bluuebunny/crossref_metadata_2025 huggingface dataset:
Adipose Tissue Dysfunction: Impact on Metabolic Changes?
Authors: Morais Jennifer Beatriz Silva , Dias Thaline Millany da Silva , Cardoso Bruna Emanuele Pereira , de Paiva Sousa Mickael , Sousa Thayanne Gabryelle Visgueira de , Araújo Diana Stefany Cardoso de , Marreiro Dilina do Nascimento
Published: August 2022

Adipose tissue is a metabolically dynamic organ that is the primary site of storage for excess energy, but it serves as an endocrine organ capable of synthesizing a number of biologically active compounds that regulate metabolic homeostasis. However, when the capacity of expansion of this tissue exceeds, dysfunction occurs, favoring ectopic accumulation of fat in the visceral, which has been implicated in several disease states, most notably obesity. This review highlights the mechanisms involved in the structure of adipose tissue, tissue expandability, adipocyte dysfunction, as well as the impact of these events on the manifestation of important metabolic disorders associated with adipose tissue dysfunction. A literature search using Pubmed, Web of Science, Scopus, and Cochrane databases were used to identify relevant studies, using clinical trials, experimental studies in animals and humans, case-control studies, case series, letters to the editor, and review articles published in English, without restrictions on year of publication. The excessive ectopic lipid accumulation leads to local inflammation and insulin resistance. Indeed, overnutrition triggers uncontrolled inflammatory responses white adipose tissue, leading to chronic low-grade inflammation, therefore fostering the progression of important metabolic disorders. Thus, it is essential to advance the understanding of the molecular mechanisms involved in adipose tissue dysfunction in order to mitigate the negative metabolic consequences of obesity.
Post-EMR for colorectal polyps, thermal ablation of defects reduces adenoma recurrence: A meta-analysis
Authors: Kandel Pujan , Hussain Murtaza , Yadav Deepesh , Dhungana Santosh K. , Brahmbhatt Bhaumik , Raimondo Massimo , Lukens Frank J. , Bachuwa Ghassan , Wallace Michael B.
Published: August 2022

Background and study aims Adenoma recurrence is one of the key limitations of endoscopic mucosal resection (EMR), which occurs in 15 % to 30 % of cases during first surveillance colonoscopy. The main hypothesis behind adenoma recurrence is leftover micro-adenomas at the margins of post-EMR defects. In this systematic review and meta-analysis, we evaluated the efficacy of snare tip soft coagulation (STSC) at the margins of mucosal defects to reduce adenoma recurrence and bleeding complications.

Methods Electronic databases such as PubMed and the Cochrane library were used for systematic literature search. Studies with polyps only resected by piecemeal EMR and active treatment: with STSC, comparator: non-STSC were included. A random effects model was used to calculate the summary of risk ratio and 95 % confidence intervals. The main outcome of the study was to compare the effect of STSC versus non-STSC with respect to adenoma recurrence at first surveillance colonoscopy after thermal ablation of post-EMR defects.

Results Five studies were included in the systematic review and meta-analysis. The total number patients who completed first surveillance colonoscopy (SC1) in the STSC group was 534 and in the non-STSC group was 514. The pooled adenoma recurrence rate was 6 % (37 of 534 cases) in the STSC arm and 22 % (115 of 514 cases) in the non-STSC arm, (odds ratio [OR] 0.26, 95 % confidence interval [CI], 0.16–0.41, P = 0.001). The pooled delayed post-EMR bleeding rate 19 % (67 of 343) in the STSC arm and 22 % (78 of 341) in the non-STSC arm (OR 0.82, 95 %CI, 0.57–1.18).

Conclusions Thermal ablation of post-EMR defects significantly reduces adenoma recurrence at first surveillance colonoscopy.
Health Information Technology Use among Chronic Disease Patients: An Analysis of the United States Health Information National Trends Survey
Authors: Rajamani Geetanjali , Lindemann Elizabeth , Evans Michael D. , Pillai Raghu , Badlani Sameer , Melton Genevieve B.
Published: August 2022

Background Chronic disease is the leading cause of mortality in the United States. Health information technology (HIT) tools show promise for improving disease management.

Objectives This study aims to understand the following: (1) how self-perceptions of health compare between those with and without disease; (2) how HIT usage varies between chronic disease profiles (diabetes, hypertension, cardiovascular disease, pulmonary disease, depression, cancer, and comorbidities); (3) how HIT trends have changed in the past 6 years; and (4) the likelihood that a given chronic disease patient uses specific HIT tools.

Methods The Health Information National Trends Survey (HINTS) inclusive of 2014 to 2020 served as the primary data source with statistical analysis completed using Stata. Bivariate analyses and two-tailed t-tests were conducted to compare self-perceived health and HIT usage to chronic disease. Logistic regression models were created to examine the odds of a specific patient using various forms of HIT, controlling for demographics and comorbidities.

Results Logistic regression models controlling for sociodemographic factors and comorbidities showed that pulmonary disease, depression, and cancer patients had an increased likelihood of using HIT tools, for example, depression patients had an 81.1% increased likelihood of looking up health information (p < 0.0001). In contrast, diabetic, high blood pressure, and cardiovascular disease patients appeared to use HIT tools at similar rates to patients without chronic disease. Overall HIT usage has increased during the timeframe examined.

