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Assessing the impact of data-driven limitations on tracing and forecasting the outbreak dynamics of COVID-19

The availability of the epidemiological data strongly affects the reliability of several mathematical models in tracing and forecasting COVID-19 pandemic, hampering a fair assessment of their relative performance. The marked difference between the lethality of the virus when comparing the first and second waves is an evident sign of the poor reliability of the data, also related to the variability over time in the number of performed swabs. During the early epidemic stage, swabs were made onl...

Transcriptomics and metabolomics integration reveals redox-dependent metabolic rewiring in breast cancer cells

Rewiring glucose metabolism toward aerobic glycolysis provides cancer cells with a rapid generation of pyruvate, ATP, and NADH, while pyruvate oxidation to lactate guarantees refueling of oxidized NAD+ to sustain glycolysis. CtPB2, an NADH-dependent transcriptional co-regulator, has been proposed to work as an NADH sensor, linking metabolism to epigenetic transcriptional reprogramming. By integrating metabolomics and transcriptomics in a triple-negative human breast cancer cell line, we show ...

The role of FOSL1 in stem-like cell reprogramming processes

Cancer stem-like cells (CSCs) have self-renewal abilities responsible for cancer progression, therapy resistance, and metastatic growth. The glioblastoma stem-like cells are the most studied among CSC populations. A recent study identified four transcription factors (SOX2, SALL2, OLIG2, and POU3F2) as the minimal core sufficient to reprogram differentiated glioblastoma (GBM) cells into stem-like cells. Transcriptomic data of GBM tissues and cell lines from two different datasets were then ana...

CAMUR: Knowledge extraction from RNA-seq cancer data through equivalent classification rules

Motivation: Nowadays, knowledge extraction methods from Next Generation Sequencing data are highly requested. In this work, we focus on RNA-seq gene expression analysis and specifically on case-control studies with rule-based supervised classification algorithms that build a model able to discriminate cases from controls. State of the art algorithms compute a single classification model that contains few features (genes). On the contrary, our goal is to elicit a higher amount of knowledge by ...

Impact of Drug–Drug Interactions on Clinical Outcomes in Metastatic Melanoma Patients Treated With Combined BRAF/MEK Inhibitors: A Real-World Study

The unique pharmacokinetics of BRAF and MEK inhibitors make patients vulnerable to drug–drug interactions (DDIs), which may compromise treatment efficacy in metastatic melanoma. This study evaluates the impact of DDIs on clinical outcomes in patients with metastatic melanoma treated with BRAF/MEK inhibitors. This multicenter, observational, retrospective study assessed DDIs using the Drug-PIN software. Associations between the Drug-PIN continuous score, Drug-PIN light, and treatment outscomes...

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