bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of Ciprofloxacin Based on BPN/TDNA Photoelectrode
Authors: Yuan Jiangnan , Wei Shusheng , Ji Zhiheng , Wang Juan
Published: October 2023

The photoelectrochemical (PEC) process has been demonstrated to exert enormous potential in the fields of analysis, and the rational design of PEC sensors are vital for practical applications. In this study, Titanium Dioxide Nanoarrays (TDNA) and black phosphorus nanosheets (BPN) were prepared, and a BPN/TDNA composite was proposed as the photoelectrochemical sensing material for the detection of ciprofloxacin (Cip). The formation and excellent optoelectronic properties of BPN/TDNA composite materials have been demonstrated through a series of characterization methods. Moreover, the measurement of PEC properties exhibited that the introduction of BPN and natural light would improve the electron migration efficiency and the separation of photogenerated electron–hole pairs, thereby displaying the synergistic effect to promote photoelectric performance. More importantly, the current density of BPN/TDNA was linearly proportional to the concentration of Cip ranging from 1.14 to 438.86 ng/mL, and the detection limit (3S/N) was 7.56 ng/mL. In addition, such a PEC sensor demonstrated long-term stability, good reproducibility, and selectivity. Finally, the real commercial sample detection was measured to confirm the possibility of practical applications. Thus, the BPN/TDNA photoelectrocatalyst provides a new method for Cip detection with high selectivity and sensitivity.
Hypothermic Protection in Neocortex Is Topographic and Laminar, Seizure Unmitigating, and Partially Rescues Neurons Depleted of RNA Splicing Protein Rbfox3/NeuN in Neonatal Hypoxic-Ischemic Male Piglets
Authors: Primiani Christopher T. , Lee Jennifer K. , O’Brien Caitlin E. , Chen May W. , Perin Jamie , Kulikowicz Ewa , Santos Polan , Adams Shawn , Lester Bailey , Rivera-Diaz Natalia , Olberding Valerie , Niedzwiecki Mark V. , Ritzl Eva K. , Habela Christa W. , Liu Xiuyun , Yang Zeng-Jin , Koehler Raymond C. , Martin Lee J.
Published: October 2023

The effects of hypothermia on neonatal encephalopathy may vary topographically and cytopathologically in the neocortex with manifestations potentially influenced by seizures that alter the severity, distribution, and type of neuropathology. We developed a neonatal piglet survival model of hypoxic-ischemic (HI) encephalopathy and hypothermia (HT) with continuous electroencephalography (cEEG) for seizures. Neonatal male piglets received HI-normothermia (NT), HI-HT, sham-NT, or sham-HT treatments. Randomized unmedicated sham and HI piglets underwent cEEG during recovery. Survival was 2–7 days. Normal and pathological neurons were counted in different neocortical areas, identified by cytoarchitecture and connectomics, using hematoxylin and eosin staining and immunohistochemistry for RNA-binding FOX-1 homolog 3 (Rbfox3/NeuN). Seizure burden was determined. HI-NT piglets had a reduced normal/total neuron ratio and increased ischemic-necrotic/total neuron ratio relative to sham-NT and sham-HT piglets with differing severities in the anterior and posterior motor, somatosensory, and frontal cortices. Neocortical neuropathology was attenuated by HT. HT protection was prominent in layer III of the inferior parietal cortex. Rbfox3 immunoreactivity distinguished cortical neurons as: Rbfox3-positive/normal, Rbfox3-positive/ischemic-necrotic, and Rbfox3-depleted. HI piglets had an increased Rbfox3-depleted/total neuron ratio in layers II and III compared to sham-NT piglets. Neuronal Rbfox3 depletion was partly rescued by HT. Seizure burdens in HI-NT and HI-HT piglets were similar. We conclude that the neonatal HI piglet neocortex has: (1) suprasylvian vulnerability to HI and seizures; (2) a limited neuronal cytopathological repertoire in functionally different regions that engages protective mechanisms with HT; (3) higher seizure burden, insensitive to HT, that is correlated with more panlaminar ischemic-necrotic neurons in the somatosensory cortex; and (4) pathological RNA splicing protein nuclear depletion that is sensitive to HT. This work demonstrates that HT protection of the neocortex in neonatal HI is topographic and laminar, seizure unmitigating, and restores neuronal depletion of RNA splicing factor.
Epithelial Transport in Disease: An Overview of Pathophysiology and Treatment
Authors: Clemente-Suárez Vicente Javier , Martín-Rodríguez Alexandra , Redondo-Flórez Laura , Villanueva-Tobaldo Carlota Valeria , Yáñez-Sepúlveda Rodrigo , Tornero-Aguilera José Francisco
Published: October 2023

Epithelial transport is a multifaceted process crucial for maintaining normal physiological functions in the human body. This comprehensive review delves into the pathophysiological mechanisms underlying epithelial transport and its significance in disease pathogenesis. Beginning with an introduction to epithelial transport, it covers various forms, including ion, water, and nutrient transfer, followed by an exploration of the processes governing ion transport and hormonal regulation. The review then addresses genetic disorders, like cystic fibrosis and Bartter syndrome, that affect epithelial transport. Furthermore, it investigates the involvement of epithelial transport in the pathophysiology of conditions such as diarrhea, hypertension, and edema. Finally, the review analyzes the impact of renal disease on epithelial transport and highlights the potential for future research to uncover novel therapeutic interventions for conditions like cystic fibrosis, hypertension, and renal failure.
Female Infertility in Chronic Kidney Disease
Authors: Bhaduri Mahua , Sarris Ippokratis , Bramham Kate
Published: October 2023

