Results 181 to 190 of about 223,659 (276)

Global Nitrogen Deposition Promotes Carbon Sink Formation in Terrestrial Ecosystems

Advanced Science, EarlyView.
Nitrogen deposition alleviates ecosystem N limitation and enhances carbon sinks. Using 829 observations, we show 36% of deposited N is retained globally (39.15 Tg N yr−1), with distinct NHx and NOy contributions. This retention drives a terrestrial C sink of 0.88 Pg C yr−1 (25.48%), highlighting the importance of pool‐specific C:N stoichiometry ...
Lei Li, Mingyu Xie, Nan Jia, Li‐Dong Mo, Qiang Yu, Fanjiang Zeng, Xiangyi Li   +6 more
wiley   +1 more source

Propagation of solitary waves for hydrodynamical nonlinear complex model in a fractional derivative setting. [PDF]

Sci Rep
Bilal M, Alawaideh YM, Rehman SU, Yousif MA, Baleanu D, Mohammed PO, Abdeljawad T.   +6 more
europepmc   +1 more source

Integrating Spatial Proteogenomics in Cancer Research

Advanced Science, EarlyView.
Xx xx. ABSTRACT Background: Spatial proteogenomics marks a paradigm shift in oncology by integrating molecular analysis with spatial information from both spatial proteomics and other data modalities (e.g., spatial transcriptomics), thereby unveiling tumor heterogeneity and dynamic changes in the microenvironment.
Yida Wang, Yang Wu, Feng Zhang, Parthiban Periasamy, Haiyue You, Denise Goh, Rachel Elizabeth Ann Fincham, Xin Ning, Danping Wu, Lu Liu, Ying Jiang, Zhiwen Qian, Joe Yeong, Yan Zhang   +13 more
wiley   +1 more source

Understanding phonon polaritons and epsilon-near-zero modes in sapphire nanocones across the broad Reststrahlen band (385-1050 cm^-1). [PDF]

RSC Adv
Nourbakhsh M, Arledge KE, Whiteside VR, Ma J, Tischler JG, Weng B.   +5 more
europepmc   +1 more source

SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics

Advanced Science, EarlyView.
ABSTRACT Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial
Hongyan Cao, Gaiqin Liu, Jingyi Xia, Runle Chen, Tong Wang, Xiaoling Yang, Ruiling Fang, Yanhong Luo, Ping Zeng, Hongmei Yu, Yanbo Zhang, Yuehua Cui   +11 more
wiley   +1 more source

Artificial neural network paradigm of magneto-thermal behavior in tangent hyperbolic hybrid-nanofluid flow. [PDF]

Sci Rep
Athar T, Qureshi H, Muhammad T.
europepmc   +1 more source

Persistently Increased Expression of PKMzeta and Unbiased Gene Expression Profiles Identify Hippocampal Molecular Traces of a Long‐Term Active Place Avoidance Memory and “Shadow” Proteins

Advanced Science, EarlyView.
Protein complexes like KIBRA‐PKMζ are crucial for maintaining memories, forming month‐long protein traces in memory‐tagged neurons, but conventional RNA‐seq analysis fails to detect their transcript changes, leaving memory molecules undetected in the shadows of abundantly‐expressed genes.
Jiyeon Han, Alejandro Grau‐Perales, Rayna M. Harris, Edith Lesburguères, Hsin‐Yi Kao, Asit Pal, Juan Marcos Alarcon, Todd C. Sacktor, Stefano Martiniani, Hans A. Hofmann, André A. Fenton   +10 more
wiley   +1 more source

Multilayered hyperbolic Au/TiO₂ nanostructures for enhancing the nonlinear response around the epsilon-near-zero point. [PDF]

Beilstein J Nanotechnol
Araiza-Sixtos FA, Gomez-Robles M, Salas-Montiel R, Rangel-Rojo R.   +3 more
europepmc   +1 more source

Rapid Proteome‐Wide Discovery of Protein–Protein Interactions With ppIRIS

Advanced Science, EarlyView.
ppIRIS is a lightweight deep learning framework for proteome‐wide protein–protein interaction prediction directly from sequence. By fusing evolutionary and structural embeddings with a regularized Siamese architecture, ppIRIS achieves state‐of‐the‐art accuracy across species, enables minute‐scale screening, and reveals biologically validated bacterial ...
Luiz Felipe Piochi, Di Tang, Johan Malmström, Yasaman Karami, Hamed Khakzad   +4 more
wiley   +1 more source

Triaging Casual From Critical-Leveraging Machine Learning to Detect Self-Harm and Suicide Risks for Youth on Social Media: Algorithm Development and Validation Study. [PDF]

JMIR Ment Health
Qadir S, Alsoubai A, Park JK, Ali NS, Choudhury M, Wisniewski P.   +5 more
europepmc   +1 more source