Bandit Online Optimization Over the Permutahedron

The permutahedron is the convex polytope with vertex set consisting of the vectors $(\pi(1),\dots, \pi(n))$ for all permutations (bijections) $\pi$ over $\{1,\dots, n\}$. We study a bandit game in which, at each step $t$, an adversary chooses a hidden weight weight vector $s_t$, a player chooses a vertex $\pi_t$ of the permutahedron and suffers an observed loss of $\sum_{i=1}^n \pi(i) s_t(i)$. A previous algorithm CombBand of Cesa-Bianchi et al (2009) guarantees a regret of $O(n\sqrt{T \log n})$ for a time horizon of $T$. Unfortunately, CombBand requires at each step an $n$-by-$n$ matrix permanent approximation to within improved accuracy as $T$ grows, resulting in a total running time that is super linear in $T$, making it impractical for large time horizons. We provide an algorithm of regret $O(n^{3/2}\sqrt{T})$ with total time complexity $O(n^3T)$. The ideas are a combination of CombBand and a recent algorithm by Ailon (2013) for online optimization over the permutahedron in the full information setting. The technical core is a bound on the variance of the Plackett-Luce noisy sorting process's "pseudo loss". The bound is obtained by establishing positive semi-definiteness of a family of 3-by-3 matrices generated from rational functions of exponentials of 3 parameters

An efficient algorithm for learning with semi-bandit feedback

We consider the problem of online combinatorial optimization under semi-bandit feedback. The goal of the learner is to sequentially select its actions from a combinatorial decision set so as to minimize its cumulative loss. We propose a learning algorithm for this problem based on combining the Follow-the-Perturbed-Leader (FPL) prediction method with a novel loss estimation procedure called Geometric Resampling (GR). Contrary to previous solutions, the resulting algorithm can be efficiently implemented for any decision set where efficient offline combinatorial optimization is possible at all. Assuming that the elements of the decision set can be described with d-dimensional binary vectors with at most m non-zero entries, we show that the expected regret of our algorithm after T rounds is O(m sqrt(dT log d)). As a side result, we also improve the best known regret bounds for FPL in the full information setting to O(m^(3/2) sqrt(T log d)), gaining a factor of sqrt(d/m) over previous bounds for this algorithm.Comment: submitted to ALT 201

Integrin activation - the importance of a positive feedback

Integrins mediate cell adhesion and are essential receptors for the development and functioning of multicellular organisms. Integrin activation is known to require both ligand and talin binding and to correlate with cluster formation but the activation mechanism and precise roles of these processes are not yet resolved. Here mathematical modeling, with known experimental parameters, is used to show that the binding of a stabilizing factor, such as talin, is alone insufficient to enable ligand-dependent integrin activation for all observed conditions; an additional positive feedback is required.Comment: in press in Bulletin of Mathematical Biolog

A Comparative Analysis of the Murine Thymic Microenvironment in Normal, Autoimmune, and Immunodeficiency States

It is widely accepted that the thymic microenvironment regulates normal thymopoiesis through a highly coordinated and complex series of cellular and cytokine interactions. A direct corollary of this is that abnormalities within the microenvironment could be of etiologic significance in T-cell-based diseases. Our laboratory has developed a large panel of monoclonal antibodies (mAbs) that react specifically with epithelial or nonepithelial markers in the thymus. We have taken advantage of these reagents to characterize the thymic microenvironment of several genetic strains of mice, including BALB/cJ, C57BL/6J, NZB/BlnJ, SM/J, NOD/Ltz, NOD/Ltz-scid/sz, C57BL/6J-Hcph me/Hcph me, and ALY/NscJcl-aly/aly mice, and littermate control animals. We report herein that control mice, including strains of several backgrounds, have a very consistent phenotypic profile with this panel of monoclonal antibodies, including reactivity with thymic epithelial cells in the cortex, the medulla and the corticomedullary junction, and the extracellular matrix. In contrast, the disease-prone strains studied have unique, abnormal staining of thymic cortex and medulla at both the structural and cellular levels. These phenotypic data suggest that abnormalities in interactions between developing thymocytes and stromal cells characterize disease-prone mice

