bluuebunny/crossref_metadata_2025 huggingface dataset:
Calendar Aging Effect on the Open Circuit Voltage of Lithium-Ion Battery
Authors: Barcellona Simone , Codecasa Lorenzo , Colnago Silvia , Piegari Luigi
Published: June 2023

In recent years, lithium-ion batteries (LiBs) have gained a lot of importance due to the increasing use of renewable energy sources and electric vehicles. To ensure that batteries work properly and limit their degradation, the battery management system needs accurate battery models capable of precisely predicting their parameters. Among them, the state of charge (SOC) estimation is one of the most important, as it enables the prediction of the battery’s available energy and prevents it from operating beyond its safety limits. A common method for SOC estimation involves utilizing the relationship between the state of charge and the open circuit voltage (OCV). On the other hand, the latter changes with battery aging. In a previous work, the authors studied a simple function to model the OCV curve, which was expressed as a function of the absolute state of discharge, q, instead of SOC. They also analyzed how the parameters of such a curve changed with the cycle aging. In the present work, a similar analysis was carried out considering the calendar aging effect. Three different LiB cells were stored at three different SOC levels (low, medium, and high levels) for around 1000 days, and an analysis of the change in the OCV-q curve model parameters with the calendar aging was performed.
Optimization of Polypropylene Waste Recycling Products as Alternative Fuels through Non-Catalytic Thermal and Catalytic Hydrocracking Using Fresh and Spent Pt/Al2O3 and NiMo/Al2O3 Catalysts
Authors: Al-Iessa Murtadha , Al-Zaidi Bashir , Almukhtar Riaydh , Shakor Zaidoon , Hamawand Ihsan
Published: June 2023

In this work, the conversion of waste polypropylene to alternative fuels (liquid and gas) was performed through non-catalytic thermal and catalytic hydrocracking over NiMo/Al2O3 and Pt/Al2O3 catalysts. The process was carried out in an autoclave batch reactor at a temperature of 450 °C and a pressure of 20 bar, which were selected based on experimental optimization. The spent catalyst was also successfully regenerated at 700 °C under a hot airflow. Experiments were conducted to determine the optimum conditions to completely separate the deactivated catalyst from the solid residue easily. The regenerated catalyst was reused to facilitate the economic cost reduction of the process. The reactivated catalysts have almost the same catalytic properties as the fresh catalysts; this was confirmed by several characterization techniques, such as TGA, XRD, SEM, EDX, BET and FTIR. The produced liquids/gases were quantified and classified into their fractions by the number of carbon atoms and gasoline to diesel ratio using GC/MS. The viscosity, density, API gravity, pour point and flash point of oil cuts were also investigated to evaluate the quality of the resulting liquid from the reactions. The NiMo/Al2O3 catalyst gave the highest liquid hydrocarbons yield of 86 wt%, while the highest weight products of gasoline range hydrocarbon fractions of 49.85 wt% were found over the Pt/Al2O3 catalyst. Almost the same catalytic behavior was found with the regenerated catalysts compared to the fresh catalysts. However, the highest gaseous products at 20.8 wt% were found in the non-catalytic thermal products with an increase in the diesel fuel range of 80.83 wt%. The kinetic model was implemented using six lumps and fifteen reactions, and the apparent activation energies for the gasoline and diesel fractions were calculated. In general, all primary and secondary reactions show greater activation energy values on the Pt/Al2O3 catalyst than on the NiMo/Al2O3 catalyst.
Fundamentals of State-Space Based Load Flow Calculation of Modern Energy Systems
Authors: Blenk Tobias , Weindl Christian
Published: June 2023

Our current energy landscape is ever-changing, resulting from the ongoing energy transition and introducing a massive expansion of volatile generation feed-in and energy consumption (due to electrification). In turn, the energy supply’s requirements are also being affected. In this context, the energy system’s optimisation across all sectors will only grow in significance, especially in terms of future developments. Facilitating and researching methods for carrying out the aforementioned optimisation creates new demands pertaining to load flow simulation programmes. The volatility of specific participants and their interactions within existing power grids must be evaluated, wherefore the consideration of a large number of time steps but also dynamic simulations becomes inevitable. Carrying out such simulations is possible but very time-consuming. This article compared a variety of conventional load flow simulations such as the current iteration and Newton–Raphson methods and also introduced a novel, state-space based calculation approach, which boasts the potential of structurally increasing simulation speeds. Each of the method’s underlying principles, requirements, and mathematical correlations will be discussed and explained. In the second part of this article, the most important state-space equivalent circuit models of critical operating equipment are introduced. These models are essential for carrying out load flow simulation tests for an exemplary test network but could also be used for dynamic purposes. The previously showcased load flow methods were applied to a test network, with which the simulation methods should be validated. The results show that the state-space simulation has high accuracy while also being very flexible. All in all, the load flow calculation in state-space offers many advantages that could be an interesting alternative to conventional load flow simulations, especially for the analysis of complex, time series-based, and intelligently controlled smart grid power systems. In this context, the direct application of system theoretical methods for stability calculations, controllability, and dynamic system studies is to be mentioned. Optimisation options regarding the processes within the state-space calculation software still promise further significant increases in performance.
Implicit Mathematical Model of Photovoltaic Arrays with Improved Calculation Speed Based on Inflection Points of the Current–Voltage Curves
Authors: Bastidas-Rodriguez Juan David , Ramos-Paja Carlos Andres , Saavedra-Montes Andres Julian
Published: June 2023

