Dynamic Heterogeneity Research Articles

Exploring Mitochondrial Heterogeneity and Evolutionary Dynamics in Thelephora ganbajun through Population Genomics.

Limited exploration in fungal mitochondrial genetics has uncovered diverse inheritance modes. The mitochondrial genomes are inherited uniparentally in the majority of sexual eukaryotes, our discovery of persistent mitochondrial heterogeneity within the natural population of the basidiomycete fungus Thelephora ganbajun represents a significant advance in understanding mitochondrial inheritance and evolution in eukaryotes. Here, we present a comprehensive analysis by sequencing and assembling the complete mitogenomes of 40 samples exhibiting diverse cox1 heterogeneity patterns from various geographical origins. Additionally, we identified heterogeneous variants in the nad5 gene, which, similar to cox1, displayed variability across multiple copies. Notably, our study reveals a distinct prevalence of introns and homing endonucleases in these heterogeneous genes. Furthermore, we detected potential instances of horizontal gene transfer involving homing endonucleases. Population genomic analyses underscore regional variations in mitochondrial genome composition among natural samples exhibiting heterogeneity. Thus, polymorphisms in heterogeneous genes, introns, and homing endonucleases significantly influence mitochondrial structure, structural variation, and evolutionary dynamics in this species. This study contributes valuable insights into mitochondrial genome architecture, population dynamics, and the evolutionary implications of mitochondrial heterogeneity in sexual eukaryotes.

Exploring the Premelting Transition through Molecular Simulations Powered by Neural Network Potentials

The premelting layer on crystal surfaces significantly affects the stability, surface reactivity, and phase transition behaviors of crystals. Traditional methods for studying this layer—experimental techniques, classical simulations, and even first-principle simulations—have significant limitations in accuracy and scalability. To overcome these challenges, we employ molecular dynamic simulations based on neural network potentials to investigate the structural and dynamic behavior of the premelting layer on ice. This approach matches the accuracy of first-principle calculations while greatly improving computational efficiency, allowing us to simulate the ice–vapor interface on a much larger scale. In this study, we conducted a one-nanosecond simulation of the ice–vapor interface involving 1024 water molecules. This significantly exceeds the time and size scales of previous first-principle studies. Our simulation results indicate complete surface melting. Furthermore, our simulation results reveal dynamic heterogeneity within the premelting layer, with molecules segregated into clusters of low and high mobility.

Heterogeneous dynamics of diffusive motion in organic ionic plastic crystal studied using spin–spin relaxation time: N,N-diethylpyrrolidinium bis(fluorosulfonyl)amide

Abstract The temperature dependences of the spin–spin relaxation times (T2) of 1H and 19F nuclei were measured for N,N-diethylpyrrolidinium bis(fluorosulfonyl)amide with a plastic crystal phase. In the plastic crystal phase, 2 types of T2 were observed in both 1H and 19F experiments, which were considered to be the appearance of heterogeneous dynamics of diffusive motion. By examining temperature dependences of the T2 values and the existence ratios, the following conclusions were reached. (i) The prepared plastic crystal sample was in a polycrystalline state, and each crystallite comprised 2 phases: the core phase (plastic crystal phase) and the surface phase formed to relieve surface stress. (ii) The 1H-T2 (19F-T2) values of the 2 phases differed, and ions in the surface phase were more mobile. The 1H-T2 (19F-T2) values for the 2 phases increased with temperature rise. In particular, the 1H-T2 (19F-T2) values of the surface phase were smoothly connected to the liquid T2 values. (iii) The cations and anions exhibited a cooperative diffusive motion. (iv) When the temperature was considerably lower than the melting point, the ratio of the surface phase did not significantly differ from when it first formed. However, it rapidly increased near the melting point and became liquid.

