Numerous Processes Research Articles

132 Detailed Characterization of a Novel Human Ex Vivo Model for Burn Injuries

Abstract Introduction Burn injuries belong to the most common soft tissue injuries and often result in extensive trauma but are also associated with cases of major emergency such as sepsis or systemic inflammatory response syndrome. The early phase after burn injury is critical and decides about later potential complications in wound healing. Burn injuries activate numerous processes, including heat shock, inflammation and tissue regeneration responses and thereby promote the release of cytokines and other signalling molecules such as miRNAs and metabolites. Despite extensive research, skin tissue reactions in the early phases after burn injuries still need to be investigated in more detail. Therefore, reliable burn models are needed to elucidate the exact sequence of events during the healing process and to monitor potential biomarkers that could give information about treatment success. Methods We induced contact burns on fresh human abdominal skin explants that were resected during abdominoplasty. Gene and miRNA expression patterns, cytokine production profiles of key mediators such as IL8 and IL6 and skin ultrastructure were analysed for 24 hours after the burn injury. Additionally, we used open flow microperfusion (OFM), a sampling technique that allows time and location dependent collection of dermal interstitial fluid (dISF), to also monitor the release of specific miRNAs, cytokines and metabolites. Results In burn injuries, we found significant changes in gene and miRNA expression as soon as one hour after burn injury. Inflammatory genes such as IL8 were significantly up-regulated whereas miRNAs were systematically down-regulated. miRNAs were actively released and mobilized into the dISF, while miR-497-5p could be identified stably downregulated in tissue and dISF in the early phase after a burn injury. Metabolome analysis of dISF showed a striking metabolic shift in burn injuries, linking burn injury to increased amino acid and glucose turnover in wounds. Conclusions By using this ex vivo human skin model for burn injuries we were able to study the immediate early responses to burns for up to 24 h. We found that miR-497-5p could serve as potential biomarker to assess burn severity since it is not only down-regulated in skin but also mobilized into the dISF after burn injury. Furthermore, we found distinct metabolite signatures after burn injury. Applicability of Research to Practice Identification and research on potential biomarkers to assess burn severity and treatment success.

Direct observation on H-elimination enhancement from C2H4 through non-adiabatic process by femtosecond laser induced Coulomb explosion

Abstract Ethylene, the simplest model of a carbon-carbon double bond system, is pivotal in numerous chemical and biological processes. By employing intense infrared (IR) laser pump-probe techniques alongside coincidence measurements, we investigated the ultrafast non-adiabatic dynamics involved in the breakage of carbon-carbon double bonds and hydrogen elimination in ethylene's dissociation. Our study entailed analyzing the dynamic Kinetic Energy Release (KER) spectra to assess three bond-breaking scenarios, the movements of nuclei, and the structural changes around the carbon atoms. This allowed us to evaluate the relaxation dynamics and characteristics of various dissociative states. Notably, we observed a significant rise in the yield of fragments resulting from CH bond breakage as the delay time extended, suggesting non-adiabatic coupling through conical intersections from CC bond breakage as a probable cause.

Land/Water Aerobic Activities: Two Sides of the Same Coin. A Comparative Analysis on the Effects in Cognition of Alzheimer's Disease.

Evidence in the literature indicates that aerobic physical activity may have a protective role in aging pathologies. However, it has not been clarified whether different types of aerobic exercise produce different effects. In particular, these potential differences have not been explored in patients with Alzheimer's disease (AD). The present narrative review has the specific aim of evaluating whether land (walking/running) and water (swimming) aerobic activities exert different effects on cognitive functions and neural correlates in AD patients. In particular, the investigation is carried out by comparing the evidence provided from studies on AD animal models and on patients. On the whole, we ascertained that both human and animal studies documented beneficial effects of land and water aerobic exercise on cognition in AD. Also, the modulation of numerous biological processes is documented in association with structural modifications. Remarkably, we found that aerobic activity appears to improve cognition per se, independently from the specific kind of exercise performed. Aerobic exercise promotes brain functioning through the secretion of molecular factors from skeletal muscles and liver. These molecular factors stimulate neuroplasticity, reduce neuroinflammation, and inhibit neurodegenerative processes leading to amyloid-β accumulation. Additionally, aerobic exercise improves mitochondrial activity, reducing oxidative stress and enhancing ATP production. Aerobic activities protect against AD, but implementing exercise protocols for patients is challenging. We suggest that health policies and specialized institutions should direct increasing attention on aerobic activity as lifestyle modifiable factor for successful aging and age-related conditions.

