bluuebunny/crossref_metadata_2025_split huggingface dataset:
Associations of media use and early childhood development: cross-sectional findings from the LIFE Child study
Authors: Schwarzer Clarissa , Grafe Nico , Hiemisch Andreas , Kiess Wieland , Poulain Tanja 
Published: March 2021

Abstract
Background
Excessive media usage affects children’s health. This study investigated associations between children’s and mother’s media use, parent–child interactions, and early-childhood development outcomes.

Methods
Two hundred and ninety-six healthy 2–5-year-old preschoolers (52.4% male, mean age = 3.5 years) and 224 mothers from the LIFE Child cohort study were analyzed. Screen times and parent–child interactions were assessed using standardized parental questionnaires. Developmental skills were investigated using the standardized development test ET 6-6-R.

Results
High screen times in children (>1 h/day) were significantly associated with lower percentile ranks in cognition (b = −10.96, p < 0.01), language (b = −12.88, p < 0.01), and social–emotional skills (b = −7.80, p = 0.05). High screen times in mothers (>5 h/day) were significantly associated with high media use by children (OR = 3.86, p < 0.01). Higher parent–child interaction scores were significantly associated with better body motor (b = 0.41, p = 0.05), cognition (b = 0.57, p < 0.01), language (b = 0.48, p = 0.02), and social–emotional outcomes (b = 0.80, p < 0.01) in children.

Conclusions
Public health strategies should seek to educate caregivers as competent mediators for their children’s media habits, with focus on the need for children to have frequent parent–child interactions.

Impact

High media usage in children is related to poorer cognition, language, and social–emotional skills.

More frequent parent–child interactions are associated with better body motor, cognition, language, and social–emotional skills in children.

High level of media use in mothers is not directly related to children’s development outcomes but is directly related to high media usage of children.

Public health strategies should seek to raise media awareness and management in both parents and children.
Data-driven control of complex networks
Authors: Baggio Giacomo , Bassett Danielle S. , Pasqualetti Fabio 
Published: March 2021

AbstractOur ability to manipulate the behavior of complex networks depends on the design of efficient control algorithms and, critically, on the availability of an accurate and tractable model of the network dynamics. While the design of control algorithms for network systems has seen notable advances in the past few years, knowledge of the network dynamics is a ubiquitous assumption that is difficult to satisfy in practice. In this paper we overcome this limitation, and develop a data-driven framework to control a complex network optimally and without any knowledge of the network dynamics. Our optimal controls are constructed using a finite set of data, where the unknown network is stimulated with arbitrary and possibly random inputs. Although our controls are provably correct for networks with linear dynamics, we also characterize their performance against noisy data and in the presence of nonlinear dynamics, as they arise in power grid and brain networks.
T-cell CX3CR1 expression as a dynamic blood-based biomarker of response to immune checkpoint inhibitors
Authors: Yamauchi Takayoshi , Hoki Toshifumi , Oba Takaaki , Jain Vaibhav , Chen Hongbin , Attwood Kristopher , Battaglia Sebastiano , George Saby , Chatta Gurkamal , Puzanov Igor , Morrison Carl , Odunsi Kunle , Segal Brahm H. , Dy Grace K. , Ernstoff Marc S. , Ito Fumito 
Published: March 2021

AbstractImmune checkpoint inhibitors (ICI) have revolutionized treatment for various cancers; however, durable response is limited to only a subset of patients. Discovery of blood-based biomarkers that reflect dynamic change of the tumor microenvironment, and predict response to ICI, will markedly improve current treatment regimens. Here, we investigate CX3C chemokine receptor 1 (CX3CR1), a marker of T-cell differentiation, as a predictive correlate of response to ICI therapy. Successful treatment of tumor-bearing mice with ICI increases the frequency and T-cell receptor clonality of the peripheral CX3CR1+CD8+ T-cell subset that includes an enriched repertoire of tumor-specific and tumor-infiltrating CD8+ T cells. Furthermore, an increase in the frequency of the CX3CR1+ subset in circulating CD8+ T cells early after initiation of anti-PD-1 therapy correlates with response and survival in patients with non-small cell lung cancer. Collectively, these data support T-cell CX3CR1 expression as a blood-based dynamic early on-treatment predictor of response to ICI therapy.
Efficient and bright warm-white electroluminescence from lead-free metal halides
Authors: Chen Hong , Zhu Lin , Xue Chen , Liu Pinlei , Du Xuerong , Wen Kaichuan , Zhang Hao , Xu Lei , Xiang Chensheng , Lin Chen , Qin Minchao , Zhang Jing , Jiang Tao , Yi Chang , Cheng Lu , Zhang Chenglong , Yang Pinghui , Niu Meiling , Xu Wenjie , Lai Jingya , Cao Yu , Chang Jin , Tian He , Jin Yizheng , Lu Xinhui , Jiang Lang , Wang Nana , Huang Wei , Wang Jianpu 
Published: March 2021

