Model Of Complex Research Articles

Model-based conceptualization of thyroid hormone equilibrium via set point and stability behavior

The HPT complex, consisting of the hypothalamus, pituitary and thyroid, functions as a regulated system controlled by the respective hormones. This system maintains an intrinsic equilibrium, called the set point, which is unique to each individual. In order to optimize the treatment of thyroid patients and understand the dynamics of the system, a validated theoretical representation of this set point is required. Therefore, the research field of mathematical modeling of the HPT complex is significant as it provides insights into the interactions between hormones and the determination of this endogenous equilibrium. In literature, two mathematical approaches are presented for the theoretical determination of the set point in addition to a time-dependent model. The two approaches are based on the maximum curvature of the pituitary response function and the optimal gain factor in the representation of the HPT complex as a closed feedback system. This paper demonstrates that all hormone curves described by the model converge to the derived set point with increasing time. This result establishes a clear correlation between the physiological equilibrium described by the set point and the mathematical equilibrium with respect to autonomous systems of differential equations. It thus substantiates the validity of the theoretical set point approaches.

Уравнения, описывающие процессы эксплуатации траловых комплексов

Exploring deep-sea resources is an important step towards sustainable and efficient use of marine resources. Research may include analysis of biodiversity, ecosystem characteristics, and deep-sea fishing technologies and practices. Research in this area provides unique opportunities to advance understanding of the marine ecosystem for the development of deep-sea fisheries. This, in turn, helps to strengthen the sustainability and competitiveness of the Russian fishery complex in the long term. In the Russian Federation, the priority is to conduct scientific research in the field of deep-sea fishing, aimed both at developing the fishing of deep-sea objects and at studying them for the purpose of processing for the pharmaceutical industry. The development of innovative methods for catching mesopelagic fish and deep-sea aquatic organisms is an important task for the scientific community of the Russian Federation. The equations designed to describe various processes that occur during the operation of bottom and mid-depth trawl systems are discussed. The complexity of solving the above equations indicates the advisability of dividing exploitation processes into micro-level, macro-level and meta-level. The theory of multiphysics similarity allows you to simulate processes at various levels. Computer programs are presented that make it possible to recalculate the results of model experiments from a model of a trawl complex to a full-scale trawl complex.

Underappreciated layers of antibody-mediated immune synapse architecture and dynamics.

The biologic activities of antibody drugs are dictated by structure-function relationships-emerging from the kind, composition, and degree of interactions with a target antigen and with soluble and cellular antibody receptors of the innate immune system. These activities are canonically understood to be both modular: antigen recognition is driven by the heterodimeric antigen-binding fragment, and innate immune recruitment by the homodimeric constant/crystallizable fragment. The model that treats these domains with a high degree of independence has served the field well but is not without limitations. Here, we consider how new insights, particularly from structural studies, complicate the model of neat biophysical separation between these domains and shape our understanding of antibody effector functions. The emerging model endeavors to explain the phenotypic impact of both antibody intrinsic characteristics and extrinsic features-fitting them within a spatiotemporal paradigm that better accounts for observed antibody activities. In this review, we will use insights from recent models of classical complement complexes and T cell immune synapse formation to explore how structural differences in antibody-mediated immune synapses may relate to their functional diversity.