Nanophase Segregation Drives Heterogeneous Dynamics in Amphiphilic PLMA‐b‐POEGMA Block‐Copolymers with Densely Grafted Architecture

AbstractThe self‐assembly and dynamics of amphiphilic diblock copolymers composed of densely grafted poly(oligo ethylene glycol methacrylate) (POEGMA) and poly(lauryl methacrylate) (PLMA) by means of calorimetry, small‐angle X‐ray scattering (SAXS), and dielectric spectroscopy are investigated. It is reported that the inherent immiscibility between the parent homopolymers, combined with the increased molar mass, results in strong segregation, maintained up to elevated temperatures (i.e., T = 423 K). SAXS reveals that well‐separated POEGMA and PLMA domains self‐assemble into spheres with bicontinuous cubic packing and in lamellar nanostructure in copolymers with respective compositions of 16 and 52 wt.% PLMA. This strong segregation enables the weak crystallization/melting of the short ethylene glycol chains. Additionally, molecular dynamics are investigated through isothermal dielectric and calorimetry measurements. The segmental dynamics (i.e., Tg‐related) of POEGMA and PLMA closely resemble that found in respective homopolymers, implying heterogeneous dynamics. In the glassy state, the local motions of the POEGMA side chains predominantly govern the observed secondary processes in the copolymers. The results on the heterogeneous dynamics in the current amphiphilic diblock copolymers with the densely grafted architecture are compared and contrasted with copolymers having a bottle–brush architecture lacking the amphiphilic nature.

Identification of a Novel ECM Remodeling Macrophage Subset in AKI to CKD Transition by Integrative Spatial and Single-Cell Analysis.

The transition from acute kidney injury (AKI) to chronic kidney disease (CKD) is a critical clinical issue. Although previous studies have suggested macrophages as a key player in promoting inflammation and fibrosis during this transition, the heterogeneity and dynamic characterization of macrophages are still poorly understood. Here, we used integrated single-cell RNA sequencing and spatial transcriptomic to characterize the spatiotemporal heterogeneity of macrophages in murine AKI-to-CKD model of unilateral ischemia-reperfusion injury. A marked increase in macrophage infiltration at day 1 was followed by a second peak at day 14 post AKI. Spatiotemporal profiling revealed that injured tubules and macrophages co-localized early after AKI, whereas in late chronic stages had spatial proximity to fibroblasts. Further pseudotime analysis revealed two distinct lineages of macrophages in this transition: renal resident macrophages differentiated into the pro-repair subsets, whereas infiltrating monocyte-derived macrophages contributed to chronic inflammation and fibrosis. A novel macrophage subset, extracellular matrix remodeling-associated macrophages (EAMs) originating from monocytes, linked to renal fibrogenesis and communicated with fibroblasts via insulin-like growth factors (IGF) signalling. In sum, our study identified the spatiotemporal dynamics of macrophage heterogeneity with a unique subset of EAMs in AKI-to-CKD transition, which could be a potential therapeutic target for preventing CKD development.

Brain-Engrafted Monocyte-derived Macrophages from Blood and Skull-Bone Marrow Exhibit Distinct Identities from Microglia.

Microglia are thought to originate exclusively from primitive macrophage progenitors in the yolk sac (YS) and to persist throughout life without much contribution from definitive hematopoiesis. Here, using lineage tracing, pharmacological manipulation, and RNA-sequencing, we elucidated the presence and characteristics of monocyte-derived macrophages (MDMs) in the brain parenchyma at baseline and during microglia repopulation, and defined the core transcriptional signatures of brain-engrafted MDMs. Lineage tracing mouse models revealed that MDMs transiently express CD206 during brain engraftment as CD206 + microglia precursors in the YS. We found that brain-engrafted MDMs exhibit transcriptional and epigenetic characteristics akin to meningeal macrophages, likely due to environmental imprinting within the meningeal space. Utilizing parabiosis and skull transplantation, we demonstrated that monocytes from both peripheral blood and skull bone marrow can repopulate microglia-depleted brains. Our results reveal the heterogeneous origins and cellular dynamics of brain parenchymal macrophages at baseline and in models of microglia depletion.

