Learning preferences for large scale multi-label problems

Despite that the majority of machine learning approaches aim to solve binary classification problems, several real-world applications require specialized algorithms able to handle many different classes, as in the case of single-label multi-class and multi-label classification problems. The Label Ranking framework is a generalization of the above mentioned settings, which aims to map instances from the input space to a total order over the set of possible labels. However, generally these algorithms are more complex than binary ones, and their application on large-scale datasets could be untractable. The main contribution of this work is the proposal of a novel general online preference-based label ranking framework. The proposed framework is able to solve binary, multi-class, multi-label and ranking problems. A comparison with other baselines has been performed, showing effectiveness and efficiency in a real-world large-scale multi-label task

Differential replication of avian influenza H9N2 viruses in human alveolar epithelial A549 cells

Avian influenza virus H9N2 isolates cause a mild influenza-like illness in humans. However, the pathogenesis of the H9N2 subtypes in human remains to be investigated. Using a human alveolar epithelial cell line A549 as host, we found that A/Quail/Hong Kong/G1/97 (H9N2/G1), which shares 6 viral "internal genes" with the lethal A/Hong Kong/156/97 (H5N1/97) virus, replicates efficiently whereas other H9N2 viruses, A/Duck/Hong Kong/Y280/97 (H9N2/Y280) and A/Chicken/Hong Kong/G9/97 (H9N2/G9), replicate poorly. Interestingly, we found that there is a difference in the translation of viral protein but not in the infectivity or transcription of viral genes of these H9N2 viruses in the infected cells. This difference may possibly be explained by H9N2/G1 being more efficient on viral protein production in specific cell types. These findings suggest that the H9N2/G1 virus like its counterpart H5N1/97 may be better adapted to the human host and replicates efficiently in human alveolar epithelial cells

Proof of concept: A bioinformatic and serological screening method for identifying new peptide antigens for Chlamydia trachomatis related sequelae in women

This study aimed to identify new peptide antigens from Chlamydia (C.) trachomatis in a proof of concept approach which could be used to develop an epitope-based serological diagnostic for C. trachomatis related infertility in women. A bioinformatics analysis was conducted examining several immunodominant proteins from C. trachomatis to identify predicted immunoglobulin epitopes unique to C. trachomatis. A peptide array of these epitopes was screened against participant sera. The participants (all female) were categorized into the following cohorts based on their infection and gynecological history; acute (single treated infection with C. trachomatis), multiple (more than one C. trachomatis infection, all treated), sequelae (PID or tubal infertility with a history of C. trachomatis infection), and infertile (no history of C. trachomatis infection and no detected tubal damage). The bioinformatics strategy identified several promising epitopes. Participants who reacted positively in the peptide 11 ELISA were found to have an increased likelihood of being in the sequelae cohort compared to the infertile cohort with an odds ratio of 16.3 (95% c.i. 1.65-160), with 95% specificity and 46% sensitivity (0.19-0.74). The peptide 11 ELISA has the potential to be further developed as a screening tool for use during the early IVF work up and provides proof of concept that there may be further peptide antigens which could be identified using bioinformatics and screening approaches. © 2013 The Authors

Bioactivity-guided identification and cell signaling technology to delineate the immunomodulatory effects of Panax ginseng on human promonocytic U937 cells

<p>Abstract</p> <p>Background</p> <p>Ginseng is believed to have beneficial effects against human diseases, and its active components, ginsenosides, may play critical roles in its diverse physiological actions. However, the mechanisms underlying ginseng's effects remain to be investigated. We hypothesize some biological effects of ginseng are due to its anti-inflammatory effects.</p> <p>Methods</p> <p>Human promonocytic U937 cells were used to investigate the immunomodulatory effects of ginseng following TNF-α treatment. A global gene expression profile was obtained by using genechip analysis, and specific cytokine expression was measured by quantitative RT-PCR and ELISA. HPLC was used to define the composition of ginsenosides in 70% ethanol-water extracts of ginseng. Activation of signalling kinases was examined by Western blot analysis.</p> <p>Results</p> <p>Seventy percent ethanol-water extracts of ginseng significantly inhibited the transcription and secretion of CXCL-10 following TNF-α stimulation. Nine ginsenosides including Rb₁, Rb₂, Rc, Rd, Re, Rf, Rg₁, Rg₃and Rh₁were identified in our extract by HPLC. Seven out of nine ginsenosides could significantly inhibit TNF-α-induced CXCL-10 expression in U937 cells and give comparable inhibition of CXCL-10 transcription to those with the extract. However, the CXCL-10 suppressive effect of individual ginsenosides was less than that of the crude extract or the mixture of ginsenosides. The CXCL-10 suppression can be correlated with the inactivation of ERK1/2 pathways by ginseng.</p> <p>Conclusion</p> <p>We showed ginseng suppressed part of the TNF-α-inducible cytokines and signalling proteins in promonocytic cells, suggesting that it exerts its anti-inflammatory property targeting at different levels of TNF-α activity. The anti-inflammatory role of ginseng may be due to the combined effects of ginsenosides, contributing in part to the diverse actions of ginseng in humans.</p