Epithetization as a way of categorizing football discourse

INTRODUCTION. The relevance of the study is due to the need to study the linguistic methods of categorization of socially significant fragments of the external world and different types of discourse. The purpose of the study is to identify epithets characterizing the game of the Russian national team and its rivals at the 2018 FIFA World Cup; to determine the composition of their thematic groups and subgroups, as well as linguistic means that are carriers of the characteristic nomination, in the process of lexical, grammatical and functional categorization of linguistic units.MATERIALS AND METHODS. The subject of the study is a feature nomination (epithetation) as a way of categorizing sports (football) discourse based on the material of the journalistic book by the Russian sports journalist I.Ya. Rabiner “Team-2018: Champions of Our Hearts”. During the analysis of the linguistic material, the method of continuous sampling, contextual analysis, the method of semantic-cognitive analysis, the modeling method, and the statistical method are used.RESULTS AND DISCUSSION. In the process of lexical and functional categorization of characteristic words (epithets), two thematic groups were identified: 1) epithets characterizing the game of the Russian national team; 2) epithets characterizing the game of the opponent. Each group is represented by several subgroups. Cases of interaction of epithetization and metaphorization were revealed, demonstrating the transition from one conceptual area to another (crazy blow, aggressive football, iron penalty). In the process of grammatical categorization of epithets, means of expressing the characteristic nomination (adjectival and adverbial vocabulary) and 8 structural models of epithet complexes were determined.CONCLUSION. According to statistics, the number of epithets characterizing the play of the Russian national team is 5 times greater than the number of epithets characterizing the play of the opponent; the number of subgroups of the first thematic group is almost 2 times greater than the number of subgroups of the second thematic group. Such quantitative indicators reveal the ethnocultural and personal features of the linguistic understanding of a fragment of the world and emphasize attention, special interest in national (Russian) realities. Many epithets characterizing the play of the Russian national team have a positive connotation (wonderful attack, united, integral, brotherly play, excellent defender), in contrast to epithets with a negative connotation characterizing the play of the opponent (terrible, panicky play, empty, slow and clumsy players).

Physics-Based and Data Driven Modeling of Electrophoretic Coatings: Hybrid and Multiphysics Strategy

Electrophoretic coatings are used in several applications where surface treatment is intended to provide corrosion protection. These coatings are widely used in the automotive, aerospace, or many other sectors. These kind of coatings are electrochemically applied and have good levelling, penetration, adhesion, and corrosion resistance properties. A wide variety of materials can be deposited by this technique and among these coatings, this presentation will focus on ceramic deposits. In this case, electrophoretic deposition is carried out using a suspension containing ceramic particles and the deposition takes place on a conductive substrate through the application of an electric field. The control of process parameters and post-processing parameters (heat treatment or sintering) necessary to consolidate the raw coatings obtained can be difficult to define. In order to improve process management and understanding of electrophoretic deposition, we will explore several strategies and modelling theories implemented in the field of electrophoretic coating through a comprehensive analysis in order to optimize the coating process, improve quality and increase efficiency on complex geometry parts. Several theoretical approaches and models have been used to better understand electrochemical interactions and forces involved in electrophoresis to identify parameters related to electrophoretic mobility. The multiple parameters involved in electrophoretic coatings make the modelling of this process complex and the models developed are neither universal nor applicable to all chemistries which requires a specific development for each electrolyte and suspension. In a second part, we discuss limits of theoretical models and describes a strategy to develop a new modelling approach. This approach combines a physics-based model of current distribution and a data-driven optimization applied to electrophoretic coating. This methodology allows to model the thickness distribution on a part with complex geometry on an industrial scale, with the ability to adapt to a variation in the chemistry of the suspension used. This hybrid methodology allow to reduce experimental and fundamental characterizations, and can be easily applied to a new chemistry to estimate and well describe the throwing power at a macroscale. Furthermore, in some cases, physics-based modeling with secondary distribution can exhibit accuracy defects when the local concentration of particles drops, due to their consumption and low mass transport phenomena. In order to better describe the process behavior in this specific case, we develop a multiphysics model of tertiary current distribution than can account for the local distribution of particles, particularly near the part. This modeling approach allows to better anticipate thickness distribution in areas with low fluid mixing and agitation. The local efficiency is linked to the local current and particle concentration, as describe by a two phase flow model. The models developed are intended to help accurately predict and control the distribution of coating thickness and also local particle concentration to predict critical depletion zones. In conclusion, this conference explore different modeling strategies of electrophoretic coatings, by focusing on the optimization of process parameters and the consideration of the different mechanisms governing deposition with the objective of improving coating distribution on complex part.

