This paper uses constructs from machine learning to define pairs of learning tasks that either shared or did not share a common subspace. Human subjects then learnt these tasks using a feedback-based approach and we hypothesised that learning would be boosted for shared subspaces. Our findings broadly supported this hypothesis with either better performance on the second task if it shared the same subspace as the first, or positive correlations over task performance for shared subspaces. These empirical findings were compared to the behaviour of a Neural Network model trained using sequential Bayesian learning and human performance was found to be consistent with a minimal capacity variant of this model. Networks with an increased representational capacity, and networks without Bayesian learning, did not show these transfer effects. We propose that the concept of shared subspaces provides a useful framework for the experimental study of human multitask and transfer learning.Insecticide resistance in Anopheles mosquitoes is a major obstacle in maintaining the momentum in reducing the malaria burden; mitigating strategies require improved understanding of the underlying mechanisms. Mutations in the target site of insecticides (the voltage gated sodium channel for the most widely used pyrethroid class) and over-expression of detoxification enzymes are commonly reported, but their relative contribution to phenotypic resistance remain poorly understood. Here we present a genome editing pipeline to introduce single nucleotide polymorphisms in An. gambiae which we have used to study the effect of the classical kdr mutation L1014F (L995F based on An. gambiae numbering), one of the most widely distributed resistance alleles. Introduction of 1014F in an otherwise fully susceptible genetic background increased levels of resistance to all tested pyrethroids and DDT ranging from 9.9-fold for permethrin to >24-fold for DDT. The introduction of the 1014F allele was sufficient to reduce mortality of mosquitoes after exposure to deltamethrin treated bednets, even as the only resistance mechanism present. When 1014F was combined with over-expression of glutathione transferase Gste2, resistance to permethrin increased further demonstrating the critical combined effect between target site resistance and detoxification enzymes in vivo. We also show that mosquitoes carrying the 1014F allele in homozygosity showed fitness disadvantages including increased mortality at the larval stage and a reduction in fecundity and adult longevity, which can have consequences for the strength of selection that will apply to this allele in the field.The formation and maintenance of microtubules requires their polymerisation, but little is known about how this polymerisation is regulated in cells.  https://www.selleckchem.com/products/reparixin-repertaxin.html  Focussing on the essential microtubule bundles in axons of Drosophila and Xenopus neurons, we show that the plus-end scaffold Eb1, the polymerase XMAP215/Msps and the lattice-binder Tau co-operate interdependently to promote microtubule polymerisation and bundle organisation during axon development and maintenance. Eb1 and XMAP215/Msps promote each other's localisation at polymerising microtubule plus-ends. Tau outcompetes Eb1-binding along microtubule lattices, thus preventing depletion of Eb1 tip pools. The three factors genetically interact and show shared mutant phenotypes reductions in axon growth, comet sizes, comet numbers and comet velocities, as well as prominent deterioration of parallel microtubule bundles into disorganised curled conformations. This microtubule curling is caused by Eb1 plus-end depletion which impairs spectraplakin-mediated guidance of extending microtubules into parallel bundles. Our demonstration that Eb1, XMAP215/Msps and Tau co-operate during the regulation of microtubule polymerisation and bundle organisation, offers new conceptual explanations for developmental and degenerative axon pathologies.Drug-drug interactions account for up to 30% of adverse drug reactions. Increasing prevalence of electronic health records (EHRs) offers a unique opportunity to build machine learning algorithms to identify drug-drug interactions that drive adverse events. In this study, we investigated hospitalizations' data to study drug interactions with non-steroidal anti-inflammatory drugs (NSAIDS) that result in drug-induced liver injury (DILI). We propose a logistic regression based machine learning algorithm that unearths several known interactions from an EHR dataset of about 400,000 hospitalization. Our proposed modeling framework is successful in detecting 87.5% of the positive controls, which are defined by drugs known to interact with diclofenac causing an increased risk of DILI, and correctly ranks aggregate risk of DILI for eight commonly prescribed NSAIDs. We found that our modeling framework is particularly successful in inferring associations of drug-drug interactions from relatively small EHR datasets. Furthermore, we have identified a novel and potentially hepatotoxic interaction that might occur during concomitant use of meloxicam and esomeprazole, which are commonly prescribed together to allay NSAID-induced gastrointestinal (GI) bleeding. Empirically, we validate our approach against prior methods for signal detection on EHR datasets, in which our proposed approach outperforms all the compared methods across most metrics, such as area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC).Quorum sensing is a chemical communication process that bacteria use to coordinate group behaviors. In the global pathogen Vibrio cholerae, one quorum-sensing receptor and transcription factor, called VqmA (VqmAVc), activates expression of the vqmR gene encoding the small regulatory RNA VqmR, which represses genes involved in virulence and biofilm formation. Vibriophage VP882 encodes a VqmA homolog called VqmAPhage that activates transcription of the phage gene qtip, and Qtip launches the phage lytic program. Curiously, VqmAPhage can activate vqmR expression but VqmAVc cannot activate expression of qtip. Here, we investigate the mechanism underlying this asymmetry. We find that promoter selectivity is driven by each VqmA DNA-binding domain and key DNA sequences in the vqmR and qtip promoters are required to maintain specificity. A protein sequence-guided mutagenesis approach revealed that the residue E194 of VqmAPhage and A192, the equivalent residue in VqmAVc, in the helix-turn-helix motifs contribute to promoter-binding specificity.