Pan-cancer and multiomics: advanced strategies for diagnosis, prognosis, and therapy in the complex genetic and molecular universe of cancer.

The pan-cancer and multi-omics approach is motivated by the genetic and molecular complexity inherent in the varied types of cancer. This method presents itself as a crucial resource for advancing early diagnosis, defining prognoses and identifying treatments that share common bases between different forms of tumors. The aim of this article is to explore pan-cancer analysis in conjunction with multi-omics strategies, evaluating laboratory, computational, clinical procedures and their consequences, as well as examining the tumor microenvironment, epigenetics and future directions of these technologies in patient management.

Characterization and analysis of the bioactivity of the Piper rivinoides Kunth essential oil and its components myristicin and elemicin, against opportunistic fungal pathogens.

Candidiasis is an infectious disease caused by some fungi of the genus Candida. In Brazil, the incidence rate is higher than in European countries and the United States, and health problems occur mainly due to the virulence factors of the fungi, which have made treatment with commercial drugs difficult. Considering the context, plants rich in phenolic compounds, such as those of the genus Piper, have been studied due to their antimicrobial properties.

Time domain NMR for polymorphism characterization: Current status and future perspectives.

Polymorphism is the ability of a compound to exist in multiple crystal forms while maintaining the same chemical composition. This phenomenon is reflected in different solid-state physicochemical properties due to variations in structural energy and the degree of lattice disorder. The pharmaceutical industry places significant emphasis on thoroughly characterizing polymorphism in Active Pharmaceutical Ingredients (APIs) because of its impact on the pharmacokinetic properties on the final medicine product.

Machine Learning-Driven Discovery and Database of Cyanobacteria Bioactive Compounds: A Resource for Therapeutics and Bioremediation.

Cyanobacteria strains have the potential to produce bioactive compounds that can be used in therapeutics and bioremediation. Therefore, compiling all information about these compounds to consider their value as bioresources for industrial and research applications is essential. In this study, a searchable, updated, curated, and downloadable database of cyanobacteria bioactive compounds was designed, along with a machine-learning model to predict the compounds' targets of newly discovered molecules.