Modeling of Complex Integrated Photonic Resonators Using the Scattering Matrix Method

Modeling of Complex Integrated Photonic Resonators Using the Scattering Matrix Method

Structural Evaluation of Interleukin-19 Cytokine and Interleukin-19-Bound Receptor Complex Using Computational Immuno-Engineering Approach

Interleukin 19 (IL-19) is an anti-inflammatory cytokine that belongs to the IL-10 family, where IL-20 and IL-24 also exist. While IL-19 and IL-20 share some comparable structural folds, there are certain structural divergences in their N-terminal ends. To date, there are no reported IL-19 receptors; although, it has been suggested in the literature that IL-19 would bind to lL-20 receptor (IL-20R) and trigger the JAK-STAT signaling pathways. The present report examines the structure of the IL-19 cytokine and its receptor complex using a computational approach. Specifically, the postulated modes of interactions for IL-20R as an IL-19 receptor are examined on the basis of a set of computational findings. The author has used molecular docking and molecular dynamics simulation to generate a 3D model for the IL-19 complex with IL-20R. When a protein’s crystal structure is not available in the literature, predictive modeling is often employed to determine the protein’s 3D structure. The model assessment can be based on various factors, which include stability analysis using RMSD calculations, tracking changes in time-based secondary structures and the associated Gibbs energies, ΔG. Since one model complex (referred to as model A throughout this paper) can be used as a working hypothesis for future experiments, this structure has been explored here in detail to check its stability, subunit interfaces, and binding residues. The information gathered in this approach can potentially help to design specific experiments to test the validity of the model protein structure. Additionally, the results of this research should be relevant for understanding anti-inflammatory mechanisms and, eventually, could contribute to the efforts for therapeutic developments and targeted therapy.

GPCRdb in 2025: adding odorant receptors, data mapper, structure similarity search and models of physiological ligand complexes.

G protein-coupled receptors (GPCRs) are membrane-spanning transducers mediating the actions of numerous physiological ligands and drugs. The GPCR databaseGPCRdb supports a large global research community with reference data, analysis, visualization, experiment design and dissemination. Here, we describe our sixth major GPCRdb release starting with an overview of all resources for receptors and ligands. As a major addition, all ∼400 human odorant receptors and their orthologs in major model organisms can now be studied across the various data and tool resources. For the first time, a Data mapper page enables users to map their own data onto receptors visualized as a GPCRome wheel, tree, clusters, list or heatmap. The structure model data have been expanded with models of physiological ligand complexes and updated with new state-specific structure models of all human GPCRs (built using AlphaFold, RoseTTAFold and AlphaFold-Multistate). Furthermore, a structure or model (pdb file) can now be queried against GPCRdb's entire structure/model collection through a Structuresimilarity search page implementing FoldSeek. Finally, for ligands, new search tools can query names, database identifiers, similarities or substructures against integrated entries from the ChEMBL, Guide to Pharmacology, PDSP Ki, PubChem, DrugCentral and DrugBank databases. GPCRdb is available at https://gpcrdb.org.

Advancing Non-Atom-Centered Basis Methods for More Accurate Interaction Energies: Benchmarks and Large-Scale Applications.

