bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficacy of noninvasive respiratory support modes as postextubation respiratory support in preterm neonates: A systematic review and network meta‐analysis
Authors: Ramaswamy Viraraghavan Vadakkencherry , Bandyopadhyay Tapas , Nanda Debasish , Bandiya Prathik , More Kiran , Oommen Vinod Idicula , Gupta Amit 
Published: August 2020

AbstractBackgroundMultiple noninvasive respiratory support (NRS) modalities are used for postextubation support in preterm neonates. Seven NRS modalities were compared—constant flow continuous positive airway pressure (CPAP) (CF‐CPAP) (bubble CPAP; ventilator CPAP), variable flow CPAP (VF‐CPAP), high flow nasal cannula (HFNC), synchronized noninvasive positive pressure ventilation (S‐NIPPV), nonsynchronized NIPPV (NS‐NIPPV), bilevel CPAP (BiPAP), noninvasive high‐frequency oscillation ventilation (nHFOV).DesignSystematic review and network meta‐analysis (NMA) using the Bayesian random‐effects approach. MEDLINE, EMBASE, CENTRAL, WHO‐ICTRP were searched.Main Outcome MeasureRequirement of invasive mechanical ventilation within 7 days of extubation.ResultsA total of 33 studies with 4080 preterm neonates were included. S‐NIPPV, NS‐NIPPV, nHFOV, and VF‐CPAP were more efficacious in preventing reintubation than CF‐CPAP (risk ratio [RR] [95% credible intervals {CrI}]: 0.22 [0.12, 0.35]; 0.44 [0.27, 0.67]; 0.42 [0.18, 0.81]; 0.73 [0.52, 0.99]). Surface under the cumulative ranking curve (SUCRA) value ranked S‐NIPPV to be the best postextubation intervention (SUCRA: 0.98). S‐NIPPV was more effective than NS‐NIPPV, BiPAP, VF‐CPAP, and HFNC (RR [95% CrI]: 0.52 [0.24, 0.97]; 0.32 [0.14, 0.64]; 0.30 [0.16, 0.50]; 0.24 [0.12, 0.41]). NS‐NIPPV resulted in lesser reintubation compared to VF‐CPAP and HFNC (RR [95% CrI]: 0.61 [0.36, 0.97]; 0.49 [0.27, 0.80]). BiPAP, VF‐CPAP, and HFNC had comparable efficacies. The overall quality of evidence was very low to moderate.ConclusionResults of this NMA indicate that S‐NIPPV might be the most effective and CF‐CPAP the least effective NRS modality for preventing extubation failure.
Microcavity Polaritons for Quantum Simulation
Authors: Boulier Thomas , Jacquet Maxime J. , Maître Anne , Lerario Giovanni , Claude Ferdinand , Pigeon Simon , Glorieux Quentin , Amo Alberto , Bloch Jacqueline , Bramati Alberto , Giacobino Elisabeth 
Published: August 2020

AbstractQuantum simulations are one of the pillars of quantum technologies. These simulations provide insight in fields as varied as high energy physics, many‐body physics, or cosmology to name only a few. Several platforms, ranging from ultracold‐atoms to superconducting circuits through trapped ions have been proposed as quantum simulators. This article reviews recent developments in another well established platform for quantum simulations: polaritons in semiconductor microcavities. These quasiparticles obey a nonlinear Schrödigner equation (NLSE), and their propagation in the medium can be understood in terms of quantum hydrodynamics. As such, they are considered as “fluids of light.” The challenge of quantum simulations is the engineering of configurations in which the potential energy and the nonlinear interactions in the NLSE can be controlled. Here, some landmark experiments with polaritons in microcavities are revisited, how the various properties of these systems may be used in quantum simulations is discussed, and the richness of polariton systems to explore nonequilibrium physics is highlighted.
Large dam renewals and removals—Part 1: Building a science framework to support a decision‐making process
Authors: Curry R. Allen , Yamazaki Gordon , Linnansaari Tommi , Monk Wendy , Samways Kurt M. , Dolson Rebecca , Munkittrick Kelly R. , Bielecki Anthony 
Published: August 2020