This review summarises the current literature regarding infertility in women with chronic kidney disease (CKD), describing the epidemiology, pathophysiology, investigations, and management options. The pathophysiology is multifactorial, with proposed mechanisms including disruption of the hypothalamus−pituitary−ovarian axis, chronic inflammation, oxidative stress, psychological factors, and gonadotoxic effects of medications such as cyclophosphamide. Diagnostic investigations in CKD patients seeking to conceive should be considered earlier than in the healthy population. Investigations should include hormonal profiling, including markers such as Anti-Mullerian Hormone and imaging such as ultrasound, to evaluate ovarian reserve and identify gynaecology pathology. Treatment options for infertility in CKD patients include GnRH agonists to preserve ovarian function during cyclophosphamide treatment, as well as assisted reproductive technologies including in vitro fertilisation and ovulation induction. However, these treatments must be tailored to the individual’s health status, comorbidities, fertility requirements, and CKD stage. In conclusion, fertility is an important consideration for women with CKD, necessitating early investigation and tailored management. Early discussions regarding fertility are important in order to understand patients’ family planning and allow for prompt referral to fertility services. While challenges exist, ongoing research aims to clarify the underlying mechanism and optimise treatment strategies, which are crucial for improving quality of life and overall health outcomes.
Pullback Bundles and the Geometry of Learning
Authors: Puechmorel Stéphane
Published: October 2023

Explainable Artificial Intelligence (XAI) and acceptable artificial intelligence are active topics of research in machine learning. For critical applications, being able to prove or at least to ensure with a high probability the correctness of algorithms is of utmost importance. In practice, however, few theoretical tools are known that can be used for this purpose. Using the Fisher Information Metric (FIM) on the output space yields interesting indicators in both the input and parameter spaces, but the underlying geometry is not yet fully understood. In this work, an approach based on the pullback bundle, a well-known trick for describing bundle morphisms, is introduced and applied to the encoder–decoder block. With constant rank hypothesis on the derivative of the network with respect to its inputs, a description of its behavior is obtained. Further generalization is gained through the introduction of the pullback generalized bundle that takes into account the sensitivity with respect to weights.
Central Bank Credibility’s Effect on Stock Exchange Returns’ Volatility: Evidence from OECD Countries
Authors: Dokas Ioannis , Oikonomou Georgios , Papadamou Stephanos , Spyromitros Eleftherios
Published: October 2023

Central bank characteristics are important determinants of stock market returns and their volatility. While the literature has examined the effects of transparency and independence, no research has been conducted so far on the effect of central bank credibility on stock market returns’ volatility. A panel regression using financial and macroeconomic data from 45 OECD member countries over the period of 1998–2022 tested the hypothesis that central bank credibility determines stock exchange returns’ volatility. The results indicated that credibility reduces stock returns’ volatility, remaining robust and statistically significant across models. Economic growth also decreases stock market volatility, while money-market interest rates’ volatility, the stock market’s turnover ratio, and economic/financial crises act as amplifying factors of stock market volatility. All variables, except for economic growth, exhibit unidirectional causality, leading to changes in stock market volatility.
Experimental Programs of Critical Thinking Enhancement: A Worked-Based, Blended Learning Higher Education Curriculum for Economics
Authors: Dumitru Daniela , Minciu Mihaela , Mihaila Robert Alexandru , Livinti Raluca , Paduraru Monica Elisabeta
Published: October 2023

In an increasingly changing world, critical thinking is one of the key skills that ensure organizations’ competitive advantage. Thus, in higher education institutions, there is an accelerating emphasis on developing critical thinking (CT) among students. This paper presented the results of three experimental courses (pedagogy and didactics of financial accounting, virtual learning environments in economics, and business communication), using a blended learning method, aimed at improving students’ CT skills. The three courses were delivered by both higher education teachers and trainers from the labor market. After analyzing the data from the three experimental courses, it will be possible to assess whether the intervention of labor market trainers contributed to the improvement of students’ critical thinking skills, and in particular, at the level of which these component improvements have been identified.
Chinese Multicategory Sentiment of E-Commerce Analysis Based on Deep Learning
Authors: Li Hongchan , Wang Jianwen , Lu Yantong , Zhu Haodong , Ma Jiming
Published: October 2023

