Results 141 to 150 of about 156,625 (312)

Cis‐ and Trans‐Regulatory Factors Independently Shape Phenotypic Heterogeneity of Retinitis Pigmentosa

open access: yesAdvanced Science, EarlyView.
A zebrafish model carrying an identical human RHO S334X allele reveals two independent genetic layers shaping retinitis pigmentosa (RP) severity: a protective 3‐bp cis‐regulatory insertion that attenuates transgene expression, and a dominant trans‐acting modifier that restores a severe phenotype.
Cong Cui   +9 more
wiley   +1 more source

Physical ecosystem engineering by emergent aquatic vegetation: the importance of biomechanical traits

open access: yes, 2011
PhDThis thesis explores the potential of the emergent macrophyte Sparganium erectum to act as a physical ecosystem engineer and delivers an understanding of the vegetative processes that enable it to function in such a capacity.
Liffen, Thomas Matthew Richard
core  

Natural Variation of NAR5 Determines Nitrogenase Activity and the Yield in Soybean

open access: yesAdvanced Science, EarlyView.
This study identified NAR5, a gene encoding a subtilisin‐like protease, that regulates nitrogenase activity in soybean nodules. Overexpressing NAR5 delayed nodule senescence, enhancing nitrogenase activity, yield, and low‐nitrogen tolerance. The elite haplotype NAR5HapI‐1 linked to superior nitrogenase activity and greater seed weight has been ...
Chao Ma   +11 more
wiley   +1 more source

Pharmacologic Modulation of ARID3A with Rimegepant Reactivates Type I Interferon Signaling and Sensitizes Triple‐Negative Breast Cancer to PD‐1 Blockade

open access: yesAdvanced Science, EarlyView.
This study identifies ARID3A as a key immunosuppressive transcription factor in TNBC. Its inhibition activates the type I IFN pathway, boosting CD8+ T cell infiltration and sensitizing tumors to anti‐PD‐1. The FDA‐approved migraine drug Rimegepant targets ARID3A, enhances immunotherapy efficacy in preclinical models, and establishes a druggable axis to
Teng Zhou   +12 more
wiley   +1 more source

Haplotype‐Resolved 3D Genomic Landscapes and Their Impacts on Agronomic Traits in Grapevine

open access: yesAdvanced Science, EarlyView.
This study presents a haplotype‐resolved 3D genomic landscape of grapevine, revealing that structural variations (SVs) are closely associated with phased topologically associating domain (TAD) boundary transitions. These rearrangements coordinate with allele‐specific DNA methylation (ASM) and allele‐biased gene expression (ASE) to shape key agronomic ...
Yanling Peng   +18 more
wiley   +1 more source

Genetic and clinical studies of teat traits in the pig [PDF]

open access: yes, 2013
A major goal of pig breeding is to produce sows with good longevity, which can raise many uniform litters with healthy, fast-growing piglets. The fitness of the sow, including the presence of sufficient number of functional teats, is one key to the ...
Chalkias, Helena
core  

Mean traits ± 95% confidence limits of ‘morphological size and shape’ leaf traits.

open access: yes, 2019
Mean traits ± 95% confidence limits of ‘morphological size and shape’ leaf traits.
Jean-Frederic Terral (6990227)   +3 more
core   +1 more source

The Role of Aquaculture in Shaping the Morphology of Babylonia areolata: A Comparative Study of Cultured and Wild Populations

open access: yesBiology
Background: With the rapid expansion of aquaculture, the impact of rearing environments on the morphological characteristics of marine species has become a critical research focus.
Haishan Wang   +4 more
doaj   +1 more source

EFFECT OF THE MORPHOLOGICAL TRAITS ON SEED YIELD OF LUCERNE BREEDING POPULATIONS IN LITHUANIA [PDF]

open access: yesJournal of Central European Agriculture, 2010
Phenotypic correlation coefficients between seed yield and morphological traits of lucerne (Medicago sativa L.) breeding populations were determined. Ranking of populations by seed yield and subsequent calculating of correlations showed that as higher ...
Aurelija LIATUKIENĖ   +2 more
doaj  

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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