AbstractAltered rivers and managed flows are a hallmark of civilization and dams are a principal agent of alteration. Peak dam construction occurred at the turn of the last century in Western countries, and many of the largest dams are reaching the end of their service life. As a result, dam operators are increasingly facing a complex renewal/removal decision‐making process in a large part because the economic and social values of dams have changed. The Mactaquac Hydroelectric Generating Station (New Brunswick, Canada), operated by NB Power Corporation (NB Power), is Canada's 25th largest dam and it is reaching the end of its service life. A decision is required for the dam's future state and three options were originally proposed: renew, rebuild, or remove. An overarching science framework was developed with NB Power to inform and support decision‐making for the dam's decision process and an impending Environmental Impact Assessment. The framework guides research and monitoring for dam renewal/removal using science‐based solutions that aim to minimize impacts on the aquatic environment while supporting an efficient and cost‐effective decision‐making process. The framework has five components: (a) establish long‐term baselines of environmental conditions; (b) develop normal ranges describing the river's natural variability; (c) integrated physical and biological modelling; (d) assess the specific and cumulative state of fish passage; and (e) create and sustain a user‐friendly geospatial data management system. In this paper we present a case study that implements the science framework (Part 1) through the Mactaquac Aquatic Ecosystem Study (MAES) with a view to revisit and assess its final impact post‐project completion (Part 2).
Computational intelligence within a resource budget: The case of the honey bee (Apis mellifera) swarm
Authors: Foss Richard A. 
Published: August 2020

AbstractThis study investigated the resource budget available to a typical honey bee swarm as it gathered information and decided which was the best of some 13–34 potential nest sites to move into and become its new home. After a brief description of the decision‐making mechanisms involved, the utilization of the swarm's finite energy, memory and carrier resources is described. It was found that each individual scout decision maker only carried enough energy reserves to provide for 2.6 days of visits to evaluate distant sites and, effectively, only enough memory space to remember the location and quality of approximately one site. Scouts, who only formed 4.4% of the swarm bees, consumed 22.8% of the swarm's energy budget, showing that their best‐of‐N computations were energetically very expensive. A typical swarm of 12,000 bees only contained enough energy reserves to last for 13.5 days after which foraging had to restart.
Development of Antimicrobial Biodegradable Films Based on Corn Starch with Aqueous Extract of Hibiscus sabdariffa L
Authors: Gómez‐Aldapa Carlos Alberto , Díaz‐Cruz Claudio Alonso , Castro‐Rosas Javier , Jiménez‐Regalado Enrique Javier , Velazquez Gonzalo , Gutierrez Miguel C. , Aguirre‐Loredo Rocio Yaneli 
Published: August 2020

AbstractThe objective of this work is to prepare biodegradable films of corn starch, replacing a part of the distilled water used in the formulation of the filmogenic solution with an aqueous extract of Hibiscus sabdariffa L. (HSE) and evaluate its functional properties and antimicrobial capacity. The films are made by casting method, adding different HSE:water volume ratios: 100:0, 75:25, 50:50, 25:75, and 0:100 as control. All films with HSE showed an antimicrobial effect, giving positive results against Listeria monocytogenes, Staphylococcus aureus, Salmonella spp., and Escherichia coli. It is observed that, with the increase in the proportion of HSE, the films are more manageable and glossy than those of starch alone and a more intense red color as the extract content increased, significantly improving its mechanical properties, mainly when the HSE content is above 25% on the filmogenic solution. Likewise, the addition of the extract significantly improved the water vapor barrier capacity of the films. According to the results obtained in this study, corn starch films with aqueous extract of H. sabdariffa are an excellent alternative as a biodegradable packaging material for the food industry, with good functional properties and antimicrobial capacity.
Dark‐field hyperspectral imaging for label free detection of nano‐bio‐materials
Authors: Mehta Nishir , Sahu Sushant P. , Shaik Shahensha , Devireddy Ram , Gartia Manas Ranjan 
Published: August 2020