Numerical analysis of age-structured HIV model with general transmission mechanism

In this paper, we discuss the numerical representation of the linearly implicit Euler method for an age-structured HIV infection model with a general transmission mechanism. We first define the basic reproduction number of the continuous model, and present the stability results of the equilibriums. For the numerical process, we establish the solvability of the system and the non-negativity and convergence of numerical solutions. In the analysis of the long-term dynamical behavior, this paper mainly focus on the existence of the infection equilibrium determined by the numerical reproduction number R0Δt. To overcome the difficulty caused by the complexity of epidemic transmission mechanisms, the 1-order convergence analysis of numerical basic reproduction numbers R0Δt is implemented by using the properties of the fundamental solution matrix. By a comparison principle, we show that the disease-free equilibrium is globally asymptotically stable if R0Δt<1. Moreover, for R0Δt>1, a unique numerical endemic equilibrium exists, which converges to the exact one, is locally asymptotically stable. Hence, numerical processes visually represent the dynamic properties of nonlinear age-structured HIV models. Finally, some numerical experiments demonstrate the verification and the efficiency of our results.

CPK10 protein kinase regulates Arabidopsis tolerance to borondeficiency through phosphorylation and activation of BOR1 transporter.

Boron (B) is crucial for plant growth and development. B deficiency can impair numerous physiological and metabolic processes, particularly in root development and pollen germination, seriously impeding crop growth and yield. However, the molecular mechanism underlying boron signal perception and signal transduction is rather limited. In this study, we discovered that CPK10, a calcium-dependent protein kinase in the CPK family, has the strongest interaction with the boron transporter BOR1. Mutations in CPK10 led to growth and root development defects under B-deficiency conditions, while constitutively active CPK10 enhanced plant tolerance to B deficiency. Furthermore, we found that CPK10 interacted with and phosphorylated BOR1 at the Ser689 residue. Through various biochemical analyses and complementation of B transport in yeast and plants, we revealed that Ser689 of BOR1 is important for its transport activity. In summary, these findings highlight the significance of the CPK10-BOR1 signaling pathway in maintaining B homeostasis in plants and provide targets for the genetic improvement of crop tolerance to B-deficiency stress.

Photodriven electron-transfer dynamics in a series of heteroleptic Cu(I)-anthraquinone dyads.

Solar fuels catalysis is a promising route to efficiently harvesting, storing, and utilizing abundant solar energy. To achieve this promise, however, molecular systems must be designed with sustainable components that can balance numerous photophysical and chemical processes. To that end, we report on the structural and photophysical characterization of a series of Cu(I)-anthraquinone-based electron donor-acceptor dyads. The dyads utilized a heteroleptic Cu(I) bis-diimine architecture with a copper(I) bis-phenanthroline chromophore donor and anthraquinone electron acceptor. We characterized the structures of the complexes using x-ray crystallography and density functional theory calculations and the photophysical properties via resonance Raman and optical transient absorption spectroscopy. The calculations and resonance Raman spectroscopy revealed that excitation of the Cu(I) metal-to-ligand charge-transfer (MLCT) transition transfers the electron to a delocalized ligand orbital. The optical transient absorption spectroscopy demonstrated that each dyad formed the oxidized copper-reduced anthraquinone charge-separated state. Unlike most Cu(I) bis-phenanthroline complexes where increasingly bulky substituents on the phenanthroline ligands lead to longer MLCT excited-state lifetimes, here, we observe a decrease in the long-lived charge-separated state lifetime with increasing steric bulk. The charge-separated state lifetimes were best explained in the context of electron-transfer theory rather than with the energy gap law, which is typical for MLCT excited states, despite the complete conjugation between the phenanthroline and anthraquinone moieties.

