Results 211 to 220 of about 1,194,668 (308)

Multi‐Targeting Non‐Specific Genome Engineering in Bacteria

open access: yesAdvanced Science, EarlyView.
In this study, we provide the first case to use the multi‐targeting integrase (MTI) systems in bacteria and develop a host‐independent generalizable approach, MNGE (Multi‐targeting Non‐specific Genome Engineering), for multi‐copy and random integration of metabolic genes or pathways in both Gram‐positive and Gram‐negative bacteria, which will ...
Runze Sun   +7 more
wiley   +1 more source

A New Culicid Genus [PDF]

open access: yesAnnals of Tropical Medicine & Parasitology, 1909
openaire   +1 more source

Metarhizium anisopliae Mitigates the Phytotoxicity of Lead and Nanoplastics on Rice by Modifying Physiological, Transcriptomic, Metabolomic Activities, and Soil Microbiome

open access: yesAdvanced Science, EarlyView.
Metarhizium anisopliae alleviates the phytotoxic effects of polyethylene nanoplastics (NP) and lead (Pb) in rice by decreasing Pb uptake, restoring antioxidant and hormonal equilibrium, and promoting growth. Additionally, the fungus modifies the rhizosphere microbiota, enhancing both contaminant tolerance and plant growth, thereby effectively ...
Jing Peng   +7 more
wiley   +1 more source

<i>Somnuekiaflaviflora</i> (Malvaceae, Brownlowioideae), a new genus and species from Thailand. [PDF]

open access: yesPhytoKeys
Chalermwong P   +12 more
europepmc   +1 more source

Coronavirus Nsp3 Hijacks CLTC to Modulate Autophagosome Nucleation for Promoting DMV Formation and Viral Replication

open access: yesAdvanced Science, EarlyView.
In wild‐type cells, FIPV infection recruits CLTC to nsp3, facilitates DMV biogenesis and block autophagic flux to promote viral replication. CLTC knockout impairs autophagosome nucleation by reducing Beclin1–ATG14 complex expression. This disrupts the formation of autophagic precursor membranes, thereby preventing their hijacking by nsp3 for DMV ...
Juan Xu   +9 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

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