Turnip mosaic potyvirus probably first spread to Eurasian brassica crops from wild orchids about 1000 years ago

Turnip mosaic potyvirus (TuMV) is probably the most widespread and damaging virus that infects cultivated brassicas worldwide. Previous work has indicated that the virus originated in western Eurasia, with all of its closest relatives being viruses of monocotyledonous plants. Here we report that we have identified a sister lineage of TuMV-like potyviruses (TuMV-OM) from European orchids. The isolates of TuMV-OM form a monophyletic sister lineage to the brassica-infecting TuMVs (TuMV-BIs), and are nested within a clade of monocotyledon-infecting viruses. Extensive host-range tests showed that all of the TuMV-OMs are biologically similar to, but distinct from, TuMV-BIs and do not readily infect brassicas. We conclude that it is more likely that TuMV evolved from a TuMV-OM-like ancestor than the reverse. We did Bayesian coalescent analyses using a combination of novel and published sequence data from four TuMV genes [helper component-proteinase protein (HC-Pro), protein 3(P3), nuclear inclusion b protein (NIb), and coat protein (CP)]. Three genes (HC-Pro, P3, and NIb), but not the CP gene, gave results indicating that the TuMV-BI viruses diverged from TuMV-OMs around 1000 years ago. Only 150 years later, the four lineages of the present global population of TuMV-BIs diverged from one another. These dates are congruent with historical records of the spread of agriculture in Western Europe. From about 1200 years ago, there was a warming of the climate, and agriculture and the human population of the region greatly increased. Farming replaced woodlands, fostering viruses and aphid vectors that could invade the crops, which included several brassica cultivars and weeds. Later, starting 500 years ago, inter-continental maritime trade probably spread the TuMV-BIs to the remainder of the world

OP0291 TOFACITINIB FOR THE TREATMENT OF POLYARTICULAR COURSE JUVENILE IDIOPATHIC ARTHRITIS: RESULTS OF A PHASE 3, RANDOMISED, DOUBLE-BLIND, PLACEBO-CONTROLLED WITHDRAWAL STUDY