Dynamic reconfiguration, the monitoring of power production, and the fault diagnosis of photovoltaic arrays, among other applications, require fast and accurate models of photovoltaic arrays. In the literature, some models use the Lambert-W function to represent each module of the array, which increases the calculation time. Other models that use implicit equations to avoid the Lambert-W function do not use the inflection voltages to simplify the system of nonlinear equations that represent the array, increasing the computational burden. Therefore, this paper proposes mathematical models for series-parallel (SP) and total-cross-tied (TCT) photovoltaic arrays based on the implicit equations of the single-diode model and the inflection points of the current–voltage curves. These models decrease the calculation time by reducing the complexity of the nonlinear equation systems that represent each string of SP arrays and the whole TCT. Consequently, the calculation process that solves the model speeds up in comparison with processes that solve traditional explicit models based on the Lambert-W function. The results of several simulation scenarios using the proposed SP model with different array sizes show a reduction in the computation time by 82.97% in contrast with the traditional solution. Additionally, when the proposed TCT model for arrays larger than 2×2 is used, the reduction in the computation time is between 47.71% and 92.28%. In dynamic reconfiguration, the results demonstrate that the proposed SP model provides the same optimal configuration but 7 times faster than traditional solutions, and the TCT model is solved at least 4 times faster than classical solutions.
Adaptive Optimization Operation of Electric Vehicle Energy Replenishment Stations Considering the Degradation of Energy Storage Batteries
Authors: Bai Yuhang , Zhu Yun
Published: June 2023

As the construction of supporting infrastructure for electric vehicles (EV) becomes more and more perfect, an energy replenishment station (ERS) involving photovoltaics (PV) that can provide charging and battery swapping services for electric vehicle owners comes into the vision of humanity. The operation optimization of each device in the ERS is conducive to improving the service capacity of the ERS, extending the service life of the energy storage batteries (ESB), and enhancing the economic benefits of the ERS. However, traditional model-based optimization algorithms cannot fully consider the stochastic nature of EV owners’ charging and battery swapping demands, the uncertainty of PV output, and the complex operating characteristics of ESB. Therefore, we propose a deep reinforcement learning-based adaptive optimal operation method for ERS considering ESB’s losses. Firstly, a mathematical model of each device in the ERS is established, and a refined energy storage model is introduced to describe ESB’s capacity degradation and efficiency decay. Secondly, to solve the dimensional disaster problem, the state space and action space selection method, and the charging strategy of batteries in the battery swapping station (BSS) are proposed to apply to the ERS, thus modeling the ERS optimization operation problem as a Markov decision process. Then, the solution is performed using a neural network-based proximal policy optimization (PPO) algorithm, consisting of a recurrent neural network that extracts information about the PV outflow trend and a deep neural network used to generate a control policy. Finally, the effectiveness of the proposed method is verified by simulation calculations, which not only enable adaptive decision-making under different PV output scenarios, but also consider the availability of EV battery swapping services, energy storage losses, and the economic benefits of the ERS.
Spatial Decision-Making under Uncertainties for Supporting the Prospection of Sites for Hybrid Renewable Energy Generation Systems
Authors: Silva Lívia Maria Leite , Ekel Petr , Vieira Douglas Alexandre Gomes , Libório Matheus Pereira , D’angelo Marcos Flávio Silveira Vasconcelos
Published: June 2023

This research aims at developing methodological tools for decision makers (DMs) to determine the locations for generating sites for hybrid renewable energy systems, considering complementarity characteristics of the corresponding sources and their seasonal availability. The decision process on new sites starts using Geographic Information Systems for modeling relevant spatial criteria. The problem solution is associated with using the Slide-OWA operator, which permits one to control the inter-criteria compensation levels by adjusting pessimism and optimism parameters. After constructing multicriteria estimates for generating sites, the general scheme of multi-objective decision-making is applied in conditions of uncertainty since these estimates are subject to significant levels of uncertainty. Such a scheme is based on the possibilistic approach, which involves the construction of payoff matrices. At this point, it is possible that some alternatives cannot be distinguished based only on the criteria considered so far, or the DM may want to evaluate the alternatives from the point of view of additional considerations. For this purpose, the framework of multi-attribute decision-making models is applied by employing methods for preference modeling in a fuzzy environment. The present work results are applied to a case study of the Minas Gerais State in Brazil. These results play a strategic role for governments and investors in their decisions while considering the ability to meet a wide range of criteria.
Optimized Power Dispatch for Smart Building and Electric Vehicles with V2V, V2B and V2G Operations
Authors: Ahsan Syed Muhammad , Khan Hassan Abbas , Sohaib Sarmad , Hashmi Anas M.
Published: June 2023