A fractional-order model for optimizing combination therapy in heterogeneous lung cancer: integrating immunotherapy and targeted therapy to minimize side effects

This research presents a novel approach to address the complexities of heterogeneous lung cancer dynamics through the development of a Fractional-Order Model. Focusing on the optimization of combination therapy, the model integrates immunotherapy and targeted therapy with the specific aim of minimizing side effects. Notably, our approach incorporates a clever fusion of Proportional-Integral-Derivative (PID) feedback controls alongside the optimization process. Unlike previous studies, our model incorporates essential equations accounting for the interaction between regular and mutated cancer cells, delineates the dynamics between immune cells and mutated cancer cells, enhances immune cell cytotoxic activity, and elucidates the influence of genetic mutations on the spread of cancer cells. This refined model offers a comprehensive understanding of lung cancer progression, providing a valuable tool for the development of personalized and effective treatment strategies. the findings underscore the potential of the optimized treatment strategy in achieving key therapeutic goals, including primary tumor control, metastasis limitation, immune response enhancement, and controlled genetic mutations. The dynamic and adaptive nature of the treatment approach, coupled with economic considerations and memory effects, positions the research at the forefront of advancing precision and personalized cancer therapeutics.

Crystallization and topology-induced dynamical heterogeneities in soft granular clusters

Crystallization and topology-induced dynamical heterogeneities in soft granular clusters

Taking the Big Leap | understanding, accessing and improving behavioural science interventions.

Applied behaviour science's focus on individual-level behaviours has led to overestimation of and reliance on biases and heuristics in understanding behaviour and behaviour change. Behaviour-change interventions experience difficulties such as effect sizes, validity, scale-up, and long-term sustainability. One such area where we need to re-examine underlying assumptions for behavioural interventions in Human Immunodeficiency Virus (HIV) and Tuberculosis (TB) prevention, which seek population-level benefits and sustained, measurable impact. This requires taking a "Big Leap." In our view, taking the big leap refers to using a behavioural science-informed approach to overcome the chasms due to misaligned assumptions, tunnel focus, and overweighting immediate benefits, which can limit the effectiveness and efficiency of public health programmes and interventions. Crossing these chasms means that decision-makers should develop a system of interventions, promote end-user agency, build choice infrastructure, embrace heterogeneity, recognise social and temporal dynamics, and champion sustainability. Taking the big leap toward a more holistic approach means that policymakers, programme planners, and funding bodies should "Ask" pertinent questions to evaluate interventions to ensure they are well informed and designed.

Consensus Control of Heterogeneous Uncertain Multiple Autonomous Underwater Vehicle Recovery Systems in Scenarios of Implicit Reduced Visibility

This paper investigates consensus control in heterogeneous and uncertain multiple autonomous underwater vehicle (AUV) systems under implicit reduced visibility conditions. We address challenges such as environmental uncertainties and system nonlinearity by utilizing a unified connectivity approach to model low-visibility interactions and heterogeneous multi-AUV dynamics. Our main contributions include developing a feedback linearization model for heterogeneous multi-AUV systems that accounts for uncertainties, introducing an adaptive consensus controller based on relative positioning that effectively manages implicit visual interaction limitations and validating our strategies through stability analysis and numerical simulations. Our simulations demonstrate approximately a 60% improvement in accuracy compared to previous algorithms, highlighting the practical value of our approach in AUV recovery operations. These advancements provide a robust solution for consensus control in complex underwater environments.

Understanding patient-derived tumor organoid growth through an integrated imaging and mathematical modeling framework.

Patient-derived tumor organoids (PDTOs) are novel cellular models that maintain the genetic, phenotypic and structural features of patient tumor tissue and are useful for studying tumorigenesis and drug response. When integrated with advanced 3D imaging and analysis techniques, PDTOs can be used to establish physiologically relevant high-throughput and high-content drug screening platforms that support the development of patient-specific treatment strategies. However, in order to effectively leverage high-throughput PDTO observations for clinical predictions, it is critical to establish a quantitative understanding of the basic properties and variability of organoid growth dynamics. In this work, we introduced an innovative workflow for analyzing and understanding PDTO growth dynamics, by integrating a high-throughput imaging deep learning platform with mathematical modeling, incorporating flexible growth laws and variable dormancy times. We applied the workflow to colon cancer organoids and demonstrated that organoid growth is well-described by the Gompertz model of growth. Our analysis showed significant intrapatient heterogeneity in PDTO growth dynamics, with the initial exponential growth rate of an organoid following a lognormal distribution within each dataset. The level of intrapatient heterogeneity varied between patients, as did organoid growth rates and dormancy times of single seeded cells. Our work contributes to an emerging understanding of the basic growth characteristics of PDTOs, and it highlights the heterogeneity in organoid growth both within and between patients. These results pave the way for further modeling efforts aimed at predicting treatment response dynamics and drug resistance timing.