With the continuous rise of information technology and social networks, and the explosive growth of network text information, text sentiment analysis technology now plays a vital role in public opinion monitoring and product development analysis on networks. Text data are high-dimensional and complex, and traditional binary classification can only classify sentiment from positive or negative aspects. This does not fully cover the various emotions of users, and, therefore, natural language semantic sentiment analysis has limitations. To solve this deficiency, we propose a new model for analyzing text sentiment that combines deep learning and the bidirectional encoder representation from transformers (BERT) model. We first use an advanced BERT language model to convert the input text into dynamic word vectors; then, we adopt a convolutional neural network (CNN) to obtain the relatively significant partial emotional characteristics of the text. After extraction, we use the bidirectional recurrent neural network (BiGRU) to bidirectionally capture the contextual feature message of the text. Finally, with the MultiHeadAttention mechanism we obtain correlations among the data in different information spaces from different subspaces so that the key information related to emotion in the text can be selectively extracted. The final emotional feature representation obtained is classified using Softmax. Compared with other similar existing methods, our model in this research paper showed a good effect in comparative experiments on an e-commerce text dataset, and the accuracy and F1-score of the classification were significantly improved.
Contamination Detection Using a Deep Convolutional Neural Network with Safe Machine—Environment Interaction
Authors: Hassan Syed Ali , Khalil Muhammad Adnan , Auletta Fabrizia , Filosa Mariangela , Camboni Domenico , Menciassi Arianna , Oddo Calogero Maria
Published: October 2023

In the food and medical packaging industries, clean packaging is crucial to both customer satisfaction and hygiene. An operational Quality Assurance Department (QAD) is necessary for detecting contaminated packages. Manual examination becomes tedious and may lead to instances of contamination being missed along the production line. To address this issue, a system for contamination detection is proposed using an enhanced deep convolutional neural network (CNN) in a human–robot collaboration framework. The proposed system utilizes a CNN to identify and classify the presence of contaminants on product surfaces. A dataset is generated, and augmentation methods are applied to the dataset for nine classes such as coffee, spot, chocolate, tomato paste, jam, cream, conditioner, shaving cream, and toothpaste contaminants. The experiment was conducted using a mechatronic platform with a camera for contamination detection and a time-of-flight sensor for safe machine–environment interaction. The results of the experiment indicate that the reported system can accurately identify contamination with 99.74% mean average precision (mAP).
Research on Reactive Power Coordination Control Strategies of Multi-Infeed Line-Commutated Converter–High-Voltage Direct Current Systems
Authors: Yin Yueyang , Huang Ying , Zhang Zheren , Wang Guoteng , Zhang Yijing , Li Jianhua
Published: October 2023

For a receiving-end power grid with multi-infeed LCC-HVDC systems, simultaneous commutation failures may seriously threaten the safe and stable operation of the system. To evaluate the impact of commutation failure and improve the voltage stability of the commutation buses in multi-infeed HVDC systems, this paper proposes a method for evaluating the voltage stability of commutation buses and a reactive power coordination control (RPCC) method for commutation failure of multiple HVDC systems. Firstly, three indicators and the entropy weight method are adopted to comprehensively evaluate the voltage stability of commutation buses. Then, an RPCC method is proposed to resist commutation failure. The proposed RPCC method uses the voltage interaction factor (VIF) to screen out DC systems that are strongly related to dynamic reactive power compensation devices and activates the devices to provide RPCC to the DC systems through an auxiliary controller. Finally, the effectiveness of the proposed method is verified through a practical example of the Jiangsu power grid.
Multicast Space-Conversion-Space Strict-Sense Nonblocking Switching Fabrics with Multicast Opportunity in the Last Stage for Continuous Multislot Connections
Authors: Danilewicz Grzegorz
Published: October 2023

This paper introduces two nonblocking switching fabric architectures designed for multicast connections. These connections are defined using the multislot connection approach, mainly applied in elastic optical networks. In contrast to earlier solutions, this approach assumes that multislot connections are consistently established in adjacent continuous slots. This implies that previously established solutions could not be applied. Our study presents a comprehensive theoretical framework applicable to the general case of three-stage switching fabrics. These fabrics feature external stages equipped with space switches, while the middle stage incorporates conversion switches that operate in the wavelength, time, or frequency domain. In addition, multicast capabilities are deliberately confined to the output-stage switch or switches. A fundamental contribution of this work lies in the formulation of the worst-case scenario, which serves as the foundational basis for deriving strict-sense nonblocking conditions governing such multicast switching fabrics. Our analysis formally demonstrates that the fundamental structure of the multicast nonblocking switching fabric aligns closely with that of the previously examined point-to-point fabric. The only difference is related to the ability to multicast within the output stage of the switching fabric.
Explicit Representation of Mechanical Functions for Maintenance Decision Support
Authors: Song Mengchu , Santos Ilmar F. , Zhang Xinxin , Wu Jing , Lind Morten
Published: October 2023

Artificial intelligence (AI) has been increasingly applied to condition-based maintenance (CBM), a knowledge-based method taking advantage of human expertise and other system knowledge that can serve as an alternative in cases in which machine learning is inapplicable due to a lack of training data. Functional information is seen as the most fundamental and important knowledge in maintenance decision making. This paper first proposes a mechanical functional modeling approach based on a functional modeling and reasoning methodology called multilevel flow modeling (MFM). The approach actually bridges the modeling gap between the mechanical level and the process level, which potentially extends the existing capability of MFM in rule-based diagnostics and prognostics from operation support to maintenance support. Based on this extension, a framework of optimized CBM is proposed, which can be used to diagnose potential mechanical failures from condition monitoring data and predict their future impacts in a qualitative way. More importantly, the framework uses MFM-based reliability-centered maintenance (RCM) to determine the importance of a detected potential failure, which can ensure the cost-effectiveness of CBM by adapting the maintenance requirements to specific operational contexts. This ability cannot be offered by existing CBM methods. An application to a mechanical test apparatus and hypothetical coupling with a process plant are used to demonstrate the proposed framework.
Optimizing Energy Efficiency of Dielectric Materials’ Electrodischarge Dispersion as One Sustainable Development Green Trend
Authors: Malyushevskaya Antonina , Petrychenko Serhii , Przystupa Krzysztof , Mitryasova Olena , Majka Michał , Kochan Orest
Published: October 2023