Recent advances in local electron correlation approaches have enabled the relatively routine access to CCSD(T) [that is, coupled cluster (CC) with single, double, and perturbative triple excitations] computations for molecules of a hundred or more atoms. Here, approaching their complete basis set (CBS) limit becomes more challenging due to extensive basis set superposition errors, often necessitating the use of large atomic orbital (AO) basis sets with diffuse functions. Here, we study a potential remedy in the form of non-atom-centered or floating orbitals (FOs). FOs are still rarely employed even for small molecules due to the practical complication of defining their position, number, exponents, etc. The most frequently used FO method thus simply places a single FO center with a large number of FOs toward the middle of noncovalent dimers; however, a single FO center for larger complexes can soon become insufficient. A recent alternative uses a grid of FO centers around the monomers with a single s function per center, which is currently applicable only for H, C, N, and O atoms. Here, we build on the above advantages and mitigate some drawbacks of previous FO approaches by using a layer of FO centers and 4-9 FOs/center for each monomer. Thus, a double layer of FOs is placed between the interacting subsystems. When extending the double-ζ AO basis with this double layer of FOs, the quality of conventional augmented double-ζ or conventional triple-ζ AO bases can be reached or surpassed with less orbitals, leading to few tenths of a kcal/mol basis set errors for medium-sized dimers. This good performance extends to larger molecules (shown here up to 72 atoms), as efficient local natural orbital (LNO) CCSD(T) computations with only double-ζ AO and 4 FOs/center FO bases match our LNO-CCSD(T)/CBS reference within ca. 0.1 kcal/mol. These developments introduce FO methods to the accurate modeling of large molecular complexes without limitations to atom types by further accelerating efficient correlation calculations, like LNO-CCSD(T).

VIRTUAL DESIGN OF NOVEL OF ORALLY BIOAVAILABLE PIPERAZINE INHIBITORS OF ENOYL-ACYL CARRIER PROTEIN REDUCTASE OF MYCOBACTERIUM TUBERCULOSIS WITH FAVORABLE PHARMACOKINETIC PROFILES

Background: During the previous decade, Anti-tuberculosis therapies were confronted with drug-resistant strains. We report here virtual design and evaluation of novel piperazine (PPZ) as inhibitors of InhA-Mt endowed with favorable predicted pharmacokinetic profiles. Method: Three-dimensional (3D) models of InhA-PPZx complexes were prepared by in situ modifications of the crystal structure of InhA-PPZ1 (Protein Data Bank (PDB) entry code: 1P44), the reference compound of a training set of 12 PPZs with known experimental inhibitory potencies (IC50exp). First, in the search for active conformation of the PPZ 1-12, we built a gas phase quantitative structure-activity relationships (QSAR) model, linearly correlating the computed enthalpy of the InhA-PPZ complex formation and the pIC50exp. Finally, the VCL filtered by Lipinski’s rule-of-five was screened by the PH4 model and the potencies of the new PPZ analogs obtained were evaluated with the initial QSAR and their pharmacokinetic profile was evaluated. Results: The VCL of 310,500 PPZs s was filtered down to 19,044 analogs by the Lipinski’s rule. The five-point PH4 screening retained 50 new potent PPZs with predicted inhibitory potencies IC50pre up to 100-times better than that of PPZ1 (IC50exp=160 nM). Predicted pharmacokinetic profile of the new analogs showed enhanced cell membrane permeability, side effect and high human oral absorption compared to current anti-tuberculosis candidates Conclusions: Combining molecular modeling and PH4 in virtual screening of the VL resulted in the proposed novel potent antituberculotic agent candidates with favorable pharmacokinetic profiles. Peer Review History: Received 21 July 2024; Reviewed 13 September 2024; Accepted 20 October; Available online 15 November 2024 Academic Editor: Dr. Asia Selman Abdullah, Pharmacy institute, University of Basrah, Iraq, asia_abdullah65@yahoo.com Average Peer review marks at initial stage: 6.0/10 Average Peer review marks at publication stage: 7.5/10 Reviewers: Antonio José de Jesus Evangelista, Federal University of Ceará, UFC, Brazil, tony_biomed@hotmail.com Asmaa Ahmed Mohamed Ahmed Khalifa, Pharos University, Alexandria, Egypt, asmaa.khalifa@pua.edu.eg

CRISPR-Cas9 mediated knockout of NDUFS4 in human iPSCs: A model for mitochondrial complex I deficiency