Conclusion This study demonstrates that certain chronic disease cohorts appear to have greater HIT usage than others. Further analysis should be done to understand what factors influence patients to utilize HIT which may provide additional insights into improving design and user experience for other populations with the goal of improving management of disease. Such analyses could also establish a new baseline to account for differences in HIT usage as a direct consequence of the novel coronavirus disease 2019 (COVID-19) pandemic.
Observation of a solid phase under measuring the 3He diffusion coefficient in the nanopores of the MCM-41 adsorbent
Authors: Birchenko A. P. , Maidanov V. A. , Mikhin N. P. , Sokolov S. S. , Sopelnyk Ya. Yu.
Published: August 2022

Using nuclear magnetic resonance, the stimulated spin-echo method was applied to measure the diffusion coefficient in a 3He monolayer adsorbed inside cylindrical pores (channel diameter 25 Å) of a new-generation nanostructured adsorbent MCM-41. Helium was let into the sample in small portions, which made it possible to change in a controlled way the coverage of the walls of the cavities in the adsorbent. It is found that the measured dependence of the stimulated spin-echo amplitude on the square of the magnetic field gradient is exponential. The nature of this dependence made it possible to determine the diffusion coefficient in the adsorbed monolayer. The value of this coefficient turned out to be close to the diffusion coefficient in solid helium, which indicates that the first 3He monolayer on the inner surface of the cylindrical cavity is solid. This conclusion was confirmed when calculating the pressure acting on the helium monolayer due to the van der Waals forces from the adsorbent substance.
Helium in uranium dioxide: Computer simulation (Review Article)
Authors: Yakub E. , Yakub L.
Published: August 2022

Recent results of experimental studies, as well as computer modeling of the helium behavior in uranium-based nuclear fuels, are reviewed. Potential models of interaction of helium atoms, uranium and oxygen ions, results of application and perspectives of computer simulation methods in prediction of the most important properties of solid solutions of helium, such as its solubility and diffusion coefficients in stoichiometric and nonstoichiometric uranium dioxide, are discussed.
Hydrogen targetry in laser-plasma physics
Authors: Chagovets Timofej
Published: August 2022

The development of various types of cryogenic target systems opens new opportunities for laser-matter interaction experiments. Existing systems of solid hydrogen targets, which are used with high-power laser systems for various experiments, including laser acceleration of protons, are considered. The details of target formation techniques are discussed. We also discussed some most challenging issues in target fabrication at low temperature and laser operation high repetition rate.
Impact of demographic variability on the disease dynamics for honeybee model
Authors: Sarathi Mandal Partha , Maity Sunil
Published: August 2022

For the last few years, annual honeybee colony losses have been center of key interest for many researchers throughout the world. The spread of the parasitic mite and its interaction with specific honeybee viruses carried by Varroa mites has been linked to the decline of honeybee colonies. In this investigation, we consider honeybee–virus and honeybee–infected mite–virus models. We perform sensitivity analysis locally and globally to see the effect of the parameters on the basic reproduction number for both models and to understand the disease dynamics in detail. We use the continuous-time Markov chain model to develop and analyze stochastic epidemic models corresponding to both deterministic models. By using the disease extinction process, we compare both deterministic and stochastic models. We have observed that the numerically approximated probability of disease extinction based on 30 000 sample paths agrees well with the calculated probability using multitype branching process approximation. In particular, it is observed that the disease extinction probability is higher when infected honeybees spread the disease instead of infected mites. We conduct a sensitivity analysis for the stochastic model also to examine how the system parameters affect the probability of disease extinction. We have also derived the equation for the expected time required to reach disease-free equilibrium for stochastic models. Finally, the effect of the parameters on the expected time is represented graphically.
Fabrication of grooved LGS resonators based high temperature SAW sensors and analysis with FEM simulation
Authors: Shan Qingchuan , Shi Ruchuan , Zhang Qilun , Hao Wenchang , Luo Wei , Han Tao
Published: August 2022

Langasite (LGS) based surface acoustic wave (SAW) sensors are widely used in high temperature circumstances due to their advantages of being passive and wireless. In this research, the platinum electrodes are deposited into the grooves of the LGS instead of on the surface to further improve the acoustic properties and prolong the lifetime of the resonators at high temperature. Proper MEMS fabrication techniques are proposed to fabricate such structures. The result of every step is evaluated, and the corresponding process parameters are optimized. With the optimal processes, two types of resonators with different Euler angles of (0∘, 22∘, 30∘) and (0∘, 22∘, 90∘) are fabricated on the LGS substrate. Furthermore, the process-influenced structure parameters such as metal ratio and sidewall angle are well investigated via a weak form nonlinear finite element method simulation model. The temperature dependence of the resonance frequency is measured, and the recorded thermal behaviors match well with the prediction of the simulation. In addition, the further endurance test shows that the devices could work at 1000 ∘C for 12 h. This research proves the validity of the grooved resonator structure and the prominent role of the simulation model in further optimizing the LGS-based SAW devices design.
Quantitative signal quality assessment for large-scale continuous scalp electroencephalography from a big data perspective
Authors: Zhao Lingling , Zhang Yufan , Yu Xue , Wu Hanxi , Wang Lei , Li Fali , Duan Mingjun , Lai Yongxiu , Liu Tiejun , Dong Li , Yao Dezhong
Published: August 2022

