Results 191 to 200 of about 4,443,421 (294)
Isolation and identification of bacterial isolates producing Arginine deiminase from assorted soil environments in Egypt using16S rRNA sequencing technique [PDF]
Mohammed Kassab
openalex +1 more source
Forecasting Root Rot Disease through Predictive Microbial Functional Profiling
Predicting soil‐borne disease moves beyond observation with a framework that elevates microbial functional genes into reliable forecasting biomarkers. By coupling targeted qPCR assays for core stress‐response genes with machine learning, this method detects root rot risks in pre‐symptomatic soils with over 80% accuracy.
Chuan You +11 more
wiley +1 more source
Long-term cropping system and nitrogen management effects on soil properties
Clay Robinson
openalex +2 more sources
This review surveys nanoparticle‐based strategies to enhance adoptive cell therapy, particularly CAR‐T cell approaches, in solid tumor treatment. It describes how nanoparticles can improve tumor immunogenicity and T‐cell infiltration while reducing toxicity, and how they enable in vivo CAR‐T cell generation.
Erica Frostegård +19 more
wiley +1 more source
Additive and Partially Dominant Effects from Genomic Variation Contribute to Rice Heterosis
Additive and partially dominant effects, namely at mid‐parent levels or values between mid‐parent and parental levels, respectively, are the predominant inheritance patterns of heterosis‐associated molecules. These two genetic effects contribute to heterosis of agronomic traits in both rice and maize, as well as biomass heterosis in Arabidopsis ...
Zhiwu Dan +8 more
wiley +1 more source
ABSTRACT Current therapies for Parkinson's disease (PD) fail to concurrently address α‐synuclein (α‐syn) aggregation and microglia‐mediated neuroinflammation. Herein, we engineer a near‐infrared‐II (NIR‐II) phototheranostic nanoplatform, CAG/FD1080@MM‐aTRPV4, for synergistic regulation of microglial function and real‐time monitoring of PD pathology. We
Hsuan Lo +9 more
wiley +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source

