Results 131 to 140 of about 289,055 (256)

Earliest geometries: A cognitive investigation of Howiesons Poort engraved ostrich eggshells. [PDF]

PLoS One
Decembrini V, Ottaviano L, Cartolano M, Spinapolice EE, Ferrara S.   +4 more
europepmc   +1 more source

Mapping the Cerebral Organoid Landscape: A Systematic Review of Preclinical 3D Models in Neuroscience

Advanced Healthcare Materials, EarlyView.
Cerebral organoids are transforming brain research, yet the field remains fragmented. This comprehensive systematic review maps 738 studies published between 2014 and 2024 to uncover trends, gaps, and opportunities across neuroscience. Introducing OrganoidMap—an interactive, open‐access platform to explore and compare models—this work enables ...
Anna Wolfram, Vanessa Arnold, Maik Wolfram‐Schauerte, Anastassiya Moskalchuk, Caroline Trust, Marie Vontz, Mona Scheurenbrand, Vijayasarathy Sampath‐Kumar, Sogand Ahari, Carlos Romero‐Nieto, Lisa Sevenich   +10 more
wiley   +1 more source

PSLite Online: A Portable, Modern Web Application to Analyze Top-Down Mass Spectrometry Fragmentation Data. [PDF]

J Mass Spectrom
Fellers RT, Greer JB, Early BP, Hollas MAR, Robey MT, Kelleher NL, Durbin KR.   +6 more
europepmc   +1 more source

Polyimide‐Linked Hexaazatriphenylene‐Based Porous Organic Polymer with Multiple Redox‐Active Sites as a High‐Capacity Organic Cathode for Lithium‐Ion Batteries

Advanced Materials, EarlyView.
A high‐capacity polyimide‐linked porous organic polymer (HAT‐PTO) incorporating numerous redox‐active centers is synthesized via a hydrothermal reaction, delivering a high theoretical capacity of 484 mAh g−1. In situ hybridization with carboxyl‐functionalized multiwalled carbon nanotubes enhances conductivity and stability, achieving 397 mAh g−1 at C ...
Arindam Mal, Jonathan Caroni, Asia Patriarchi, Olivera Luzanin, Rafael Ramos, Jan Bitenc, Manuel Melle‐Franco, Manuel Souto   +7 more
wiley   +1 more source

Acetylation of H3K115 is associated with fragile nucleosomes at CpG island promoters and active regulatory sites. [PDF]

Elife
Kumar Y, Sengupta D, Friman ET, Illingworth RS, Soleil M, Fan Z, Wang H, Helin K, Gérard M, Bickmore WA.   +9 more
europepmc   +1 more source

Machine Learning‐Informed Nano Co‐Assembly Inhibits Fibroblast Activation Protein and Improves Drug Delivery in Fibrotic Tissue

Advanced Materials, EarlyView.
We present SP‐13786 (SP), a fibroblast activation protein (FAP) inhibitor, as a universal excipient for co‐assembling stable drug nanoparticles (SCAN). Assembly mechanism deciphered by molecular dynamics and explainable machine learning, SCAN attenuate fibrosis‐induced stromal barriers, enhances lesional drug accumulation, and improves therapeutic ...
Zehua Liu, Qiang Long, Yihao Liu, Xiuqiao Sun, Baoding Zhang, Binxin Liao, Weibin Wu, Wangxi Hai, Pei Zhang, Wenhua Lian, Yuewen Zhu, Zheng Wang, Caisheng Wu, Xianming Deng, Hélder A. Santos, Xiaofeng Ye   +15 more
wiley   +1 more source

Single-step integrated minimally invasive static-guided microsurgery for file retrieval from the periapex of mandibular molar. [PDF]

J Conserv Dent Endod
Priya MS, Dakshindas DM, Bhesaniya VK, Dahiwade AP, Warhadpande MM.   +4 more
europepmc   +1 more source

Low‐Dimensional MOF Nanoarchitectonics: Progress in MOF‐2D Material Hybrid Architectures for Energy Conversion and Storage

Advanced Materials, EarlyView.
This review highlights the integration of metal‐organic frameworks (MOFs) and two‐dimensional (2D) materials through dimensional interface engineering. By addressing intrinsic limitations like poor conductivity and agglomeration, these hybrid architectures optimize interfacial charge and mass transport.
Prashant Dubey, Norman C.‐R. Chen, Xiangyang Liu, Yongqi Yin, Keisuke Shirasaki, Kevin C.‐W. Wu, Yingji Zhao, Yusuke Yamauchi   +7 more
wiley   +1 more source

RioCC: Efficient and Accurate Class-Level Code Recommendation Based on Deep Code Clone Detection. [PDF]

Entropy (Basel)
Gao H, Guo C, Yang H.
europepmc   +1 more source

Generative Models for Crystalline Materials

Advanced Materials, EarlyView.
Generative machine learning models are increasingly used in crystalline materials design. This review outlines major generative approaches and assesses their strengths and limitations. It also examines how generative models can be adapted to practical applications, discusses key experimental considerations for evaluating generated structures, and ...
Houssam Metni, Laura Ruple, Lauren N. Walters, Luca Torresi, Jonas Teufel, Henrik Schopmans, Jona Östreicher, Yumeng Zhang, Marlen Neubert, Yuri Koide, Kevin Steiner, Paul Link, Lukas Bär, Mariana Petrova, Gerbrand Ceder, Pascal Friederich   +15 more
wiley   +1 more source