Mitochondrial diseases, often caused by defects in complex I (CI) of the oxidative phosphorylation system, currently lack curative treatments. Human-relevant, high-throughput drug screening platforms are crucial for the discovery of effective therapeutics, with induced pluripotent stem cells (iPSCs) emerging as a valuable technology for this purpose. Here, we present a novel iPSC model of NDUFS4-related CI deficiency that displays a strong metabolic phenotype in the pluripotent state. Human iPSCs were edited using CRISPR-Cas9 to target the NDUFS4 gene, generating isogenic NDUFS4 knockout (KO) cell lines. Sanger sequencing detected heterozygous biallelic deletions, whereas no indel mutations were found in isogenic control cells. Western blotting confirmed the absence of NDUFS4 protein in KO iPSCs and CI enzyme kinetics showed a ~56 % reduction in activity compared to isogenic controls. Comprehensive metabolomic profiling revealed a distinct metabolic phenotype in NDUFS4 KO iPSCs, predominantly associated with an elevated NADH/NAD+ ratio, consistent with alterations observed in other models of mitochondrial dysfunction. Additionally, β-lapachone, a recognized NAD+ modulator, alleviated reductive stress in KO iPSCs by modifying the redox state in both the cytosol and mitochondria. Although undifferentiated iPSCs cannot fully replicate the complex cellular dynamics of the disease seen in vivo, these findings highlight the utility of iPSCs in providing a relevant metabolic milieu that can facilitate early-stage, high-throughput exploration of therapeutic strategies for mitochondrial dysfunction.

Perturbational Analysis of Magnetic Force Theorem for Magnetic Exchange Interactions in Molecules and Solids.

There have been increasing efforts to compute magnetic exchange coupling constants for transition metal complexes and magnetic insulators using the magnetic force theorem and Green's function-based linear response methods. These were originally conceived for magnetic metals, yet it has not been clear how these methods fare conceptually with the conventional models based on electron-correlation interactions among so-called magnetic orbitals. We present a spinor-based theoretical analysis pertinent to the magnetic force theorem and linear response theory using Brillouin-Wigner perturbation method and Green's function perturbation method, and we shed light on the conceptual nature of the Lichtenstein formula in its applications for calculations of the total energy and magnetic exchange coupling constants for both molecules and solids. Derivation of the magnetic force theorem in this perturbational analysis identifies the first-order energy correction terms, which are considered as the ferromagnetic component for the magnetic exchange interactions of transition metal compounds but are not included in the Lichtenstein formula. Detailed perturbational analysis of the energy components involved in the magnetic force theorem identifies the energy components that are missing in the Lichtenstein formula but are critical in the Anderson's model for transition metal complexes and magnetic insulators where magnetic orbitals can overlap.

Parameter estimation and hypothesis tests in logistic model for complex correlated data

Observations are frequently generated in clinical trials from correlated multiple organs (or parts) of individuals. The statistical inference is little about conducting regression analysis based on such data. This paper first develops a logistic regression for correlated multiple responses using a stable correlation binomial (SCB) model. Then, we obtain maximum likelihood estimators (MLEs) of unknown parameters through a fast quadratic lower bound (QLB) algorithm. Further, likelihood ratio, score and Wald statistics are used to test the effect of covariates based on the MLEs. Finally, the QLB algorithm and asymptotic tests are evaluated through simulations and applied to real dental data.

Parameterized inapproximability of Morse matching

We study the problem of minimizing the number of critical simplices from the point of view of inapproximability and parameterized complexity. We first show inapproximability of Min-Morse Matching within a factor of 2log(1−ϵ)⁡n. Our second result shows that Min-Morse Matching is W[P]-hard with respect to the standard parameter. Next, we show that Min-Morse Matching with standard parameterization has no FPT approximation algorithm for any approximation factor ρ. The above hardness results are applicable to complexes of dimension ≥2.On the positive side, we provide a factor O(nlog⁡n) approximation algorithm for Min-Morse Matching on 2-complexes, noting that no such algorithm is known for higher dimensional complexes. Finally, we devise discrete gradients with very few critical simplices for typical instances drawn from a fairly wide range of parameter values of the Costa–Farber model of random complexes.

