Results 151 to 160 of about 1,449,650 (280)
18F‐FGln PET/CT imaging serves as a marker of Gln uptake in hepatocellular carcinoma. Tumors with high Gln uptake drive Treg‐mediated immunosuppression and immune evasion during antitumor immunotherapy. Conversely, tumors with low Gln uptake maintain sufficient Gln in the TME, suppressing Tregs and enabling cytotoxic T cells to inhibit tumor growth ...
Yi Liu +8 more
wiley +1 more source
GWMAC- A TDMA Based MAC Protocol for a Glacial Sensor Network
Wireless sensor networks demand the need to design practical and robust communication protocols to meet the application specifications. Our research focuses on designing and implementing an environmental sensor network to be used for sub-glacial study ...
Martinez, Kirk +3 more
core +1 more source
Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali +3 more
wiley +1 more source
This study investigates the feasibility of scaling up Prussian White (PW)‐based cathode manufacturing at a pilot scale. Through careful PW dehydration combined with optimized aqueous processing, we report the stepwise development of industrially relevant 1 Ah pouch cells and evaluate their performance under various conditions.
Faduma M. Maddar +7 more
wiley +1 more source
The Nature of Cell‐Penetrating Poly(disulfide)s
The mode of action of cell‐penetrating poly(disulfide)s (CPDs) is elucidated to understand thiol‐mediated uptake (TMU) in general and guide future efforts to control cellular entry for chemicals delivery and pathogen defense. ABSTRACT Cell‐penetrating poly(disulfide)s (CPDs) are the most popular thiol‐mediated uptake (TMU) tools for delivering attached
Saidbakhrom Saidjalolov +7 more
wiley +2 more sources
Calendering‐Dependent Electrochemical and Cost‐Energy Tradeoffs in Layered – Olivine Blend Cathodes
Blends comprised of LiNi0.9Mn0.05Co0.05O2 (NMC) and LiMn0.7Fe0.3PO4 (LMFP) are investigated to assess the performance – cost tradeoffs. Their rate‐capability benefit is retained only under uncalendered‐to‐moderately calendered states. Although blends reduce voltage decay and improve energy retention, they do not deliver measureable improvement in ...
Huyen T. K. Nguyen, Arumugam Manthiram
wiley +1 more source
Advancing European Plant Variety Registration: Data‐Driven Insights and Stakeholder Perspectives
ABSTRACT Efficient plant variety registration is crucial for fostering innovation in the European Union, yet the current regulatory framework is complex and faces calls for reform. This study provides data‐driven evidence to inform the ongoing legislative debate by employing a mixed‐methods approach.
Sergio Urioste Daza +2 more
wiley +1 more source
M2BPGi reflects background liver fibrosis and hepatic functional impairment. PET SUVmax reflects tumor metabolic aggressiveness. Their combination identifies a dual‐high subgroup with the poorest recurrence‐free and overall survival. ABSTRACT Aim To evaluate the prognostic significance of preoperative Mac‐2 binding protein glycosylation isomer (M2BPGi)
Kojiro Shirabe +8 more
wiley +1 more source
Steatotic HCC can be diagnosed by MRI and forms a pro‐tumor immune microenvironment with high expression of PD‐L1, M2 polarization of macrophages and activation of CAFs, which may be a good target for combined immunotherapy. Abstract Background and Aims Immunotherapy has become the standard‐of‐care treatment for hepatocellular carcinoma (HCC), but its ...
Hiroki Murai +29 more
wiley +1 more source
A Scalable and Resource‐Efficient Pipelined p‐Computer for Probabilistic Ising Machines
(a) Block diagram of the portfolio optimization problem: given M assets, the goal is to determine the optimal weights w that maximize the expected return (based on the mean historical assets return u), while minimizing the risk, quantified by the assets covariance matrix S.
Deborah Volpe +9 more
wiley +1 more source