PWHT influence on welding residual stress in 45 mm bridge steel butt-welded joint

To investigate the spatial distribution of welding residual stress (WRS) and effect of post welding heat treatment (PWHT) on WRS relaxation in the welded components of steel bridges, a 45 mm-thick Q345qD butt-welded specimen was manufactured. Experimental measurement and numerical simulation methods were employed to examine specimen surface and internal WRSs. The simulated results exhibited good agreement with the measured ones, confirming the rationality of the numerical simulation process. Subsequently, through the PWHT simulation in ABAQUS, the evolution of WRS during PWHT was comprehensively analyzed and the effect of PWHT parameters on the stress relaxation was studied. The measured and simulated results show that the longitudinal welding residual stresses (LWRSs) are tensile in the weld region and compressive away from the weld. High-value stresses are mainly concentrated on specimen surfaces and the mid-thickness. Transverse welding residual stresses (TWRSs) present multi-layered distribution, alternating between tension and compression within the weld region. WRS reduction mainly occurs during the heating stage of PWHT, with slight decrease during the holding stage and an increase during the cooling stage. Optimizing PWHT parameters, including temperature, and holding time, heating/cooling rates, proved effective in achieving substantial WRS relaxation.

Application of spatial filtering high order FDTD method in the multi-physics field coupled equations

The traditional finite-difference time-domain method (FDTD(2, 2)) is widely employed to solve the coupled equations of quantum-electromagnetic multi-physics. However, the time step of the traditional explicit FDTD(2, 2) method is limited by the Courant-Friedrichs-Lewy (CFL) condition. Besides, the FDTD(2, 2) method only achieves the second-order accuracy, which can result in significant error accumulation. To overcome this problem, we propose the SF-HO-FDTD(2, q) method with scalable time stability conditions for solving the multi-physics field coupled equations (q denotes q-th order spatial difference scheme). This approach integrates spatial filtering (SF) and higher-order FDTD (HO-FDTD) methods. Moreover, the proposed method requires no further derivation of the iterative equations of the traditional HO-FDTD(2, q) method. It only needs to introduce the SF operation in each numerical iteration process to filter out the spatial high-frequency components arising from the use of time steps that do not satisfy the CFL stability condition. This condition is applied to ensure the stability of the numerical method. Therefore, the proposed method has a high compatibility with the traditional HO-FDTD(2, q) method. Then, the numerical dispersion analysis of the SF-HO-FDTD(2, q) method is theoretically studied. Finally, numerical examples are carried out to confirm the accuracy and efficiency of the strategy suggested in this study.

AI guided workflows for efficiently screening the materials space

Artificial intelligence (AI) may capture the properties and functions of materials better than previous theoretical/computational methods because it targets correlations and does not assume a single, specific underlying physical model. Therefore, it addresses the full intricacy of the numerous processes that govern the function of materials. However, the statistical analysis and interpretation of AI models require careful attention. The review article started with a brief discussion of historical aspects of data-centric science. It then focused on the recently developed, explainable AI methods [8,10] and applications [2,11,12]. The identified "rules" determine the properties and functions of materials. The rules depend on descriptive parameters called "materials genes." As genes in biology, they are correlated with a certain material property or function. Thus, these materials genes help to identify materials that are, for example, better electrical conductors or better heat insulators or better catalysts.

What makes different number-space mappings interact?