The operation of smart buildings (with solar, storage and suitable power routing infrastructure) can be optimized with the addition of parking stations for electric vehicles (EVs) with vehicle-to-everything (V2X) operations including vehicle-to-vehicle (V2V), vehicle-to-building (V2B) and vehicle-to-grid (V2G) operations. In this paper, a multi-objective optimization framework is proposed for the smart charging and discharging of EVs along with the maximization of revenue and savings of smart building (prosumers with solar power, a battery storage system and a parking station) and non-primary/ordinary buildings (consumers of electricity without solar power, a battery storage system and parking station). A mixed-integer linear program is developed to maximize the profits of smart buildings that have bilateral contracts with non-primary buildings. The optimized charging and discharging (V2X) of EVs at affordable rates utilizing solar power and a battery storage system in the smart building helps to manage the EV load during on-peak hours and prevent utility congestion. The results indicate that in addition to the 4–9% daily electricity cost reductions for non-primary buildings, a smart building can achieve up to 60% of the daily profits. Further, EVs can save 50–69% in charging costs while performing V2X operations.
Purified Glycerine from Biodiesel Production as Biomass or Waste-Based Green Raw Material for the Production of Biochemicals
Authors: Borówka Grzegorz , Semerjak Grzegorz , Krasodomski Wojciech , Lubowicz Jan
Published: June 2023

Glycerine (glycerol) is a polyol consisting of three carbon atoms bonded to hydroxyl groups. It is a by-product of the transesterification of triglycerides, such as animal fats, vegetable oils, or used cooking oils during the biodiesel production process. Crude glycerine is subject to purification processes resulting in distilled glycerine containing at least 99.5% glycerol. Currently, produced high-quality distilled glycerine is used in the food, pharmaceutical, and cosmetic industries. Recently, technologies for converting glycerol to other chemicals through catalytic processes have been intensively developed, e.g., production of bio-based 1,2-propanediol. In the near future, glycerol will certainly become a promising renewable raw material in many modern biorefineries for the synthesis of biofuels, chemicals, and bioenergy production. This paper presents the possibility of using ion exchange resins to remove impurities with trace amounts of sulphur and nitrogen compounds from crude and distilled glycerine, produced during the biodiesel production process from used cooking oils. It was determined that using ion exchange resins at the preliminary purification stage (before distillation) was ineffective. Using cationite resins to purify distilled glycerine produced from waste materials enables the removal of impurities in the form of sulphur and nitrogen compounds.
Response of Soil Microbial Communities and Functions to Long-Term Tea (Camellia sinensis L.) Planting in a Subtropical Region
Authors: Zheng Xiangzhou , Wu Yiqun , Xu Aiai , Lin Cheng , Wang Huangping , Yu Juhua , Ding Hong , Zhang Yushu
Published: June 2023

Soil microbes are the key to revealing the mechanisms driving variation in soil biogeochemical processes. In recent decades, forests in Southeast China have been widely transformed into tea plantations due to the drivers of economic benefits. However, the changes in the soil microbial community and their potential function during the transition from a typical forest ecosystem to tea plantations remain poorly understood. This study investigated the soil microbial community in tea plantation soils with different planting ages, i.e., 6, 12, 23 and 35 years, and in an adjacent woodland control. We discovered that tea planting significantly increased soil bacterial richness (ACE and Chao1) and decreased fungal richness, the diversity of bacteria (Simpson and Shannon) show a trend of initially decreasing and then increasing while there was no significant effect on fungal diversity. After tea planting, the relative abundances of Actinobacteria and Proteobacteria increased by 180.9%–386.6% and 62.3%–97.5%, respectively; the relative abundances of Acidobacteria decreased by 11.4%–66.8%. However, the fungal phyla were not significantly different among different aged tea plantations and woodlands. FAPROTAX and FUNGuild revealed that the transition of natural woodland to tea plantations significantly increased the relative abundances of aerobic_chemoheterotrophy (14.66%–22.69%), chemoheterotrophy (34.36%–37.04%), ureolysis (0.68%–1.35%) and pathogenic fungi (26.17%–37.02%). db-RDA proved that the bacterial community structure was more strongly related to soil pH and available nitrogen (AN), while the main determinants of the fungal community composition were soil pH and soil organic matter (SOM). These findings indicate that tea planting has a strong effect on the soil microbial community and potential function. The change in soil pH during tea planting was the most important factor affecting the soil microbial community, while soil bacteria were more sensitive to tea planting than fungi.
Social Representations of Hesitant Brazilians about Vaccination against COVID-19
Authors: Santos Keila Cristina Oliveira dos , Junqueira-Marinho Maria de Fátima , Reis Adriana Teixeira , Camacho Karla Gonçalves , Nehab Marcio Fernandes , Abramov Dimitri Marques , Azevedo Zina Maria Almeida de , Menezes Livia Almeida de , Salú Margarida dos Santos , Figueiredo Carlos Eduardo da Silva , Moreira Maria Elisabeth Lopes , Vasconcelos Zilton Farias Meira de , Carvalho Flavia Amendola Anisio de , Mello Livia de Rezende de , Correia Roberta Fernandes , Gomes Junior Saint Clair dos Santos , Moore Daniella Campelo Batalha Cox
Published: June 2023

Background: The control of the COVID-19 pandemic has been a great challenge. Understanding the thoughts and beliefs underlying vaccine hesitancy can help in the formulation of public policies. The present study aimed to analyze the social representations of hesitant Brazilians about vaccination against COVID-19. Methods: Qualitative research guided by the Theory of Social Representations, carried out through an online survey among Brazilian adults living in Brazil. The data were analyzed using the IRaMuTeQ software. Results: Of the 173,178 respondents, 10,928 were hesitant and declared reasons for vaccination hesitation. The analysis generated three classes: mistrust of the vaccine and underestimation of the severity of the pandemic; (dis)information and distrust of political involvement; and fear of adverse reactions to COVID-19 vaccines. Conclusions: Social knowledge, presented by the representations apprehended in this study, demonstrates difficulty in discerning the reliability of information and a social imagination full of doubts and uncertainties. Understanding the internal dynamics of these groups, with their representations of the world, is important to propose policies and actions that echo and cause changes in the understanding of the role of immunization. It is essential to shed light on the sociological imagination so that gaps filled with false information can be dismantled and confronted with scientific knowledge accessible to the population.
Lyophilization Based Isolation of Exosomes
Authors: Qazi Rida e Maria , Sajid Zahra , Zhao Chunqiu , Hussain Irfan , Iftikhar Fizza , Jameel Muhammad , Rehman Fawad Ur , Mian Afsar Ali
Published: June 2023

