Results 131 to 140 of about 702,342 (267)

Persistently Increased Expression of PKMzeta and Unbiased Gene Expression Profiles Identify Hippocampal Molecular Traces of a Long‐Term Active Place Avoidance Memory and “Shadow” Proteins

open access: yesAdvanced Science, EarlyView.
Protein complexes like KIBRA‐PKMζ are crucial for maintaining memories, forming month‐long protein traces in memory‐tagged neurons, but conventional RNA‐seq analysis fails to detect their transcript changes, leaving memory molecules undetected in the shadows of abundantly‐expressed genes.
Jiyeon Han   +10 more
wiley   +1 more source

Implementation of a hospice community service redesign: Qualitative research identifying lessons learned. [PDF]

open access: yesPalliat Care Soc Pract
Sugar K   +7 more
europepmc   +1 more source

Rapid and Direct Detection of Methamphetamine in Biofluids using a MXene‐Enabled Electrochemical Sensor

open access: yesAdvanced Science, EarlyView.
A MXene‐enhanced electrochemical sensor enables the rapid and direct detection of methamphetamine. Molecular simulations reveal that specific MXene surface functional groups act as key signal amplifiers by facilitating interfacial interactions. The sensor demonstrates high sensitivity and robust performance in complex biological matrices.
Ri Wang   +7 more
wiley   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

open access: yesAdvanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu   +4 more
wiley   +1 more source

Automatically Defining Protein Words for Diverse Functional Predictions Based on Attention Analysis of a Protein Language Model

open access: yesAdvanced Science, EarlyView.
Understanding protein sequence–function relationships remains challenging due to poorly defined motifs and limited residue‐level annotations. An annotation‐agnostic framework is introduced that segments protein sequences into “protein words” using attention patterns from protein language models.
Hedi Chen   +9 more
wiley   +1 more source

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