Objective. Despite electroencephalography (EEG) being a widely used neuroimaging technique with an excellent temporal resolution, in practice, the signals are heavily contaminated by artifacts masking responses of interest in an experiment. It is thus essential to guarantee a prompt and effective detection of artifacts that provides quantitative quality assessment (QA) on raw EEG data. This type of pipeline is crucial for large-scale EEG studies. However, current EEG QA studies are still limited. Approach. In this study, combined from a big data perspective, we therefore describe a quantitative signal quality assessment pipeline, a stable and general threshold-based QA pipeline that automatically integrates artifact detection and new QA measures to assess continuous resting-state raw EEG data. One simulation dataset and two resting-state EEG datasets from 42 healthy subjects and 983 clinical patients were utilized to calibrate the QA pipeline. Main Results. The results demonstrate that (1) the QA indices selected are sensitive: they almost strictly and linearly decrease as the noise level increases; (2) stable, replicable QA thresholds are valid for other experimental and clinical EEG datasets; and (3) use of the QA pipeline on these datasets reveals that high-frequency noises are the most common noises in EEG practice. The QA pipeline is also deployed in the WeBrain cloud platform (https://webrain.uestc.edu.cn/, the Chinese EEG Brain Consortium portal). Significance. These findings suggest that the proposed QA pipeline may be a stable and promising approach for quantitative EEG signal quality assessment in large-scale EEG studies.
Superconductivity of disordered NbN films deposited on magnesium oxide and oxidized silicon substrates
Authors: Zhang Lu , You Lixing , Chen Lei , Peng Wei , Wang Zhen
Published: August 2022

This study investigates the evolution of superconducting properties as a function of disorder in epitaxial and polycrystalline niobium nitride (NbN) thin films grown on MgO and SiO2/Si substrates, respectively. By reducing the film thickness from 100 to 4 nm, the effective disorder in these two sets of films encompasses a large range, with the Ioffe–Regel parameter in the range of 5.7–9.3 and 1.5–3.0, respectively. Moreover, the density of states at the Fermi level [N(0)] of epitaxial NbN films decreases from 1.91 × 1028 to 1.46 × 1028 states eV−1m−3 with the superconducting transition temperature (Tc
) ranging from 16.0 to 11.8 K. In contrast, the N(0) of polycrystalline NbN films decreases from 2.18 × 1028 to 1.80 × 1028 states eV−1m−3 with Tc
ranging from 14.9 to 2.56 K. The experimental results reveal that the Tc
of NbN films with different thicknesses is mainly controlled by N(0), and the greater Coulomb pseudopotential (μ*) in the polycrystalline films leads to lower Tc
and larger resistivity. The changes in N(0) and μ* should collectively account for the reduction of Tc
with disorder in NbN thin films.
A general scenario of tunneling time in different energy regimes
Authors: Li Sheng-Chang
Published: August 2022

We theoretically study the tunneling time by investigating a wave packet of Bose-condensed atoms passing through a square barrier. We find that the tunneling time exhibits different scaling laws in different energy regimes. For negative incident energy of the wave packet, counterintuitively, the tunneling time decreases very rapidly with decreasing incident velocity. In contrast, for positive incident energy smaller than the barrier height, the tunneling time increases slowly and then reaches a maximum, which is in agreement with the Larmor clock experiments. The effect of the barrier width related to the uncertainty principle on the maximum tunneling time is also addressed. Our work provides a general scenario of tunneling time that can be used to understand and explain the controversy over tunneling time.
Thermal local Fisher information and quantum uncertainty in Heisenberg model
Authors: Mohamed A-B A , Eleuch H
Published: August 2022

This study explores the spontaneous emergence of local Fisher information and local quantum uncertainty beyond entanglement in a noisy two-qubit Heisenberg XXX model with Dzyaloshinskii-Moria (DM) and Kaplan-Shekhtman-Entin-Wohlman-Aharony (KSEA) interactions. Local quantum Fisher information, local quantum uncertainty, and logarithmic negativity are used to examine two-spin non-locality. We find that by employing strong two-spin, Dzyaloshinskii- Moriya, and Kaplan-Shekhtman-Entin-Wohlman-Aharony interactions, we can prevent noise-induced losses in local Fisher information, local quantum uncertainty, and logarithmic negativity. The robustness of the two-spin non-localities is greater for a strong spin’s coupling strength than for the strong DM and KSEA interactions. Local Fisher information and local quantum uncertainty, as well as logarithmic-negativity, display asymmetric behaviors with respect to two-spin coupling and symmetric behaviors with respect to the Dzyaloshinskii-Moriya and Kaplan-Shekhtman-Entin-Wohlman-Aharony interactions. At high bath temperatures, the phenomenon of sudden-death two-spin entanglement emerges. Furthermore, by combining the parameters of the strong two-spin, DM, and KSEA interactions, the robustness of the produced two-spin non-localities can be improved.
Role of coordination site in governing the structural, electronic and optical properties of Ca-doped strontium barium niobate
Authors: Ahmad Tahir , Tomar Monika , Jindal Kajal , Jha Pradip K
Published: August 2022