Exosomes are nanoscale extracellular vesicles which regulate intercellular communication. They have great potential for application in nanomedicine. However, techniques for their isolation are limited by requirements for advanced instruments and costly reagents. In this study, we developed a lyophilization-based method for isolating exosomes from cultured cells. The isolated exosomes were characterized for protein content using Bradford assay, and for size distribution and shape using scanning electron microscopy (SEM) and nanoparticles tracking analysis (NTA). In addition, CD63, CD9, CD81, HSP70 and TSG101 were evaluated as essential exosomal surface markers using Western blot. Drug loading and release studies were performed to confirm their drug delivery properties using an in vitro model. Exosomes were also loaded with commercial dyes (Cy5, Eosin) for the evaluation of their drug delivery properties. All these characterizations confirmed successful exosome isolation with measurements of less than 150 nm, having a typical shape, and by expressing the known exosome surface protein markers. Finally, tyrosine kinase inhibitors (dasatinib and ponatinib) were loaded on the exosomes to evaluate their anticancer effects on leukemia cells (K562 and engineered Ba/F3-BCR-ABL) using MTT and Annexin-PI assays. The expression of MUC1 protein on the exosomes isolated from MCF-7 cells also indicated that their potential diagnostic properties were intact. In conclusion, we developed a new method for exosome isolation from cultured cells. These exosomes met all the essential requirements in terms of characterization, drug loading and release ability, and inhibition of proliferation and apoptosis induction in Ph+ leukemia cells. Based on these results, we are confident in presenting the lyophilization-based exosome isolation method as an alternative to traditional techniques for exosome isolation from cultured cells.
Treatment of Cardiac Fibrosis with Extracellular Vesicles: What Is Missing for Clinical Translation?
Authors: Neuber Sebastian , Ermer Miriam R. , Emmert Maximilian Y. , Nazari-Shafti Timo Z.
Published: June 2023

Heart failure is the leading cause of morbidity and mortality and currently affects more than 60 million people worldwide. A key feature in the pathogenesis of almost all forms of heart failure is cardiac fibrosis, which is characterized by excessive accumulation of extracellular matrix components in the heart. Although cardiac fibrosis is beneficial in the short term after acute myocardial injury to preserve the structural and functional integrity of the heart, persistent cardiac fibrosis contributes to pathological cardiac remodeling, leading to mechanical and electrical dysfunction of the heart. Despite its high prevalence, standard therapies specifically targeting cardiac fibrosis are not yet available. Cell-based approaches have been extensively studied as potential treatments for cardiac fibrosis, but several challenges have been identified during clinical translation. The observation that extracellular vesicles (EVs) derived from stem and progenitor cells exhibit some of the therapeutic effects of the parent cells has paved the way to overcome limitations associated with cell therapy. However, to make EV-based products a reality, standardized methods for EV production, isolation, characterization, and storage must be established, along with concrete evidence of their safety and efficacy in clinical trials. This article discusses EVs as novel therapeutics for cardiac fibrosis from a translational perspective.
Target Identification in Anti-Tuberculosis Drug Discovery
Authors: Capela Rita , Félix Rita , Clariano Marta , Nunes Diogo , Perry Maria de Jesus , Lopes Francisca
Published: June 2023

Mycobacterium tuberculosis (Mtb) is the etiological agent of tuberculosis (TB), a disease that, although preventable and curable, remains a global epidemic due to the emergence of resistance and a latent form responsible for a long period of treatment. Drug discovery in TB is a challenging task due to the heterogeneity of the disease, the emergence of resistance, and uncomplete knowledge of the pathophysiology of the disease. The limited permeability of the cell wall and the presence of multiple efflux pumps remain a major barrier to achieve effective intracellular drug accumulation. While the complete genome sequence of Mtb has been determined and several potential protein targets have been validated, the lack of adequate models for in vitro and in vivo studies is a limiting factor in TB drug discovery programs. In current therapeutic regimens, less than 0.5% of bacterial proteins are targeted during the biosynthesis of the cell wall and the energetic metabolism of two of the most important processes exploited for TB chemotherapeutics. This review provides an overview on the current challenges in TB drug discovery and emerging Mtb druggable proteins, and explains how chemical probes for protein profiling enabled the identification of new targets and biomarkers, paving the way to disruptive therapeutic regimens and diagnostic tools.
Physical Mapping of QTLs for Root Traits in a Population of Recombinant Inbred Lines of Hexaploid Wheat
Authors: Li Xiaoqing , Wasson Anton P. , Zwart Alexander B. , Whan Alex , Ryan Peter R. , Forrest Kerrie , Hayden Matthew , Chin Sabrina , Richards Richard , Delhaize Emmanuel
Published: June 2023

