Gastric cancer (GC) is one of the leading causes of cancer-related death. The combination of new molecular classifications with clinicopathological data could contribute to the individualization of patients and to the development of new therapeutic strategies. We examined the various associations in two molecular types of GC: HER2-positive (human epidermal growth factor receptor 2) and microsatellite instability (MSI), assessing their influence on treatment and prognosis. A retrospective study of 142 GC patients was performed with molecular characterization through HER2 overexpression and DNA repair protein expression for MSI. The percentage of HER2-positive tumors was 13.4%, predominantly in men. Correlations were found with intestinal type, metastases, advanced stages and chemotherapy. Almost 75% of HER2-positive patients died. MSI occurred in 16.2%, associated with advanced age, female sex, distal location and intestinal type. These patients had few metastases and low stages. The percentage of deaths was higher among MSI patients who received perioperative chemotherapy. The determination of HER2 and MSI status in GC is important for their association with specific clinicopathological features and for their prognostic and predictive value.

In the last decade, the role of the microbiota–gut–brain axis has been gaining momentum in the context of many neurodegenerative and metabolic disorders, including Alzheimer’s disease (AD) and diabetes, respectively. Notably, a balanced gut microbiota contributes to the epithelial intestinal barrier maintenance, modulates the host immune system, and releases neurotransmitters and/or neuroprotective short-chain fatty acids. However, dysbiosis may provoke immune dysregulation, impacting neuroinflammation through peripheral–central immune communication. Moreover, lipopolysaccharide or detrimental microbial end-products can cross the blood–brain barrier and induce or at least potentiate the neuropathological progression of AD. Thus, after repeated failure to find a cure for this dementia, a necessary paradigmatic shift towards considering AD as a systemic disorder has occurred. Here, we present an overview of the use of germ-free and/or transgenic animal models as valid tools to unravel the connection between dysbiosis, metabolic diseases, and AD, and to investigate novel therapeutical targets. Given the high impact of dietary habits, not only on the microbiota but also on other well-established AD risk factors such as diabetes or obesity, consistent changes of lifestyle along with microbiome-based therapies should be considered as complementary approaches.

Purpose: The aim of this study is to investigate the effects of low frequency and intensity sinusoidal magnetic field (SMF) and pulsed magnetic field (PMF) exposure on the chronological aging and cellular stability of Saccharomyces cerevisiae. Materials and methods: The S. cerevisiae wild type strain (WS8105-1C) was exposed to SMF (2.45 mT, 50 Hz, continuous) and PMF (1.5 mT, 25 Hz, 8 h/day). Chronological aging was evaluated during 40 days. Survival was assayed by clonogenic assay and drop test. Cellular stability was studied by spontaneous mutation count and the index of respiratory competence (IRC). Results: We found that exposure to PMF produces an acceleration of cellular chronological aging, not observed in the groups treated with SMF. A decrease in the spontaneous frequency of mitochondrial mutation during aging was observed in PMF-treated samples. However, no alterations in the IRC during aging were found for both, SMF and PMF, treatments. Conclusions: Exposure to PMF produces the acceleration of aging and an alteration in cellular stability.

This study evaluates the DNA damage induced by pulsed magnetic field (MF) on S. cerevisiae cells exposed during chronological aging. Samples were exposed to 25 Hz pulsed MF (1.5mT, 8 h/day) while cells were aging chronologically. Clonogenic drop test was used to study cellular survival and the mutation frequency was evaluated by scoring the spontaneous revertant mutants. DNA damage analysis was performed after aging by electrophoresis and image analysis. Yeast cells aged during 40 days of exposure showing that pulsed MF exposure induced a premature aging. In addition, a gradual increase in spontaneous mutants was found in pulsed MF samples in relation to unexposed controls. An increase in DNA degradation, over the background level in relation to controls, was observed at the end of the exposure period. In conclusion, exposure of S. cerevisiae cells to pulsed MF during chronological aging could induce genomic DNA damage.

The repair of the damage produced to the genome and proteome by the action of ionizing radiation, oxidizing agents, and during aging is important to maintain cellular homeostasis. Many of the metabolic pathways influence multiple processes. In this way, this work aims to study the relationship between resistance/response to ionizing radiation, cellular aging, and the response mechanisms to oxidative stress, free radicals, reactive oxygen species (ROS), and antioxidant activity in the yeast S. cerevisiae. Systems biology allows us to use tools that reveal the molecular mechanisms common to different cellular response phenomena. The results found indicate that homologous recombination, non-homologous end joining, and base excision repair pathways are the most important common processes necessary to maintain cellular homeostasis. The metabolic routes of longevity regulation are those that jointly contribute to the three phenomena studied. This study proposes eleven common biomarkers for response/resistance to ionizing radiation and aging (EXO1, MEC1, MRE11, RAD27, RAD50, RAD51, RAD52, RAD55, RAD9, SGS1, YKU70) and two biomarkers for response/resistance to radiation and oxidative stress, free radicals, ROS, and antioxidant activity (NTG1, OGG1). In addition, it is important to highlight that the HSP104 protein could be a good biomarker common to the three phenomena studied.

Breast, colon, and ovarian cancers are among the most prevalent malignancies worldwide, with distinct clinical features. This study aims to identify key proteins as common biomarkers for breast, colon, and ovarian cancer through protein analysis, molecular mechanisms, and patient sample validation. Data mining from curated databases identified 483 proteins for breast cancer, 521 for colon cancer, and 223 for ovarian cancer. Interaction network analysis revealed shared clusters involved in cancer progression, DNA repair, and cell proliferation. A core set of 27 proteins was found to be common across all three cancer types, participating in key biological processes such as DNA damage response, cell proliferation, and apoptosis. Notably, these proteins are implicated in KEGG pathways linked to multiple cancers. Differential gene expression analysis revealed significant alterations in the expressions of MSH2 and KIT across the three cancers, suggesting their potential as common biomarkers. The high expression of these proteins was associated with better survival outcomes, highlighting their potential as common biomarkers for breast, colon, and ovarian cancers. The in-silico methodology integrated various bioinformatic tools—including cluster identification, gene expression profiling, protein network visualization, and biomarker prediction—enhancing the understanding of shared molecular mechanisms and potential therapeutic targets.