Osteosarcoma: Current status of immunotherapy and future trends (Review)

Osteosarcoma is the most common primary bone tumor and represents a major therapeutic challenge in medical oncology. While the use of aggressive chemotherapy has drastically improved the prognosis of the patients with non-metastatic osteosarcomas, the very poor prognosis of patients with metastasis have led to the exploration of new, more effective and less toxic treatments, such as immunotherapy for curing osteosarcoma. Compared to the numerous reports describing successful immunotherapy for other solid tumors, the number of reports concerning immunotherapy for osteosarcoma is low. However, this therapeutic strategy opens new areas for the treatment of osteosarcoma. In this review, the reasons for delay and all elements essential to develop immunotherapy concerning osteosarcoma are defined. Several pieces of evidence strongly support the potential capability of new therapies such as cellular therapy and gene therapy to eradicate osteosarcoma. Thus, clinical human trials using peptides, cytokines and dendritic cells have been performed. Tumor-infiltrating lymphocytes and some tumor antigens have been identified in osteosarcoma and resulted in an important breakthrough in cellular immunotherapy. Also, RANKL/RANK/OPG, the key regulator of bone metabolism, is a hot spot in this field as therapeutic tools. Immunotherapy for osteosarcomas has great potential, promising improvement in the survival rate and better quality of life for the patients

The Computer Science Ontology: A Large-Scale Taxonomy of Research Areas

Ontologies of research areas are important tools for characterising, exploring, and analysing the research landscape. Some fields of research are comprehensively described by large-scale taxonomies, e.g., MeSH in Biology and PhySH in Physics. Conversely, current Computer Science taxonomies are coarse-grained and tend to evolve slowly. For instance, the ACM classification scheme contains only about 2K research topics and the last version dates back to 2012. In this paper, we introduce the Computer Science Ontology (CSO), a large-scale, automatically generated ontology of research areas, which includes about 26K topics and 226K semantic relationships. It was created by applying the Klink-2 algorithm on a very large dataset of 16M scientific articles. CSO presents two main advantages over the alternatives: i) it includes a very large number of topics that do not appear in other classifications, and ii) it can be updated automatically by running Klink-2 on recent corpora of publications. CSO powers several tools adopted by the editorial team at Springer Nature and has been used to enable a variety of solutions, such as classifying research publications, detecting research communities, and predicting research trends. To facilitate the uptake of CSO we have developed the CSO Portal, a web application that enables users to download, explore, and provide granular feedback on CSO at different levels. Users can use the portal to rate topics and relationships, suggest missing relationships, and visualise sections of the ontology. The portal will support the publication of and access to regular new releases of CSO, with the aim of providing a comprehensive resource to the various communities engaged with scholarly data

Estimates for the Sobolev trace constant with critical exponent and applications

In this paper we find estimates for the optimal constant in the critical Sobolev trace inequality S\|u\|^p_{L^{p_*}(\partial\Omega) \hookrightarrow \|u\|^p_{W^{1,p}(\Omega)} that are independent of $\Omega$. This estimates generalized those of [3] for general $p$. Here $p_* := p(N-1)/(N-p)$ is the critical exponent for the immersion and $N$ is the space dimension. Then we apply our results first to prove existence of positive solutions to a nonlinear elliptic problem with a nonlinear boundary condition with critical growth on the boundary, generalizing the results of [16]. Finally, we study an optimal design problem with critical exponent.Comment: 22 pages, submitte

A compactness theorem for scalar-flat metrics on manifolds with boundary

Let (M,g) be a compact Riemannian manifold with boundary. This paper is concerned with the set of scalar-flat metrics which are in the conformal class of g and have the boundary as a constant mean curvature hypersurface. We prove that this set is compact for dimensions greater than or equal to 7 under the generic condition that the trace-free 2nd fundamental form of the boundary is nonzero everywhere.Comment: 49 pages. Final version, to appear in Calc. Var. Partial Differential Equation