Publications by authors named "I K Fedorova"
Tongue cancer at a young age demonstrates an increase in incidence, aggressiveness, and poor response to therapy. Classic etiological factors for head and neck tumors such as tobacco, alcohol, and human papillomavirus are not related to early-onset tongue cancer. Mechanisms of development and progression of this cancer remain unclear.
View Article and Find Full Text PDFProkaryotic anti-phage immune systems use TIR and cGAS-like enzymes to produce 1''-3'-glycocyclic ADP-ribose (1''-3'-gcADPR) and cyclic dinucleotide (CDN) and cyclic trinucleotide (CTN) signalling molecules, respectively, which limit phage replication. However, how phages neutralize these distinct and common systems is largely unclear. Here we show that the Thoeris anti-defence proteins Tad1 and Tad2 both achieve anti-cyclic-oligonucleotide-based anti-phage signalling system (anti-CBASS) activity by simultaneously sequestering CBASS cyclic oligonucleotides.
View Article and Find Full Text PDFTo identify genetic alterations associated with tongue cancer recurrence in young adults, whole exome sequencing of the primary tumor, recurrence, and whole blood samples from young patients with tongue cancer was performed. A frameshift mutation in the TP53 gene was detected in the primary tumor and recurrence tumor tissue. A mutation in the EPHB6 gene was detected in the recurrence and was absent in the primary tumor.
View Article and Find Full Text PDFArticle Synopsis
- - As human activities increase, more heavy metals like chromium (Cr) are being released into wetlands and estuaries, where they stick to sediments and can later be re-released, leading to pollution.
- - Experiments showed that under different flow conditions, concentrations of particulate and dissolved Cr initially rise and later stabilize, especially with vegetation present, impacting how Cr is released from sediments.
- - The Elovich equation was the best model for predicting Cr release from sediments, and when adjusted for vegetation, it significantly improved accuracy, offering valuable insights for managing heavy metal pollution in aquatic ecosystems.
Article Synopsis
- Pollution from heavy metals in estuaries like the Yangtze River Estuary (YRE) poses risks to aquatic ecosystems and public health, particularly highlighted by high levels of arsenic (As) and cadmium (Cd).
- Field studies in 2021 showed that zinc (Zn) and arsenic (As) had the highest concentrations in water, while sediment analysis revealed similar trends, with Cd contributing significantly to ecological risks.
- A modified artificial neural network model was developed to predict heavy metal pollution more accurately, achieving a 95.1% accuracy rate, which can help in assessing and preventing future pollution in estuarine environments.