The structural, electronic and optical properties of Ca doped SBN60 are studied via first principle calculations based on density functional theory. Influence of Sr site substitution by Ca at square and pentagonal sites has been studied. The bandgap of Ca incorporated SBN is found to depend largely on the coordination of site of doping, where the bandgap increases for the square site substitution and decreases for the pentagonal site substitution. The formation energy calculations reveal that the Ca is more favorable to occupy the pentagonal site which is supported by the UV-Visible spectra study of the thin films of doped and undoped SBN60 grown using PLD technique in which a decrease in the bandgap can be seen in Ca doped SBN. A detailed analysis is provided for the changes in structural parameters upon doping at square and pentagonal sites. Dependence of the optical properties like dielectric constant, refractive index, reflectance and absorption of doped and undoped SBN60 on different polarization directions ‘(100), (010) and (001)’ are reported. The anisotropy in the optical properties can be observed which makes Ca doped SBN a promising material for optoelectronic device applications.
Dark sector domain walls could explain the observed planes of satellites
Authors: Naik Aneesh P. , Burrage Clare
Published: August 2022

The observed 'planes of satellites' around the Milky Way and other nearby galaxies are notoriously difficult to explain under the ΛCDM paradigm. Here, we propose an alternative solution: domain walls arising in theories with symmetry-breaking scalar fields coupled to matter. Because of the matter coupling, satellite galaxies experience fifth forces as they pass through domain walls, leading to a subset of satellites with orbits confined to the domain wall plane. We demonstrate this effect using simple simulations of a toy model comprising point-like satellites and an infinite domain wall, and explore the efficacy of various planarity metrics in detecting this effect. We believe this is the first potential 'new physics' explanation for the observed planes of satellites which does not do away with dark matter.
The effect of multiple features on the power spectrum in two-field inflation
Authors: Boutivas K. , Dalianis I. , Kodaxis G.P. , Tetradis N.
Published: August 2022

We extend our previous work
on the enhancement of the curvature spectrum during inflation to the two-field case.
We identify the slow-roll parameter η as the quantity
that can trigger the rapid growth of perturbations.
Its two components, η
∥ along the background trajectory
and η
⊥ perpendicular to it, remain small during most of the evolution,
apart from short intervals during which they take large, positive or negative, values.
The typical reason for the appearance of strong features in η
∥ is
sharp steps or inflection points in the inflaton potential,
while η
⊥ grows large during sharp turns in
field space. We focus on the additive effect of several features
leading to the resonant growth of the curvature spectrum.
Three or four features in the evolution of 
η are sufficient in order to induce an enhancement of the
power spectrum by six or seven orders of magnitude, which can
lead to the significant production of primordial black holes and stochastic
gravitational waves.
A big part of our study focuses on understanding the evolution
of the perturbations and the resulting spectra through analytic means.
The presence of multiple features in
the background evolution points to a more complex inflationary paradigm,
which is also more natural in the multi-field case.
The critical examination of this possibility is within
the reach of experiment.
Coherent manipulation of perfect optical vortex via inelastic four-wave mixing in a cold five-level atomic system
Authors: Zhang Tong , Hu Die , Shui Tao , Jiang Li-Bo , Li Ling , Yang Wen-Xing , Liao Yingqi
Published: August 2022

We propose an efficient scheme to manipulate the perfect optical vortex (POV) beam in a cold atomic ensemble with a five-level configuration. The orbital angular momentum can be completely transferred from a POV control beam to the generated mixing field via inelastic four-wave mixing (IFWM) process. It is found that the intensity and helical phase of the generated vortex IFWM field can be coherently controlled by adjusting the relevant parameters, such as the atomic population, and the intensity and detuning of the pumping field. The obtained results can be reasonably explained via the combination of inherent and modal dispersion relation. Our result may find potential applications in POV-based large-particle manipulation and optical communication.
Electric Vehicle Charging Station Load Prediction Based on IWOA-LSSVM Combined Model with Improved Variational Mode Decomposition
Authors: Ru Feng , Yang Xiaoqian , Zou Haoquan , Zhang Lina , Xu Xianfeng
Published: August 2022

Accurately predicting the electric vehicle charging station load is the basis for the optimal design of power supply planning. Aiming at the problem that the load data of electric vehicle charging station has strong randomness and volatility due to the interaction of various factors. The electric vehicle charging load prediction model is constructed, which considers the highest temperature, day type and weather type factors to select similar days. Firstly, an algorithm for optimizing variational modal decomposition parameters with relative entropy is proposed to decompose the extracted similar daily charging load data into multiple sub-sequences. Then, the decomposed data are respectively input into the combined prediction model of the least squares support vector machine optimized by the whale algorithm improved by the adaptive probability threshold and the random difference mutation strategy, and finally the predicted value of each subsequence is superimposed and summed to obtain the final predicted value. Based on the measured charging load data and weather forecast data of an electric vehicle charging station in Shanghai, simulation experiments are carried out to compare and verify the accuracy and effectiveness of the model in this paper.
Lightning Transient Analysis Comparison and Wind Turbine Models Using PSCAD/EMTDC Circuit Simulator
Authors: Chinges Tserensambuu , Li Qingmin , Zhao Jiyao
Published: August 2022

