bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanisms of RNA export and nuclear retention
Authors: Khan Misbah , Hou Shuai , Chen Mo , Lei Haixin 
Published: August 2022

AbstractWith the identification of huge amount of noncoding RNAs in recent years, the concept of RNA localization has extended from traditional mRNA export to RNA export of mRNA and ncRNA as well as nuclear retention of ncRNA. This review aims to summarize the recent findings from studies on the mechanisms of export of different RNAs and nuclear retention of some lncRNAs in higher eukaryotes, with a focus on splicing‐dependent TREX recruitment for the export of spliced mRNA and the sequence‐dependent mechanism of mRNA export in the absence of splicing. In addition, evidence to support the involvement of m6A modification in RNA export with the coordination between the methylase complex and TREX complex as well as sequence‐dependent nuclear retention of lncRNA is recapitulated. Finally, a model of sequence‐dependent RNA localization is proposed along with the many questions that remain to be answered.This article is categorized under:
RNA Export and Localization > RNA Localization
RNA Export and Localization > Nuclear Export/Import
Metal‐Organic Framework with High Densities of Open Metal Sites for Efficient Separation of Propylene from Propane
Authors: Wang Xue , Yong Jiayi , Wang Bo , Chen Jiazhen , Zhou Yitong , Cai Youlie , Gao Junkuo 
Published: August 2022

AbstractThe separation of propylene/propane (C3H6/C3H8) is a critical yet challenging process owing to their similar physical properties and molecular size. So it's urgent to explore efficient porous adsorbents to take place of the energy‐intensive consumption and high cost of traditional cryogenic distillation technologies. Here, we report a mixed metal‐organic framework (M'MOF), [Fe(pyz)Pt(CN)4] (FePt‐M'MOF, pyz=pyrazine) for selective adsorptive separation of C3H6/C3H8at room temperature, which has multiple functional sites and optimized pore channels of about 4.0 Å. This MOF has an excellent separation performance with C3H6uptake of 47.4 cm3/g and a high C3H6/C3H8selectivity of 4.7 under ambient conditions. The separation performance of propylene in this material is driven by π‐π stacking and multiple intermolecular interactions between propylene molecules and the binding sites of FePt‐M'MOF. This material can be prepared at room temperature and is stable in water, providing potential applications for industrial C3H6/C3H8separation.
Five psychological principles of codesigning conservation with (not for) communities
Authors: Cranston Kayla A. , Wong Wei Ying , Knowlton Shareen , Bennett Curtis , Rivadeneira Shannen 
Published: August 2022

AbstractA growing number of environmental professionals are realizing that equitable and meaningful engagement of local community members in the development of programming is essential for catalyzing the durable, long‐term action needed to conserve wildlife. Many who attempt to codesign programs with (not for) communities find that choosing the most effective strategies to accomplish this task is crucial and can oftentimes feel daunting. In this paper, a validated psychometric instrument called the Five Factors of Sustained Engagement (Five Factors) was used to analyze community engagement projects from two AZA‐accredited institutions, highlighting how the leaders of each project believe they have fostered each factor in their projects. Professionals can use the Five Factors as guideposts and evaluation criteria to increase the long‐term motivation of community members to engage in conservation efforts over time. The discussion offers strategies that psychological research has shown to increase long‐term motivation for wildlife conservation and suggest how to implement them in the codesign of conservation programming with the communities that are impacted by it the most. Together, this synthesis offers an innovative, psychology‐based approach to fostering and evaluating the success of sustainable community engagement for conservation Wildlife conservation projects are rarely su long‐term engagement from the humans who are most impacted by those projects.
Street Vending in Downtown Rabat: In Resistance to Imported Urban Models
Authors: Bouallala Wafae 
Published: August 2022