AbstractSolution-processed metal-halide perovskites are emerging as one of the most promising materials for displays, lighting and energy generation. Currently, the best-performing perovskite optoelectronic devices are based on lead halides and the lead toxicity severely restricts their practical applications. Moreover, efficient white electroluminescence from broadband-emission metal halides remains a challenge. Here we demonstrate efficient and bright lead-free LEDs based on cesium copper halides enabled by introducing an organic additive (Tween, polyethylene glycol sorbitan monooleate) into the precursor solutions. We find the additive can reduce the trap states, enhancing the photoluminescence quantum efficiency of the metal halide films, and increase the surface potential, facilitating the hole injection and transport in the LEDs. Consequently, we achieve warm-white LEDs reaching an external quantum efficiency of 3.1% and a luminance of 1570 cd m−2 at a low voltage of 5.4 V, showing great promise of lead-free metal halides for solution-processed white LED applications.
pHmScarlet is a pH-sensitive red fluorescent protein to monitor exocytosis docking and fusion steps
Authors: Liu Anyuan , Huang Xiaoshuai , He Wenting , Xue Fudong , Yang Yanrui , Liu Jiajia , Chen Liangyi , Yuan Lin , Xu Pingyong 
Published: March 2021

AbstractpH-sensitive fluorescent proteins (FPs) are highly advantageous for the non-invasive monitoring of exocytosis events. Superecliptic pHluorin (SEP), a green pH-sensitive FP, has been widely used for imaging single-vesicle exocytosis. However, the docking step cannot be visualized using this FP, since the fluorescence signal inside vesicles is too low to be observed during docking process. Among the available red pH-sensitive FPs, none is comparable to SEP for practical applications due to unoptimized pH-sensitivity and fluorescence brightness or severe photochromic behavior. In this study, we engineer a bright and photostable red pH-sensitive FP, named pHmScarlet, which compared to other red FPs has higher pH sensitivity and enables the simultaneous detection of vesicle docking and fusion. pHmScarlet can also be combined with SEP for dual-color imaging of two individual secretory events. Furthermore, although the emission wavelength of pHmScarlet is red-shifted compared to that of SEP, its spatial resolution is high enough to show the ring structure of vesicle fusion pores using Hessian structured illumination microscopy (Hessian-SIM).
Minimally invasive delivery of therapeutic agents by hydrogel injection into the pericardial cavity for cardiac repair
Authors: Zhu Dashuai , Li Zhenhua , Huang Ke , Caranasos Thomas G. , Rossi Joseph S. , Cheng Ke 
Published: March 2021

AbstractCardiac patches are an effective way to deliver therapeutics to the heart. However, such procedures are normally invasive and difficult to perform. Here, we develop and test a method to utilize the pericardial cavity as a natural “mold” for in situ cardiac patch formation after intrapericardial injection of therapeutics in biocompatible hydrogels. In rodent models of myocardial infarction, we demonstrate that intrapericardial injection is an effective and safe method to deliver hydrogels containing induced pluripotent stem cells-derived cardiac progenitor cells or mesenchymal stem cells-derived exosomes. After injection, the hydrogels form a cardiac patch-like structure in the pericardial cavity, mitigating immune response and increasing the cardiac retention of the therapeutics. With robust cardiovascular repair and stimulation of epicardium-derived cells, the delivered therapeutics mitigate cardiac remodeling and improve cardiac functions post myocardial infarction. Furthermore, we demonstrate the feasibility of minimally-invasive intrapericardial injection in a clinically-relevant porcine model. Collectively, our study establishes intrapericardial injection as a safe and effective method to deliver therapeutic-bearing hydrogels to the heart for cardiac repair.
Predictive learning as a network mechanism for extracting low-dimensional latent space representations
Authors: Recanatesi Stefano , Farrell Matthew , Lajoie Guillaume , Deneve Sophie , Rigotti Mattia , Shea-Brown Eric 
Published: March 2021

