Combinatorial Markov chains on linear extensions

We consider generalizations of Schuetzenberger's promotion operator on the set L of linear extensions of a finite poset of size n. This gives rise to a strongly connected graph on L. By assigning weights to the edges of the graph in two different ways, we study two Markov chains, both of which are irreducible. The stationary state of one gives rise to the uniform distribution, whereas the weights of the stationary state of the other has a nice product formula. This generalizes results by Hendricks on the Tsetlin library, which corresponds to the case when the poset is the anti-chain and hence L=S_n is the full symmetric group. We also provide explicit eigenvalues of the transition matrix in general when the poset is a rooted forest. This is shown by proving that the associated monoid is R-trivial and then using Steinberg's extension of Brown's theory for Markov chains on left regular bands to R-trivial monoids.Comment: 35 pages, more examples of promotion, rephrased the main theorems in terms of discrete time Markov chain

Enhanced stochastic optimization algorithm for finding effective multi-target therapeutics

<p>Abstract</p> <p>Background</p> <p>For treating a complex disease such as cancer, we need effective means to control the biological network that underlies the disease. However, biological networks are typically robust to external perturbations, making it difficult to beneficially alter the network dynamics by controlling a single target. In fact, multi-target therapeutics is often more effective compared to monotherapies, and combinatory drugs are commonly used these days for treating various diseases. A practical challenge in combination therapy is that the number of possible drug combinations increases exponentially, which makes the prediction of the optimal drug combination a difficult combinatorial optimization problem. Recently, a stochastic optimization algorithm called the Gur Game algorithm was proposed for drug optimization, which was shown to be very efficient in finding potent drug combinations.</p> <p>Results</p> <p>In this paper, we propose a novel stochastic optimization algorithm that can be used for effective optimization of combinatory drugs. The proposed algorithm analyzes how the concentration change of a specific drug affects the overall drug response, thereby making an informed guess on how the concentration should be updated to improve the drug response. We evaluated the performance of the proposed algorithm based on various drug response functions, and compared it with the Gur Game algorithm.</p> <p>Conclusions</p> <p>Numerical experiments clearly show that the proposed algorithm significantly outperforms the original Gur Game algorithm, in terms of reliability and efficiency. This enhanced optimization algorithm can provide an effective framework for identifying potent drug combinations that lead to optimal drug response.</p

Inhibition of the Nicotinic Acetylcholine Receptors by Cobra Venom α-Neurotoxins: Is There a Perspective in Lung Cancer Treatment?

Nicotine exerts its oncogenic effects through the binding to nicotinic acetylcholine receptors (nAChRs) and the activation of downstream pathways that block apoptosis and promote neo-angiogenesis. The nAChRs of the α7 subtype are present on a wide variety of cancer cells and their inhibition by cobra venom neurotoxins has been proposed in several articles and reviews as a potential innovative lung cancer therapy. However, since part of the published results was recently retracted, we believe that the antitumoral activity of cobra venom neurotoxins needs to be independently re-evaluated

The Indian cobra reference genome and transcriptome enables comprehensive identification of venom toxins

Snakebite envenoming is a serious and neglected tropical disease that kills ~100,000 people annually. High-quality, genome-enabled comprehensive characterization of toxin genes will facilitate development of effective humanized recombinant antivenom. We report a de novo near-chromosomal genome assembly of Naja naja, the Indian cobra, a highly venomous, medically important snake. Our assembly has a scaffold N50 of 223.35 Mb, with 19 scaffolds containing 95% of the genome. Of the 23,248 predicted protein-coding genes, 12,346 venom-gland-expressed genes constitute the \u27venom-ome\u27 and this included 139 genes from 33 toxin families. Among the 139 toxin genes were 19 \u27venom-ome-specific toxins\u27 (VSTs) that showed venom-gland-specific expression, and these probably encode the minimal core venom effector proteins. Synthetic venom reconstituted through recombinant VST expression will aid in the rapid development of safe and effective synthetic antivenom. Additionally, our genome could serve as a reference for snake genomes, support evolutionary studies and enable venom-driven drug discovery

C4.4A as a candidate marker in the diagnosis of colorectal cancer

C4.4A is a member of the Ly-6 family with restricted expression in non-transformed tissues. C4.4A expression in human cancer has rarely been evaluated. Thus, it became important to explore C4.4A protein expression in human tumour tissue to obtain an estimate on the frequency of expression and the correlation with tumour progression, the study focusing on colorectal cancer. The analysis of C4.4A in human tumour lines by western blot and immunoprecipitation using polyclonal rabbit antibodies that recognize different C4.4A epitopes revealed C4.4A oligomer and heavily glycosylated C4.4A isoform expression that, in some instances, inhibited antibody binding and interaction with the C4.4A ligand galectin-3. In addition, tumour cell lines released C4.4A by vesicle shedding and proteolytic cleavage. C4.4A was expressed in over 80% of primary colorectal cancer and liver metastasis with negligible expression in adjacent colonic mucosa, inflamed colonic tissue and liver. This compares well with EpCAM and CO-029 expression in over 90% of colorectal cancer. C4.4A expression was only observed in about 50% of pancreatic cancer and renal cell carcinoma. By de novo expression in colonic cancer tissue, we consider C4.4A as a candidate diagnostic marker in colorectal cancer, which possibly can be detected in body fluids

Solution Structure and Phylogenetics of Prod1, a Member of the Three-Finger Protein Superfamily Implicated in Salamander Limb Regeneration

Prod1 is a cell-surface molecule of the three-finger protein (TFP) superfamily involved in the specification of newt limb PD identity. The TFP superfamily is a highly diverse group of metazoan proteins that includes snake venom toxins, mammalian transmembrane receptors and miscellaneous signaling molecules..The available data suggest that Prod1, and thereby its role in encoding PD identity, is restricted to salamanders. The lack of comparable limb-regenerative capability in other adult vertebrates could be correlated with the absence of the Prod1 gene

Identification and Structural Characterization of a New Three-Finger Toxin Hemachatoxin from Hemachatus haemachatus Venom

10.1371/journal.pone.0048112PLoS ONE710