This paper aims to compute the lightning electromagnetic transient overvoltage and current on the wind turbine using the PSCAD/EMTDC simulation program. The double-peaked lightning current, tower, grounding system models, and dangerous situation of the grounding system are investigated by the PSCAD simple circuit branch segment codes and defining components. A comparison analysis has been performed to see the influence of lightning current wave shapes and grounding characteristics. The simulation results show that 43 kA and 31 kA lightning currents produce 200 kV overvoltage on the turbine grounding in case of 1000 Ω·m soil resistivity. However, current amplitudes on the equipotential grounding system become 28 kA and 20 kA. The influencing factors of the surge protection device are determined using good accuracy computer simulation.
Detection of Self-explosive Insulators in Aerial Images Based on Improved YOLO v4
Authors: Yi Li , Jinguo Li , Yongjie Zhai , Ping Meng
Published: August 2022

In view of the low detection efficiency of traditional aerial image-based self-explosive insulators and the need to manually extract the features of self-explosive insulators, a self-explosive insulator detection algorithm based on the improved YOLO v4 is proposed: We use the hybrid data augmentation method to increase the number of defective samples of self-explosive insulators and increase the diversity of self-explosive insulators to improve the detection accuracy of the algorithm. In addition, the channel attention mechanism is combined with the YOLO v4 algorithm to improve the feature extraction capability of algorithms to self-explosion insulators. The proposed algorithm is verified using the expanded self-explosive insulator dataset and the traffic signs dataset TT100K. The experimental results show that the proposed algorithm has a mAP of 92.0 % on the self-explosive insulator dataset and has an F1-score of 78.70% on TT100K dataset, which has positive significance for the research on self-explosive insulator detection.
Hybrid Model Compression for Multi-Task Network
Authors: Xie Min , Sun Weize , Huang Lei
Published: August 2022

In recent years, deep neural networks have made significant achievements in various fields in science and engineering. To achieve outstanding performance, neural network models with very deep structures and an extensive number of parameters are usually used, leading to huge memory storage and computational resources requirements of the hardware systems, and thus preventing them from being deployed in devices with hardware limits. In particular, such problem will be further amplified when multiple neural network models for several tasks are to be integrated into one single platform at the same time. In this paper, a hybrid joint-network optimization model is proposed to solve this multi-task multi-model compression problem. The idea of hard parameter sharing in multi-task learning is adopted. Specifically, we turn the sub-network of the same structure of multiple models into a hybrid network model, in which the same parameters are shared for all the tasks. In addition, a unique sparse matrix for each task is added to each task independently. Experimental results show that the proposed compression methods can not only achieve a high compression ratio but also get performance improvement for some tasks.
Photovoltaic Output Prediction Method Based on Weather Forecast and Machine Learning
Authors: Zhang Kaikai , Zou Guibin
Published: August 2022

This paper conducts prediction research based on the historical power generation data and meteorological data of a photovoltaic power station. The obtained data is firstly classified by season, and the correlation analysis of meteorological factors is carried out. The data closely related to PV generation is selected for prediction, which improves the prediction efficiency. Then the Kmeans algorithm is used to cluster the historical data, and data are divided into four types: sunny, partly cloudy, cloudy, and rainy, further each type of data is separately trained to obtain four training models. The classified data is decomposed by EEMD, and a set of frequency-distributed IMF components and a monotonic distribution of residual components are obtained. Use support vector machine to predict the dimension-reduced components, and reconstruct the result to obtain the final predicted value. After obtaining the future weather forecast data, select the same type of historical data set for model training. The results show that the prediction accuracy will be significantly improved after signal processing in cloudy and rainy weather.
Systematic review: Analysis of the use of D-limonene to Reduce the Environmental Impact of Discarded Expanded Polystyrene (EPS).
Authors: Mollehuara MA , Cuadrado AR , Vidal VL , Camargo SD
Published: August 2022

The article presents a systematic review on the use of D-limonene with the aim of analyzing its efficiency to reduce the environmental impact of expanded polystyrene (EPS). Initially, an analysis of the life cycle of the EPS was carried out in a general way to identify the stage where the greatest impact on the environment is evident. Subsequently, primary sources were examined that raise the issue of reducing EPS using this green solvent, in view of the fact that it generates sustainability through recycling, optimization and application of various methods that could allow the circular economy of this waste in order to be applied in the industrial field and contribute to the socio-environmental aspect. Finally, the importance of this solvent was demonstrated according to the analysis and evaluation of each EPS recycling examining country.
Revealing heterogeneity in correlation times of EGFP encapsulated in complex coacervate core micelles by analysis of fluorescence anisotropies
Authors: Skakun Victor , Digris Anatoli , Nolles Antsje , Borst Jan Willem , Visser Antonie
Published: August 2022