Models of numerical cognition consider a visuo-spatial representation to be at the core of numerical processing, the 'mental number line'. Two main interference effects between number and space have been described: the SNARC effect reflects a small number/left side and large number/right side association (number-location mapping); the size-congruity effect (SCE) reflects a small number/small size and large number/large size association (number-size mapping). Critically, a thorough investigation on the representational source for these two number-space mappings is lacking, leaving open the question of whether the same representation underlies both phenomena. Here, we build on a recent study (Viarouge and de Hevia in Front Hum Neurosci 15:750964, 2021) in order to address this question in three experiments, by systematically manipulating the presence of the two conditions that might elicit an interaction between SNARC and SCE: (i) an implicit task whereby numerical and spatial information are task-irrelevant, (ii) a design in which the number-space congruency relative to both mappings vary at the same level -either both within or between blocks. Experiment 1 replicated the interaction between the two mappings when both factors were present. Experiments 2 and 3 dissociated the two factors by varying the two mappings at the same level but using an explicit comparison task (Experiment 2), or by using an implicit task but with mappings varying at different levels (Experiment 3). We found that both factors, either in combination or used in isolation, drive the interaction between the two number-space mappings. These findings are discussed in terms of the weight given to each mapping, suggesting that a single representation encompassing both number-space mappings is therefore activated whenever both mappings are given equal weight through task requirements.

Unraveling the influence of health protocol implementation for different clusters on COVID‐19 transmission in West Java, Indonesia

This article formulates and analyzes the COVID‐19 transmission model on West Java by considering the health protocol implementation level on three different clusters. The transmission possibilities are classified into three clusters based on the society's daily activities, including (1) retailing, (2) transit, and (3) recreation. The model was constructed by dividing the population into seven compartments, namely, susceptible ; susceptible in Clusters 1–3 ( , , and ); infected ; quarantined ; and recovered sub‐populations. To confirm the biological validity of the model, the existence, uniqueness, non‐negativity, and boundedness of the solution are investigated. The dynamical behaviors are studied analytically by applying linearization for local stability and the Lyapunov function along with the LaSalle's invariant principle for global stability. Some numerical processes are demonstrated to investigate the most global sensitivity of parameters, parameter estimation, fitting data, and the impact of health protocol implementation on the density of each population.

From the grapevine to the glass: A wine metabolomics tale by FT-ICR-MS.

Wine is one of the most consumed beverages around the world. Its unique characteristics arise from numerous processes, from the selection of grapevine varieties and grapes, the effect of the terroir and geographical origin, through the biochemical process of fermentation by microorganisms, until its aging. All molecules found in wine define its chemical fingerprint and can be used to tell the story of its origin, production, authenticity and quality. Wine's chemical composition can be characterized using an untargeted metabolomics approach based on extreme resolution mass spectrometry. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is currently the most powerful analytical technique to analyse such complex sample, providing the most comprehensive analysis of the chemical fingerprint of wine.

Next-Generation Metabolic Glycosylation Reporters Enable Detection of Protein O-GlcNAcylation in Living Cells without S-Glyco Modification.

Protein O-GlcNAcylation is a ubiquitous posttranslational modification of cytosolic and nuclear proteins involved in numerous fundamental regulation processes. Investigation of O-GlcNAcylation by metabolic glycoengineering (MGE) has been carried out for two decades with peracetylated N-acetylglucosamine (GlcNAc) and N-acetylgalactosamine derivatives modified with varying reporter groups. Recently, it has been shown that these derivatives can result in non-specific protein labeling termed S-glyco modification. Here, we report norbornene-modified GlcNAc derivatives with a protected phosphate at the anomeric position and their application in MGE. These derivatives overcome two limitations of previously used O-GlcNAc reporters. They do not lead to detectable S-glyco modification, and they efficiently react in the inverse-electron-demand Diels-Alder (IEDDA) reaction, which can be carried out even within living cells. Using a derivative with an S-acetyl-2-thioethyl-protected phosphate, we demonstrate the protein-specific detection of O-GlcNAcylation of several proteins and the protein-specific imaging of O-GlcNAcylation inside living cells by Förster resonance energy transfer (FRET) visualized by confocal fluorescence lifetime imaging microscopy (FLIM).

