Results 211 to 220 of about 1,867,604 (284)

Spatial interrelationships between flood risk and ecosystem services in the Beijing-Tianjin-Hebei region at multiple scales. [PDF]

Sci Rep
Xi MH, Zhang HX, Yao P, Li UM, Tang Y, Huang LS, Yao LL, Fan HY.   +7 more
europepmc   +1 more source

Pre‐Regenerative Endothelial Cells Empowered by Antler Blood Exosomes Orchestrate Peripheral Nerve Repair

Advanced Science, EarlyView.
The pre‐regenerative vascular niche (PVN) is essential for nerve repair, yet its endothelial blueprint remains unclear. We identified angiogenic ECs (AECs) as the dominant pre‐regenerative subset and found that antler blood–derived exosomes (AB‐EXO) promote repair via IMP3.
Jinsheng Huang, Qiang Chen, Aihua Jin, Xiaoqi Yang, Hui Zhou, Weiquan Gong, Jin Cheng, Jun Dai, Minjin Wang, Meihua Piao, Yuanyi Wang, Nan Zhou   +11 more
wiley   +1 more source

Shaping light in 3D for direct asymmetric photochemistry: a 1000-fold enantioselectivity enhancement. [PDF]

Nat Commun
Ordóñez A, García González D, Vindel-Zandbergen P, Ayuso D.   +3 more
europepmc   +1 more source

The Importance of Metal‐Organic Framework Linker Atoms for CO2 Reduction: A DFT Study

Advanced Science, EarlyView.
Using DFT, we examine the role of linker atoms in CO2 reduction on copper‐based metal organic frameworks (Cu MOFs). Our calculations reveal that linker atoms may serve as both CO2 and H‐shuttling sites and suggest linker electrostatics as a descriptor for linker activity. ABSTRACT Although the metal within the secondary building unit of a metal‐organic
Ugochukwu Nwosu, Samira Siahrostami
wiley   +1 more source

Adapting and implementing health systems guidelines: learning lessons from countries. [PDF]

Health Res Policy Syst
Zeitouny S, Fahim C, Adewuya AO, Adjorlolo S, Mwamba C, Velez CM, Straus SE, Marten R.   +7 more
europepmc   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

Low Latency Global Carbon Budget Reveals Late 2024 Carbon Losses and Contrasting Early 2025 Land Sink Recovery Signals. [PDF]

Adv Sci (Weinh)
Ke P, Ciais P, Yao Y, Sitch S, Li W, Du X, Gui X, Poulter B, Colligan T, van der Woude AM, Hooghiem J, Peters W, Liu Z, Deng Z, Jin Z, Tian X, Wang Y, Liu J, Pandey S, O'Dell C, Bian J, Miller J, Lan X, Goncalves De Souza J, O'Sullivan M, Friedlingstein P, Alléon J, Xi Y, Goll DS, Zhu L, van der Werf GR, Piao S, Chevallier F.   +32 more
europepmc   +1 more source

Integrative Multi‐Omics Analysis Reveals a Mitochondrial–Immune Axis Associated With Neoadjuvant Chemotherapy Response in High‐Grade Serous Ovarian Cancer

Advanced Science, EarlyView.
Integrative multi‐omics analysis delineates a mitochondrial–immune axis governing neoadjuvant chemotherapy response in high‐grade serous ovarian cancer. Immune‐active tumors exhibit enhanced B‐cell infiltration and favorable sensitivity, whereas metabolically rewired tumors display oxidative phosphorylation dependency and resistance.
Wei Jiang, Yi Wang, Xiaohang Lu, Qianlan Yao, Libing Xiang, Xu Cai, Xiaoyu Tu, Shaoxian Tang, Ying Xu, Yufan Cheng, Liming Shen, Huijuan Yang   +11 more
wiley   +1 more source

Fourier Evaluation of Tracings and Acidosis in Labor (FETAL) Framework: An In-Silico Evaluation of a Spectral-Divergence Method. [PDF]

Cureus
Balayla J.
europepmc   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source