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Editorial: new Editor-in-Chief and the 360th anniversary of .
Philos Trans A Math Phys Eng Sci
January 2025
Department of Chemistry, University College London, 20 Gordon Street, London WC1HOAJ , UK.
Retraction notice to "Photocatalytic degradation of organic synthetic dyes and textile dyeing waste water by Al and F co-doped TiO nanoparticles" [Environ. Res. 206 (2022) 112492].
Environ Res
January 2025
Grassland and Forages Division, National Institute of Animal Science, Rural Development Administration, Cheonan, 31000, South Korea.
This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/locate/withdrawalpolicy).
View Article and Find Full Text PDFRetraction notice to "UV light assisted photocatalytic degradation of textile waste water by MgZnFeO synthesized by combustion method and in-vitro antimicrobial activities" [Environ. Res. 204 (2022) 111917].
Environ Res
January 2025
Department of Botany and Microbiology, College of Science, King Saud University, P.O. 2455, Riyadh, 11451, Saudi Arabia.
This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/locate/withdrawalpolicy).
View Article and Find Full Text PDFVariations in linear energy transfer distributions within a European proton therapy planning comparison of paediatric posterior fossa tumours.
Phys Imaging Radiat Oncol
October 2024
Aarhus University Hospital, Danish Centre for Particle Therapy, Aarhus N, Denmark.
Background And Purpose: Radiotherapy for paediatric posterior fossa tumours may cause complications in the brainstem and upper spinal cord due to high doses. With proton therapy (PT) this risk may increase due to higher relative biological effectiveness (RBE) from elevated linear energy transfer (LET). This study assesses variations in LET in the brainstem and spinal cord in proton treatment plans from European centres.
View Article and Find Full Text PDFtransCAE: Enhancing cell type annotation in single-cell RNA-seq data with transfer learning and convolutional autoencoder.
J Mol Biol
January 2025
School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, 100083, China. Electronic address:
Single-cell RNA sequencing (scRNA-seq) analysis offers tremendous potential for addressing various biological questions, with one key application being the annotation of query datasets with unknown cell types using well-annotated external reference datasets. However, the performance of existing supervised or semi-supervised methods largely depends on the quality of source data. Furthermore, these methods often struggle with the batch effects arising from different platforms when handling multiple reference or query datasets, making precise annotation challenging.
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