Biology subjects

Kuroda, K.

Publications and source records attributed to Kuroda, K..

3 recordsLinked to original sources

bioRxiv2022

Collaborative workflow between pathologists and deep learning for evaluation of tumor cellularity in lung adenocarcinoma

Owing to the high demand for molecular testing, the reporting of tumor cellularity in cancer samples has become a mandatory task for pathologists. However, the pathological estimation of tumor cellularity is often inaccurate. We developed a collaborative workflow between pathologists and artificial intelligence (AI) models to evaluate tumor cellularity in lung cancer samples and prospectively applied it to routine practice. We also developed a quantitative model that we validated and tested on retrospectively analyzed cases and ran the model prospectively in a collaborative workflow where pathologists could access the AI results and apply adjustments (Adjusted-Score). The Adjusted-Scores were validated by comparing them with the ground truth established by manual annotation of hematoxylin-eosin slides with reference to immunostains with thyroid transcription factor-1 and napsin A. For training, validation, retrospective testing, and prospective application of the model, we used 40, 10, 50, and 151 whole slide images, respectively. The sensitivity and specificity of tumor segmentation were 97% and 87%, and the accuracy of nuclei recognition was 99%. Pathologists altered the initial scores in 87% of the cases after referring to the AI results and found that the scores became more precise after collaborating with AI. For validation of Adjusted-Score, we found the Adjusted-Score was significantly closer to the ground truth than non-AI-aided estimates (p<0.05). Thus, an AI-based model was successfully implemented into the routine practice of pathological investigations. The proposed model for tumor cell counting efficiently supported the pathologists to improve the prediction of tumor cellularity for genetic tests.

pathology↗

bioRxiv2022

Identification of domestic cat hepadnavirus from a cat blood sample in Japan

The hepatitis B virus (Hepadnaviridae) induces chronic hepatitis and hepatic cancer in humans. A novel domestic cat hepadnavirus (DCH) was recently identified in several countries, however, the DCH infection status of cats in Japan is unknown. Therefore, we investigated the DCH infection rate of 139 cat samples collected in Japan. We identified one positive blood sample (0.78%) from a 17-year-old female cat with chronically elevated alanine aminotransferase. Phylogenetic analysis demonstrated that the DCH strain identified in this study is genetically distinct from strains in other countries. Further investigations are required to elucidate the evolution of DCH and the impact of DCH infection on hepatic diseases in domestic cats.

microbiology↗

bioRxiv2020

Towards designing globular antimicrobial peptide mimics: role of polar functional groups in biomimetic ternary antimicrobial polymers

Using atomistic molecular dynamics simulations, we study the interaction of ternary methacrylate polymers, composed of charged cationic, hydrophobic and neutral polar groups, with model bacterial membrane. Our simulation data shows that the random ternary polymers can penetrate deep into the membrane interior and partitioning of even a single polymer has a pronounced effect on the membrane structure. Lipid reorganization, on polymer binding, shows a strong affinity of the ternary polymer for anionic POPG lipids and the same is compared with the control case of binary polymers (only cationic and hydrophobic groups). While binary polymers exhibit strong propensity of acquired amphiphilic conformations upon membrane insertion, our results strongly suggest that such amphiphilic conformations are absent in the case of random ternary polymers. The ternary polymers adopt a more folded conformation, staying aligned in the direction of the membrane normal and subsequently penetrating deeper into the membrane interior suggesting a novel membrane partitioning mechanism without amphiphilic conformations. Finally, we also examine the interactions of ternary polymer aggregates with model bacterial membranes, which show that replacing some of the hydrophobic groups by polar groups leads to weakly held ternary aggregates enabling them to undergo rapid partitioning and insertion into membrane interior. Our work thus underscores the role of inclusion of polar groups into the framework of traditional binary biomimetic antimicrobial polymers and suggests different mode of partitioning into bacterial membranes, mimicking antimicrobial mechanism of globular antimicrobial peptides like Defensin.

biophysics↗