AbstractIn recent years street vending has become a major feature of the public space in downtown Rabat, Morocco’s capital city. Home to the Parliament and governmental institutions, downtown Rabat holds a powerful political symbolism in the collective representation of its inhabitants. Street vending is thus considered an intruder activity that must be banned from the area. However, history describes the downtown as a commercial zone where open-air markets—called Souks—were held regularly alongside brick-and-mortar shops before the advent of The French Protectorate in 1912, which transformed it into a “European zone” with a new “modern-formal” economy, pushing the local population to dwell in informal settlements and live from informal economy on the outskirts of the city. Through a historical analysis of the evolution of the downtown’s public space use induced by the French urban laws and models, and perpetuated by the Moroccan policies after independence, this chapter argues that itinerant trade belongs to the downtown as a central function and key element of its urban dynamics that has been disrupted by alien policies. This study makes an original contribution by evaluating the impact of colonial urban policies on urban informality in the Moroccan context. Results suggest that street vending, now considered as misappropriation of space by authorities, could be considered as a form of resistance to imported planning models and that efficient urban interventions depend on an in-depth understanding of rooted local urban design.
Contributions of Local Authorities to Community Adaptive Capacity to Impacts of Climate Change; A Case Study of Sea Level Rise in Pangani Division, Pangani District
Authors: Magembe-Mushi Dawah , Matingas Ramadhani 
Published: August 2022

AbstractCommunities around the world are facing tremendous climate change impacts, among others, sea level rise. Local authorities try to respond to the impacts of climate change by implementing localised adaptive measures to improve capacity. Impacts of climate change are worse in developing countries especially the Sub-Saharans due to inabilities to implement adaptive measures with inadequate resources; hence hindering the ability of communities to adapt to the impacts of climate change. It is the purpose of this chapter to explore the contributions of a local authority as one of the corresponding authorities responsible for enhancing a community’s adaptive capacity and its behaviour to climate change impacts. Interviews, mapping, observation and photographing, were conducted in the Pangani division in Tanzania. SPSS and QGIS software were used for analysis. It was found that sea level rise caused communities to suffer beach erosion, land inundation, saltwater intrusion, changes in fish availability, destruction of infrastructure and vegetation. The local authority implemented localised adaptive measures which improved adaptive capacity. These measures included construction and maintenance of seawall, planting and protecting mangroves and preparation of land-use plans. Also, an institutional arrangement involved different departments, committees and the community at large, with actors collaborating through the local authority in developing community adaptive capacity. This chapter recommends that the local authority should; enhance coordination among actors, make use of spatial analysis tools, mobilise resources and enhance community participation.
The spacetime geometry of fixed-area states in gravitational systems
Authors: Dong Xi , Marolf Donald , Rath Pratik , Tajdini Amirhossein , Wang Zhencheng 
Published: August 2022

Abstract
The concept of fixed-area states has proven useful for recent studies of quantum gravity, especially in connection with gravitational holography. We explore the Lorentz-signature spacetime geometry intrinsic to such fixed-area states in this paper. This contrasts with previous treatments which focused instead on Euclidean-signature saddles for path integrals that prepare such states. We analyze general features of fixed-area state geometries and construct explicit examples. The spacetime metrics are real at real times and have no conical singularities. With enough symmetry the classical metrics are in fact smooth, though more generally their curvatures feature power-law divergences along null congruences launched orthogonally from the fixed-area surface. While we argue that such divergences are not problematic at the classical level, quantum fields in fixed-area states feature stronger divergences. At the quantum level we thus expect fixed-area states to be well-defined only when the fixed-area surface is appropriately smeared.
Visualizing the Domino-Like Prepore-to-Pore Transition of Streptolysin O by High-Speed AFM
Authors: Ariyama Hirotaka 
Published: August 2022

AbstractPore-forming proteins (PFPs) are produced by various organisms, including pathogenic bacteria, and form pores within the target cell membrane. Streptolysin O (SLO) is a PFP produced by Streptococcus pyogenes and forms high-order oligomers on the membrane surface. In this prepore state, multiple α-helices in domain 3 of each subunit exist as unfolded structures and transiently interact with each other. They subsequently transition into transmembrane β-hairpins (TMHs) and form pores with diameters of 20–30 nm. However, in this pore formation process, the trigger of the transition in a subunit and collaboration between subunits remains elusive. Here, I observed the dynamic pore formation process using high-speed atomic force microscopy. During the oligomer transition process, each subunit was sequentially inserted into the membrane, propagating along the oligomer in a domino-like fashion (chain reaction). This process also occurred on hybrid oligomers containing wildtype and mutant subunits, which cannot insert into the membrane because of an introduced disulfide bond. Furthermore, propagation still occurred when an excessive force was added to hybrid oligomers in the prepore state. Based on the observed chain reactions, I estimate the free energies and forces that trigger the transition in a subunit. Furthermore, I hypothesize that the collaboration between subunits is related to the structure of their TMH regions and interactions between TMH–TMH and TMH–lipid molecules.
Graphical Abstract
How do providers of artificial intelligence (AI) solutions propose and legitimize the values of their solutions for supporting diagnostic radiology workflow? A technography study in 2021
Authors: Mehrizi Mohammad H. Rezazade , Gerritsen Simon H. , de Klerk Wouter M. , Houtschild Chantal , Dinnessen Silke M. H. , Zhao Luna , van Sommeren Rik , Zerfu Abby 
Published: August 2022