AbstractArtificial neural networks have recently achieved many successes in solving sequential processing and planning tasks. Their success is often ascribed to the emergence of the task’s low-dimensional latent structure in the network activity – i.e., in the learned neural representations. Here, we investigate the hypothesis that a means for generating representations with easily accessed low-dimensional latent structure, possibly reflecting an underlying semantic organization, is through learning to predict observations about the world. Specifically, we ask whether and when network mechanisms for sensory prediction coincide with those for extracting the underlying latent variables. Using a recurrent neural network model trained to predict a sequence of observations we show that network dynamics exhibit low-dimensional but nonlinearly transformed representations of sensory inputs that map the latent structure of the sensory environment. We quantify these results using nonlinear measures of intrinsic dimensionality and linear decodability of latent variables, and provide mathematical arguments for why such useful predictive representations emerge. We focus throughout on how our results can aid the analysis and interpretation of experimental data.
Staphylococcus aureus induces an itaconate-dominated immunometabolic response that drives biofilm formation
Authors: Tomlinson Kira L. , Lung Tania Wong Fok , Dach Felix , Annavajhala Medini K. , Gabryszewski Stanislaw J. , Groves Ryan A. , Drikic Marija , Francoeur Nancy J. , Sridhar Shwetha H. , Smith Melissa L. , Khanal Sara , Britto Clemente J. , Sebra Robert , Lewis Ian , Uhlemann Anne-Catrin , Kahl Barbara C. , Prince Alice S. , Riquelme Sebastián A. 
Published: March 2021

AbstractStaphylococcus aureus is a prominent human pathogen that readily adapts to host immune defenses. Here, we show that, in contrast to Gram-negative pathogens, S. aureus induces a distinct airway immunometabolic response dominated by the release of the electrophilic metabolite, itaconate. The itaconate synthetic enzyme, IRG1, is activated by host mitochondrial stress, which is induced by staphylococcal glycolysis. Itaconate inhibits S. aureus glycolysis and selects for strains that re-direct carbon flux to fuel extracellular polysaccharide (EPS) synthesis and biofilm formation. Itaconate-adapted strains, as illustrated by S. aureus isolates from chronic airway infection, exhibit decreased glycolytic activity, high EPS production, and proficient biofilm formation even before itaconate stimulation. S. aureus thus adapts to the itaconate-dominated immunometabolic response by producing biofilms, which are associated with chronic infection of the human airway.
Blood pressure variability is related to faster cognitive decline in ischemic stroke patients: PICASSO subanalysis
Authors: Kim Yerim , Lim Jae-Sung , Oh Mi Sun , Yu Kyung-Ho , Lee Ji Sung , Park Jong-Ho , Kim Yong-Jae , Rha Joung-Ho , Hwang Yang-Ha , Heo Sung Hyuk , Ahn Seong Hwan , Lee Ju-Hun , Kwon Sun U. 
Published: March 2021

AbstractBlood pressure variability (BPV) is associated with higher cardiovascular morbidity risks; however, its association with cognitive decline remains unclear. We investigated whether higher BPV is associated with faster declines in cognitive function in ischemic stroke (IS) patients. Cognitive function was evaluated between April 2010 and August 2015 using the Mini-mental State Examination (MMSE) and Montreal Cognitive Assessment in 1,240 Korean PICASSO participants. Patients for whom baseline and follow-up cognitive test results and at least five valid BP readings were available were included. A restricted maximum likelihood–based Mixed Model for Repeated Measures was used to compare changes in cognitive function over time. Among a total of 746 participants (64.6 ± 10.8 years; 35.9% female). Baseline mean-MMSE score was 24.9 ± 4.7. The median number of BP readings was 11. During a mean follow-up of 2.6 years, mean baseline and last follow-up MMSE scores were 25.4 ± 4.8 vs. 27.8 ± 4.4 (the lowest BPV group) and 23.9 ± 5.2 vs. 23.2 ± 5.9 (the highest BPV group). After adjusting for multiple variables, higher BPV was independently associated with faster cognitive decline over time. However, no significant intergroup difference in cognitive changes associated with mean systolic BP was observed. Further research is needed to elucidate how BPV might affect cognitive function.
Bayesian Optimization of Bose-Einstein Condensates
Authors: Bakthavatchalam Tamil Arasan , Ramamoorthy Suriyadeepan , Sankarasubbu Malaikannan , Ramaswamy Radha , Sethuraman Vijayalakshmi 
Published: March 2021

