Results 231 to 240 of about 5,379,261 (318)

Systematic Benchmarking of a Noise‐Tolerant Conductive Hydrogel Electrode for Epidermal Bioelectronics

Advanced Science, EarlyView.
General schematic of the approach. Abstract Conventional Silver/Silver Chloride (Ag/AgCl) electrodes remain the clinical standard for electrophysiological monitoring but are hindered by poor skin conformity, mechanical rigidity, and signal degradation, particularly under motion or sweat.
Nazmi Alsaafeen, Ioannis Ziogas, Shirina Alsaedi, Mouza Alshehhi, Shahd Almheiri, Adil Rehman, Khulood Al Shehhi, Hani Saleh, Ahsan Khandoker, Charalampos Pitsalidis, Antoun Khawaja, Anna‐Maria Pappa   +11 more
wiley   +1 more source

Integrating Digital Health into School Nursing for Food Allergy Management: A Systematic Review. [PDF]

Children (Basel)
Nocerino R, Lotito F, Montella E, Berni Canani R.   +3 more
europepmc   +1 more source

cDC1 Subtype‐Specific In Vivo Targeting of Liposomes

Advanced Science, EarlyView.
Dendritic cells, particularly the cDC1 subtype, offer a promising target for drug delivery via liposomes due to their pivotal role in immune regulation, allowing for amplified therapeutic responses. Herein, we show an integration of physicochemical characterization and cell experiments to achieve effective in vivo cDC1 targeting through anti‐CLEC9A ...
Maximilian Schaaf, Michael Fichter, Lin Jian, Felicia Schön, Carina Jung, Paul Schneider, Kai Speth, Ana Mateos‐Maroto, Volker Mailänder, Kaloian Koynov, Svenja Morsbach, Katharina Landfester   +11 more
wiley   +1 more source

Digital competence for sustainable education of pre-service teachers: a systematic literature review (2014-2024). [PDF]

Front Psychol
Zhang L, Yang C, Zheng Y.
europepmc   +1 more source

Pathomics Signature for Prognosis and CA19‐9 Interception in Pancreatic Ductal Adenocarcinoma: A Real‐Life, Multi‐Center Study

Advanced Science, EarlyView.
This study develops a deep learning‐based pathomics model to predict survival outcomes in pancreatic cancer patients. The CrossFormer architecture analyzes routine H&E‐stained tissue slides, identifying key prognostic features including stromal patterns, cellular characteristics, and immune infiltration.
Qiangda Chen, Zhihang Xu, Yiping Zou, Zhenlai Jiang, Yecheng Li, Taochen He, Hanlin Yin, Jiali Li, Yanfei An, Jiande Han, Yuqi Xie, Wei Gan, Yaolin Xu, Wenquan Wang, Junyi He, Haibo Wang, Wenchuan Wu, Zhenyu Ye, Wenhui Lou, Jihui Hao, Liang Liu, Jun Yu, Ning Pu   +22 more
wiley   +1 more source

Patient Self-Recorded Digital Otoscopy in Otology Diagnostics. [PDF]

Laryngoscope Investig Otolaryngol
Appelberg E, Viitasalo S, Sinkkonen ST.
europepmc   +1 more source

From Sample to Mixed Reality: A Translational 3D MALDI Imaging Platform for Advanced 3D Spatial Omics Analysis of 3D Cell Culture Disease Models

Advanced Science, EarlyView.
A comprehensive technology platform enables high‐fidelity, volumetric MALDI imaging of 3D cell cultures by integrating custom embedding molds, a semi‐automated computational framework for 3D reconstruction, voxel‐instead of pixel‐based biomarker discovery, and immersive mixed reality data exploration.
Stefania Alexandra Iakab, Jonas Cordes, Thomas Enzlein, Florian Keller, Kevin Kastner, Theresa Mulholland, Björn Christian Fröhlich, Lars Gruber, James Lucas Cairns, Stefan Schmidt, Mathias Hafner, Richard Schneider, Johannes Betge, Frank Fischer, Julian Reichwald, Rüdiger Rudolf, Carsten Hopf   +16 more
wiley   +1 more source

S3RL: Enhancing Spatial Single‐Cell Transcriptomics With Separable Representation Learning

Advanced Science, EarlyView.
Separable Spatial Representation Learning (S3RL) is introduced to enhance the reconstruction of spatial transcriptomic landscapes by disentangling spatial structure and gene expression semantics. By integrating multimodal inputs with graph‐based representation learning and hyperspherical prototype modeling, S3RL enables high‐fidelity spatial domain ...
Laiyi Fu, Penglei Wang, Gaoyuan Xu, Jitao Lu, Qinke Peng, Danyang Wu, Hequan Sun   +6 more
wiley   +1 more source

Cohort‐Scale Spatial Autocorrelation for Tumor Prediction in Mid‐Infrared Pathology and Spatial Biomarker Discovery Using MALDI Imaging Lipidomics

Advanced Science, EarlyView.
Computational annotation of various tissue types in heterogeneous samples such as colorectal cancer liver metastasis (CRLM) using spatial autocorrelation analysis on non‐destructive mid‐infrared (MIR) imaging data enabled correlative multimodal mass spectrometry imaging (MSI) for spatial investigation of lipid tumor marker candidates. The method can be
Miriam F. Rittel, Nikolas Ebert, Denis Abu Sammour, Sebastian Graf, Björn C. Fröhlich, Emrullah Birgin, Shad A. Mohammed, Nuh N. Rahbari, Axel Wellmann, Oliver Wasenmüller, Cleo‐Aron Weis, Stefan Schmidt, Carsten Hopf   +12 more
wiley   +1 more source