Abstract
Objectives
How do providers of artificial intelligence (AI) solutions propose and legitimize the values of their solutions for supporting diagnostic radiology workflow?

Methods
We systematically analyze 393 AI applications developed for supporting diagnostic radiology workflow. We collected qualitative and quantitative data by analyzing around 1250 pages of documents retrieved from companies’ websites and legal documents. Five investigators read and interpreted collected data, extracted the features and functionalities of the AI applications, and finally entered them into an excel file for identifying the patterns.

Results
Over the last 2 years, we see an increase in the number of AI applications (43%) and number of companies offering them (34%), as well as their average age (45%). Companies claim various value propositions related to increasing the “efficiency” of radiology work (18%)—e.g., via reducing the time and cost of performing tasks and reducing the work pressure—and “quality” of offering medical services (31%)—e.g., via enhancing the quality of clinical decisions and enhancing the quality of patient care, or both of them (28%). To legitimize and support their value propositions, the companies use multiple strategies simultaneously, particularly by seeking legal approvals (72%), promoting their partnership with medical and academic institutions (75%), highlighting the expertise of their teams (56%), and showcasing examples of implementing their solutions in practice (53%).

Conclusions
Although providers of AI applications claim a wide range of value propositions, they often provide limited evidence to show how their solutions deliver such systematic values in clinical practice.

Key Points
• AI applications in radiology continue to grow in number and diversity.
• Companies offering AI applications claim various value propositions and use multiple ways to legitimize these propositions.
• Systematic scientific evidence showing the actual effectiveness of AI applications in clinical context is limited.
Cost-effectiveness analysis of gene-based therapies for patients with spinal muscular atrophy type I in Australia
Authors: Wang Tianjiao , Scuffham Paul , Byrnes Joshua , Downes Martin 
Published: August 2022

Abstract
Introduction
Spinal muscular atrophy (SMA) is an inherited neuromuscular disorder and regarded as one of the most frequent genetic causes of infant mortality. The aim of this study is to develop a cost-effectiveness analysis of AVXS-101 (Onasemnogene Abeparvovec/Zolgensma®) and nusinersen (Spinraza®) for SMA to inform decision-making on reimbursement policies in Australia.

Methods
A Markov model was developed with five health states to evaluate the costs and effects for patients with SMA Type I from a healthcare system perspective over a time-horizon of 100 years. The model parameters were based on clinical trials, parametric distributions, published literature, and Australian registries. One-way and probabilistic sensitivity analysis were performed to appraise the uncertainties of the parameters in the model. A threshold analysis was conducted to estimate the cost of AVXS-101 of being cost-effective.

Results
The incremental cost-effectiveness ratio (ICER) of AVXS-101 was $1,808,471 per quality-adjusted life year (QALY) and that of nusinersen was $2,772,798 per QALY, compared to standard of care, respectively. The ICER of AVXS-101 was $1,238,288 per QALY compared to nusinersen. The key drivers influencing on ICERs were costs of using treatments and utility values of sitting and walking independently.

