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Colorectal cancer is one of the most incident types of cancer in the world, with almost 2 million new cases annually. In Brazil, the scenery is the same, around 41 thousand new cases were estimated in the last 3 years. This increase in cases further intensifies the interest and importance of studies related to the topic, especially using new approaches. The use of machine learning algorithms for cancer studies has grown in recent years, and they can provide important information to medicine, in addition to making predictions based on the data. In this study, five different classifications were performed, considering patients' survival. Data were extracted from Hospital Based Cancer Registries of São Paulo, which is coordinated by Fundação Oncocentro de São Paulo, containing patients with colorectal cancer from São Paulo state, Brazil, treated between 2000 and 2021. The machine learning models used provided us the predictions and the most important features for each one of the algorithms of the studies. Using part of the dataset to validate our models, the results of the predictors were around 77% of accuracy, with AUC close to 0.86, and the most important column was the clinical staging in all of them., (© 2023. The Author(s).)

Detecting signs of potential extant/extinct life on Mars is challenging because the presence of organics on that planet is expected to be very low and most likely linked to radiation-protected refugia and/or preservative strategies (e.g., organo-mineral complexes). With scarcity of organics, accounting for biomineralization and potential relationships between biomarkers, mineralogy, and geochemistry is key in the search for extraterrestrial life. Here we explored microbial fingerprints and their associated mineralogy in Icelandic hydrothermal systems analog to Mars (i.e., high sulfur content, or amorphous silica), to identify potentially habitable locations on that planet. The mineralogical assemblage of four hydrothermal substrates (hot springs biofilms, mud pots, and steaming and inactive fumaroles) was analyzed concerning the distribution of biomarkers. Molecular and isotopic composition of lipids revealed quantitative and compositional differences apparently impacted by surface geothermal alteration and environmental factors. pH and water showed an influence (i.e., greatest biomass in circumneutral settings with highest supply and turnover of water), whereas temperature conditioned the mineralogy that supported specific microbial metabolisms related with sulfur. Raman spectra suggested the possible coexistence of abiotic and biomediated sources of minerals (i.e., sulfur or hematite). These findings may help to interpret future Raman or GC-MS signals in forthcoming Martian missions.

Insertion sequences (ISs) are ubiquitous and abundant mobile genetic elements in prokaryotic genomes. ISs often encode only one protein, the transposase, which catalyzes their transposition. Recent studies have shown that transposases of many different IS families interact with the β sliding clamp, a DNA replication factor of the host. However, it was unclear to what extent this interaction limits or favors the ability of ISs to colonize a chromosome from a phylogenetically-distant organism, or if the strength of this interaction affects the transposition rate. Here we describe the proliferation of a member of the IS1634 family in Acidiphilium over ~600 generations of cultured growth. We demonstrate that the purified transposase binds to the β sliding clamp of Acidiphilium, Leptospirillum and E. coli. Further, we also demonstrate that the Acidiphilium IS1634 transposase binds to the archaeal sliding clamp (PCNA) from Methanosarcina, and that the transposase encoded by Methanosarcina IS1634 binds to Acidiphilium β. Finally, we demonstrate that increasing the strength of the interaction between β and transposase results in a higher transposition rate in vivo. Our results suggest that the interaction could determine the potential of ISs to be mobilized in bacterial populations and also their ability to proliferate within chromosomes.