BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback

In this paper, we study the problem of safe online learning to re-rank, where user feedback is used to improve the quality of displayed lists. Learning to rank has traditionally been studied in two settings. In the offline setting, rankers are typically learned from relevance labels created by judges. This approach has generally become standard in industrial applications of ranking, such as search. However, this approach lacks exploration and thus is limited by the information content of the offline training data. In the online setting, an algorithm can experiment with lists and learn from feedback on them in a sequential fashion. Bandit algorithms are well-suited for this setting but they tend to learn user preferences from scratch, which results in a high initial cost of exploration. This poses an additional challenge of safe exploration in ranked lists. We propose BubbleRank, a bandit algorithm for safe re-ranking that combines the strengths of both the offline and online settings. The algorithm starts with an initial base list and improves it online by gradually exchanging higher-ranked less attractive items for lower-ranked more attractive items. We prove an upper bound on the n-step regret of BubbleRank that degrades gracefully with the quality of the initial base list. Our theoretical findings are supported by extensive experiments on a large-scale real-world click dataset

Non-variant specific antibody responses to the C-terminal region of merozoite surface protein-1 of Plasmodium falciparum (PfMSP-119) in Iranians exposed to unstable malaria transmission

<p>Abstract</p> <p>Background</p> <p>The C-terminal region of <it>Plasmodium falciparum </it>merozoite surface protein-1 (PfMSP-1₁₉) is a leading malaria vaccine candidate antigen. However, the existence of different variants of this antigen can limit efficacy of the vaccine development based on this protein. Therefore, in this study, the main objective was to define the frequency of PfMSP-1₁₉haplotypes in malaria hypoendemic region of Iran and also to analyse cross-reactive and/or variant-specific antibody responses to four PfMSP-1₁₉variant forms.</p> <p>Methods</p> <p>The PfMSP-1₁₉was genotyped in 50 infected subjects with <it>P. falciparum </it>collected during 2006-2008. Four GST-PfMSP-1₁₉variants (E/TSR/L, E/TSG/L, E/KNG/F and Q/KNG/L) were produced in <it>Escherichia coli </it>and naturally occurring IgG antibody to these proteins was evaluated in malaria patients' sera (n = 50) using ELISA. To determine the cross-reactivity of antibodies against each PfMSP-1₁₉variant in <it>P. falciparum-</it>infected human sera, an antibody depletion assay was performed in eleven corresponding patients' sera.</p> <p>Results</p> <p>Sequence data of the PfMSP-1₁₉revealed five variant forms in which the haplotypes Q/KNG/L and Q/KNG/F were predominant types and the second most frequent haplotype was E/KNG/F. In addition, the prevalence of IgG antibodies to all four PfMSP-1₁₉variant forms was equal and high (84%) among the studied patients' sera. Immunodepletion results showed that in Iranian malaria patients, Q/KNG/L variant could induce not only cross-reactive antibody responses to other PfMSP-1₁₉variants, but also could induce some specific antibodies that are not able to recognize the E/TSG/L or E/TSR/L variant forms.</p> <p>Conclusion</p> <p>The present findings demonstrated the presence of non-variant specific antibodies to PfMSP-1₁₉in Iranian falciparum malaria patients. This data suggests that polymorphism in PfMSP-1₁₉is less important and one variant of this antigen, particularly Q/KNG/L, may be sufficient to be included in PfMSP-1₁₉-based vaccine.</p

Curation and expansion of Human Phenotype Ontology for defined groups of inborn errors of immunity.