Architectural Organization of Ecological Tourist Complexes (The South Russia Case Studies)

This article analyzes the domestic and foreign experience in design of ecological tourist complexes, their architectural organization, three architectural models of ecological tourist complexes, and identifies the main design techniques. The relevance is determined by the growing interest of society in ecology; an increase in the tourist potential of the territories of southern Russia due to changing conditions; the emergence of a new type of tourist architecture, as well as an insufficient amount of design experience.Purpose: To identify the architecture of ecological tourist complexes and develop design proposals for such complexes in the south of Russia.Methodology/approach: The analysis of formative factors: urban planning, architectural planning, functional, environmental, affecting the architecture of ecological tourist complexes, their classification by organizational structure, functional content, accessibility, social efficiency and environmental factors. The concept of an ecological tourist complex in Krasnodar is proposed.Research findings: The organization of ecological tourism in the natural environment, environmental education of the population in the process of recreation are considered. Architectural models of ecological tourist complexes are proposed: adventure, scientific and recreational elements of environmental education, their comparative analysis, and selection of the effective model for Krasnodar.

Atomistic Insights into gp82 Binding: A Microsecond, Million-Atom Exploration of Trypanosoma cruzi Host-Cell Invasion.

Chagas disease, caused by the protozoan Trypanosoma cruzi , affects millions globally, leading to severe cardiac and gastrointestinal complications in its chronic phase. The invasion of host cells by T. cruzi is mediated by the interaction between the parasite's glycoprotein gp82 and the human receptor lysosome-associated membrane protein 2 (LAMP2). While experimental studies have identified a few residues involved in this interaction, a comprehensive molecular-level understanding has been lacking. In this study, we present a 1.44-million-atom computational model of the gp82 complex, including over 3,300 lipids, glycosylation sites, and full molecular representations of gp82 and LAMP2, making it the most complete model of a parasite-host interaction to date. Using microsecond-long molecular dynamics simulations and dynamic network analysis, we identified critical residue interactions, including novel regions of contact that were previously uncharacterized. Our findings also highlight the significance of the transmembrane domain of LAMP2 in stabilizing the complex. These insights extend beyond traditional hydrogen bond interactions, revealing a complex network of cooperative motions that facilitate T. cruzi invasion. This study not only confirms key experimental observations but also uncovers new molecular targets for therapeutic intervention, offering a potential pathway to disrupt T. cruzi infection and combat Chagas disease.

Phosphorylation of the HMGN1 Nucleosome Binding Domain Decreases Helicity and Interactions with the Acidic Patch.

Intrinsically disordered proteins are abundant in the nucleus and are prime sites for posttranslational modifications that modulate transcriptional regulation. Lacking a defined three-dimensional structure, intrinsically disordered proteins populate an ensemble of several conformational states, which are dynamic and often altered by posttranslational modifications, or by binding to interaction partners. Although there is growing appreciation for the role that intrinsically disordered regions have in regulating protein-protein interactions, we still have a poor understanding of how to determine conformational population shifts, their causes under various conditions, and how to represent and model conformational ensembles. Here, we study the effects of serine phosphorylation in the nucleosome-binding domain of an intrinsically disordered protein - HMGN1 - using NMR spectroscopy, circular dichroism and modelling of protein complexes. We show that phosphorylation induces local conformational changes in the peptide backbone and decreases the helical propensity of the nucleosome binding domain. Modelling studies using AlphaFold3 suggest that phosphorylation disrupts the interface between HMGN1 and the nucleosome acidic patch, but that the models over-predict helicity in comparison to experimental data. These studies help us to build a picture of how posttranslational modifications might shift the conformational populations of disordered regions, alter access to histones, and regulate chromatin compaction.

Parameterization of a Fluctuating Charge Model for Complexes Containing 3d Transition Metals.

