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Purpose There is an unmet need for biomarkers for identifying patients likely to benefit from anticancer treatments, selecting dose, and understanding mechanisms of resistance. Plasma vascular endothelial growth factor (VEGF) and soluble VEGF receptor 2 (sVEGFR-2) are known to be modulated by VEGF pathway inhibitors. It is unknown whether chemotherapy or VEGFR inhibitor/chemotherapy combinations induce changes in these or other cytokines and angiogenic factors (CAFs) and whether such changes could be markers of benefit. Methods Thirty-five plasma CAFs were analyzed using multiplexed bead arrays and enzyme-linked immunosorbent assays from 123 patients with non–small-cell lung cancer in a randomized phase II study who received vandetanib, a VEGFR and epidermal growth factor receptor inhibitor, monotherapy carboplatin and paclitaxel (CP), or the combination (VCP). Changes in CAFs at days 8, 22, and 43 from baseline were correlated with progression risk. Results VEGF increased and sVEGFR-2 decreased by day 43 in the vandetanib arm, whereas a distinct pattern was observed in the CP and VCP arms, with significant decreases in interleukin (IL) -12, IL-1 receptor antagonist, and matrix metalloproteinase 9 (MMP-9) and increased macrophage chemoattractant protein 1. In each treatment arm, changes in different markers were associated with progression risk. For example, increases in IL-8 with VCP, MMP-9 with CP, and VEGF with vandetanib monotherapy were associated with increased progression risk, and increase in intercellular adhesion molecule 1 with vandetanib was associated with decreased risk. Conclusion Vandetanib and chemotherapy treatment led to distinct patterns of CAF changes; the combination resembled chemotherapy alone. Changes in specific CAFs correlated with clinical outcome, but markers differed for each treatment arm. CAF profiling may provide insights into the biologic effects of treatment and identify drug-specific markers of activity and clinical benefit.

Background: We investigated cytokines and angiogenic factors (CAFs) in patients with metastatic renal cell carcinoma (mRCC) treated in a randomized phase II clinical trial of sorafenib versus sorafenib+ interferon-a (IFN-a) that yielded no differences in progression-free survival (PFS). We aimed to link the CAF profile to PFS and select candidate predictive and prognostic markers for further study. Methods: The concentrations of 52 plasma CAFs were measured pretreatment (n = 69), day 28, and day 56 using multiplex bead arrays and enzyme-linked immunosorbent assay. We investigated the association between baseline levels of CAFs with PFS and posttreatment changes. Results: Unsupervised CAF clustering analysis revealed two distinct mRCC patient groups with elevated proangiogenic or proinflammatory mediators. A six-marker baseline CAF signature [osteopontin, vascular endothelial growth factor (VEGF), carbonic anhydrase 9, collagen IV, VEGF receptor-2, and tumor necrosis factor-related apoptosis-inducing ligand] correlated with PFS benefit (hazard ratio 0.20 versus 2.25, signature negative versus positive, respectively; P = 0.0002). While changes in angiogenic factors were frequently attenuated by the sorafenib+ IFN combination, most key immunomodulatory mediators increased. Conclusions: Using CAF profiling, we identified two mRCC patient groups, a candidate plasma signature for predicting PFS benefit, and distinct marker changes occurring with each treatment. This platform may provide valuable insights into renal cell carcinoma biology and the molecular consequences of targeted therapies.

Basal stem rot (BSR) of oil palm (Elaeis guineensis) is caused by Ganoderma boninense, and, commercially, is one of the most devastating diseases in South East Asia. Losses of more than 80% of stands by the time they are halfway through their normal economic life have been reported. High incidence of BSR results in economic losses due to zero yields from dead palms and significantly reduced weight and number of fruit bunches in infected but living palms. Due to the importance of oil palm industry to Malaysia’s economy, the transfer of any materials that are related to Ganoderma is strictly prohibited from Peninsular Malaysia to Sabah and Sarawak. No basic identification method using molecular techniques for the identification of G. boninense exist in this study for G. boninense isolates from Sabah. The only report on this pathogens isolate in Sabah was based on their morphology and pathogencity. In conjunction with the morphological similarities among the different isolates, there are numerous opinions on the aggressiveness of the pathogen in Sabah. The isolates of G. boninense from Sabah were claimed to be less aggressive compared to those from Peninsular Malaysia. This may be due to lower incidence of BSR in Sabah and Sarawak compared to Peninsular Malaysia. Since the oil palm industry is a fast income-generating tool, data related to it may be highly sensitive. Researchers, plantation managers and entrepreneurs are not forthcoming with the information on oil palm genetic materials or isolates of G. boninense with others. The current speculations on the Sabah isolates need further investigation. In this study, we report the identity of isolates Ganoderma from Langkon Oil Palm Estate in Sabah, Malaysia. The identity of these isolates was confirmed using DNA sequence analysis after PCR amplification. The latter method shows that the Sabah isolates were very similar to aggressive G. boninense strains FA5017 or FA5035 from West Malaysia, with a maximum similarity of 98%.Key words: Aggressive, FA5017, FA5035, G1_5, isolate.

Let P be a set of n points on the euclidean plane. Let Ls(P) and Lm(P) denote the lengths of the Steiner minimum tree and the minimum spanning tree on P, respectively. In 1968, Gilbert and Pollak conjectured that for any P, Ls(P) >/= (radical3/2)Lm(P). We provide an abridged proof for their conjecture in this paper.

We show that the Steiner minimal tree for a set of points on a circle is the shortest path connecting them if at most one distance between two consecutive points is "large". We prove this by making an interesting use of the Steiner ratio ρ \rho which has been well studied in the literature.

In this paper we address the problem of estimating the number of stations in a wireless network. Under the assumption that each station can detect collisions, we show that it is possible to estimate the number stations in the network within a factor 2 from the correct value in time O(log n log log n). We further show that if no station can detect collisions, the same task can be accomplished within a factor of 3 in time O(log2n) and maximum energy O(log n) per node, with high probability. Finally, we present an algorithm that computes the minimum value held by the stations in the wireless network in time O(log2n).