Next‐Generation Metabolic Glycosylation Reporters Enable Detection of Protein O−GlcNAcylation in Living Cells without S‐Glyco Modification

AbstractProtein O−GlcNAcylation is a ubiquitous posttranslational modification of cytosolic and nuclear proteins involved in numerous fundamental regulation processes. Investigation of O−GlcNAcylation by metabolic glycoengineering (MGE) has been carried out for two decades with peracetylated N‐acetylglucosamine (GlcNAc) and N‐acetylgalactosamine derivatives modified with varying reporter groups. Recently, it has been shown that these derivatives can result in non‐specific protein labeling termed S‐glyco modification. Here, we report norbornene‐modified GlcNAc derivatives with a protected phosphate at the anomeric position and their application in MGE. These derivatives overcome two limitations of previously used O−GlcNAc reporters. They do not lead to detectable S‐glyco modification, and they efficiently react in the inverse‐electron‐demand Diels–Alder (IEDDA) reaction, which can be carried out even within living cells. Using a derivative with an S‐acetyl‐2‐thioethyl‐protected phosphate, we demonstrate the protein‐specific detection of O−GlcNAcylation of several proteins and the protein‐specific imaging of O−GlcNAcylation inside living cells by Förster resonance energy transfer (FRET) visualized by confocal fluorescence lifetime imaging microscopy (FLIM).

Clinical significance of small extracellular vesicles in cholangiocarcinoma.

Cholangiocarcinoma is an aggressive and heterogeneous malignancy originating from the bile duct epithelium. It is associated with poor prognosis and high mortality. The global incidence of cholangiocarcinoma is rising, and there is an urgent need for effective early diagnosis and treatment strategies to reduce the burden of this devastating tumor. Small extracellular vesicles, including exosomes and microparticles, are nanoscale vesicles formed by membranes that are released both normally and pathologically from cells, mediating the intercellular transfer of substances and information. Recent studies have demonstrated the involvement of small extracellular vesicles in numerous biological processes, as well as the proliferation, invasion, and metastasis of tumor cells. The present review summarizes the tumorigenic roles of small extracellular vesicles in the cholangiocarcinoma microenvironment. Owing to their unique composition, accessibility, and stability in biological fluids, small extracellular vesicles have emerged as ideal biomarkers for use in liquid biopsies for diagnosing and outcome prediction of cholangiocarcinoma. Specific tissue tropism, theoretical biocompatibility, low clearance, and strong biological barrier penetration of small extracellular vesicles make them suitable drug carriers for cancer therapy. Furthermore, the potential value of small extracellular vesicle-based therapies for cholangiocarcinoma is also reviewed.

BoaBZR1.1 mediates brassinosteroid-induced carotenoid biosynthesis in Chinese kale

Abstract Brassinazole resistant 1 (BZR1), a brassinosteroid (BR) signaling component, plays a pivotal role in regulating numerous specific developmental processes. Our study demonstrated that exogenous treatment with 2,4-epibrassinolide (EBR) significantly enhanced the accumulation of carotenoids and chlorophylls in Chinese kale (Brassica oleracea var. alboglabra). The underlying mechanisms was deciphered through yeast one-hybrid (Y1H) and dual-luciferase (LUC) assays, whereby BoaBZR1.1 directly interacts with the promoters of BoaCRTISO and BoaPSY2, activating their expression. This effect was further validated through overexpression of BoaBZR1.1 in Chinese kale calli and plants, both of which exhibited increased carotenoid accumulation. Additionally, qPCR analysis unveiled upregulation of carotenoid and chlorophyll biosynthetic genes in the T1 generation of BoaBZR1.1-overexpressing plants. These findings underscored the significance of BoaBZR1.1-mediated BR signaling in regulating carotenoid accumulation in Chinese kale and suggested the potential for enhancing the nutritional quality of Chinese kale through genetic engineering of BoaBZR1.1.

Kosambi-Cartan-Chern perspective on chaos: Unveiling hidden attractors in nonlinear autonomous systems.

