Natural Language Processing (NLP) makes use of Artificial Intelligence algorithms to extract meaningful information from unstructured texts, i.e., content that lacks metadata and cannot easily be indexed or mapped onto standard database fields. It has several applications, from sentiment analysis and text summary to automatic language translation. In this work, we use NLP to figure out similar structural linguistic patterns among several different languages. We apply the word2vec algorithm that creates a vector representation for the words in a multidimensional space that maintains the meaning relationship between the words. From a large corpus we built this vectorial representation in a 100-dimensional space for English, Portuguese, German, Spanish, Russian, French, Chinese, Japanese, Korean, Italian, Arabic, Hebrew, Basque, Dutch, Swedish, Finnish, and Estonian. Then, we calculated the fractal dimensions of the structure that represents each language. The structures are multi-fractals with two different dimensions that we use, in addition to the token-dictionary size rate of the languages, to represent the languages in a three-dimensional space. Finally, analyzing the distance among languages in this space, we conclude that the closeness there is tendentially related to the distance in the Phylogenetic tree that depicts the lines of evolutionary descent of the languages from a common ancestor.
Osteosarcoma is the most common type of bone cancer. Despite therapeutic progress, survival rates for metastatic cases or that do not respond well to chemotherapy remain in the 30% range. In this sense, the use of nanotechnology to develop targeted and more effective therapies is a promising tool in the fight against cancer. Nanostructured hydroxyapatite, due to its biocompatibility and the wide possibility of functionalization, is an interesting material to design nanoplatforms for targeted drug delivery. These platforms have the potential to enable the use of natural substances in the fight against cancer, such as curcumin. Curcumin is a polyphenol with promising properties in treating various types of cancer, including osteosarcoma. In this work, hydroxyapatite (n-HA) nanorods synthesized by the hydrothermal method were investigated as a carrier for curcumin. For this, first-principle calculations based on the Density Functional Theory (DFT) were performed, in which the modification of curcumin (CM) with the coupling agent (3-aminopropyl) triethoxysilane (APTES) was theoretically evaluated. Curcumin was incorporated in n-HA and the drug loading stability was evaluated by leaching test. Samples were characterized by a multi-techniques approach, including Fourier transform infrared spectroscopy (FTIR), UV–visible spectroscopy (UV–Vis), X-ray diffraction (XRD), X-ray fluorescence spectrometry (FRX), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), zeta potential analysis (ζ), X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM). The results show that n-HAs with a 90 nm average size were obtained and successful incorporation of curcumin in the nanostructure was achieved. Cell viability and the number of osteosarcoma cells were decreased by CMAP-HA treatment. Furthermore, the stability test suggests that hydroxyapatite nanoparticles present great potential for the transportation of curcumin in the bloodstream, crediting this system for biological performance evaluations aiming at the treatment of osteosarcomas. Keywords: nanostructures, curcumin, hydroxyapatite, osteosarcoma.