AbstractNanomaterials are playing an increasingly important role in cancer diagnosis and treatment. Nanoparticle (NP)‐based technologies have been utilized for targeted drug delivery during chemotherapies, photodynamic therapy, and immunotherapy. Another active area of research is the toxicity studies of these nanomaterials to understand the cellular uptake and transport of these materials in cells, tissues, and environment. Traditional techniques such as transmission electron microscopy, and mass spectrometry to analyze NP‐based cellular transport or toxicity effect are expensive, require extensive sample preparation, and are low‐throughput. Dark‐field hyperspectral imaging (DF‐HSI), an integration of spectroscopy and microscopy/imaging, provides the ability to investigate cellular transport of these NPs and to quantify the distribution of them within bio‐materials. DF‐HSI also offers versatility in non‐invasively monitoring microorganisms, single cell, and proteins. DF‐HSI is a low‐cost, label‐free technique that is minimally invasive and is a viable choice for obtaining high‐throughput quantitative molecular analyses. Multimodal imaging modalities such as Fourier transform infrared and Raman spectroscopy are also being integrated with HSI systems to enable chemical imaging of the samples. HSI technology is being applied in surgeries to obtain molecular information about the tissues in real‐time. This article provides brief overview of fundamental principles of DF‐HSI and its application for nanomaterials, protein‐detection, single‐cell analysis, microbiology, surgical procedures along with technical challenges and future integrative approach with other imaging and measurement modalities.This article is categorized under:
Diagnostic Tools > in vitro Nanoparticle‐Based Sensing
Diagnostic Tools > in vivo Nanodiagnostics and Imaging
Implantable Materials and Surgical Technologies > Nanoscale Tools and Techniques in Surgery
Emerging translation strategies during virus–host interaction
Authors: Hoang Huy‐Dung , Neault Serge , Pelin Adrian , Alain Tommy 
Published: August 2020

AbstractTranslation control is crucial during virus–host interaction. On one hand, viruses completely rely on the protein synthesis machinery of host cells to propagate and have evolved various mechanisms to redirect the host's ribosomes toward their viral mRNAs. On the other hand, the host rewires its translation program in an attempt to contain and suppress the virus early on during infection; the antiviral program includes specific control on protein synthesis to translate several antiviral mRNAs involved in quenching the infection. As the infection progresses, host translation is in turn inhibited in order to limit viral propagation. We have learnt of very diverse strategies that both parties utilize to gain or retain control over the protein synthesis machinery. Yet novel strategies continue to be discovered, attesting for the importance of mRNA translation in virus–host interaction. This review focuses on recently described translation strategies employed by both hosts and viruses. These discoveries provide additional pieces in the understanding of the complex virus–host translation landscape.This article is categorized under:
Translation > Translation Mechanisms
Translation > Translation Regulation
Multiscale Modeling of EEG/MEG Response of a Compact Cluster of Tightly Spaced Pyramidal Neocortical Neurons
Authors: Makarov Sergey N. , Ahveninen Jyrki , Hämäläinen Matti , Okada Yoshio , Noetscher Gregory M. , Nummenmaa Aapo 
Published: August 2020

AbstractIn this study, the boundary element fast multipole method or BEM-FMM is applied to model compact clusters of tightly spaced pyramidal neocortical neurons firing simultaneously and coupled with a high-resolution macroscopic head model. The algorithm is capable of processing a very large number of surface-based unknowns along with a virtually unlimited number of elementary microscopic current dipole sources distributed within the neuronal arbor.The realistic cluster size may be as large as 10,000 individual neurons, while the overall computation times do not exceed several minutes on a standard server. Using this approach, we attempt to establish how well the conventional lumped-dipole model used in electroencephalography/magnetoencephalography (EEG/MEG) analysis approximates a compact cluster of realistic neurons situated either in a gyrus (EEG response dominance) or in a sulcus (MEG response dominance).
Insights from Computational Modelling: Selective Stimulation of Retinal Ganglion Cells
Authors: Guo Tianruo , Tsai David , Bai Siwei , Shivdasani Mohit , Muralidharan Madhuvanthi , Li Liming , Dokos Socrates , Lovell Nigel H. 
Published: August 2020

