A new, but old, nucleoside analog: the first synthesis of 1-deaza-2′-deoxyguanosine and its properties as a nucleoside and as oligodeoxynucleotides

The first synthesis of 5-amino-3-(2′-deoxy-β-d-ribofuranosyl)imidazo[4,5-b]pyridin-7-one (1-deaza-2′-deoxyguanosine) is described. The compound was converted from the known AICA-deoxyriboside. The tautomeric structure of the base moiety was determined by theoretical calculation to be a hydroxyl form. Although the analog was found to be labile to acidic conditions, 1-deaza-2′-deoxyguanosine was successfully converted into a phosphoramidite derivative, which was incorporated into oligodeoxynucleotides by the standard phosphoramidite method. Thermal stabilities of oligodeoxynucleotides containing 1-deaza-2′-deoxyguanosine were investigated by thermal denaturing experiments. Also, a triphosphate analog of 1-deaza-2′-deoxyguanosine was synthesized for polymerase extension reactions. Single nucleotide insertion reactions using a template containing 1-deaza-2′-deoxyguanosine, as well as 1-deaza-2′-deoxyguanosine triphosphate, were performed using the Klenow fragment (exonuclease minus) polymerase and other polymerases. No hydrogen bonded base pairs, even a 1-deaza-2′-deoxyguanosine:cytidine base pair, were indicated by thermal denaturing studies. However, though less selective and less effective than the natural guanosine counterpart, the polymerase extension reactions suggested the formation of a base pair of 1-deaza-2′-deoxyguanosine with cytidine during the insertion reactions

Crystallization and preliminary X-ray analysis of ZHE1, a hatching enzyme from the zebrafish Danio rerio

The hatching enzyme of zebrafish, ZHE1, was expressed, purified and crystallized using the hanging-drop vapour-diffusion method. The crystal belonged to space group P212121 and diffracted X-rays to a resolution of 1.14 Å

Deep learning predicts the 1-year prognosis of pancreatic cancer patients using positive peritoneal washing cytology

Abstract Peritoneal washing cytology (CY) in patients with pancreatic cancer is mainly used for staging; however, it may also be used to evaluate the intraperitoneal status to predict a more accurate prognosis. Here, we investigated the potential of deep learning of CY specimen images for predicting the 1-year prognosis of pancreatic cancer in CY-positive patients. CY specimens from 88 patients with prognostic information were retrospectively analyzed. CY specimens scanned by the whole slide imaging device were segmented and subjected to deep learning with a Vision Transformer (ViT) and a Convolutional Neural Network (CNN). The results indicated that ViT and CNN predicted the 1-year prognosis from scanned images with accuracies of 0.8056 and 0.8009 in the area under the curve of the receiver operating characteristic curves, respectively. Patients predicted to survive 1 year or more by ViT showed significantly longer survivals by Kaplan–Meier analyses. The cell nuclei found to have a negative prognostic impact by ViT appeared to be neutrophils. Our results indicate that AI-mediated analysis of CY specimens can successfully predict the 1-year prognosis of patients with pancreatic cancer positive for CY. Intraperitoneal neutrophils may be a novel prognostic marker and therapeutic target for CY-positive patients with pancreatic cancer