Glycotope structures and intramolecular affinity factors of plant lectins for Tn/T antigens

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Cirmtuzumab inhibits Wnt5a-induced Rac1 activation in chronic lymphocytic leukemia treated with ibrutinib.

Signaling via the B cell receptor (BCR) plays an important role in the pathogenesis and progression of chronic lymphocytic leukemia (CLL). This is underscored by the clinical effectiveness of ibrutinib, an inhibitor of Bruton's tyrosine kinase (BTK) that can block BCR-signaling. However, ibrutinib cannot induce complete responses (CR) or durable remissions without continued therapy, suggesting alternative pathways also contribute to CLL growth/survival that are independent of BCR-signaling. ROR1 is a receptor for Wnt5a, which can promote activation of Rac1 to enhance CLL-cell proliferation and survival. In this study, we found that CLL cells of patients treated with ibrutinib had activated Rac1. Moreover, Wnt5a could induce Rac1 activation and enhance proliferation of CLL cells treated with ibrutinib at concentrations that were effective in completely inhibiting BTK and BCR-signaling. Wnt5a-induced Rac1 activation could be blocked by cirmtuzumab (UC-961), an anti-ROR1 mAb. We found that treatment with cirmtuzumab and ibrutinib was significantly more effective than treatment with either agent alone in clearing leukemia cells in vivo. This study indicates that cirmtuzumab may enhance the activity of ibrutinib in the treatment of patients with CLL or other ROR1+ B-cell malignancies

Sorafenib dose escalation is not uniformly associated with blood pressure elevations in normotensive patients with advanced malignancies.

Hypertension after treatment with vascular endothelial growth factor (VEGF) receptor inhibitors is associated with superior treatment outcomes for advanced cancer patients. To determine whether increased sorafenib doses cause incremental increases in blood pressure (BP), we measured 12-h ambulatory BP in 41 normotensive advanced solid tumor patients in a randomized dose-escalation study. After 7 days' treatment (400 mg b.i.d.), mean diastolic BP (DBP) increased in both study groups. After dose escalation, group A (400 mg t.i.d.) had marginally significant further increase in 12-h mean DBP (P = 0.053), but group B (600 mg b.i.d.) did not achieve statistically significant increases (P = 0.25). Within groups, individuals varied in BP response to sorafenib dose escalation, but these differences did not correlate with changes in steady-state plasma sorafenib concentrations. These findings in normotensive patients suggest BP is a complex pharmacodynamic biomarker of VEGF inhibition. Patients have intrinsic differences in sensitivity to sorafenib's BP-elevating effects

Effective Edge-Fault-Tolerant Single-Source Spanners via Best (or Good) Swap Edges

Computing \emph{all best swap edges} (ABSE) of a spanning tree $T$ of a given $n$-vertex and $m$-edge undirected and weighted graph $G$ means to select, for each edge $e$ of $T$, a corresponding non-tree edge $f$, in such a way that the tree obtained by replacing $e$ with $f$ enjoys some optimality criterion (which is naturally defined according to some objective function originally addressed by $T$). Solving efficiently an ABSE problem is by now a classic algorithmic issue, since it conveys a very successful way of coping with a (transient) \emph{edge failure} in tree-based communication networks: just replace the failing edge with its respective swap edge, so as that the connectivity is promptly reestablished by minimizing the rerouting and set-up costs. In this paper, we solve the ABSE problem for the case in which $T$ is a \emph{single-source shortest-path tree} of $G$, and our two selected swap criteria aim to minimize either the \emph{maximum} or the \emph{average stretch} in the swap tree of all the paths emanating from the source. Having these criteria in mind, the obtained structures can then be reviewed as \emph{edge-fault-tolerant single-source spanners}. For them, we propose two efficient algorithms running in $O(m n +n^2 \log n)$ and $O(m n \log \alpha(m,n))$ time, respectively, and we show that the guaranteed (either maximum or average, respectively) stretch factor is equal to 3, and this is tight. Moreover, for the maximum stretch, we also propose an almost linear $O(m \log \alpha(m,n))$ time algorithm computing a set of \emph{good} swap edges, each of which will guarantee a relative approximation factor on the maximum stretch of $3/2$ (tight) as opposed to that provided by the corresponding BSE. Surprisingly, no previous results were known for these two very natural swap problems.Comment: 15 pages, 4 figures, SIROCCO 201