AbstractMachine Learning methods are emerging as faster and efficient alternatives to numerical simulation techniques. The field of Scientific Computing has started adopting these data-driven approaches to faithfully model physical phenomena using scattered, noisy observations from coarse-grained grid-based simulations. In this paper, we investigate data-driven modelling of Bose-Einstein Condensates (BECs). In particular, we use Gaussian Processes (GPs) to model the ground state wave function of BECs as a function of scattering parameters from the dimensionless Gross Pitaveskii Equation (GPE). Experimental results illustrate the ability of GPs to accurately reproduce ground state wave functions using a limited number of data points from simulations. Consistent performance across different configurations of BECs, namely Scalar and Vectorial BECs generated under different potentials, including harmonic, double well and optical lattice potentials pronounces the versatility of our method. Comparison with existing data-driven models indicates that our model achieves similar accuracy with only a small fraction ($$\frac{1}{50}$$

1
50

th) of data points used by existing methods, in addition to modelling uncertainty from data. When used as a simulator post-training, our model generates ground state wave functions $$36 \times $$

36
×

faster than Trotter Suzuki, a numerical approximation technique that uses Imaginary time evolution. Our method is quite general; with minor changes it can be applied to similar quantum many-body problems.
Synthesis of tetrazolo[1,5-a]pyrimidine-6-carbonitriles using HMTA-BAIL@MIL-101(Cr) as a superior heterogeneous catalyst
Authors: Abdollahi-Basir Mohammad Hossein , Mirhosseini-Eshkevari Boshra , Zamani Farzad , Ghasemzadeh Mohammad Ali 
Published: March 2021

AbstractA one-pot three component reaction of benzaldehydes, 1H-tetrazole-5-amine, and 3-cyanoacetyl indole in the presence of a new hexamethylenetetramine-based ionic liquid/MIL-101(Cr) metal–organic framework as a recyclable catalyst was explored. This novel catalyst, which was fully characterized by XRD, FE-SEM, EDX, FT-IR, TGA, BET, and TEM exhibited outstanding catalytic activity for the preparation of a range of pharmaceutically important tetrazolo[1,5-a]pyrimidine-6-carbonitriles with good to excellent yields in short reaction time.
Analysis of column reactor results with organic decay by native organic microbiota and varying permeability
Authors: da Silva Maciel Fernanda Costa , Machado Sandro Lemos , de Souza Queiroz Antonio Fernando , Lima Fernando Antonio Leite Vieira 
Published: March 2021

AbstractField bio-remediation techniques (FBRT) can be a low cost method to avoid the removal of top layers of soil which are rich in organic matter and bio diversity. The use of native microorganisms in FBRT is preferable because non-indigenous species can transfer their genetic material to the environment with negative impacts on the local ecological equilibrium. Petroleum Produced Water (PPW) is an important pollutant source in onshore production areas. However, due to high sodium concentrations in PPW and the occurrence of organic matter in dissolved and dispersed forms, obtaining pollutant transport parameters may be a difficult task. Results of column tests performed using a natural soil permeated by PPW are presented. All the samples presented a permeability decrease over time and the total hydrocarbon petroleum (TPH) breakthrough curves presented evidence of biological decay. Soil samples underwent biological characterization after tests (Metagenomic analyses and cultural media tests). Curves were modelled in an incremental way using a non-constant decay rate to better simulate the growing process of the microorganisms and consider the occurrence of varying velocity/permeability. Biological characterization results indicate the native organisms that are potentially more able to degrade PPW, including four bacteria (Bacillus and Lysinibacillus genus) and two fungi species (Malassezia and Talaromyces genus) that have not previously been mentioned in the consulted literature. The obtained results contribute to the development of more sustainable FBRTs focusing on native microorganisms, already adapted to the local environmental conditions.
18S rRNA gene sequences of leptocephalus gut contents, particulate organic matter, and biological oceanographic conditions in the western North Pacific
Authors: Watanabe Tsuyoshi , Nagai Satoshi , Kawakami Yoko , Asakura Taiga , Kikuchi Jun , Inaba Nobuharu , Taniuchi Yukiko , Kurogi Hiroaki , Chow Seinen , Tomoda Tsutomu , Ambe Daisuke , Hasegawa Daisuke 
Published: March 2021