Increasing the energy efficiency of production processes is closely related to minimizing the impact on the environment and is one of the priorities of the concept of sustainable development. Electric discharge is an effective tool for multilevel grinding of non-metallic materials in various working fluids and obtaining coarse and fine suspensions. We introduce the technique for calculating the electrotechnological parameters necessary for energy-efficient electric discharge dispersion. This technique considers the strength characteristics of the crushed material (dispersed phase) and the electrical conductivity of the working fluid (dispersed medium). It is also essential to consider the energy stored in the capacitor bank, the energy criterion, the critical value of the working fluid’s electrical strength, the radius of the high-voltage electrode point, and the distance from the discharge channel axis to the disintegration object. All this allows obtaining a given granulometric composition of the dispersed phase with minimal energy consumption. Experiments confirmed the validity of the proposed calculation technique. We obtained the water-brown coal suspension with a given dispersion two times faster and consumed four times less energy in comparison with the known methods that did not take into account the electrical conductivity of the working liquid and the mechanical strength of the crushed material.
A Decentralized Control Strategy for Series-Connected Single-Phase Two-Stage Photovoltaic Grid-Connected Inverters
Authors: Luo Zhaoxu , Zhang Bo , Li Lang , Tang Lixing
Published: October 2023

Currently, most of the series inverter control methods rely on communication, which greatly reduces the reliability of the system and increases the cost. To address the above problems, this paper proposes a decentralized control strategy for series-connected single-phase two-stage grid-connected photovoltaic (PV) inverters. By improving the traditional droop control, the frequency and phase of the output voltage of each inverter unit are consistent and self-synchronized with the power grid while relying only on local independent control, and each unit realizes maximum power point tracking (MPPT). At different light intensities, each series-connected unit can quickly track the new maximum power point while still maintaining self-synchronization between the units. The system stability is analyzed via the small signal method, and sufficient conditions for system stability are obtained. Finally, the simulation results verify the correctness and effectiveness of the proposed control strategy.
Ecophysiological Behavior of Fagus sylvatica L. Growing at Its Southern Distribution Limit: Insights for Understanding the Fate of the European Beech under Warmer and Dryer Growth Conditions
Authors: Prigoliti Maria , Chiofalo Maria Teresa , Petruzzellis Francesco , Lo Gullo Maria Assunta , Trifilò Patrizia
Published: October 2023

In the last 20 years, a significant mortality of Fagus sylvatica L. (European beech) has been documented in central and northern European forests. Surprisingly, no beech die off occurred at the southern limit. This fact leads us to hypothesize that European beech populations growing at the southern limit of the distribution might have a significant phenotypic plasticity to better cope with low water availability and rising temperatures. To check this hypothesis, we evaluated the ecophysiological behavior of F. sylvatica growing along an altitudinal transect in Calabria (Italy). We selected three study sites (750 m a.s.l., 976 m a.sl. m a.s.l., 1450 m a.s.l.) showing narrow ranges of temperature, rainfall and air humidity. Trees growing at 976 m a.s.l. showed the highest stomatal conductance values during the entire experimental period. The lowest gas exchange and highest leaf mass area were recorded in plants growing at 750 m a.s.l. In the European beech growing at 1450 m a.s.l., higher vessel density, lower mean vessel diameter and higher vessel grouping index values were recorded. Overall, our results highlighted that the measured populations show a considerable phenotypic plasticity leading them to adjust anatomical and physiological traits in response to narrow ranges of environmental parameters. Despite that, the distribution of F. sylvatica seems to be limited to areas with a growing season rainfall of at least 400 mm and vapor pressure deficit (VPD) values < 3 kPa, which may represent the main environmental thresholds which strongly limit the beech growth and, therefore, influence the ability of this species to cope with future environmental conditions.
Reinforcement Learning Approach for Adaptive C-V2X Resource Management
Authors: Bayu Teguh Indra , Huang Yung-Fa , Chen Jeang-Kuo
Published: October 2023

The modulation coding scheme (MCS) index is the essential configuration parameter in cellular vehicle-to-everything (C-V2X) communication. As referenced by the 3rd Generation Partnership Project (3GPP), the MCS index will dictate the transport block size (TBS) index, which will affect the size of transport blocks and the number of physical resource blocks. These numbers are crucial in the C-V2X resource management since it is also bound to the transmission power used in the system. To the authors’ knowledge, this particular area of research has not been previously investigated. Ultimately, this research establishes the fundamental principles for future studies seeking to use the MCS adaptability in many contexts. In this work, we proposed the application of the reinforcement learning (RL) algorithm, as we used the Q-learning approach to adaptively change the MCS index according to the current environmental states. The simulation results showed that our proposed RL approach outperformed the static MCS index and was able to attain stability in a short number of events.
Comparative Analysis of Saccharification Characteristics of Different Type Sweetpotato Cultivars
Authors: Li Chen , Kou Meng , Song Weihan , Arisha Mohamed Hamed , Gao Runfei , Tang Wei , Yan Hui , Wang Xin , Zhang Yungang , Li Qiang
Published: October 2023