Root architecture is key in determining how effective plants are at intercepting and absorbing nutrients and water. Previously, the wheat (Triticum aestivum) cultivars Spica and Maringa were shown to have contrasting root morphologies. These cultivars were crossed to generate an F6:1 population of recombinant inbred lines (RILs) which was genotyped using a 90 K single nucleotide polymorphisms (SNP) chip. A total of 227 recombinant inbred lines (RILs) were grown in soil for 21 days in replicated trials under controlled conditions. At harvest, the plants were scored for seven root traits and two shoot traits. An average of 7.5 quantitative trait loci (QTL) were associated with each trait and, for each of these, physical locations of the flanking markers were identified using the Chinese Spring reference genome. We also compiled a list of genes from wheat and other monocotyledons that have previously been associated with root growth and morphology to determine their physical locations on the Chinese Spring reference genome. This allowed us to determine whether the QTL discovered in our study encompassed genes previously associated with root morphology in wheat or other monocotyledons. Furthermore, it allowed us to establish if the QTL were co-located with the QTL identified from previously published studies. The parental lines together with the genetic markers generated here will enable specific root traits to be introgressed into elite wheat lines. Moreover, the comprehensive list of genes associated with root development, and their physical locations, will be a useful resource for researchers investigating the genetics of root morphology in cereals.
ARL6IP5 Ameliorates α-Synuclein Burden by Inducing Autophagy via Preventing Ubiquitination and Degradation of ATG12
Authors: Siddique Ibrar , Kamble Kajal , Gupta Sakshi , Solanki Kavita , Bhola Sumnil , Ahsan Nuzhat , Gupta Sarika
Published: June 2023

Recent advanced studies in neurodegenerative diseases have revealed several links connecting autophagy and neurodegeneration. Autophagy is the major cellular degradation process for the removal of toxic protein aggregates responsible for neurodegenerative diseases. More than 30 autophagy-related proteins have been identified as directly participating in the autophagy process. Proteins regulating the process of autophagy are much more numerous and unknown. To address this, in our present study, we identified a novel regulator (ARL6IP5) of neuronal autophagy and showed that the level of ARL6IP5 decreases in the brain with age and in Parkinson’s disease in mice and humans. Moreover, a cellular model of PD (Wild type and A53T mutant α-synuclein overexpression) has also shown decreased levels of ARL6IP5. ARL6IP5 overexpression reduces α-synuclein aggregate burden and improves cell survival in an A53T model of Parkinson’s disease. Interestingly, detailed mechanistic studies revealed that ARL6IP5 is an autophagy inducer. ARL6IP5 enhances Rab1-dependent autophagosome initiation and elongation by stabilizing free ATG12. We report for the first time that α-synuclein downregulates ARL6IP5 to inhibit autophagy-dependent clearance of toxic aggregates that exacerbate neurodegeneration.
Environmental Air Pollutants Affecting Skin Functions with Systemic Implications
Authors: Bocheva Georgeta , Slominski Radomir M. , Slominski Andrzej T.
Published: June 2023

The increase in air pollution worldwide represents an environmental risk factor that has global implications for the health of humans worldwide. The skin of billions of people is exposed to a mixture of harmful air pollutants, which can affect its physiology and are responsible for cutaneous damage. Some polycyclic aromatic hydrocarbons are photoreactive and could be activated by ultraviolet radiation (UVR). Therefore, such UVR exposure would enhance their deleterious effects on the skin. Air pollution also affects vitamin D synthesis by reducing UVB radiation, which is essential for the production of vitamin D3, tachysterol, and lumisterol derivatives. Ambient air pollutants, photopollution, blue-light pollution, and cigarette smoke compromise cutaneous structural integrity, can interact with human skin microbiota, and trigger or exacerbate a range of skin diseases through various mechanisms. Generally, air pollution elicits an oxidative stress response on the skin that can activate the inflammatory responses. The aryl hydrocarbon receptor (AhR) can act as a sensor for small molecules such as air pollutants and plays a crucial role in responses to (photo)pollution. On the other hand, targeting AhR/Nrf2 is emerging as a novel treatment option for air pollutants that induce or exacerbate inflammatory skin diseases. Therefore, AhR with downstream regulatory pathways would represent a crucial signaling system regulating the skin phenotype in a Yin and Yang fashion defined by the chemical nature of the activating factor and the cellular and tissue context.
Genomic Prediction of Resistance to Tan Spot, Spot Blotch and Septoria Nodorum Blotch in Synthetic Hexaploid Wheat
Authors: García-Barrios Guillermo , Crossa José , Cruz-Izquierdo Serafín , Aguilar-Rincón Víctor Heber , Sandoval-Islas J. Sergio , Corona-Torres Tarsicio , Lozano-Ramírez Nerida , Dreisigacker Susanne , He Xinyao , Singh Pawan Kumar , Pacheco-Gil Rosa Angela
Published: June 2023

Genomic prediction combines molecular and phenotypic data in a training population to predict the breeding values of individuals that have only been genotyped. The use of genomic information in breeding programs helps to increase the frequency of favorable alleles in the populations of interest. This study evaluated the performance of BLUP (Best Linear Unbiased Prediction) in predicting resistance to tan spot, spot blotch and Septoria nodorum blotch in synthetic hexaploid wheat. BLUP was implemented in single-trait and multi-trait models with three variations: (1) the pedigree relationship matrix (A-BLUP), (2) the genomic relationship matrix (G-BLUP), and (3) a combination of the two matrices (A+G BLUP). In all three diseases, the A-BLUP model had a lower performance, and the G-BLUP and A+G BLUP were statistically similar (p ≥ 0.05). The prediction accuracy with the single trait was statistically similar (p ≥ 0.05) to the multi-trait accuracy, possibly due to the low correlation of severity between the diseases.
Generation and Functional Characterization of Anti-CD19 Chimeric Antigen Receptor-Natural Killer Cells from Human Induced Pluripotent Stem Cells
Authors: Klaihmon Phatchanat , Kang Xing , Issaragrisil Surapol , Luanpitpong Sudjit
Published: June 2023