Conclusion
Both nusinersen and AVXS-101 resulted in health benefits, but they were not cost-effective with a commonly used willingness-to-pay (WTP) threshold of $50,000 per QALY. Developing high-quality clinical data and exploring appropriate WTP thresholds are critical for decision-making on reimbursement policies in the treatment of rare diseases.
Primary mitochondrial myopathy: 12-month follow-up results of an Italian cohort
Authors: Montano V. , Lopriore P. , Gruosso F. , Carelli V. , Comi G. P. , Filosto M. , Lamperti C. , Mongini T. , Musumeci O. , Servidei S. , Tonin P. , Toscano A. , Primiano G. , Valentino M. L. , Bortolani S. , Marchet S. , Ricci G. , Modenese A. , Cotti Piccinelli S. , Risi B. , Meneri M. , Arena I. G. , Siciliano G. , Mancuso Michelangelo 
Published: August 2022

Abstract
Objectives
To assess natural history and 12-month change of a series of scales and functional outcome measures in a cohort of 117 patients with primary mitochondrial myopathy (PMM).

Methods
Twelve months follow-up data of 117 patients with PMM were collected. We analysed the 6-min walk test (6MWT), timed up-and-go test (× 3) (3TUG), five-times sit-to-stand test (5XSST), timed water swallow test (TWST), and test of masticating and swallowing solids (TOMASS) as functional outcome measures; the Fatigue Severity Scale and West Haven-Yale Multidimensional pain inventory as patient-reported outcome measures. PMM patients were divided into three phenotypic categories: mitochondrial myopathy (MiMy) without extraocular muscles involvement, pure chronic progressive external ophthalmoplegia (PEO) and PEO&MiMy. As 6MWT is recognized to have significant test–retest variability, we calculated MCID (minimal clinically important difference) as one third of baseline 6 min walking distance (6MWD) standard deviation.

Results
At 12-month follow-up, 3TUG, 5XSST and FSS were stable, while TWST and the perceived pain severity (WHYMPI) worsened. 6MWD significantly increased in the entire cohort, especially in the higher percentiles and in PEO patients, while was substantially stable in the lower percentile (< 408 m) and MiMy patients. This increase in 6MWD was considered not significant, as inferior to MCID (33.3 m). NMDAS total score showed a slight but significant decline at 12 months (0.9 point). The perceived pain severity significantly worsened. Patients with PEO performed better in functional measures than patients with PEO&MiMy or MiMy, and had lower values of NMDAS.

Conclusions
PMM patients showed a slow global decline valued by NMDAS at 12 months; 6MWT was a more reliable measurement below 408 m, substantially stable at 12 months. PEO patients had better motor performance and lower NMDAS than PEO&MiMy and MiMy also at 12 months of follow-up.
Bayesian inference for random field parameters with a goal-oriented quality control of the PGD forward model’s accuracy
Authors: Coelho Lima Isabela , Robens-Radermacher Annika , Titscher Thomas , Kadoke Daniel , Koutsourelakis Phaedon-Stelios , Unger Jörg F. 
Published: August 2022

AbstractNumerical models built as virtual-twins of a real structure (digital-twins) are considered the future of monitoring systems. Their setup requires the estimation of unknown parameters, which are not directly measurable. Stochastic model identification is then essential, which can be computationally costly and even unfeasible when it comes to real applications. Efficient surrogate models, such as reduced-order method, can be used to overcome this limitation and provide real time model identification. Since their numerical accuracy influences the identification process, the optimal surrogate not only has to be computationally efficient, but also accurate with respect to the identified parameters. This work aims at automatically controlling the Proper Generalized Decomposition (PGD) surrogate’s numerical accuracy for parameter identification. For this purpose, a sequence of Bayesian model identification problems, in which the surrogate’s accuracy is iteratively increased, is solved with a variational Bayesian inference procedure. The effect of the numerical accuracy on the resulting posteriors probability density functions is analyzed through two metrics, the Bayes Factor (BF) and a criterion based on the Kullback-Leibler (KL) divergence. The approach is demonstrated by a simple test example and by two structural problems. The latter aims to identify spatially distributed damage, modeled with a PGD surrogate extended for log-normal random fields, in two different structures: a truss with synthetic data and a small, reinforced bridge with real measurement data. For all examples, the evolution of the KL-based and BF criteria for increased accuracy is shown and their convergence indicates when model refinement no longer affects the identification results.
A walk in the black-box: 3D visualization of large neural networks in virtual reality
Authors: Linse Christoph , Alshazly Hammam , Martinetz Thomas 
Published: August 2022