Encapsulation of enhanced green fluorescent protein (EGFP) in complex coacervate core micelles (C3Ms) can be established by mixing EGFP with diblock polymers at equal charge ratio. It has previously been shown that this encapsulation system is highly dynamic, implying existence of different populations; GFP free in solution or complexed with polymers (small complexes) and EGFP encapsulated in C3Ms. We performed time resolved fluorescence anisotropy experiments to determine the relative populations of EGFP encapsulated in C3Ms using three different fluorescence anisotropy decay analysis methods. First, Maximum Entropy Method (MEM) data analysis was employed for five different EGFP concentrations in C3Ms that were mixed with dark fluorescent proteins (10, 20, 30, 40 and 50% EGFP, respectively). In all cases, correlation-time distributions between 0.1 and 100 ns (on a logarithmic timescale) are clearly visible showing bimodal distribution. The distribution between 0.1 and 2.0 ns is due to homo-FRET between EGFP molecules packed in micelles and the distribution between 8 and 30 ns coincides with the correlation-time distribution of free EGFP in solution. The fraction of homo-FRET distribution linearly increases with increase of relative micellar EGFP concentrations. These MEM results were corroborated by two different analysis methods: global population analysis of all five fluorescence anisotropy decays arising from EGFP in micelles together with the one of free EGFP (direct analysis of anisotropies) and global associative population analysis of anisotropies by fitting parallel and perpendicular fluorescence decay components. In contrast to global analyses approaches, the MEM method directly reveals distributions of correlation times without any prior information about the sample. However, global associative analysis of anisotropies by fitting parallel and perpendicular fluorescence decay components is the only method that allows to estimate accurately fractions of free fluorophores in solution and encapsulated fluorophores.
Microstructure and texture evolution of pure niobium in cold-drawn Mg+B/Nb/Cu wires
Authors: Park Sang-Yong , Lee Jong-Beom , Jeong Ha-Guk
Published: August 2022

In this study, Mg+B wires were prepared by powder in tube method using Nb and Cu tubes as barrier and sheath, respectively, followed by cold drawing. Microstructural, textural, and mechanical properties of the Nb barrier at different drawing strains (ε
d) were investigated. The results showed that the Nb barrier demonstrated a saturation hardness of 159.4 HV. The microstructure of the Nb barrier became elongated along the drawing direction increasing ε
d. Sub-grains existing inside the deformed grains rotated from low-angle grain boundaries to high-angle grain boundaries and developed into new grains. The main textural components of the Nb barrier were {111} γ-fiber and {hkl}〈110 〉 α-fiber. Recrystallized grains exhibited a low maximum orientation distribution function intensity, weak {100}〈110 〉 α-fibers, and strong {111}〈110 〉 γ-fibers as compared to those of the deformed grains. The relationship between the microstructure evolution and mechanical properties of the Nb barrier and the changes in the cross-sectional area fractions of the materials constituting the Mg+B composite wire are discussed. The current study provides details about the misorientation profile inside deformed grains and continuous dynamic recrystallization mechanism of the cold-drawn Nb barrier.
GameRank: R package for feature selection and construction
Authors: Henneges Carsten , Paulson Joseph N
Published: August 2022

Motivation

Building calibrated and discriminating predictive models can be developed through the direct optimization of model performance metrics with combinatorial search algorithms. Often, predictive algorithms are desired in clinical settings to identify patients that may be high and low risk. However, due to the large combinatorial search space, these algorithms are slow and do not guarantee the global optimality of their selection.

Results

Here, we present a novel and quick maximum likelihood-based feature selection algorithm, named GameRank. The method is implemented into an R package composed of additional functions to build calibrated and discriminative predictive models.

Availability and implementation

GameRank is available at https://github.com/Genentech/GameRank and released under the MIT License.
Pathways to Drug Dealing in the Middle and Upper Classes: Early Marginalization, Relative Disadvantage and Countercultural Opposition
Authors: Berger Eirik Jerven , Pedersen Willy , Sandberg Sveinung
Published: August 2022

Drug dealing is widespread in all sectors of society but is still studied predominantly in disadvantaged urban areas. We identify three main pathways to drug dealing based on qualitative interviews with middle- and upper-class individuals in Oslo, Norway. First, problems in the family and school and a lack of belonging in affluent neighbourhoods intersected with drug use and eventually led to recruitment into the illegal drug economy. Second, criminal entrepreneurship developed among relatively disadvantaged people who dealt drugs in an affluent low-risk context. Third, dealing emerged from involvement in drug liberalization and medical marihuana countercultures. The first pathway is similar to trajectories in disadvantaged urban areas, while the others reveal the importance of studying drug dealing in the upper layers of society.
Elevated expression of the membrane-anchored serine protease TMPRSS11E in NSCLC progression
Authors: Li Shufeng , Chen Zhenfa , Zhang Wei , Wang Ting , Wang Xihua , Wang Chao , Chao Jie , Liu Ling
Published: August 2022

TMPRSS11E was found to be upregulated in human nonsmall cell lung cancer samples (NSCLC) and cell lines, and high expression was associated with poor survival of NSCLC patients. The results of in vitro and in vivo experiments showed that overexpressing TMPRSS11E resulted in A549 cell proliferation and migration promotion, while the TMPRSS11E S372A mutant with the mutated catalytic domain lost the promoting function. In addition, in mouse xenograft models, silencing TMPRSS11E expression inhibited the growth of 95D cell-derived tumors. To explore the mechanism of marked upregulation of TMPRSS11E in NSCLC cells, promoter analysis, EMSA, and ChIP assays were performed. STAT3 was identified as the transcription factor responsible for TMPRSS11E transcription. Moreover, the purified recombinant TMPRSS11E catalytic domain exhibited enzymatic activity for the proteolytic cleavage of PAR2. Recombinant TMPRSS11E catalytic domain incubation further activated the PAR2-EGFR-STAT3 pathway. These findings established a mechanism of TMPRSS11E-PAR2-EGFR-STAT3 positive feedback, and the oncogenic role of TMPRSS11E as a PAR2 modulator in NSCLC was revealed.
Periventricular nodular heterotopia is coupled with the neocortex during resting and task states
Authors: Gao Yayue , Chen Guanpeng , Teng Pengfei , Zhang Xin , Fang Fang , Englot Dario J , Luan Guoming , Wang Xiongfei , Wang Qian
Published: August 2022