Natural killer (NK) cells are a part of innate immunity that can be activated rapidly in response to malignant transformed cells without prior sensitization. Engineering NK cells to express chimeric antigen receptors (CARs) allows them to be directed against corresponding target tumor antigens. CAR-NK cells are regarded as a promising candidate for cellular immunotherapy alternatives to conventional CAR-T cells, due to the relatively low risk of graft-versus-host disease and safer clinical profile. Human induced pluripotent stem cells (iPSCs) are a promising renewable cell source of clinical NK cells. In the present study, we successfully introduced a third-generation CAR targeting CD19, which was validated to have effective signaling domains suitable for NK cells, into umbilical cord blood NK-derived iPSCs, followed by a single-cell clone selection and thorough iPSC characterization. The established single-cell clone of CAR19-NK/iPSCs, which is highly desirable for clinical application, can be differentiated using serum- and feeder-free protocols into functional CAR19-iNK-like cells with improved anti-tumor activity against CD19-positive hematologic cancer cells when compared with wild-type (WT)-iNK-like cells. With the feasibility of being an alternative source for off-the-shelf CAR-NK cells, a library of single-cell clones of CAR-engineered NK/iPSCs targeting different tumor antigens may be created for future clinical application.
The Antimicrobial and Antibiofilm Potential of New Water-Soluble Tris-Quaternary Ammonium Compounds
Authors: Frolov Nikita A. , Seferyan Mary A. , Valeev Anvar B. , Saverina Evgeniya A. , Detusheva Elena V. , Vereshchagin Anatoly N.
Published: June 2023

The invention and innovation of highly effective antimicrobials are always crucial tasks for medical and organic chemistry, especially at the current time, when there is a serious threat of shortages of effective antimicrobials following the pandemic. In the study presented in this article, we established a new approach to synthesizing three novel series of bioactive water-soluble tris-quaternary ammonium compounds using an optimized one-pot method, and we assessed their antimicrobial and antibiofilm potential. Five pathogenic microorganisms of the ESKAPE group, including highly resistant clinical isolates, were used as the test samples. Moreover, we highlighted the dependence of antibacterial activity from the hydrophilic–hydrophobic balance of the QACs and noted the significant performance of the desired products on biofilms with MBEC as low as 16 mg/L against bacteria and 8 mg/L against fungi. Particularly notable was the high activity against Pseudomonas aeruginosa and Acinetobacter baumannii, which are among the most resilient bacteria known. The presented work will provide useful insights for future research on the topic.
Genome-Wide Investigation of BAM Gene Family in Annona atemoya: Evolution and Expression Network Profiles during Fruit Ripening
Authors: Wang Luli , Jing Minmin , Gu Shuailei , Li Dongliang , Dai Xiaohong , Chen Zhihui , Chen Jingjing
Published: June 2023

β-amylase proteins (BAM) are important to many aspects of physiological process such as starch degradation. However, little information was available about the BAM genes in Annona atemoya, an important tropical fruit. Seven BAM genes containing the conservative domain of glycoside hydrolase family 14 (PF01373) were identified with Annona atemoya genome, and these BAM genes can be divided into four groups. Subcellular localization analysis revealed that AaBAM3 and AaBAM9 were located in the chloroplast, and AaBAM1.2 was located in the cell membrane and the chloroplast. The AaBAMs belonging to Subfamily I contribute to starch degradation have the higher expression than those belonging to Subfamily II. The analysis of the expression showed that AaBAM3 may function in the whole fruit ripening process, and AaBAM1.2 may be important to starch degradation in other organs. Temperature and ethylene affect the expression of major AaBAM genes in Subfamily I during fruit ripening. These expressions and subcellular localization results indicating β-amylase play an important role in starch degradation.
Heterologous DNA Prime- Subunit Protein Boost with Chikungunya Virus E2 Induces Neutralizing Antibodies and Cellular-Mediated Immunity
Authors: Coirada Fernanda Caroline , Fernandes Edgar Ruz , Mello Lucas Rodrigues de , Schuch Viviane , Soares Campos Gúbio , Braconi Carla Torres , Boscardin Silvia Beatriz , Santoro Rosa Daniela
Published: June 2023