Measuring single-cell immune clonality to track haematological cancers.

While paediatric blood cancers are deadly, modern medical advances have enabled clinicians to measure levels of residual cancer cells to manage therapeutic strategies for patients. However, blood cancers, including leukaemias and lymphomas, are highly heterogeneous and is comprised of complex clonal populations that can hinder efforts in detecting the cancer cells as well as managing treatments. Furthermore, the tumour microenvironment is comprised of heterogenous immune dynamics that may be different between patients. High-throughput sequencing has constributed to new discoveries in genetic and transcriptomic alterations underpinning cancer, including blood cancers, and has changed how patients are monitored and managed. Here we discuss the recent efforts using single-cell approach, particularly on efforts to track clonal heterogenity of paediatric blood cancer and the underlying immune response, highlighting avenues for novel biomarker discovery that may have significant impact on clinical oncology practice.

Crop water productivity assessment and planting structure optimization in typical arid irrigation district using dynamic Bayesian network

Enhancing crop water productivity is crucial for regional water resource management and agricultural sustainability, particularly in arid regions. However, evaluating the spatial heterogeneity and temporal dynamics of crop water productivity in face of data limitations poses a challenge. In this study, we propose a framework that integrates remote sensing data, time series generative adversarial network (TimeGAN), dynamic Bayesian network (DBN), and optimization model to assess crop water productivity and optimize crop planting structure under limited water resources allocation in the Qira oasis. The results demonstrate that the combination of TimeGAN and DBN better improves the accuracy of the model for the dynamic prediction, particularly for short-term predictions with 4 years as the optimal timescale (R2 > 0.8). Based on the spatial distribution of crop suitability analysis, wheat and corn are most suitable for cultivation in the central and eastern parts of Qira oasis while cotton is unsuitable for planting in the western region. The walnuts and Chinese dates are mainly unsuitable in the southeastern part of the oasis. Maximizing crop water productivity while ensuring food security has led to increased acreage for cotton, Chinese dates and walnuts. Under the combined action of the five optimization objectives, the average increase of crop water productivity is 14.97%, and the average increase of ecological benefit is 3.61%, which is much higher than the growth rate of irrigation water consumption of cultivated land. It will produce a planting structure that relatively reduced irrigation water requirement of cultivated land and improved crop water productivity. This proposed framework can serve as an effective reference tool for decision-makers when determining future cropping plans.

Controllability of heterogeneous multi-agent systems via cooperative output regulation

This paper investigates the controllability of heterogeneous linear multi-agent systems (MASs) based on the cooperative output regulation, in which the considered agents are of high-degree heterogeneity, including different dimensions, heterogeneous dynamics and nonidentical interactions varying with agent and its neighbors. A design framework is developed for nonidentical external input and interaction gains, with the help of the improved cooperative regulators and virtual triple. Some necessary and/or sufficient conditions are derived to ensure the controllability of MASs. The obtained controllability criteria require lower computational cost and are much easier to examine compared with directly performing the traditional controllability test on heterogeneous MASs. Furthermore, extended controllability analysis without regulation assumptions is also provided to illustrate the effect of interactions among diverse agents on the controllability. The effectiveness of theoretical results is substantiated finally by two examples: a 6-agents heterogeneous MAS and a practical MAS composed of heterogeneous aircrafts and vehicles.

Effective Reproduction Number of Smear-Positive Pulmonary Tuberculosis in Iran: A Registry-Based Study (2011-2021).