Periventricular nodular heterotopia (PVNH) is a well-defined developmental disorder characterized by failed neuronal migration, which forms ectopic neuronal nodules along the ventricular walls. Previous studies mainly focus on clinical symptoms caused by the PVNH tissue, such as seizures. However, little is known about whether and how neurons in the PVNH tissue functionally communicate with neurons in the neocortex. To probe this, we applied magnetoencephalography (MEG) and stereo-electroencephalography (sEEG) recordings to patients with PVNH during resting and task states. By estimating frequency-resolved phase coupling strength of the source-reconstructed neural activities, we found that the PVNH tissue was spontaneously coupled with the neocortex in the α–β frequency range, which was consistent with the synchronization pattern within the neocortical network. Furthermore, the coupling strength between PVNH and sensory areas effectively modulated the local neural activity in sensory areas. In both MEG and sEEG visual experiments, the PVNH tissue exhibited visual-evoked responses, with a similar pattern and latency as the ipsilateral visual cortex. These findings demonstrate that PVNH is functionally integrated into cognition-related cortical circuits, suggesting a co-development perspective of ectopic neurons after their migration failure.
Case report: the role of multimodal imaging to optimize the timing of return to sports in an elite athlete with persistent COVID-19 myocardial inflammation
Authors: Daems Joelle J N , van Hattum Juliette C , Pinto Yigal M , Jørstad Harald T
Published: August 2022

Background

COVID-19 has been associated with myocardial abnormalities on cardiac magnetic resonance imaging (CMR). We report a case of COVID-19 myocarditis in an elite athlete.

Case summary

A male, 21-year-old elite football player had tested positive for SARS-CoV-2 on a polymerase-chain-reaction test and was referred for cardiac evaluation after experiencing palpitations after returning to sports (RTS). Biochemical evaluation demonstrated elevated N-terminal pro b-type natriuretic peptide (NT-proBNP) and high-sensitive Troponin T. Echocardiography demonstrated left ventricular function within normal ranges for athletes but with diminished basal, posterolateral, and septal strain. Cardiac magnetic resonance imaging (CMR) showed increased T1 values and late gadolinium enhancement (LGE) in the basolateral and mid-ventricular posterior segments. Focal COVID-19 myocarditis was diagnosed and the patient remained restricted from sports, in line with the 2020 ESC sports cardiology guidelines. Two months later, his electrocardiogram (ECG) showed inferoposterolateral T-wave inversion (TWI). Serial imaging studies were performed to optimize RTS timing. Cardiac magnetic resonance imaging showed persistently increased T1/T2 values and persistent LGE at 5 and 7 months. At 9 months, 18 F-fluorodeoxyglucose (FDG)-positron emission tomography (PET)-computerized tomography (CT) demonstrated no pathologically increased cardiac FDG-uptake. Subsequent exercise ECG and Holters demonstrated no complex ventricular arrhythmias. The patient made a complete return to elite competitive sports, without any adverse events at 15 months of follow-up.

Discussion

Cardiac symptoms in athletes post-COVID-19 should prompt cardiac evaluation. As COVID-19 myocarditis inflammation can persist beyond the 3–6 months of recommended sports restriction, a more personalized approach to RTS timing can be warranted. In cases with myocardial oedema without other signs of inflammation, FDG-PET-CT can be of added value to assess active myocardial inflammation.
Mobile health vs. standard care after cardiac surgery: results of The Box 2.0 study
Authors: Biersteker Tom E , Boogers Mark J , Schalij Martin Jan , Penning de Vries Bas B L , Groenwold Rolf H H , van Alem Anouk P , de Weger Arend , van Hof Nicolette , Treskes Roderick W
Published: August 2022

Aims

Postoperative atrial fibrillation (POAF) is a common complication of cardiac surgery, yet difficult to detect in ambulatory patients. The primary aim of this study is to investigate the effect of a mobile health (mHealth) intervention on POAF detection after cardiac surgery.

Methods and results

We performed an observational cohort study among 730 adult patients who underwent cardiac surgery at a tertiary care hospital in The Netherlands. Of these patients, 365 patients received standard care and were included as a historical control group, undergoing surgery between December 2017 and September 2018, and 365 patients were prospectively included from November 2018 and November 2020, undergoing an mHealth intervention which consisted of blood pressure, temperature, weight, and electrocardiogram (ECG) monitoring. One physical outpatient follow-up moment was replaced by an electronic visit. All patients were requested to fill out a satisfaction and quality of life questionnaire. Mean age in the intervention group was 62 years, 275 (70.4%) patients were males. A total of 4136 12-lead ECGs were registered. In the intervention group, 61 (16.7%) patients were diagnosed with POAF vs. 25 (6.8%) patients in the control group [adjusted risk ratio (RR) of POAF detection: 2.15; 95% confidence interval (CI): 1.55–3.97]. De novo atrial fibrillation was found in 13 patients using mHealth (6.5%) vs. 4 control group patients (1.8%; adjusted RR 3.94, 95% CI: 1.50–11.27).