Background:Tofacitinib is an oral JAK inhibitor that is being investigated for JIA.Objectives:To assess tofacitinib efficacy and safety in JIA patients (pts).Methods:This was a Phase 3, randomised, double-blind (DB), placebo (PBO)-controlled withdrawal study in pts aged 2−<18 years with polyarticular course JIA (pcJIA), PsA or ERA (NCT02592434). In the 18-week open-label Part 1, pts received weight-based tofacitinib doses (5 mg BID or lower). Pts with ≥JIA ACR30 response at Week (W)18 were randomised 1:1 in the DB Part 2 (W18−44) to continue tofacitinib or switch to PBO. Primary endpoint: disease flare rate by W44. Key secondary endpoints: JIA ACR50/30/70 response rates; change from Part 2 baseline (Δ) in CHAQ-DI at W44. Other efficacy endpoints: time to disease flare in Part 2; JADAS27-CRP in Parts 1 and 2. PsA/ERA pts were excluded from these efficacy analyses. Safety was evaluated in all pts up to W44.Results:225 enrolled pts with pcJIA (n=184), PsA (n=20) or ERA (n=21) received tofacitinib in Part 1. At W18, 173/225 (76.9%) pts entered Part 2 (pcJIA n=142, PsA n=15, ERA n=16). In pcJIA pts, disease flare rate in Part 2 was significantly lower with tofacitinib vs PBO by W44 (p=0.0031; Fig 1a). JIA ACR50/30/70 response rates (Fig 1b) and ΔCHAQ-DI (Fig 1c) at W44, and time to disease flare in Part 2 (Fig 2a), were improved with tofacitinib vs PBO. Tofacitinib reduced JADAS27-CRP in Part 1; this effect was sustained in Part 2 (Fig 2b). Overall, safety was similar with tofacitinib or PBO (Table): 77.3% and 74.1% had adverse events (AEs); 1.1% and 2.4% had serious AEs. In Part 1, 2 pts had herpes zoster (non-serious) and 3 pts had serious infections (SIs). In Part 2, SIs occurred in 1 tofacitinib pt and 1 PBO pt. No pts died.Conclusion:In pcJIA pts, tofacitinib vs PBO resulted in significantly fewer disease flares, and improved time to flare, disease activity and physical functioning. Tofacitinib safety was consistent with that in RA pts.Table.Safety in all ptsPart 1Part 2TofacitinibaN=225TofacitinibaN=88PBO N=85Pts with events, n (%)AEs153 (68.0)68 (77.3)63 (74.1)SAEs7 (3.1)1 (1.1)2 (2.4)Permanent discontinuations due to AEs26 (11.6)16 (18.2)29 (34.1)AEs of special interest Death000 Gastrointestinal perforationb000 Hepatic eventb3 (1.3)00 Herpes zoster (non-serious and serious)2 (0.9)c00 Interstitial lung diseaseb000 Major adverse cardiovascular eventsb000 Malignancy (including non-melanoma skin cancer)b000 Macrophage activation syndromeb000 Opportunistic infectionb000 SI3 (1.3)1 (1.1)d1 (1.2) Thrombotic event (deep vein thrombosis, pulmonary embolismbor arterial thromboembolism)000 Tuberculosisb000a5 mg BID or equivalent weight-based lower dose in pts <40 kgbAdjudicated eventscBoth non-seriousdOne SAE of pilonidal cyst repair was coded to surgical procedures instead of infections, and was inadvertently not identified as an SI. Following adjudication, the SAE did not meet opportunistic infection criteria; it is also included in the table as an SIAE, adverse event; BID, twice daily; PBO, placebo; pts, patients; SAE, serious AE; SI, serious infectionAcknowledgments:Study sponsored by Pfizer Inc. Medical writing support was provided by Sarah Piggott of CMC Connect and funded by Pfizer Inc.Disclosure of Interests:Nicolino Ruperto Grant/research support from: Bristol-Myers Squibb, Eli Lily, F Hoffmann-La Roche, GlaxoSmithKline, Janssen, Novartis, Pfizer, Sobi (paid to institution), Consultant of: Ablynx, AbbVie, AstraZeneca-Medimmune, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, Eli Lily, EMD Serono, GlaxoSmithKline, Hoffmann-La Roche, Janssen, Merck, Novartis, Pfizer, R-Pharma, Sanofi, Servier, Sinergie, Sobi, Takeda, Speakers bureau: Ablynx, AbbVie, AstraZeneca-Medimmune, Biogen, Boehringer Ingelheim, Bristol-Myers Squibb, Eli Lily, EMD Serono, GlaxoSmithKline, Hoffmann-La Roche, Janssen, Merck, Novartis, Pfizer, R-Pharma, Sanofi, Servier, Sinergie, Sobi, Takeda, Olga Synoverska Speakers bureau: Sanofi, Tracy Ting: None declared, Carlos Abud-Mendoza Speakers bureau: Eli Lilly, Pfizer Inc, Alberto Spindler Speakers bureau: Eli Lilly, Yulia Vyzhga Grant/research support from: Pfizer Inc, Katherine Marzan Grant/research support from: Novartis, Vladimir Keltsev: None declared, Irit Tirosh: None declared, Lisa Imundo: None declared, Rita Jerath: None declared, Daniel Kingsbury: None declared, Betül Sözeri: None declared, Sheetal Vora: None declared, Sampath Prahalad Grant/research support from: Novartis, Elena Zholobova Grant/research support from: Novartis and Pfizer Inc, Speakers bureau: AbbVie, Novartis, Pfizer Inc and Roche, Yonatan Butbul Aviel: None declared, Vyacheslav Chasnyk: None declared, Melissa Lerman Grant/research support from: Amgen, Kabita Nanda Grant/research support from: Abbott, AbbVie, Amgen and Roche, Heinrike Schmeling Grant/research support from: Janssen, Pfizer Inc, Roche and USB Bioscience, Heather Tory: None declared, Yosef Uziel Speakers bureau: Pfizer Inc, Diego O Viola Grant/research support from: Bristol-Myers Squibb, GSK, Janssen and Pfizer Inc, Speakers bureau: AbbVie and Bristol-Myers Squibb, Holly Posner Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Keith Kanik Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Ann Wouters Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Cheng Chang Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Richard Zhang Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Irina Lazariciu Consultant of: Pfizer Inc, Employee of: IQVIA, Ming-Ann Hsu Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Ricardo Suehiro Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Alberto Martini Consultant of: AbbVie, Eli Lily, EMD Serono, Janssen, Novartis, Pfizer, UCB, Daniel J Lovell Consultant of: Abbott (consulting and PI), AbbVie (PI), Amgen (consultant and DSMC Chairperson), AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb (PI), Celgene, Forest Research (DSMB Chairman), GlaxoSmithKline, Hoffman-La Roche, Janssen (co-PI), Novartis (consultant and PI), Pfizer (consultant and PI), Roche (PI), Takeda, UBC (consultant and PI), Wyeth, Employee of: Cincinnati Children's Hospital Medical Center, Speakers bureau: Wyeth, Hermine Brunner Consultant of: Hoffman-La Roche, Novartis, Pfizer, Sanofi Aventis, Merck Serono, AbbVie, Amgen, Alter, AstraZeneca, Baxalta Biosimilars, Biogen Idec, Boehringer, Bristol-Myers Squibb, Celgene, EMD Serono, Janssen, MedImmune, Novartis, Pfizer, and UCB Biosciences, Speakers bureau: GSK, Roche, and Novarti