Chikungunya virus (CHIKV) has become a significant public health concern due to the increasing number of outbreaks worldwide and the associated comorbidities. Despite substantial efforts, there is no specific treatment or licensed vaccine against CHIKV to date. The E2 glycoprotein of CHIKV is a promising vaccine candidate as it is a major target of neutralizing antibodies during infection. In this study, we evaluated the immunogenicity of two DNA vaccines (a non-targeted and a dendritic cell-targeted vaccine) encoding a consensus sequence of E2CHIKV and a recombinant protein (E2*CHIKV). Mice were immunized with different homologous and heterologous DNAprime-E2* protein boost strategies, and the specific humoral and cellular immune responses were accessed. We found that mice immunized with heterologous non-targeted DNA prime- E2*CHIKV protein boost developed high levels of neutralizing antibodies, as well as specific IFN-γ producing cells and polyfunctional CD4+ and CD8+ T cells. We also identified 14 potential epitopes along the E2CHIKV protein. Furthermore, immunization with recombinant E2*CHIKV combined with the adjuvant AS03 presented the highest humoral response with neutralizing capacity. Finally, we show that the heterologous prime-boost strategy with the non-targeted pVAX-E2 DNA vaccine as the prime followed by E2* protein + AS03 boost is a promising combination to elicit a broad humoral and cellular immune response. Together, our data highlights the importance of E2CHIKV for the development of a CHIKV vaccine.
Assessing the Novel Myval Balloon-Expandable Valve with the Evolut Valve: A Propensity-Matched Study
Authors: Halim Jonathan , Rooijakkers Maxim , den Heijer Peter , El Haddad Milad , van den Branden Ben , Vos Jeroen , Schölzel Bas , Meuwissen Martijn , van Gameren Menno , El Messaoudi Saloua , van Royen Niels , IJsselmuiden Sander
Published: June 2023

Background: The Myval balloon-expandable (BE) valve has shown encouraging early clinical data in terms of safety and efficacy. Comparative data with other well-established contemporary valves are nonetheless still scarce. This study aims to compare the performance of the Myval BE valve with the Evolut self-expanding (SE) valve. Methods: In this retrospective single-center study, 223 patients with symptomatic severe aortic stenosis (AS) were included and treated with the Myval BE valve (n = 120) or with the Evolut SE valve (n = 103). Then, 91 pairs were compared after matching. Clinical outcomes were evaluated at 30 days and 1 year. Echocardiographic follow-up was performed at 30 days. Results: Procedural complications were rare in both groups. At the 30-day follow-up, no significant difference in cardiac death (Myval: 1% vs. Evolut: 2%, p = 0.56), stroke (2% vs. 4%, p = 0.41) and myocardial infarction (1% vs. 3%, p = 0.31) was observed. A permanent pacemaker implantation (PPI) was significantly less needed in the Myval group (4% vs. 15%, p = 0.01). At 1 year, cardiac death (2% vs. 4%, p = 0.41) and the stroke rate (7% vs. 5%, p = 0.76) were similar. Moderate–severe paravalvular leakage (PVL) was also comparable in both groups (1% vs. 4%, p = 0.17). Conclusion: Safety and efficacy outcomes were comparable between the two valves, except for a higher PPI rate for the Evolut SE valve. Up to 1-year follow-up, clinical outcomes showed acceptable rates of stroke and cardiac death with both valves. Valve hemodynamics were excellent with a low rate of moderate–severe PVL in both groups.
Specific Features of Stromal Cells Isolated from the Two Layers of Subcutaneous Adipose Tissue: Roles of Their Secretion on Angiogenesis and Neurogenesis
Authors: Laloze Jérôme , Lacoste Marie , Marouf Faris , Carpentier Gilles , Vignaud Laetitia , Chaput Benoit , Varin Audrey , Desmoulière Alexis , Rovini Amandine
Published: June 2023

Human-adipose-tissue-derived mesenchymal stromal cells (AD-MSCs) are currently being tested as autologous-cell-based therapies for use in tissue healing and regeneration. Recent studies have also demonstrated that AD-MSC-derived exosomes contribute to tissue repair and peripheral nerve regeneration. Subcutaneous abdominal adipose tissue (AAT) is divided into two layers: the superficial layer (sAAT) and the deep layer (dAAT). However, it is unclear whether there are particular characteristics of each layer in terms of AD-MSC regenerative potential. Using AD-MSCs purified and characterized from three abdominoplasties, we compared their secretomes and exosome functions to identify which layer may be most suitable as a source for cell therapy. Phenotypical analysis of the AD-MSCs containing stromal vascular fraction did not reveal any difference between the two layers. The AD-MSC secretomes showed a very similar pattern of cytokine content and both layers were able to release exosomes with identical characteristics. However, compared to the secretome, the released exosomes showed better biological properties. Interestingly, dAAT exosomes appeared to be more effective on neuromodulation, whereas neither sAAT nor dAAT-derived exosomes had significant effects on endothelial function. It thus appears that AD-MSC-derived exosomes from the two abdominal adipose tissue layers possess different features for cell therapy.
Irritable Bowel Syndrome and Resilience
Authors: Fadgyas Stanculete Mihaela , Ismaiel Abdulrahman , Popa Stefan-Lucian , Capatina Octavia Oana
Published: June 2023

Irritable bowel syndrome (IBS) is a disorder of the gut–brain interaction (DGBI), characterized, mainly in severe cases, by altered psychological stress reactivity, psychological disorders, and dysfunction of the brain–gut–microbiota axis. Prior studies have highlighted significant physical and emotional impairments in the health-related quality of life of patients with IBS. Resilience is a psychosocial ability that reduces negative emotions while enhancing adaptation to adversities. Resilience is essential for health promotion and stress response. The present study aimed to carry out a review of the literature in multiple databases, using the descriptors “resilience”, “resiliency”, and “irritable bowel syndrome”. The inclusion criteria for obtaining the most relevant papers were research articles on resilience and irritable bowel syndrome written in English, published in a peer-reviewed journal, and involving human subjects. Studies specifically on resilience in IBS were sparse. These results need to be understood in light of these limitations. As resilience appears to be modifiable, it is essential to conduct direct research on resilience-enhancing interventions for people with IBS. The study of the factors involved in successful adaptation must be extended, to possibly yield new interventions that help the patients overcome the difficulties imposed by the disease.
Factors Associated with Vascular Changes at the Level of Retinal Ganglion Cell Axon versus Soma/Dendrite in Glaucoma Patients
Authors: Oh Si-Eun , Shin Hee-Jong , Park Chan-Kee , Park Hae-Young Lopilly
Published: June 2023

