STRUCTURAL CHARACTERIZATION OF A MIXED-LINKAGE GLUCAN DEFICIENT MUTANT REVEALS ALTERATION IN CELLULOSE MICROFIBRIL ORIENTATION IN RICE COLEOPTILE MESOPHYLL CELL WALLS

Structural characterization of a mixed-linkage glucan deficient mutant reveals alteration in cellulose microfibril orientation in rice coleoptile mesophyll cell walls

The CELLULOSE SYNTHASE-LIKE F6 (CslF6) gene was previously shown to mediate the biosynthesis of mixed-linkage glucan (MLG), a cell wall polysaccharide that is hypothesized to be a tightly associated with cellulose and also have a role in cell expansion in the primary cell wall of young seedlings in grass species.We have recently shown that loss-of-

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Modal shift ambitions of large North European ports: A contract-theory perspective on the role of port managing bodies

Port managing bodies (PMBs) need to respond to increased societal pressures for improving environmental performance.For many PMBs, a modal shift (MS) from road to rail and barge transport (where available) represents a strategic priority.Yet, in practice, few PMBs have set clear MS targets or have been able to achieve their MS objectives at the lev

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Mesenchymal stem cells restore frataxin expression and increase hydrogen peroxide scavenging enzymes in Friedreich ataxia fibroblasts.

Dramatic advances in CASCARA SAGRADA recent decades in understanding the genetics of Friedreich ataxia (FRDA)--a GAA triplet expansion causing greatly reduced expression of the mitochondrial protein frataxin--have thus far yielded no therapeutic dividend, since there remain no effective treatments that prevent or even slow the inevitable progressiv

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A machine learning approach to detect potentially harmful and protective suicide-related content in broadcast media.

Suicide-related media content has preventive or harmful effects depending on the specific content.Proactive media screening for suicide prevention is hampered by the scarcity of machine learning approaches to detect specific characteristics in news reports.This study applied machine learning to label large quantities of broadcast (TV and radio) med

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