BACKGROUND: Accurate, detailed, and standardized phenotypic descriptions are essential to support diagnostic interpretation of genetic variants and to discover new diseases. The Human Phenotype Ontology (HPO), extensively used in rare disease research, provides a rich collection of vocabulary with standardized phenotypic descriptions in a hierarchical structure. However, to date, the use of HPO has not yet been widely implemented in the field of inborn errors of immunity (IEIs), mainly due to a lack of comprehensive IEI-related terms. OBJECTIVES: We sought to systematically review available terms in HPO for the depiction of IEIs, to expand HPO, yielding more comprehensive sets of terms, and to reannotate IEIs with HPO terms to provide accurate, standardized phenotypic descriptions. METHODS: We initiated a collaboration involving expert clinicians, geneticists, researchers working on IEIs, and bioinformaticians. Multiple branches of the HPO tree were restructured and extended on the basis of expert review. Our ontology-guided machine learning coupled with a 2-tier expert review was applied to reannotate defined subgroups of IEIs. RESULTS: We revised and expanded 4 main branches of the HPO tree. Here, we reannotated 73 diseases from 4 International Union of Immunological Societies-defined IEI disease subgroups with HPO terms. We achieved a 4.7-fold increase in the number of phenotypic terms per disease. Given the new HPO annotations, we demonstrated improved ability to computationally match selected IEI cases to their known diagnosis, and improved phenotype-driven disease classification. CONCLUSIONS: Our targeted expansion and reannotation presents enhanced precision of disease annotation, will enable superior HPO-based IEI characterization, and hence benefit both IEI diagnostic and research activities

Cortical disinhibition occurs in chronic neuropathic, but not in chronic nociceptive pain

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to examine the relationship between chronic neuropathic pain after incomplete peripheral nerve lesion, chronic nociceptive pain due to osteoarthritis, and the excitability of the motor cortex assessed by transcranial magnetic stimulation (TMS). Hence in 26 patients with neuropathic pain resulting from an isolated incomplete lesion of the median or ulnar nerve (neuralgia), 20 patients with painful osteoarthritis of the hand, and 14 healthy control subjects, the excitability of the motor cortex was tested using paired-pulse TMS to assess intracortical inhibition and facilitation. These excitability parameters were compared between groups, and the relationship between excitability parameters and clinical parameters was examined.</p> <p>Results</p> <p>We found a significant reduction of intracortical inhibition in the hemisphere contralateral to the lesioned nerve in the neuralgia patients. Intracortical inhibition in the ipsilateral hemisphere of neuralgia patients and in both hemispheres of osteoarthritis patients did not significantly differ from the control group. Disinhibition was significantly more pronounced in neuralgia patients with moderate/severe pain intensity than in patients with mild pain intensity, whereas the relative compound motor action potential as a parameter of nerve injury severity did not correlate with the amount of disinhibition.</p> <p>Conclusions</p> <p>Our results suggest a close relationship between motor cortex inhibition and chronic neuropathic pain in the neuralgia patients, which is independent from nerve injury severity. The lack of cortical disinhibition in patients with painful osteoarthritis points at differences in the pathophysiological processes of different chronic pain conditions with respect to the involvement of different brain circuitry.</p

Towards a Physarum learning chip

Networks of protoplasmic tubes of organism Physarum polycehpalum are macro-scale structures which optimally span multiple food sources to avoid repellents yet maximize coverage of attractants. When data are presented by configurations of attractants and behaviour of the slime mould is tuned by a range of repellents, the organism preforms computation. It maps given data configuration into a protoplasmic network. To discover physical means of programming the slime mould computers we explore conductivity of the protoplasmic tubes; proposing that the network connectivity of protoplasmic tubes shows pathway-dependent plasticity. To demonstrate this we encourage the slime mould to span a grid of electrodes and apply AC stimuli to the network. Learning and weighted connections within a grid of electrodes is produced using negative and positive voltage stimulation of the network at desired nodes; low frequency (10 Hz) sinusoidal (0.5 V peak-to-peak) voltage increases connectivity between stimulated electrodes while decreasing connectivity elsewhere, high frequency (1000 Hz) sinusoidal (2.5 V peak-to-peak) voltage stimulation decreases network connectivity between stimulated electrodes. We corroborate in a particle model. This phenomenon may be used for computation in the same way that neural networks process information and has the potential to shed light on the dynamics of learning and information processing in non-neural metazoan somatic cell networks