Tuning the vertical location of helical surface states in topological insulator heterostructures via dual-proximity effects

In integrating topological insulators (TIs) with conventional materials, one crucial issue is how the topological surface states (TSS) will behave in such heterostructures. We use first-principles approaches to establish accurate tunability of the vertical location of the TSS via intriguing dual-proximity effects. By depositing a conventional insulator (CI) overlayer onto a TI substrate (Bi2Se3 or Bi2Te3), we demonstrate that, the TSS can float to the top of the CI film, or stay put at the CI/TI interface, or be pushed down deeper into the otherwise structurally homogeneous TI substrate. These contrasting behaviors imply a rich variety of possible quantum phase transitions in the hybrid systems, dictated by key material-specific properties of the CI. These discoveries lay the foundation for accurate manipulation of the real space properties of TSS in TI heterostructures of diverse technological significance

Natural variation in immune responses to neonatal mycobacterium bovis bacillus calmette-guerin (BCG) vaccination in a cohort of Gambian infants

Background There is a need for new vaccines for tuberculosis (TB) that protect against adult pulmonary disease in regions where BCG is not effective. However, BCG could remain integral to TB control programmes because neonatal BCG protects against disseminated forms of childhood TB and many new vaccines rely on BCG to prime immunity or are recombinant strains of BCG. Interferon-gamma (IFN-) is required for immunity to mycobacteria and used as a marker of immunity when new vaccines are tested. Although BCG is widely given to neonates IFN- responses to BCG in this age group are poorly described. Characterisation of IFN- responses to BCG is required for interpretation of vaccine immunogenicity study data where BCG is part of the vaccination strategy. Methodology/Principal Findings 236 healthy Gambian babies were vaccinated with M. bovis BCG at birth. IFN-, interleukin (IL)-5 and IL-13 responses to purified protein derivative (PPD), killed Mycobacterium tuberculosis (KMTB), M. tuberculosis short term culture filtrate (STCF) and M. bovis BCG antigen 85 complex (Ag85) were measured in a whole blood assay two months after vaccination. Cytokine responses varied up to 10 log-fold within this population. The majority of infants (89-98% depending on the antigen) made IFN- responses and there was significant correlation between IFN- responses to the different mycobacterial antigens (Spearman’s coefficient ranged from 0.340 to 0.675, p=10-6-10-22). IL-13 and IL-5 responses were generally low and there were more non-responders (33-75%) for these cytokines. Nonetheless, significant correlations were observed for IL-13 and IL-5 responses to different mycobacterial antigens Conclusions/Significance Cytokine responses to mycobacterial antigens in BCG-vaccinated infants are heterogeneous and there is significant inter-individual variation. Further studies in large populations of infants are required to identify the factors that determine variation in IFN- responses

A Bayesian method for evaluating and discovering disease loci associations

Background: A genome-wide association study (GWAS) typically involves examining representative SNPs in individuals from some population. A GWAS data set can concern a million SNPs and may soon concern billions. Researchers investigate the association of each SNP individually with a disease, and it is becoming increasingly commonplace to also analyze multi-SNP associations. Techniques for handling so many hypotheses include the Bonferroni correction and recently developed Bayesian methods. These methods can encounter problems. Most importantly, they are not applicable to a complex multi-locus hypothesis which has several competing hypotheses rather than only a null hypothesis. A method that computes the posterior probability of complex hypotheses is a pressing need. Methodology/Findings: We introduce the Bayesian network posterior probability (BNPP) method which addresses the difficulties. The method represents the relationship between a disease and SNPs using a directed acyclic graph (DAG) model, and computes the likelihood of such models using a Bayesian network scoring criterion. The posterior probability of a hypothesis is computed based on the likelihoods of all competing hypotheses. The BNPP can not only be used to evaluate a hypothesis that has previously been discovered or suspected, but also to discover new disease loci associations. The results of experiments using simulated and real data sets are presented. Our results concerning simulated data sets indicate that the BNPP exhibits both better evaluation and discovery performance than does a p-value based method. For the real data sets, previous findings in the literature are confirmed and additional findings are found. Conclusions/Significance: We conclude that the BNPP resolves a pressing problem by providing a way to compute the posterior probability of complex multi-locus hypotheses. A researcher can use the BNPP to determine the expected utility of investigating a hypothesis further. Furthermore, we conclude that the BNPP is a promising method for discovering disease loci associations. © 2011 Jiang et al