As an important characteristic crop in China, sweetpotato plays an important role in the intake and supplement of nutrients. The saccharification characteristics of sweetpotato determine the edible quality and processing type. Exploring the saccharification characteristics of sweetpotato is of great significance to the selection of processing materials and the formation mechanism of service quality, but there are few relevant studies. A comparison study of two high saccharification varieties (Y25 and Z13) and one low saccharification variety (X27) was conducted to analyze their storage roots physical and chemical properties. The results show that the dry matter content, starch, and amylose content of Y25 and Z13 were significantly different from those of X27. Furthermore, the total amylase activity was significantly higher than that of X27. On the other hand, the starch gelatinization temperature was significantly lower than that of X27. The starch reduction in Y25 and Z13 is four times more than that in X27, and the maltose content of Y25 and Z13 is more than two times that of X27. Finally, the scores of sensory evaluation and physiological sweetness were significantly higher than those of X27. The results provide a theoretical basis for understanding the saccharification characteristics of sweetpotato varieties and are of guiding significance for the selection of sweetpotato parents.
Non-Markovian Persistent Random Walk Model for Intracellular Transport
Authors: Korabel Nickolay , Al Shamsi Hamed , Ivanov Alexey O. , Fedotov Sergei
Published: October 2023

Transport of vesicles and organelles inside cells consists of constant-speed bidirectional movement along cytoskeletal filaments interspersed by periods of idling. This transport shows many features of anomalous diffusion. In this paper, we develop a non-Markovian persistent random walk model for intracellular transport that incorporates the removal rate of organelles. The model consists of two active states with different speeds and one resting state. The organelle transitions between states with switching rates that depend on the residence time the organelle spends in each state. The mesoscopic master equations that describe the average densities of intracellular transport in each of the three states are the main results of the paper. We also derive ordinary differential equations for the dynamics for the first and second moments of the organelles’ position along the cell. Furthermore, we analyse models with power-law distributed random times, which reveal the prevalence of the Mittag-Leffler resting state and its contribution to subdiffusive and superdiffusive behaviour. Finally, we demonstrate a non-Markovian non-additivity effect when the switching rates and transport characteristics depend on the rate of organelles removal. The analytical calculations are in good agreement with numerical Monte Carlo simulations. Our results shed light on the dynamics of intracellular transport and emphasise the effects of rest times on the persistence of random walks in complex biological systems.
A Comprehensive Study of Soft X-ray Absorption Features in GX 13+1 Using XMM-Newton Observations
Authors: Mahato Rabindra , Baruah Monmoyuri
Published: October 2023

In this study, a comprehensive analysis of the reflection grating spectrometer (RGS) data (energy range 0.33 keV to 2.5 keV) of GX 13+1 from the XMM-Newton space observatory was conducted. Numerous absorption lines have been described in earlier publications, although the majority of these investigations focused on the energy range between 3 keV and 10 keV. We considered all ten on-axis observations for spectral analysis, but during timing analysis, off-axis observations were also analysed. A fresh dip in off-axis observation 0122340701(B) was observed together with the previously reported dip in on-axis observation 0505480501(F). No burst or eclipsing was observed in any of the observations. The spectral analysis revealed the presence of the highly ionized elements, Si XIII 1s2–1s2p and 1s2–1s3p transitions with energies of 2.02 keV and 2.24 keV, respectively, as well as Mg XII 1s–6p transitions with energies of 1.91 keV and Al XIII 1s–4p transitions with energies of 2.15 keV. Before this study, no analyses of XMM-Newton data reported Mg XII and Al XIII elements. Moreover, the 1s–6p transitions of Mg XII and 1s–4p transitions of Al XIII were not even reported in any Chandra data analysis. The equivalent hydrogen column densities obtained (2.35 × 1022 cm−2 to 4.18 × 1022 cm−2) are consistent with previously reported values. The equivalent widths of neighbouring observations are found to be nearly the same. This supports us in suggesting that the absorptions may be due to the presence of an interstellar medium (ISM) in the line of sight (LOS) of the source.
Thermoreversible Gelation with Supramolecularly Polymerized Cross-Link Junctions
Authors: Tanaka Fumihiko
Published: October 2023