Superficial and deep macular vessel density (VD) is decreased in eyes with glaucoma. Superficial VD comprises both the retinal nerve fiber layer (RNFL) and ganglion cell/inner plexiform layer (GC/IPL), and various terms have been used previously to describe the layers of macular VD. In our study, we readjusted the macular segmentation. We obtained RNFL and GC/IPL VDs separately to evaluate VD changes of axon versus soma/dendrite of the retinal ganglion cells (RGCs) in detail. We included 66 eyes of normal tension glaucoma patients with inferior localized RNFL defects solely impacting the inferior hemiretina. Macular VD was measured as RNFL VD and GC/IPL VD. VD ratio was calculated by dividing the VD from the affected hemiretina by the VD from the unaffected hemiretina. RNFL VD ratio was related to RNFL and GC/IPL thicknesses (p = 0.005, p = 0.001), whereas GC/IPL VD ratio was not (p = 0.596, p = 0.783). A lower GC/IPL VD ratio was associated with lower RNFL VD (p = 0.017) and systemic hypertension (p = 0.03) in multivariate analysis. Patients with a reduced GC/IPL VD ratio were more prone to poor visual field defects (p = 0.022) and paracentral scotoma (p = 0.046) and more likely to be on treatment for systemic hypertension (p = 0.024). Therefore, glaucoma patients on systemic hypertension treatment and reduced GC/IPL VD require cautious management.
Influence of Clinical and Sociodemographic Variables on Health-Related Quality of Life in the Adult Population with Long COVID
Authors: Rodríguez-Pérez Mª Pilar , Sánchez-Herrera-Baeza Patricia , Rodríguez-Ledo Pilar , Huertas-Hoyas Elisabet , Fernández-Gómez Gemma , Montes-Montes Rebeca , Pérez-de-Heredia-Torres Marta
Published: June 2023

Worldwide, about 10 percent of patients affected by long COVID require appropriate follow-up and intervention. The main objective of this study was to analyze the long-term impact of mild long COVID in the adult population, and to determine the effect of clinical and sociodemographic variables on health-related quality of life in those affected. Methods: A cross-sectional descriptive study of a sample of Spanish adult patients with persistent COVID-19 symptoms at least three months after diagnosis. Data collection took place between April and July 2021. The health-related quality of life of the sample was low, with worse results in the physical component summary (PCS) 24.66 (SD = 4.45) compared to the mental component summary (MCS) 45.95 (SD = 8.65). The multi-regression analysis showed significant differences by sex in the dimensions of physical functioning (p = 0.040); bodily pain (p = 0.036); and health transition (p = 0.018). Additionally, a longer time since infection had a significant effect on physical functioning (p = 0.039); general health (p = 0.037); vitality (p = 0.034); and general health transition (p = 0.002). The effect of occupational imbalance was significant for all dimensions. Conclusions: people with long COVID have a reduced quality of life. Sex, time since infection, and occupational imbalance are predictors of a worse quality of life.
Unveiling the Comorbidities of Chronic Diseases in Serbia Using ML Algorithms and Kohonen Self-Organizing Maps for Personalized Healthcare Frameworks
Authors: Rankovic Nevena , Rankovic Dragica , Lukic Igor , Savic Nikola , Jovanovic Verica
Published: June 2023

In previous years, significant attempts have been made to enhance computer-aided diagnosis and prediction applications. This paper presents the results obtained using different machine learning (ML) algorithms and a special type of a neural network map to uncover previously unknown comorbidities associated with chronic diseases, allowing for fast, accurate, and precise predictions. Furthermore, we are presenting a comparative study on different artificial intelligence (AI) tools like the Kohonen self-organizing map (SOM) neural network, random forest, and decision tree for predicting 17 different chronic non-communicable diseases such as asthma, chronic lung diseases, myocardial infarction, coronary heart disease, hypertension, stroke, arthrosis, lower back diseases, cervical spine diseases, diabetes mellitus, allergies, liver cirrhosis, urinary tract diseases, kidney diseases, depression, high cholesterol, and cancer. The research was developed as an observational cross-sectional study through the support of the European Union project, with the data collected from the largest Institute of Public Health “Dr. Milan Jovanovic Batut” in Serbia. The study found that hypertension is the most prevalent disease in Sumadija and western Serbia region, affecting 9.8% of the population, and it is particularly prominent in the age group of 65 to 74 years, with a prevalence rate of 33.2%. The use of Random Forest algorithms can also aid in identifying comorbidities associated with hypertension, with the highest number of comorbidities established as 11. These findings highlight the potential for ML algorithms to provide accurate and personalized diagnoses, identify risk factors and interventions, and ultimately improve patient outcomes while reducing healthcare costs. Moreover, they will be utilized to develop targeted public health interventions and policies for future healthcare frameworks to reduce the burden of chronic diseases in Serbia.