Results 251 to 260 of about 573,942 (348)

Precision Editing of NLRS Improves Effector Recognition for Enhanced Disease Resistance

open access: yesAdvanced Science, EarlyView.
Precision engineering of plant NLR immune receptors enables rational design of enhanced pathogen resistance through mismatched pairing, domain swapping, and targeted mutagenesis. These approaches achieve multi‐fold expansion in recognition breadth while minimizing autoimmunity risks and fitness penalties.
Vinit Kumar   +7 more
wiley   +1 more source

The Neural Network for Sign Language Comprehension. [PDF]

open access: yesLang Linguist Compass
Terhune-Cotter B, Emmorey K.
europepmc   +1 more source

Enhancing Communication Accessibility: UrSL-CNN Approach to Urdu Sign Language Translation for Hearing-Impaired Individuals [PDF]

open access: diamond
Khushal Das   +5 more
openalex   +1 more source

Microglial HVCN1 Deficiency Improves Movement and Survival of SOD1G93A ALS Mice by Enhancing Microglial Migration and Neuroprotection

open access: yesAdvanced Science, EarlyView.
Hydrogen voltage gated channel 1 (HVCN1) is upregulated in microglia of both ALS patients and its mouse model. HVCN1 deficiency enhances microglial migration via suppressing Akt signaling, promotes neurotrophic capacity and motor function, and prolongs survival of the SOD1G93A ALS mice. This study identifies HVCN1 as a novel, promising druggable target
Fan Wang   +16 more
wiley   +1 more source

AUDIO TO SIGN LANGUAGE CONVERSION

open access: bronze
Lisha Kurian   +4 more
openalex   +2 more sources

The Mitochondrial Guardian α‐Amyrin Mitigates Alzheimer's Disease Pathology via Modulation of the DLK‐SARM1‐ULK1 Axis

open access: yesAdvanced Science, EarlyView.
Dietary habits play a key role in chronic diseases, and higher annual consumption of fruit and vegetable may lower risk of dementia. Artificial intelligence predicts the lipid‐like compound α‐Amyrin (αA) from plants with edible peels as a drug candidate against Alzheimer's disease.
Shu‐Qin Cao   +36 more
wiley   +1 more source

CELLama: Foundation Model for Single Cell and Spatial Transcriptomics by Cell Embedding Leveraging Language Model Abilities

open access: yesAdvanced Science, EarlyView.
CELLama is created, a framework that harnesses language models to convert cellular data into “sentences” that represent gene expression and metadata, enabling a universal embedding of cells. Unlike most single‐cell foundation models, CELLama supports scalable analysis and offers flexible applications including spatial transcriptomics.
Jeongbin Park   +7 more
wiley   +1 more source

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