AbstractImprovements to the efficacy of retinal neuroprostheses can be achieved by developing more sophisticated neural stimulation strategies to enable selective or differential activation of specific retinal ganglion cells (RGCs). Recent retinal studies have demonstrated the ability to differentially recruit ON and OFF RGCs – the two major information pathways of the retina – using high-frequency electrical stimulation (HFS). However, there remain many unknowns, since this is a relatively unexplored field. For example, can we achieve ON/OFF selectivity over a wide range of stimulus frequencies and amplitudes? Furthermore, existing demonstrations of HFS efficacy in retinal prostheses have been based on epiretinal placement of electrodes. Other clinically popular techniques include subretinal or suprachoroidal placement, where electrodes are located at the photoreceptor layer or in the suprachoroidal space, respectively, and these locations are quite distant from the RGC layer. Would HFS-based differential activation work from these locations? In this chapter, we conducted in silico investigations to explore the generalizability of HFS to differentially active ON and OFF RGCs. Computational models are particularly well suited for these investigations. The electric field can be accurately described by mathematical formulations, and simulated neurons can be “probed” at resolutions well beyond those achievable by today’s state-of-the-art experimental techniques.
Preprocessing General Head Models for BEM-FMM Modeling Pertinent to Brain Stimulation
Authors: Wartman William A. 
Published: August 2020

AbstractIntroduction: Transcranial magnetic stimulation (TMS) is a major noninvasive neurostimulation method in which a coil placed near the head employs electromagnetic induction to produce electric fields and currents within the brain. To predict the actual site of stimulation, numerical simulation of the electric fields within the head using high-resolution subject-specific head models is required. A TMS modeling software toolkit has been developed based on the boundary element fast multipole method (BEM-FMM), which has several advantages over conventional finite element method (FEM) solvers.Objective: To extend the applicability of the BEM-FMM TMS simulation toolkit to head models whose meshing scheme produces a single mesh for every unique tissue instead of producing a single mesh for every unique tissue/tissue boundary.Method: The MIDA model of the IT’IS Foundation, Switzerland, comprises 115 high-resolution tissue models in the form that the BEM-FMM toolkit is modified to accept. The updated BEM-FMM toolkit is tested using this head model.Results: The BEM-FMM toolkit has been successfully modified to accept head models consisting of one unique mesh per unique tissue while still supporting its initial model format of one unique mesh per boundary between two specific tissues. Performance impacts occur in the preprocessing phase only, meaning that the charge computation method performs equally well regardless of model format.
Personalization of Multi-electrode Setups in tCS/tES: Methods and Advantages
Authors: Salvador R. , Biagi M. C. , Puonti O. , Splittgerber M. , Moliadze V. , Siniatchkin M. , Thielscher A. , Ruffini G. 
Published: August 2020

AbstractTranscranial current stimulation (tCS or tES) protocols yield results that are highly variable across individuals. Part of this variability results from differences in the electric field (E-field) induced in subjects’ brains during stimulation. The E-field determines how neurons respond to stimulation, and it can be used as a proxy for predicting the concurrent effects of stimulation, like changes in cortical excitability, and, ultimately, its plastic effects. While the use of multichannel systems with small electrodes has provided a more precise tool for delivering tCS, individually variable anatomical parameters like the shape and thickness of tissues affect the E-field distribution for a specific electrode montage. Therefore, using the same montage parameters across subjects does not lead to the homogeneity of E-field amplitude over the desired targets. Here we describe a pipeline that leverages individualized head models combined with montage optimization algorithms to reduce the variability of the E-field distributions over subjects in tCS. We will describe the different steps of the pipeline – namely, MRI segmentation and head model creation, target specification, and montage optimization – and discuss their main advantages and limitations.
Modelling Studies of Non-invasive Electric and Magnetic Stimulation of the Spinal Cord
Authors: Fernandes Sofia Rita , Salvador Ricardo , de Carvalho Mamede , Miranda Pedro Cavaleiro 
Published: August 2020

AbstractExperimental studies on transcutaneous spinal cord direct current and magnetic stimulation (tsDCS and tsMS, respectively) show promising results in the neuromodulation of spinal sensory and motor pathways, with possible clinical application in spinal functional rehabilitation. Modelling studies on the electric field (EF) distribution during tsDCS and tsMS can be powerful tools to understand the underlying biophysics and to guide stimulation protocols for a specific clinical target. In this chapter, we review modelling studies of tsDCS and report on our own modelling findings on tsDCS and tsMS. We discuss the main differences between the EF induced by these two stimulation techniques and the implications for clinical practice, addressing the relevance of modelling studies for more personalized target protocols and individualized dosing.
The association of hyperglycaemia and insulin resistance with incident depressive symptoms over 4 years of follow-up: The Maastricht Study
Authors: Geraets Anouk F. J. , Köhler Sebastian , Muzambi Rutendo , Schalkwijk Casper G. , Oenema Anke , Eussen Simone J. P. M. , Dagnelie Pieter C. , Stehouwer Coen D. A. , Schaper Nicolaas C. , Henry Ronald M. A. , van der Kallen Carla J. H. , Wesselius Anke , Koster Annemarie , Verhey Frans R. J. , Schram Miranda T. 
Published: August 2020