Choices: Future Trade-Offs and Plausible Pathways

Policy development and management of deltas in the Anthropocene involves the consideration of trade-offs and the balancing of positive and negative consequences for delta functions and the societies that rely on them. This assessment outlines policy-driven and spatial trade-offs that dominate the landscape of choice. It highlights examples of such trade-offs using plausible delta futures and the governance choices associated with them. The analysis is based on modelling broad-scale processes and individual adaptive actions. It highlights how policy choices to maximise economic growth can, for example, have unforeseen consequences such as diminished well-being for some populations. Hence the chapter concludes that trade-offs are a crucial governance challenge for future sustainability of deltas

Challenges and key research questions for yaws eradication.

Yaws is endemic in west Africa, southeast Asia, and the Pacific region. To eradicate yaws by 2020, WHO has launched a campaign of mass treatment with azithromycin. Progress has been made towards achievement of this ambitious goal, including the validation of point-of-care and molecular diagnostic tests and piloting of the strategy in several countries, including Ghana, Vanuatu, and Papua New Guinea. Gaps in knowledge need to be addressed to allow refinement of the eradication strategy. Studies exploring determinants of the spatial distribution of yaws are needed to help with the completion of baseline mapping. The finding that Haemophilus ducreyi causes lesions similar to yaws is particularly important and further work is needed to assess the effect of azithromycin on these lesions. The integration of diagnostic tests into different stages of the eradication campaign needs investigation. Finally, studies must be done to inform the optimum mass-treatment strategy for sustainable interruption of transmission

Resident physician and hospital pharmacist familiarity with patient discharge medication costs

Objective Cost-related medication non-adherence is associated with increased health-care resource utilization and poor patient outcomes. Physicians-in-training generally receive little education regarding costs of prescribed therapy and may rely on hospital pharmacists for this information. However, little is documented regarding either of these health care providers’ familiarity with out-of pocket medication expenses borne by patients in the community. The purpose of this study was to evaluate and compare resident physician and hospital pharmacist familiarity with what patients pay for medications prescribed once discharged. Setting A major tertiary patient care and medical teaching centre in Canada. Method Internal medicine residents and hospital pharmacists within a specific health care organization were invited to participate in an online survey. Eight patient case scenarios and associated discharge therapeutic regimens were outlined and respondents asked to identify the costs patients would incur when having the prescription filled once discharged. Main Outcome Measure Total number and proportion of estimates above and below actual cost were calculated and compared between the groups using χ2 tests. Responses ±10% of the true cost were considered correct. Mean absolute values and standard deviation estimated costs, as well as cost increments above and below 10%, were calculated to assess the magnitude of the discrepancy between the respondent estimates and the actual total cost. Results Forty-four percent of physician residents and 26% of hospital pharmacists accessed the survey. Overall 39% and 47% of medication costs were under-estimated, 32% and 33% were overestimated, and 29% and 21% were correctly estimated by residents and pharmacists, respectively (P = NS). Incorrect estimates were evident across all therapeutic classes and medical indications presented in the survey. The greatest absolute cost discrepancy for both groups was under-estimation of linezolid ($800 and$400) and over-estimation of clopidogrel ($80) and bisoprolol therapy ($22) by residents and pharmacists, respectively. Conclusion Resident physicians and hospital pharmacists are unfamiliar with what patients must pay for drug therapy once discharged

Respiratory Dendritic Cell Subsets Differ in Their Capacity to Support the Induction of Virus-Specific Cytotoxic CD8+ T Cell Responses

Dendritic cells located at the body surfaces, e.g. skin, respiratory and gastrointestinal tract, play an essential role in the induction of adaptive immune responses to pathogens and inert antigens present at these surfaces. In the respiratory tract, multiple subsets of dendritic cells (RDC) have been identified in both the normal and inflamed lungs. While the importance of RDC in antigen transport from the inflamed or infected respiratory tract to the lymph nodes draining this site is well recognized, the contribution of individual RDC subsets to this process and the precise role of migrant RDC within the lymph nodes in antigen presentation to T cells is not clear. In this report, we demonstrate that two distinct subsets of migrant RDC - exhibiting the CD103+ and CD11bhi phenotype, respectively - are the primary DC presenting antigen to naïve CD4+ and CD8+ T lymphocytes in the draining nodes in response to respiratory influenza virus infection. Furthermore, the migrant CD103+ RDC subset preferentially drives efficient proliferation and differentiation of naive CD8+ T cells responding to infection into effector cells, and only the CD103+ RDC subset can present to naïve CD8+ T cells non-infectious viral vaccine introduced into the respiratory tract. These results identify CD103+ and CD11bhi RDC as critical regulators of the adaptive immune response to respiratory tract infection and potential targets in the design of mucosal vaccines