Structure and reversibility of cross-link junctions play pivotal roles in determining the nature of thermoreversible gelation and dynamic mechanical properties of the produced polymer networks. We attempt to theoretically explore new types of sol–gel transitions with mechanical sharpness by allowing cross-links to grow without upper bound. We consider thermoreversible gelation of the primary molecules R{Af} carrying the number f of low molecular weight functional groups (gelators) A. Gelators A are assumed to form supramolecular assemblies. Some examples are: telechelic polymers (f=2) carrying π–π stacking benzene derivatives at their both ends, and trifunctional star molecules (f=3) bearing multiple hydrogen-bonding gelators. The sol–gel transition of the primary molecules becomes sharper with the cooperativity parameter of the stepwise linear growth of the cross-links. There is a polymerization transition (crossover without singularity) of the junctions in the postgel region after the gel point is passed. If the gelator A tends to form supramolecular rings competitively with linear chains, there is another phase transition in the deep postgel region where the average molecular weight of the rings becomes infinite (Bose–Einstein condensation of rings). As a typical example of binary cross-links where gelators A and B form mixed junctions, we specifically consider metal-coordinated binding of ligands A by metal ions B. Two types of multi-nuclear supramolecular complexes are studied: (i) linear stacking (ladder) of the sandwich A2B units, and (ii) linear train of egg-box A4B units. To find the strategy towards experimental realization of supramolecular cross-links, the average molecular weight, the gel fraction, the average length of the cross-link junctions are numerically calculated for all of these models as functions of the functionality f, the concentration of the solute molecules, and the temperature. Potential candidates for the realization of these new types of thermoreversible gelation are discussed.
Genomic Scanning of Inbreeding Depression for Litter Size in Two Varieties of Iberian Pigs
Authors: Hervás-Rivero Carlos , Srihi Houssemeddine , López-Carbonell David , Casellas Joaquim , Ibáñez-Escriche Noelia , Negro Sara , Varona Luis
Published: October 2023

Inbreeding depression is expected to be more pronounced in fitness-related traits, such as pig litter size. Recent studies have suggested that the genetic determinism of inbreeding depression may be heterogeneous across the genome. Therefore, the objective of this study was to conduct a genomic scan of the whole pig autosomal genome to detect the genomic regions that control inbreeding depression for litter size in two varieties of Iberian pigs (Entrepelado and Retinto). The datasets consisted of 2069 (338 sows) and 2028 (327 sows) records of litter size (Total Number Born and Number Born Alive) for the Entrepelado and Retinto varieties. All sows were genotyped using the Geneseek GGP PorcineHD 70 K chip. We employed the Unfavorable Haplotype Finder software to extract runs of homozygosity (ROHs) and conducted a mixed-model analysis to identify highly significant differences between homozygous and heterozygous sows for each specific ROH. A total of eight genomic regions located on SSC2, SSC5, SSC7, SSC8, and SSC13 were significantly associated with inbreeding depression, housing some relevant genes such as FSHR, LHCGR, CORIN, AQP6, and CEP120.
Comparative Analysis of the GATA Transcription Factors in Five Solanaceae Species and Their Responses to Salt Stress in Wolfberry (Lycium barbarum L.)
Authors: Zhang Fengfeng , Wu Yan , Shi Xin , Wang Xiaojing , Yin Yue
Published: October 2023

GATA proteins are a class of zinc-finger DNA-binding proteins that participate in diverse regulatory processes in plants, including the development processes and responses to environmental stresses. However, a comprehensive analysis of the GATA gene family has not been performed in a wolfberry (Lycium barbarum L.) or other Solanaceae species. There are 156 GATA genes identified in five Solanaceae species (Lycium barbarum L., Solanum lycopersicum L., Capsicum annuum L., Solanum tuberosum L., and Solanum melongena L.) in this study. Based on their phylogeny, they can be categorized into four subfamilies (I-IV). Noticeably, synteny analysis revealed that dispersed- and whole-genome duplication contributed to the expansion of the GATA gene family. Purifying selection was a major force driving the evolution of GATA genes. Moreover, the predicted cis-elements revealed the potential roles of wolfberry GATA genes in phytohormone, development, and stress responses. Furthermore, the RNA-seq analysis identified 31 LbaGATA genes with different transcript profiling under salt stress. Nine candidate genes were then selected for further verification using quantitative real-time PCR. The results revealed that four candidate LbaGATA genes (LbaGATA8, LbaGATA19, LbaGATA20, and LbaGATA24) are potentially involved in salt-stress responses. In conclusion, this study contributes significantly to our understanding of the evolution and function of GATA genes among the Solanaceae species, including wolfberry.
Phylogenomic Analysis of Cytochrome P450 Gene Superfamily and Their Association with Flavonoids Biosynthesis in Peanut (Arachis hypogaea L.)
Authors: Zhang Kun , Qin Yongmei , Sun Wei , Shi Hourui , Zhao Shuzhen , He Liangqiong , Li Changsheng , Zhao Jin , Pan Jiaowen , Wang Guanghao , Han Zhuqiang , Zhao Chuanzhi , Yang Xiangli
Published: October 2023

Cytochrome P450s (CYPs) constitute extensive enzyme superfamilies in the plants, playing pivotal roles in a multitude of biosynthetic and detoxification pathways essential for growth and development, such as the flavonoid biosynthesis pathway. However, CYPs have not yet been systematically studied in the cultivated peanuts (Arachis hypogaea L.), a globally significant cash crop. This study addresses this knowledge deficit through a comprehensive genome-wide analysis, leading to the identification of 589 AhCYP genes in peanuts. Through phylogenetic analysis, all AhCYPs were systematically classified into 9 clans, 43 gene families. The variability in the number of gene family members suggests specialization in biological functions. Intriguingly, both tandem duplication and fragment duplication events have emerged as pivotal drivers in the evolutionary expansion of the AhCYP superfamily. Ka/Ks analysis underscored the substantial influence of strong purifying selection on the evolution of AhCYPs. Furthermore, we selected 21 genes encoding 8 enzymes associated with the flavonoid pathway. The results of quantitative real-time PCR (qRT-PCR) experiments unveiled stage-specific expression patterns during the development of peanut testa, with discernible variations between pink and red testa. Importantly, we identified a direct correlation between gene expression levels and the accumulation of metabolites. These findings offer valuable insights into elucidating the comprehensive functions of AhCYPs and the underlying mechanisms governing the divergent accumulation of flavonoids in testa of different colors.
The Effects of Adolescents’ Participation in Video Games on Cognitive Function and Motor Control Skills
Authors: Ahn Hyoyeon , Won Jongeun
Published: October 2023