AbstractWithin the last decade Deep Learning has become a tool for solving challenging problems like image recognition. Still, Convolutional Neural Networks (CNNs) are considered black-boxes, which are difficult to understand by humans. Hence, there is an urge to visualize CNN architectures, their internal processes and what they actually learn. Previously, virtual realityhas been successfully applied to display small CNNs in immersive 3D environments. In this work, we address the problem how to feasibly render large-scale CNNs, thereby enabling the visualization of popular architectures with ten thousands of feature maps and branches in the computational graph in 3D. Our software ”DeepVisionVR” enables the user to freely walk through the layered network, pick up and place images, move/scale layers for better readability, perform feature visualization and export the results. We also provide a novel Pytorch module to dynamically link PyTorch with Unity, which gives developers and researchers a convenient interface to visualize their own architectures. The visualization is directly created from the PyTorch class that defines the Pytorch model used for training and testing. This approach allows full access to the network’s internals and direct control over what exactly is visualized. In a use-case study, we apply the module to analyze models with different generalization abilities in order to understand how networks memorize images. We train two recent architectures, CovidResNet and CovidDenseNet on the Caltech101 and the SARS-CoV-2 datasets and find that bad generalization is driven by high-frequency features and the susceptibility to specific pixel arrangements, leading to implications for the practical application of CNNs. The code is available on Github https://github.com/Criscraft/DeepVisionVR.
Depression nach Schlaganfall
Authors: Ferrari Julia , Sachs Gabriele , Erfurth Andreas 
Published: August 2022

ZusammenfassungNach einem Schlaganfall treten häufig relevante depressive Symptome (poststroke depression, PSD) auf, die in der klinischen Praxis häufig übersehen oder unterschätzt werden. Die rasche Erkennung und angemessene Behandlung der PSD sind für die Rehabilitation und die Chance auf ein optimales funktionelles Ergebnis von entscheidender Bedeutung. Selektive Serotonin-Rückaufnahme-Inhibitoren (SSRI) sind sehr gut für die Behandlung der PSD untersucht, für die kognitiv-behaviorale Therapie gibt es gute Evidenz. Für eine regelhafte prophylaktische Verwendung eines SSRI nach jedem Schlaganfallereignis gibt es keine Empfehlung, in Einzelfällen sollte eine solche Prophylaxe diskutiert werden. Von Bedeutung ist die routinemäßige Erfassung kognitiver Dysfunktionen, da sowohl Schlaganfälle als auch depressive Störungen mit behandlungsbedürftigen kognitiven Störungen einhergehen können.
Direct 14C dating of equine products preserved in archaeological pottery vessels from Botai and Bestamak, Kazakhstan
Authors: Casanova Emmanuelle , Knowles Timothy D. J. , Outram Alan K. , Stear Natalie A. , Roffet-Salque Mélanie , Zaibert Viktor , Logvin Andrey , Shevnina Irina , Evershed Richard P. 
Published: August 2022

AbstractDirect and accurate radiocarbon dating of lipid residues preserved in ceramics is a recently established method that allows direct dating of specific food products and their inception in human subsistence strategies. The method targets individual fatty acids originating from animal fats such as ruminant dairy, ruminant adipose, non-ruminant adipose and aquatic fats. Horse lipid residues found in Central Asian pottery vessels are also directly dateable using this new method. Here we present the identification of equine lipid residues preserved in two pottery assemblages from the Neolithic and Eneolithic in Kazakhstan and their direct 14C dating. The site of Botai, previously radiocarbon-dated to the 4th millennium BC, was used as a reference to evaluate the dates obtained directly on horse lipids. The direct dating of equine products extracted from Botai potsherds are shown to be compatible with previous 14C dates at the site. The site of Bestamak, lacking previous14C measurements, had been relatively dated to the Neolithic based on pottery typologies. The direct dating of equine residues made it possible to anchor the pottery assemblage of Bestamak in the 6th millennium BC confirming their Neolithic attribution. These findings demonstrate the potential for dating horse products through a compound-specific approach, while highlighting challenges in 14C dating individual fatty acids from lipid extracts in which their abundances differ substantially.