Publications by authors named "M Nakazono"
Background: The JAVELIN Bladder 100 trial demonstrated improved overall survival (OS) with maintenance avelumab in patients with locally advanced or metastatic urothelial carcinoma UC (la/mUC) who achieved disease control following first-line platinum-based chemotherapy (1 L-PBC). However, real-world data on eligibility, utilization, and outcomes of maintenance avelumab therapy remain limited.
Methods: This retrospective study included patients with la/mUC who received 1 L-PBC.
Formation of Apoplastic Barriers to Radial O₂ Loss in Rice Roots: Effects of Low-O₂ and High-Fe Conditions, and the Roles of Suberin, Glycerol Esters, and Iron Plaques.
Plant Cell Environ
December 2024
Lack of O and high concentrations of iron (Fe) are common in flooded soils where Rice (Oryza sativa L.) is cultivated. We tested the hypothesis that growing in stagnant or high Fe conditions might induce the formation of apoplastic barriers in roots with different properties and chemical compositions.
View Article and Find Full Text PDFBackground/aim: Post-gastrectomy lean body mass (LBM) decrease has a significant negative impact on postoperative survival in patients with cancer. This study investigated the effect of intake of at least one-third of the daily protein requirement at breakfast on the maintenance of LBM in patients during the first month post-gastrectomy.
Patients And Methods: Among patients with gastric cancer who underwent curative distal gastrectomy between April 2011 and December 2018, without adjuvant chemotherapy, we evaluated 401 patients who had consumed more than the daily protein requirement in the first month postoperatively, using the FFQW82 nutrition intake questionnaire.
Article Synopsis
- High-throughput phenotyping can streamline breeding cycles and reduce costs, focusing on biomass-related traits in soybean using UAV remote sensing and deep learning.
- In a 2018 field experiment with 198 soybean accessions, a convolutional neural network (CNN) was used to accurately estimate traits like dry weight and plant height from UAV-collected data.
- The study showed that deep learning could identify strong correlations between input data and phenotypic traits, highlighting the potential use of these insights in improving breeding practices.