There is still a lack of understanding of the productive areas of video game participation. Therefore, in order to observe positive effects and changes in game participation, this study examines the effects of game participation on the cognitive function and motor skills from 130 adolescents. To evaluate the participants’ test performance, a cognitive function and motor control skill test program consisting of 10 tests were used (Trail Making, Corsi block, Tower of London, shooting game tasks, etc.). Differences in test performances between groups were verified using one-way ANOVA and an independent t-test. The results were as follows: first, there was no difference between groups according to the frequency of game participation in every test performance. Second, the results of this study showed statistically significant differences between groups according to the play time of game participation in several test performances (Key-mapping: p = 0.40; score of Grid Shot: p = 0.01, 0.07; score of Sphere Track: p = 0.12, 0.21; accuracy of Sphere Track: p = 0.12, 0.16). Also, all the effects’ size results were confirmed as medium (Cohen’s f > 0.20 and <0.40). Third, high school students only showed statistically significant higher results in a Multi-tasking test performance than middle school students, and the results of the effect size were confirmed to be middle and large (Multi-tasking1: p = 0.00, Cohen’s d = 0.830; Multi-tasking2: p = 0.05, Cohen’s d = 0.501). The results of this study imply the need to regard game participation as a behavior that can contribute to adolescents’ cognitive psychological health.
Efficacy and Potential Mechanism of Essential Oils of Three Labiatae Plants against the Pathogenic Fungi of Root Rot Disease in Atractylodes chinensis
Authors: Xie Siyuan , Si He , Zhang Shenfei , Zhou Ru , Xue Yuyan , Wang Shijie , Wang Shiqiang , Duan Yizhong , Niu Junfeng , Wang Zhezhi
Published: October 2023

Atractylodes chinensis has a high medicinal value and is widely cultivated. However, root rot disease seriously affects the yield and quality of A. chinensis. To develop green and safe pesticides, the inhibitory effect of essential oils (EOs) of three Labiatae plants on the pathogenic fungi that causes root rot disease in Atractylodes chinensis was investigated. The results showed that the Origanum vulgare EO and Thymus mongolicus EO exhibited strong inhibitory effects on Fusarium oxysporum, Fusarium solani, and Fusarium redolens, with 100% inhibition rate. The low MIC values of EOs and their main components against the three pathogenic fungi indicated that all of them showed strong fungicidal effects. The MIC values of O. vulgare EO against F. oxysporum, F. solani, and F. redolens were 2.60 mg/mL, 3.13 mg/mL, and 1.56 mg/mL, respectively. Analyses using scanning electron microscopy (SEM) and transmission electron microscopy (TEM) showed that the O. vulgare EO severely damaged the cell wall and cell membrane of mycelial cells. The O. vulgare EO increased cell permeability, leading to a large leakage of cell contents (DNA and proteins). In addition, O. vulgare EO inhibited F. oxysporum by inducing ROS production and reducing the amount of intracellular GSH, leading to a large accumulation of ROS. This study showed that plant EOs have excellent fungicidal activity and can be used as novel natural and environmentally friendly pesticides for the control of root rot in A. chinensis.
A Knowledge-Guided Fusion Visualisation Method of Digital Twin Scenes for Mountain Highways
Authors: Tang Ranran , Zhu Jun , Ren Ying , Ding Yongzhe , Wu Jianlin , Guo Yukun , Xie Yakun
Published: October 2023

Informatization is an important trend in the field of mountain highway management, and the digital twin is an effective way to promote mountain highway information management due to the complex and diverse terrain of mountainous areas, the high complexity of mountainous road scene modeling and low visualisation efficiency. It is challenging to construct the digital twin scenarios efficiently for mountain highways. To solve this problem, this article proposes a knowledge-guided fusion expression method for digital twin scenes of mountain highways. First, we explore the expression features and interrelationships of mountain highway scenes to establish the knowledge graph of mountain highway scenes. Second, by utilizing scene knowledge to construct spatial semantic constraint rules, we achieve efficient fusion modeling of basic geographic scenes and dynamic and static ancillary facilities, thereby reducing the complexity of scene modeling. Finally, a multi-level visualisation publishing scheme is established to improve the efficiency of scene visualisation. On this basis, a prototype system is developed, and case experimental analysis is conducted to validate the research. The results of the experiment indicate that the suggested method can accomplish the fusion modelling of mountain highway scenes through knowledge guidance and semantic constraints. Moreover, the construction time for the model fusion is less than 5.7 ms; meanwhile, the dynamic drawing efficiency of the scene is maintained above 60 FPS. Thus, the construction of twinned scenes can be achieved quickly and efficiently, the effect of replicating reality with virtuality is accomplished, and the informatisation management capacity of mountain highways is enhanced.
A Genome-Wide Comparison of Rice False Smut Fungus Villosiclava virens Albino Strain LN02 Reveals the Genetic Diversity of Secondary Metabolites and the Cause of Albinism
Authors: Xue Mengyao , Zhao Siji , Gu Gan , Xu Dan , Zhang Xuping , Hou Xuwen , Miao Jiankun , Dong Hai , Hu Dongwei , Lai Daowan , Zhou Ligang
Published: October 2023

