Results 241 to 250 of about 845,850 (303)

Wearable Morphology‐Adaptive in‐Ear Device With Active Cleansing Capability for Multimodal Health Monitoring

Advanced Materials, EarlyView.
We present SCIENCE, an in‐ear multimodal physiological monitor featuring two key innovations. Water‐triggered morphological expansion (a 2‐mm cylinder to a 9‐mm spindle) achieves conformal adaptation across complex canal geometries. Simultaneously, active biofouling mitigation disrupts cerumen barriers, reducing sensor‐skin impedance by 20%.
Shuyun Zhuo, Zihuan Wu, Anan Zhang, Shideh Kabiri Ameri   +3 more
wiley   +1 more source

An enhanced framework for knowledge graph embedding based on negative sample analogical reasoning. [PDF]

Sci Rep
Li H, Tao Y, Chen D, Tang Y, Wang J, Xue L.   +5 more
europepmc   +1 more source

Lab‐in‐a‐Tube System Integrating Hierarchically Wrinkled Electrodes and DNAzyme‐Functionalized Beads for Diagnosis of Clostridioides difficile Infection

Advanced Materials, EarlyView.
The point‐of‐care diagnosis of Clostridioides difficile infection remains challenging due to reliance on slow culture and amplification‐based methods. A lab‐in‐a‐tube electrochemical biosensor integrating DNAzymes, antifouling magnetic beads, and a hierarchically structured flow cell enables amplification‐ and culture‐free detection directly in stool ...
Survanshu Saxena, Soyeon Lee, Youngeun Choi, Jonathan L'Heureux‐Hache, Jiaying Liu, Sadman Sakib, Sara M. Imani, Marek Smieja, Yingfu Li, Todd Hoare, Leyla Soleymani   +10 more
wiley   +1 more source

getDNB: identifying dynamic network biomarkers of hepatocellular carcinoma from time-varying gene regulations utilizing graph embedding techniques for anomaly detection. [PDF]

Bioinformatics
Wang T, Liu ZP.
europepmc   +1 more source

Photoacoustic Nanotagging for In Vivo Tracking and Optimization of Macrophage Immunotherapy in Solid Tumors

Advanced Materials, EarlyView.
Macrophage‐based immunotherapy for solid tumors is limited by poor tracking of cell localization and persistence. This study introduces nanotagged macrophages enabling near‐infrared photoacoustic imaging for real‐time monitoring. IFNγ‐conjugated tags enhance antitumor polarization without harming viability.
Seoyoon Song, Melissa Cadena, Myeongsoo Kim, Euisuk Chung, Jeungyoon Lee, Zlata Brushevich, Seonghun Shin, Paul S. Pelkowski, Stanislav Y. Emelianov   +8 more
wiley   +1 more source

MGMA-PPIS: Predicting the protein-protein interaction site with multiview graph embedding and multiscale attention fusion. [PDF]

Gigascience
Han Y, Zhang SW, Zhang QQ, Shi MH.
europepmc   +1 more source

Inverse Design of Nanoparticulate Materials

Advanced Materials, EarlyView.
Inverse design shifts nanomaterial development from empirical trial‐and‐error to predictive model‐driven strategies. It can rely on knowledge‐based, data‐based, or hybrid process and property functions. This perspective article provides a practical framework for applying inverse design based on instructive examples. It discusses which modeling approach
Nabi Etienne Traoré, Annika Mauch, Michelle Berthold, Lukas Pflug, Wolfgang Peukert, Nicolas Vogel   +5 more
wiley   +1 more source

Drug-target interaction prediction using knowledge graph embedding. [PDF]

iScience
Li N, Yang Z, Wang J, Lin H.
europepmc   +1 more source

Microgels Enable iPSCs to Assemble, Expand, and Differentiate Into Organoids—From Sizable to High‐Throughput

Advanced Materials, EarlyView.
A chemically defined PEG‐based microgel platform enables scalable, reproducible production of three‐dimensional microgel‐iPSC constructs in multiple sizes. The system is compatible with high‐throughput automation and supports human iPSC expansion and differentiation within a single construct, including directed differentiation into cardiac organoids ...
Laura Klasen, Matthias Mork, Ramin Nasehi, Vasudha Turuvekere Krishnamurthy, Kira Zeevaert, Aaron Babendreyer, Jacopo Di Russo, Wolfgang Wagner, Laura De Laporte   +8 more
wiley   +1 more source

Identifying compound-protein interactions with knowledge graph embedding of perturbation transcriptomics. [PDF]

Cell Genom
Ni S, Kong X, Zhang Y, Chen Z, Wang Z, Fu Z, Huo R, Tong X, Qu N, Wu X, Wang K, Zhang W, Zhang R, Zhang Z, Shi J, Wang Y, Yang R, Li X, Zhang S, Zheng M.   +19 more
europepmc   +1 more source