the severity of impairment in a TRN-modulated network.</p

Critical discourse studies: Where to from here?

This paper surveys critical discourse studies to the present and claims that, to avoid lapsing into comfortable orthodoxy in its mature phase, CDS needs to reassert its transformative radical teleology. The initial part of the paper reasserts the need for a strong social theory given the materialist and context-bound nature of discourse in daily activity. From this basis, the paper then characterizes the “new times” in which contemporary discourse occurs, and briefly surveys those issues typically analyzed, namely political economy, race and gender, and critical literacy. By considering people's ordinary lives, the paper then suggests that subject and agency, and calculative technologies of management deserve, and new modalities need, more research. Transdisciplinarity is encouraged, particularly with social psychology and critical management studies