This article confronts the formidable task of exploring chaos within hidden attractors in nonlinear three-dimensional autonomous systems, highlighting the lack of established analytical and numerical methodologies for such investigations. As the basin of attraction does not touch the unstable manifold, there are no straightforward numerical processes to detect those attractors and one has to implement special numerical and analytical strategies. In this article we present an alternative approach that allows us to predict the basin of attraction associated with hidden attractors, overcoming the existing limitations. The method discussed here is based on the Kosambi-Cartan-Chern theory which enables us to conduct a comprehensive theoretical analysis by means of evaluating geometric invariants and instability exponents, thereby delineating the regions encompassing chaotic and periodic zones. Our analytical predictions are thoroughly validated by numerical results.

A novel coumarin-linked tetraphenylethene fluorescent probe for simultaneous sensing of ATP and GSH

Adenosine triphosphate (ATP) as the intracellular energy currency, and glutathione (GSH) as the regulator of redox homeostasis in the cell microenvironment, are all closely associated with numerous important physiological processes in living organisms. However, the fluorescent probes that can simultaneously detect ATP and GSH are rarely reported. Herein, a bifunctional coumarin-linked tetraphenylethene (TPE) probe P1 was successfully developed, which exhibits a red emission at 633 nm owing to the fluorescence resonance energy transfer (FRET) from energy donor coumarin to energy acceptor TPE. P1 can detect ATP with a fluorescence turn-on response at 633 nm in the red channel by complexation-enhanced aggregation mechanism, and showed a ratiometric detection toward GSH through the disruption of the FRET process, accompanied by an increase in the blue channel at 467 nm and a decrease in the red channel at 633 nm. P1 also displays a superior sensitivity and high selectivity to ATP and GSH, with a detection limit of 20.80 nM for ATP and 3.47 µM for GSH. Significantly, P1 can discriminate GSH from ATP and other analytes due to the different response times. Furthermore, P1 can localize mitochondria and has been discovered to be capable of imaging ATP and GSH in living cells and zebrafish.

A machine learning approach for entropy due to natural convection flow of a nanofluid under the uniform inclined magnetic field

In this study, entropy generation of natural convection flow of Cu-water nanofluid under the influence of a uniform inclined magnetic field (MF) is firstly modeled by a machine learning approach using the data obtained from a numerical process. The two dimensional, time dependent dimensionless equations are numerically solved by using global radial basis function (RBF) method in spatial derivatives and the second order backward differentiation formula (BDF2) in time derivatives. In a set of combined dimensionless problem parameters, numerical simulations are performed. In the obtained data, the inputs are a set of combined dimnesionless problem parameters and the outputs are entropy indicators. Then, global and local entropy indicators are modeled by Neural Network (NN). In view of smaller mean squared error metric results, small number of layers or layer sizes in NN seems enough in smaller data while trilayer NN (TNN) is a better modeler in case of larger data.

Coenzyme Q4 is a functional substitute for coenzyme Q10 and can be targeted to the mitochondria

Coenzyme Q10 (CoQ10) is an important cofactor and antioxidant for numerous cellular processes, and its deficiency has been linked to human disorders including mitochondrial disease, heart failure, Parkinson's disease, and hypertension. Unfortunately, treatment with exogenous CoQ10 is often ineffective, likely due to its extreme hydrophobicity and high molecular weight. Here, we show that less hydrophobic CoQ species with shorter isoprenoid tails can serve as viable substitutes for CoQ10 in human cells. We demonstrate that CoQ4 can perform multiple functions of CoQ10 in CoQ-deficient cells at markedly lower treatment concentrations, motivating further investigation of CoQ4 as a supplement for CoQ10 deficiencies. In addition, we describe the synthesis and evaluation of an initial set of compounds designed to target CoQ4 selectively to mitochondria using triphenylphosphonium. Our results indicate that select versions of these compounds can successfully be delivered to mitochondria in a cell model and be cleaved to produce CoQ4, laying the groundwork for further development.