On the minimum and maximum selective graph coloring problems in some graph classes

Given a graph together with a partition of its vertex set, the minimum selective coloring problem consists of selecting one vertex per partition set such that the chromatic number of the subgraph induced by the selected vertices is minimum. The contribution of this paper is twofold. First, we investigate the complexity status of the minimum selective coloring problem in some specific graph classes motivated by some models described in Demange et al. (2015). Second, we introduce a new problem that corresponds to the worst situation in the minimum selective coloring; the maximum selective coloring problem aims to select one vertex per partition set such that the chromatic number of the subgraph induced by the selected vertices is maximum. We motivat

Direct Identification of an HPV-16 Tumor Antigen from Cervical Cancer Biopsy Specimens

Persistent infection with high-risk human papilloma viruses (HPV) is the worldwide cause of many cancers, including cervical, anal, vulval, vaginal, penile, and oropharyngeal. Since T cells naturally eliminate the majority of chronic HPV infections by recognizing epitopes displayed on virally altered epithelium, we exploited Poisson detection mass spectrometry (MS3) to identify those epitopes and inform future T cell-based vaccine design. Nine cervical cancer biopsies from HPV-16 positive HLA-A*02 patients were obtained, histopathology determined, and E7 oncogene PCR-amplified from tumor DNA and sequenced. Conservation of E7 oncogene coding segments was found in all tumors. MS3 analysis of HLA-A*02 immunoprecipitates detected E711–19 peptide (YMLDLQPET) in seven of the nine tumor biopsies. The remaining two samples were E711–19 negative and lacked the HLA-A*02 binding GILT thioreductase peptide despite possessing binding-competent HLA-A*02 alleles. Thus, the conserved E711–19 peptide is a dominant HLA-A*02 binding tumor antigen in HPV-16 transformed cervical squamous and adenocarcinomas. Findings that a minority of HLA-A*02:01 tumors lack expression of both E711–19 and a peptide from a thioreductase important in processing of cysteine-rich proteins like E7 underscore the value of physical detection, define a potential additional tumor escape mechanism and have implications for therapeutic cancer vaccine development

Encapsulating peritoneal sclerosis

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Assessing the impact of low level laser therapy (LLLT) on biological systems: a review

PURPOSE: Low level laser therapy (LLLT) in the visible to near infrared spectral band (390-1100 nm) is absorption of laser light at the electronic level, without generation of heat. It may be applied in a wide range of treatments including wound healing, inflammation and pain reduction. Despite its potential beneficial impacts, the use of lasers for therapeutic purposes still remains controversial in mainstream medicine. Whilst taking into account the physical characteristics of different qualities of lasers, this review aims to provide a comprehensive account of the current literature available in the field pertaining to their potential impact at cellular and molecular levels elucidating mechanistic interactions in different mammalian models. The review also aims to focus on the integral approach of the optimal characteristics of LLLT that suit a biological system target to produce the beneficial effect at the cellular and molecular levels. METHODS: Recent research articles were reviewed that explored the interaction of lasers (coherent sources) and LEDs (incoherent sources) at the molecular and cellular levels. RESULTS: It is envisaged that underlying mechanisms of beneficial impact of lasers to patients involves biological processes at the cellular and molecular levels. The biological impact or effects of LLLT at the cellular and molecular level could include cellular viability, proliferation rate, as well as DNA integrity and the repair of damaged DNA. This review summarizes the available information in the literature pertaining to cellular and molecular effects of lasers. CONCLUSIONS: It is suggested that a change in approach is required to understand how to exploit the potential therapeutic modality of lasers whilst minimizing its possible detrimental effects

Recognizing Polar Planar Graphs Using New Results for Monopolarity

Abstract. Polar and monopolar graphs are natural generalizations of bipartite or split graphs. A graph G =(V,E) is polar if its vertex set admits a partition V = A∪B such that A induces a complete multipartite and B the complement of a complete multipartite graph. If A is even a stable set then G is called monopolar. Recognizing general polar or monopolar graphs is NP-complete and, as yet, efficient recognition is available only for very few graph classes. This paper considers monopolar and polar graphs that are also planar. On the one hand, we show that recognizing these graphs remains NPcomplete, on the other hand we identify subclasses of planar graphs on which polarity and monopolarity can be checked efficiently. The new NPcompleteness results cover very restricted graph classes and are sharper than all previous known cases. On the way to the positive results, we develop new techniques for efficient recognition of subclasses of monopolar graphs. These new results extend nearly all known results for efficient monopolar recognition.

On some applications of the selective graph coloring problem

In this paper we present the Selective Graph Coloring Problem, a generalization of the standard graph coloring problem as well as several of its possible applications. Given a graph with a partition of its vertex set into several clusters, we want to select one vertex per cluster such that the chromatic number of the subgraph induced by the selected vertices is minimum. This problem appeared in the literature under different names for specific models and its complexity has recently been studied for different classes of graphs. Here, we describe different models - some already discussed in previous papers and some new ones - in very different contexts under a unified framework based on this graph problem. We point out similarities between these models, offering a new approach to solve them, and show some generic situations where the selective graph coloring problem may be used. We focus on specific graph classes motivated by each model, and we briefly discuss the complexity of the selective graph coloring problem in each one of these graph classes and point out interesting future research direction

Effects of proteome rebalancing and sulfur nutrition on the accumulation of methionine rich δ-zein in transgenic soybeans

Expression of heterologous methionine-rich proteins to increase the overall sulfur amino acid content of soybean seeds has been only marginally successful, presumably due to low accumulation of transgenes in soybeans or due to gene silencing. Proteome rebalancing of seed proteins has been shown to promote the accumulation of foreign proteins. In this study, we have utilized RNAi technology to suppress the expression of the β-conglycinin, the abundant 7S seed storage proteins of soybean. Western blot and 2D-gel analysis revealed that β-conglycinin knockdown line (SAM) failed to accumulate the α', α, and β-subunits of β-conglycinin. The proteome rebalanced SAM retained the normal overall protein and oil content similar to that of wild-type soybean. We also generated transgenic soybean lines expressing methionine-rich 11 kDa δ-zein under the control of either the glycinin or β-conglycinin promoter. The introgression of the 11 kDa δ-zein into β-conglycinin knockdown line did not enhance the accumulation of the 11 kDa δ-zein. However, when the same plants were grown in sulfur-rich medium, we observed 3- to 16-fold increased accumulation of the 11 kDa δ-zein. Transmission electron microscopy observation revealed that seeds grown in sulfur-rich medium contained numerous endoplasmic reticulum derived protein bodies. Our findings suggest that sulfur availability, not proteome rebalancing, is needed for high-level accumulation of heterologous methionine-rich proteins in soybean seeds