AbstractEel larvae apparently feed on marine snow, but many aspects of their feeding ecology remain unknown. The eukaryotic 18S rRNA gene sequence compositions in the gut contents of four taxa of anguilliform eel larvae were compared with the sequence compositions of vertically sampled seawater particulate organic matter (POM) in the oligotrophic western North Pacific Ocean. Both gut contents and POM were mainly composed of dinoflagellates as well as other phytoplankton (cryptophytes and diatoms) and zooplankton (ciliophoran and copepod) sequences. Gut contents also contained cryptophyte and ciliophoran genera and a few other taxa. Dinoflagellates (family Gymnodiniaceae) may be an important food source and these phytoplankton were predominant in gut contents and POM as evidenced by DNA analysis and phytoplankton cell counting. The compositions of the gut contents were not specific to the species of eel larvae or the different sampling areas, and they were most similar to POM at the chlorophyll maximum in the upper part of the thermocline (mean depth: 112 m). Our results are consistent with eel larvae feeding on marine snow at a low trophic level, and feeding may frequently occur in the chlorophyll maximum in the western North Pacific.
Validity and reliability of myotonometry for assessing muscle viscoelastic properties in patients with stroke: a systematic review and meta-analysis
Authors: Garcia-Bernal Maria-Isabel , Heredia-Rizo Alberto Marcos , Gonzalez-Garcia Paula , Cortés-Vega María-Dolores , Casuso-Holgado María Jesús 
Published: March 2021

AbstractThere is a lack of consensus about the measurement of the muscle viscoelastic features in stroke patients. Additionally, the psychometric properties of the most-commonly used clinical tools remain controversial. Our objective is to investigate the validity and reliability of myotonometry to assess viscoelastic muscle features in stroke survivors. Pubmed, PEDro, Scopus and Cinahl were systematically searched to include studies reporting the psychometric properties of myotonometric devices used in people after stroke. The QUADAS-2 and the COSMIN checklists were used to assess the methodological quality of the studies and the psychometric properties of myotonometry. Nine studies were included in the qualitative synthesis and data from five of these were pooled in a meta-analysis. Overall, low to moderate risk of bias and applicability concerns were observed. Pooled data from intra-rater reliability for muscle tone showed a mean coefficient of correlation of 0.915 (95% CI: 0.880–0.940, I 2 = 69.2%) for upper limbs, and a mean coefficient of 0.785 (95%CI: 0.708–0.844, I 2 = 4.02%) for lower limbs. Myotonometry seems to be a valid and reliable complementary tool to assess muscle viscoelastic properties in stroke survivors, although definite conclusions about concurrent validity need further research.
Identification of the key characteristics ofBifidobacterium longumstrains for the alleviation of ulcerative colitis
Authors: Zhang Chengcheng , Zhao Yan , Jiang Jinchi , Yu Leilei , Tian Fengwei , Zhao Jianxin , Zhang Hao , Chen Wei , Zhai Qixiao 
Published: March 2021

Identification of the key characteristics of Bifidobacterium longum strains for the alleviation of ulcerative colitis.
Studies on situation reasoning approach of autonomous underwater vehicle under uncertain environment
Authors: Yin Lili , Chen Deyun , Gu Hengwen , Guan Ning , Zhang Rubo , Hou Handan 
Published: March 2021

AbstractThe purpose of this study is to provide a situation reasoning module for autonomous underwater vehicle (AUV), to make decision‐making agents know what is the current situation, what needs to be done in the present situation, and what is the risk of task present situation. This will enhance efficiency for AUV. Situation reasoning for AUV aims to communicate mission assessments to decision‐making agents. Thus, in solving this problem, it is important to design a new situation reasoning module for AUV. This article is presenting the situation reasoning module for AUV, which includes uncertain event detection, uncertain event recognition and ontology model of the situation. The article concludes by demonstrating the benefits of the situation reasoning module in a real‐world scenario. A situation reasoning simulation is demonstrated in an AUV while performing a complex mission. The approach was validated by marine experiments and simulating experiments for AUV. Results show the effectiveness of situation reasoning approach.