Rice false smut (RFS) caused by Villosiclava virens (anamorph: Ustilaginoidea virens) has become one of the most destructive fungal diseases to decrease the yield and quality of rice grains. An albino strain LN02 was isolated from the white RFS balls collected in the Liaoning Province of China in 2019. The strain LN02 was considered as a natural albino mutant of V. virens by analyzing its phenotypes, internal transcribed spacer (ITS) conserved sequence, and biosynthesis gene clusters (BGCs) for secondary metabolites. The total assembled genome of strain LN02 was 38.81 Mb, which was comprised of seven nuclear chromosomes and one mitochondrial genome with an N50 value of 6,326,845 bp and 9339 protein-encoding genes. In addition, the genome of strain LN02 encoded 19 gene clusters for biosynthesis of secondary metabolites mainly including polyketides, terpenoids and non-ribosomal peptides (NRPs). Four sorbicillinoid metabolites were isolated from the cultures of strain LN02. It was found that the polyketide synthase (PKS)-encoding gene uspks1 for ustilaginoidin biosynthesis in strain LN02 was inactivated due to the deletion of four bases in the promoter sequence of uvpks1. The normal uvpks1 complementary mutant of strain LN02 could restore the ability to synthesize ustilaginoidins. It demonstrated that deficiency of ustilaginoidin biosynthesis is the cause of albinism for RFS albino strain LN02, and V. virens should be a non-melanin-producing fungus. This study further confirmed strain LN02 as a white phenotype mutant of V. virens. The albino strain LN02 will have a great potential in the development and application of secondary metabolites. The physiological and ecological functions of ustilaginoidins in RFS fungus are needed for further investigation.
Dysfunctional and Dysregulated Nitric Oxide Synthases in Cardiovascular Disease: Mechanisms and Therapeutic Potential
Authors: Roy Roman , Wilcox Joshua , Webb Andrew J. , O’Gallagher Kevin
Published: October 2023

Nitric oxide (NO) plays an important and diverse signalling role in the cardiovascular system, contributing to the regulation of vascular tone, endothelial function, myocardial function, haemostasis, and thrombosis, amongst many other roles. NO is synthesised through the nitric oxide synthase (NOS)-dependent L-arginine-NO pathway, as well as the nitrate-nitrite-NO pathway. The three isoforms of NOS, namely neuronal (NOS1), inducible (NOS2), and endothelial (NOS3), have different localisation and functions in the human body, and are consequently thought to have differing pathophysiological roles. Furthermore, as we continue to develop a deepened understanding of the different roles of NOS isoforms in disease, the possibility of therapeutically modulating NOS activity has emerged. Indeed, impaired (or dysfunctional), as well as overactive (or dysregulated) NOS activity are attractive therapeutic targets in cardiovascular disease. This review aims to describe recent advances in elucidating the physiological role of NOS isoforms within the cardiovascular system, as well as mechanisms of dysfunctional and dysregulated NOS in cardiovascular disease. We then discuss the modulation of NO and NOS activity as a target in the development of novel cardiovascular therapeutics.
Engineered Extracellular Vesicles: Emerging Therapeutic Strategies for Translational Applications
Authors: Ziegler Jessica N. , Tian Changhai
Published: October 2023

Extracellular vesicles (EVs) are small, membrane-bound vesicles used by cells to deliver biological cargo such as proteins, mRNA, and other biomolecules from one cell to another, thus inducing a specific response in the target cell and are a powerful method of cell to cell and organ to organ communication, especially during the pathogenesis of human disease. Thus, EVs may be utilized as prognostic and diagnostic biomarkers, but they also hold therapeutic potential just as mesenchymal stem cells have been used in therapeutics. However, unmodified EVs exhibit poor targeting efficacy, leading to the necessity of engineered EVS. To highlight the advantages and therapeutic promises of engineered EVs, in this review, we summarized the research progress on engineered EVs in the past ten years, especially in the past five years, and highlighted their potential applications in therapeutic development for human diseases. Compared to the existing stem cell-derived EV-based therapeutic strategies, engineered EVs show greater promise in clinical applications: First, engineered EVs mediate good targeting efficacy by exhibiting a targeting peptide that allows them to specifically target a specific organ or even cell type, thus avoiding accumulation in undesired locations and increasing the potency of the treatment. Second, engineered EVs can be artificially pre-loaded with any necessary biomolecular cargo or even therapeutic drugs to treat a variety of human diseases such as cancers, neurological diseases, and cardiovascular ailments. Further research is necessary to improve logistical challenges in large-scale engineered EV manufacturing, but current developments in engineered EVs prove promising to greatly improve therapeutic treatment for traditionally difficult to treat diseases.