Results 121 to 130 of about 7,092,713 (292)

Structural insights and therapeutic targets in Acinetobacter baumannii capsule biosynthesis

open access: yesFEBS Letters, EarlyView.
Hypervirulent KL49 A. baumannii's capsular polysaccharide contains the nonulosonic acid 8‐epi‐Leg5,7Ac2, synthesized by epimerization via ElaA, ElaB, and ElaC. Crystal structures of ElaA, ElaB, and ElaC reveal their role in CMP‐Leg5,7Ac2 synthesis and regioselective C8 epimerization.
Woo Cheol Lee   +7 more
wiley   +1 more source

Spurious Regression and Trending Variables [PDF]

open access: yes
This paper analyses the asymptotic and finite sample implications of different types of nonstationary behavior among the dependent and explanatory variables in a linear spurious regression model.
Daniel Ventosa-Santaularia   +1 more
core  

Running Variability in Marathon—Evaluation of the Pacing Variables

open access: yesMedicina
Background and Objectives: Pacing analyses for increasingly popular long-distance running disciplines have been in researchers’ spotlight for several years. In particular, assessing pacing variability in long-distance running was hardly achievable since runners must repeat long-running trials for several days.
Cuk, Ivan   +3 more
openaire   +4 more sources

Modelling stem cell differentiation related processes—A practical overview for biologists

open access: yesFEBS Letters, EarlyView.
Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar   +4 more
wiley   +1 more source

Independent Factors Extracted from 47 Variables 1971

open access: yes
A presentation slide labeled Independent Factors Extracted from 47 Variables ...

core  

Design and analysis strategies for robust microbiome ageing research

open access: yesFEBS Letters, EarlyView.
The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik   +5 more
wiley   +1 more source

Reconstructing enzyme evolution by protein engineering

open access: yesFEBS Letters, EarlyView.
Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler   +2 more
wiley   +1 more source

Identification of a Shiga toxin A‐derived peptide internalized into Gb3 receptor‐bearing cells via interaction with the Shiga toxin B subunit

open access: yesFEBS Letters, EarlyView.
The process of internalization of the Shiga toxin A subunit via formation of a complex with the Shiga toxin B subunit, which specifically binds to the Gb3 receptor. The peptide is designed to act as a carrier of drugs into cancer cells. Here, we explored the potential of peptides derived from the catalytic A subunit of Shiga toxin (STxA) to be drug ...
Giulia Opassi   +6 more
wiley   +1 more source

A Specification Test for Instrumental Variables Regression with Many Instruments [PDF]

open access: yes
This paper considers specification testing for instrumental variables estimation in the presence of many instruments. The test proposed is a modified version of the Sargan (1958, Econometrica 26(3): 393-415) test of overidentifying restrictions. The test
Yoonseok Lee, Ryo Okui
core  

Consistent estimation in the bilinear multivariate errors-in-variables model

open access: yes, 2003
A bilinear multivariate errors-in-variables model is considered. It corresponds to an overdetermined set of linear equations AXB=C, A?Rm×n, B?Rp×q, in which the data A, B, C are perturbed by errors.
Van Huffel, S.   +2 more
core   +1 more source

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