scholarly journals COVID 19: Designing and conducting an online mini-multiple interview (MMI) in a dynamic landscape

2020 ◽  
Vol 42 (7) ◽  
pp. 776-780 ◽  
Author(s):  
Jennifer Cleland ◽  
Jowe Chu ◽  
Samuel Lim ◽  
Jamie Low ◽  
Naomi Low-Beer ◽  
...  
Keyword(s):  
Land ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 555
Author(s):  
Megan K. Jennings ◽  
Katherine A. Zeller ◽  
Rebecca L. Lewison

Until fairly recently, the majority of landscape connectivity analyses have considered connectivity as a static landscape feature, despite the widespread recognition that landscapes and the abiotic and biotic processes that influence them are dynamic [...]


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Vikram Agarwal ◽  
Sereno Lopez-Darwin ◽  
David R. Kelley ◽  
Jay Shendure

Abstract3′ untranslated regions (3′ UTRs) post-transcriptionally regulate mRNA stability, localization, and translation rate. While 3′-UTR isoforms have been globally quantified in limited cell types using bulk measurements, their differential usage among cell types during mammalian development remains poorly characterized. In this study, we examine a dataset comprising ~2 million nuclei spanning E9.5–E13.5 of mouse embryonic development to quantify transcriptome-wide changes in alternative polyadenylation (APA). We observe a global lengthening of 3′ UTRs across embryonic stages in all cell types, although we detect shorter 3′ UTRs in hematopoietic lineages and longer 3′ UTRs in neuronal cell types within each stage. An analysis of RNA-binding protein (RBP) dynamics identifies ELAV-like family members, which are concomitantly induced in neuronal lineages and developmental stages experiencing 3′-UTR lengthening, as putative regulators of APA. By measuring 3′-UTR isoforms in an expansive single cell dataset, our work provides a transcriptome-wide and organism-wide map of the dynamic landscape of alternative polyadenylation during mammalian organogenesis.


Cell ◽  
2021 ◽  
Author(s):  
Mineto Ota ◽  
Yasuo Nagafuchi ◽  
Hiroaki Hatano ◽  
Kazuyoshi Ishigaki ◽  
Chikashi Terao ◽  
...  

2002 ◽  
Vol 66 (5) ◽  
pp. 1610-1619 ◽  
Author(s):  
J. M. Schoorl ◽  
A. Veldkamp ◽  
J. Bouma

Langmuir ◽  
2019 ◽  
Vol 35 (44) ◽  
pp. 14151-14172 ◽  
Author(s):  
Veerendra Kumar Sharma ◽  
Subhankur Mitra ◽  
Ramaprosad Mukhopadhyay

2019 ◽  
Author(s):  
Paul Stephen Glazier ◽  
Sina Mehdizadeh

The development of methods that can identify athlete-specific optimum sports techniques—arguably the holy grail of sports biomechanics—is one of the greatest challenges for researchers in the field. This ‘perspectives article’ critically examines, from a dynamical systems theoretical standpoint, the claim that athlete-specific optimum sports techniques can be identified through biomechanical optimisation modelling. To identify athlete-specific optimum sports techniques, dynamical systems theory suggests that a representative set of organismic constraints, along with their non-linear characteristics, needs to be identified and incorporated into the mathematical model of the athlete. However, whether the athlete will be able to adopt, and reliably reproduce, his/her predicted optimum technique will largely be dependent on his/her intrinsic dynamics. If the attractor valley corresponding to the existing technique is deep, or if the attractor valleys corresponding to the existing technique and the predicted optimum technique are in different topographical regions of the dynamic landscape, technical modifications may be challenging or impossible to reliably implement even after extended practice. The attractor layout defining the intrinsic dynamics of the athlete, therefore, needs to be determined to establish the likelihood of the predicted optimum technique being reliably attainable by the athlete. Given the limited set of organismic constraints typically used in mathematical models of athletes, combined with the methodological challenges associated with mapping the attractor layout of an athlete, it seems unlikely that athlete-specific optimum sports techniques will be identifiable through biomechanical optimisation modelling for the majority of sports skills in the near future.


2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Albert A. Smith ◽  
Alexander Vogel ◽  
Oskar Engberg ◽  
Peter W. Hildebrand ◽  
Daniel Huster

AbstractBiomolecular function is based on a complex hierarchy of molecular motions. While biophysical methods can reveal details of specific motions, a concept for the comprehensive description of molecular dynamics over a wide range of correlation times has been unattainable. Here, we report an approach to construct the dynamic landscape of biomolecules, which describes the aggregate influence of multiple motions acting on various timescales and on multiple positions in the molecule. To this end, we use 13C NMR relaxation and molecular dynamics simulation data for the characterization of fully hydrated palmitoyl-oleoyl-phosphatidylcholine bilayers. We combine dynamics detector methodology with a new frame analysis of motion that yields site-specific amplitudes of motion, separated both by type and timescale of motion. In this study, we show that this separation allows the detailed description of the dynamic landscape, which yields vast differences in motional amplitudes and correlation times depending on molecular position.


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