Satisfação no trabalho da equipe de enfermagem: revisão integrativa

Job satisfaction consists of a feeling of wellbeing, resulting from the interaction of several occupational aspects, and may influence the worker's relationship with the organization, clients and family. Hence, it becomes important for the quality of nursing care to reflect on this topic in depth. Therefore, this study aimed to examine the scientific evidence related to job satisfaction in Brazilian nursing. An integrative literature review was carried out in the databases LILACS, MEDLINE, BDENF and Cochrane Library, totaling 17 publications, categorized in: Job Satisfaction, Job Dissatisfaction and Associated Factors. It was concluded that job satisfaction is determined by a complex network of factors and may vary depending on the group studied. Additional research, particularly of evidence level III in different nursing fields, covering all of Brazil, is necessary to support the implementation of occupational improvements.La satisfacción en el trabajo consiste en un sentimiento de bienestar resultante de la interacción de varios aspectos ocupacionales, pudiendo influenciar la relación del trabajador con la organización, clientes y familia. Es importante para la calidad de la asistencia de enfermería realizar una reflexión profunda sobre este tema, por eso se objetivó en este estudio analizar las evidencias científicas referentes a la satisfacción en el trabajo del equipo de enfermería brasileño. Se trató de una revisión integradora de la literatura en las bases de datos LILACS, MEDLINE, BDENF y Biblioteca Cochrane, totalizando 17 publicaciones categorizadas en: Satisfacción en el Trabajo, Insatisfacción en el Trabajo y Factores Asociados. Se concluyó que la satisfacción en el trabajo es determinada por una red compleja de factores, pudiendo variar conforme el grupo estudiado. Investigaciones adicionales, especialmente con niveles de evidencias III, en diferentes campos de actuación de la enfermería, abarcando todo el Brasil, son necesarias para subsidiar la implantación de mejorías ocupacionales.A satisfação no trabalho consiste em sentimento de bem-estar. resultante da interação de vários aspectos ocupacionais, podendo influenciar a relação do trabalhador com a organização, clientes e família. Torna-se importante, para a qualidade da assistência de enfermagem, reflexão aprofundada sobre esse tema, e, por isso, objetivou-se neste estudo analisar as evidências científicas referentes à satisfação no trabalho da equipe de enfermagem brasileira. Trata-se de revisão integrativa da literatura nas bases de dados LILACS, MEDLINE, BDENF e Biblioteca Cochrane, totalizando 17 publicações categorizadas em: satisfação no trabalho, insatisfação no trabalho e fatores associados. Conclui-se que a satisfação no trabalho é determinada por rede complexa de fatores, podendo variar conforme o grupo estudado. Pesquisas adicionais, especialmente com níveis de evidências III, em diferentes campos de atuação da enfermagem, abrangendo todo Brasil, são necessárias para subsidiar a implantação de melhorias ocupacionais