Abstract
Aims/hypothesis
Depression is twice as common in individuals with type 2 diabetes as in the general population. However, it remains unclear whether hyperglycaemia and insulin resistance are directly involved in the aetiology of depression. Therefore, we investigated the association of markers of hyperglycaemia and insulin resistance, measured as continuous variables, with incident depressive symptoms over 4 years of follow-up.

Methods
We used data from the longitudinal population-based Maastricht Study (n = 2848; mean age 59.9 ± 8.1 years, 48.8% women, 265 incident depression cases, 10,932 person-years of follow-up). We assessed hyperglycaemia by fasting and 2 h post-load OGTT glucose levels, HbA1c and skin autofluorescence (reflecting AGEs) at baseline. We used the Matsuda insulin sensitivity index and HOMA-IR to calculate insulin resistance at baseline. Depressive symptoms (nine-item Patient Health Questionnaire score ≥10) were assessed at baseline and annually over 4 years. We used Cox regression analyses, and adjusted for demographic, cardiovascular and lifestyle risk factors.

Results
Fasting plasma glucose, 2 h post-load glucose and HbA1c levels were associated with an increased risk for incident depressive symptoms after full adjustment (HR 1.20 [95% CI 1.08, 1.33]; HR 1.25 [1.08, 1.44]; and HR 1.22 [1.09, 1.37] per SD, respectively), while skin autofluorescence, insulin sensitivity index and HOMA-IR were not (HR 0.99 [0.86, 1.13]; HR 1.02 [0.85, 1.25]; and HR 0.93 [0.81, 1.08], per SD, respectively).

Conclusions/interpretation
The observed temporal association between hyperglycaemia and incident depressive symptoms in this study supports the presence of a mechanistic link between hyperglycaemia and the development of depressive symptoms.
Existence and uniqueness of the Liouville quantum gravity metric for $$\gamma \in (0,2)$$
Authors: Gwynne Ewain , Miller Jason 
Published: August 2020

AbstractWe show that for each $$\gamma \in (0,2)$$

γ
∈
(
0
,
2
)

, there is a unique metric (i.e., distance function) associated with $$\gamma $$
γ
-Liouville quantum gravity (LQG). More precisely, we show that for the whole-plane Gaussian free field (GFF) h, there is a unique random metric $$D_h$$

D
h

associated with the Riemannian metric tensor “$$e^{\gamma h} (dx^2 + dy^2)$$

e

γ
h

(
d

x
2

+
d

y
2

)

” on $${\mathbb {C}}$$
C
which is characterized by a certain list of axioms: it is locally determined by h and it transforms appropriately when either adding a continuous function to h or applying a conformal automorphism of $$\mathbb {C}$$
C
(i.e., a complex affine transformation). Metrics associated with other variants of the GFF can be constructed using local absolute continuity. The $$\gamma $$
γ
-LQG metric can be constructed explicitly as the scaling limit of Liouville first passage percolation (LFPP), the random metric obtained by exponentiating a mollified version of the GFF. Earlier work by Ding et al. (Tightness of Liouville first passage percolation for $$\gamma \in (0,2)$$

γ
∈
(
0
,
2
)

, 2019. arXiv:1904.08021) showed that LFPP admits non-trivial subsequential limits. This paper shows that the subsequential limit is unique and satisfies our list of axioms. In the case when $$\gamma = \sqrt{8/3}$$

γ
=

8
/
3

, our metric coincides with the $$\sqrt{8/3}$$

8
/
3

-LQG metric constructed in previous work by Miller and Sheffield, which in turn is equivalent to the Brownian map for a certain variant of the GFF. For general $$\gamma \in (0,2)$$

γ
∈
(
0
,
2
)

, we conjecture that our metric is the Gromov–Hausdorff limit of appropriate weighted random planar map models, equipped with their graph distance. We include a substantial list of open problems.