Conclusion

Scheduled self-measurements with mHealth devices could increase the probability of detecting POAF within 3 months after cardiac surgery. The effect of an increase in POAF detection on clinical outcomes needs to be addressed in future research.
Approximations to the expectations and variances of ratios of tree properties under the coalescent
Authors: Lappo Egor , Rosenberg Noah A
Published: August 2022

Properties of gene genealogies such as tree height (H), total branch length (L), total lengths of external (E) and internal (I) branches, mean length of basal branches (B), and the underlying coalescence times (T) can be used to study population-genetic processes and to develop statistical tests of population-genetic models. Uses of tree features in statistical tests often rely on predictions that depend on pairwise relationships among such features. For genealogies under the coalescent, we provide exact expressions for Taylor approximations to expected values and variances of ratios Xn/Yn, for all 15 pairs among the variables {Hn,Ln,En,In,Bn,Tk}, considering n leaves and 2≤k≤n. For expected values of the ratios, the approximations match closely with empirical simulation-based values. The approximations to the variances are not as accurate, but they generally match simulations in their trends as n increases. Although En has expectation 2 and Hn has expectation 2 in the limit as n→∞, the approximation to the limiting expectation for En/Hn is not 1, instead equaling π2/3−2≈1.28987. The new approximations augment fundamental results in coalescent theory on the shapes of genealogical trees.
How likely is septic shock to develop in a patient with Fournier's gangrene? A risk prediction model based on a 7-year retrospective study
Authors: Yang Yang , Wang Li-Chun , Yu Xin-Yang , Zhang Xiao-Fei , Yang Zhong-Qing , Zheng Yang-Zi , Jiang Bin-Yan , Chen Lei
Published: August 2022

Background

Fournier’s gangrene (FG) is a rare life-threatening form of necrotizing fasciitis. The risk factors for septic shock in patients with FG are unclear. This study aimed to identify potential risk factors and develop a prediction model for septic shock in patients with FG.

Methods

This retrospective cohort study included patients who were treated for FG between May 2013 and May 2020 at the Sixth Affiliated Hospital, Sun Yat-sen University (Guangzhou, China). The patients were divided into a septic shock group and a non-septic shock group. An L1-penalized logistic regression model was used to detect the main effect of important factors and a penalized Quadratic Discriminant Analysis method was used to identify possible interaction effects between different factors. The selected main factors and interactions were used to obtain a logistic regression model based on the Bayesian information criterion.

Results

A total of 113 patients with FG were enrolled and allocated to the septic shock group (n = 24) or non-septic shock group (n = 89). The best model selected identified by backward logistic regression based on Bayesian information criterion selected temperature, platelets, total bilirubin (TBIL) level, and pneumatosis on pelvic computed tomography/magnetic resonance images as the main linear effect and Na+ × TBIL as the interaction effect. The area under the ROC curve of the probability of FG with septic shock by our model was 0.84 (95% confidence interval, 0.78–0.95). The Harrell's concordance index for the nomogram was 0.864 (95% confidence interval, 0.78–0.95).

Conclusion

We have developed a prediction model for evaluation of the risk of septic shock in patients with FG that could assist clinicians in identifying critically ill patients with FG and prevent them from reaching a crisis state.
Variation in cytonuclear expression accommodation among allopolyploid plants
Authors: Grover Corrinne E , Forsythe Evan S , Sharbrough Joel , Miller Emma R , Conover Justin L , DeTar Rachael A , Chavarro Carolina , Arick Mark A , Peterson Daniel G , Leal-Bertioli Soraya C M , Sloan Daniel B , Wendel Jonathan F
Published: August 2022

Cytonuclear coevolution is a common feature among plants, which coordinates gene expression and protein products between the nucleus and organelles. Consequently, lineage-specific differences may result in incompatibilities between the nucleus and cytoplasm in hybrid taxa. Allopolyploidy is also a common phenomenon in plant evolution. The hybrid nature of allopolyploids may result in cytonuclear incompatibilities, but the massive nuclear redundancy created during polyploidy affords additional avenues for resolving cytonuclear conflict (i.e. cytonuclear accommodation). Here we evaluate expression changes in organelle-targeted nuclear genes for 6 allopolyploid lineages that represent 4 genera (i.e. Arabidopsis, Arachis, Chenopodium, and Gossypium) and encompass a range in polyploid ages. Because incompatibilities between the nucleus and cytoplasm could potentially result in biases toward the maternal homoeolog and/or maternal expression level, we evaluate patterns of homoeolog usage, expression bias, and expression-level dominance in cytonuclear genes relative to the background of noncytonuclear expression changes and to the diploid parents. Although we find subsets of cytonuclear genes in most lineages that match our expectations of maternal preference, these observations are not consistent among either allopolyploids or categories of organelle-targeted genes. Our results indicate that cytonuclear expression evolution may be subtle and variable among genera and genes, likely reflecting a diversity of mechanisms to resolve nuclear-cytoplasmic incompatibilities in allopolyploid species.