Machine Learning Meets Cancer.

The role of machine learning (a part of artificial intelligence-AI) in the diagnosis and treatment of various types of oncology is steadily increasing. It is expected that the use of AI in oncology will speed up both diagnostic and treatment planning processes. This review describes recent applications of machine learning in oncology, including medical image analysis, treatment planning, patient survival prognosis, and the synthesis of drugs at the point of care.

Alkylresorcinols as New Modulators of the Metabolic Activity of the Gut Microbiota.

Alkylresorcinols (ARs) are polyphenolic compounds with a wide spectrum of biological activities and are potentially involved in the regulation of host metabolism. The present study aims to establish whether ARs can be produced by the human gut microbiota and to evaluate alterations in content in stool samples as well as metabolic activity of the gut microbiota of C57BL, , and LDLR (-/-) mice according to diet specifications and olivetol (5-n-pentylresorcinol) supplementation to estimate the regulatory potential of ARs. Gas chromatography with mass spectrometric detection was used to quantitatively analyse AR levels in mouse stool samples; faecal microbiota transplantation (FMT) from human donors to germ-free mice was performed to determine whether the intestinal microbiota could produce AR molecules; metagenome sequencing analysis of the mouse gut microbiota followed by reconstruction of its metabolic activity was performed to investigate olivetol's regulatory potential.

Synthesis, Characterization and Biodistribution of GdF:Tb@RB Nanocomposites.

Herein we report the development of a nanocomposite for X-ray-induced photodynamic therapy (X-PDT) and computed tomography (CT) based on PEG-capped GdF:Tb scintillating nanoparticles conjugated with Rose Bengal photosensitizer via electrostatic interactions. Scintillating GdF:Tb nanoparticles were synthesized by a facile and cost-effective wet chemical precipitation method. All synthesized nanoparticles had an elongated "spindle-like" clustered morphology with an orthorhombic structure.

Identification of new candidate genes and signalling pathways associated with the development of neuroendocrine pancreatic tumours based on next generation sequencing data.

Despite advances in classification, treatment, and imaging, neuroendocrine tumours remain a clinically complex subject. In this work, we studied the genetic profile of well-differentiated pancreatic neuroendocrine tumours (PanNETs) in a cohort of Caucasian patients and analysed the signalling pathways and candidate genes potentially associated with the development of this oncological disease. Twenty-four formalin-fixed paraffin-embedded (FFPE) samples of well-differentiated PanNETs were subjected to massive parallel sequencing using the targeted gene panel (409 genes) of the Illumina NextSeq 550 platform (San Diego, USA).

EGFR mutations and tumor metastases in patients with nonsmall cell lung cancer in the South of Russia.

Purpose: To assess the frequencies of somatic EGFR mutations in the tumor tissues of patients with non-small cell lung cancer (NSCLC) residing in the South of Russia (SR), and to define the relationship between genetic subtypes of NSCLC and the emergence of different types of metastases.

Methods: DNA was extracted from formalin-fixed parrafin embedded (FFPE) samples of 721 patients. A total of 29 somatic EGFR mutations were detected using commercial Therascreen EGFR RGQ PCR Kit.

A Proteomics Analysis Reveals 9 Up-Regulated Proteins Associated with Altered Cell Signaling in Colon Cancer Patients.

Colorectal cancer is the second most common cancer in women and third most common cancer in men. Cell signaling alterations in colon cancer, especially in aggressive metastatic tumors, require further investigations. The present study aims to compare the expression pattern of proteins associated with cell signaling in paired tumor and non-tumor samples of patients with colon cancer, as well as to define the cluster of proteins to differentiate patients with non-metastatic (Dukes' grade B) and metastatic (Dukes' grade C&D) colon cancer.