Metalloproteins widely exist in biology, playing pivotal roles in diverse life processes. Meanwhile, molecular dynamics (MD) simulations based on classical force fields has emerged as an important tool in scientific research. Partial charges are critical parameters within classical force fields and usually derived from quantum mechanical (QM) calculations. However, QM calculations are often time-consuming and prone to basis set dependence. Alternatively, fluctuating charge (FQ) models offer another avenue for partial charge derivation, which has significant speed advantages and can be used for large-scale screening. Building upon our previous work, which introduced an FQ model for zinc-containing complexes, herein we extend this model to include additional 3d transition metals which are important to the life sciences, namely chromium, manganese, iron, cobalt, and nickel. Employing CM5 charges as target for parametrization, our FQ model accurately reproduces partial charges for 3d metal complexes featuring biologically relevant ligands. Furthermore, by using atomic charges derived by our FQ model, MD simulations have been performed. These charges showed excellent performance in simulating proteomic metal sites housing multiple metal ions, specifically, a metalloprotein containing an iron-sulfur cluster and another containing a dimanganese metal site, showcasing comparable performance to those of RESP charges. We anticipate that our study can accelerate the parametrization of atomic charges for metalloproteins featuring 3d transition metals, thereby facilitating simulations of relevant systems.

Thermostatted Kinetic Theory Structures in Biophysics: Generalizations and Perspectives

The mathematical modeling of multicellular systems is an important branch of biophysics, which focuses on how the system properties emerge from the elementary interaction between the constituent elements. Recently, mathematical structures have been proposed within the thermostatted kinetic theory for the modeling of complex living systems and have been profitably employed for the modeling of various complex biological systems at the cellular scale. This paper deals with a class of generalized thermostatted kinetic theory frameworks that can stand in as background paradigms for the derivation of specific models in biophysics. Specifically, the fundamental homogeneous thermostatted kinetic theory structures of the recent literature are recovered and generalized in order to take into consideration further phenomena in biology. The generalizations concern the conservative, the nonconservative, and the mutative interactions between the inner system and the outer environment. In order to sustain the strength of the new structures, some specific models of the literature are reset into the style of the new frameworks of the thermostatted kinetic theory. The selected models deal with breast cancer, genetic mutations, immune system response, and skin fibrosis. Future research directions from the theoretical and modeling viewpoints are discussed in the whole paper and are mainly devoted to the well-posedness in the Hadamard sense of the related initial boundary value problems, to the spatial–velocity dynamics and to the derivation of macroscopic-scale dynamics.

Disease models of Leigh syndrome: From yeast to organoids.

Leigh syndrome (LS) is a severe mitochondrial disease that results from mutations in the nuclear or mitochondrial DNA that impairs cellular respiration and ATP production. Mutations in more than 100 genes have been demonstrated to cause LS. The disease most commonly affects brain development and function, resulting in cognitive and motor impairment. The underlying pathogenesis is challenging to ascertain due to the diverse range of symptoms exhibited by affected individuals and the variability in prognosis. To understand the disease mechanisms of different LS-causing mutations and to find a suitable treatment, several different model systems have been developed over the last 30 years. This review summarizes the established disease models of LS and their key findings. Smaller organisms such as yeast have been used to study the biochemical properties of causative mutations. Drosophila melanogaster, Danio rerio, and Caenorhabditis elegans have been used to dissect the pathophysiology of the neurological and motor symptoms of LS. Mammalian models, including the widely used Ndufs4 knockout mouse model of complex I deficiency, have been used to study the developmental, cognitive, and motor functions associated with the disease. Finally, cellular models of LS range from immortalized cell lines and trans-mitochondrial cybrids to more recent model systems such as patient-derived induced pluripotent stem cells (iPSCs). In particular, iPSCs now allow studying the effects of LS mutations in specialized human cells, including neurons, cardiomyocytes, and even three-dimensional organoids. These latter models open the possibility of developing high-throughput drug screens and personalized treatments based on defined disease characteristics captured in the context of a defined cell type. By analyzing all these different model systems, this review aims to provide an overview of past and present means to elucidate the complex pathology of LS. We conclude that each approach is valid for answering specific research questions regarding LS, and that their complementary use could be instrumental in finding treatment solutions for this severe and currently untreatable disease.