Tuberculosis (TB) remains a major public health issue in Iran, especially smear-positive pulmonary tuberculosis (SPPTB), due to its high transmission rate. Examining the effective reproduction number(Rt ) of SPPTB and patient characteristics is crucial for crafting targeted TB control measures. This study aimed to assess the Rt of SPPTB in Iran from 2011 to 2021 and profile SPPTB patient demographics, initial smear bacilli density, diagnosis delays, and spatial distribution. Study Design: This is a historical cohort study. A time-dependent method was used to estimate Rt , and monthly data from the national TB registry were scrutinized from 2011 to 2021. A decline was observed in SPPTB incidence rates of 50909 SPPTB cases in Iran from 2011 to 2021. Approximately 29.1% of the cases were diagnosed within a month, while 44.5% experienced a one to three-month delay in diagnosis. The analysis revealed substantial heterogeneity in TB transmission dynamics across various provinces of Iran. Provinces such as Sistan and Baluchestan, Golestan, Guilan, Khuzestan, Tehran, and Khorasan Razavi exhibited the highest effective reproduction numbers. Additionally, there was a decreasing trend in the effective reproduction numbers across all provinces from 2011 to 2020. Effective reproduction numbers declined in most provinces from 2011 to 2020 but increased moderately after the COVID-19 pandemic, highlighting the need for targeted public health interventions. Although SPPTB incidence rates are declining nationally, elevated incidence rates and effective reproduction numbers in regions such as Sistan and Baluchestan, Golestan, Guilan, Khuzestan, Tehran, and Khorasan Razavi signify the need for persistent TB management efforts in Iran.

Response surface methodology optimization of sodium diclofenac adsorption using activated carbon derived from falcata tree sawdust

The presence of sodium diclofenac in water is a significant problem due to its adverse effects on terrestrial and aquatic organisms. Thus, this study investigated the Falcata tree sawdust as the precursor of activated carbon for the adsorption of diclofenac in an aqueous solution. The characterization of falcata tree sawdust-activated carbon (FTSAC) was evaluated by SEM and FTIR analysis. The activated falcata sawdust converted to activated carbon has a 30 % yield. The optimal values for the operating parameters, FTSAC dosage, initial sodium diclofenac concentration, reaction time and pH, were determined using the central composite design (CCD) of the response surface methodology (RSM). The optimal removal efficiency suggested by CCD is 93.98 % with the optimum conditions of parameters of 0.80 g FTSAC dosage, 200 ppm initial sodium diclofenac concentration, 20 min reaction time, and pH 4. These optimal values of parameters were validated by an actual experiment, and the result (average removal efficiency: 92.08 %) is within a 95 % confidence interval. On the other hand, the pseudo-second-order (R2 = 0.9991) kinetic model depicts the rate of absorption of FTSAC adsorbing SD. Moreover, the Langmuir-Freundlich isotherm or Sips isotherm model (R2 = 0.9904) is the best-fit model that describes the heterogeneous adsorption dynamics of FTSAC surfaces. This study indicates that falcata sawdust can serve as a promising and viable alternative raw material to produce activated carbon.

Magnetization Switching of Single Magnetite Nanoparticles Monitored Optically.

Magnetic nanomaterials record information as fast as picoseconds in computer memories but retain it for millions of years in ancient rocks. This exceedingly broad range of times is covered by hopping over a potential energy barrier through temperature, ultrafast optical excitation, mechanical stress, or microwaves. As switching depends on nanoparticle size, shape, orientation, and material properties, only single-nanoparticle studies can eliminate the ensemble heterogeneity. Here, we push the sensitivity of photothermal magnetic circular dichroism down to individual 20 nm magnetite nanoparticles. Single-particle magnetization curves display superparamagnetic to ferromagnetic behaviors, depending on the size, shape, and orientation. Some nanoparticles undergo thermally activated switching on time scales of milliseconds to minutes. Surprisingly, the switching barrier varies with time, leading to dynamical heterogeneity, a phenomenon familiar in protein dynamics and supercooled liquids. Our observations will help to identify the external parameters influencing magnetization switching and, eventually, to control it, an important step for many applications.

Ion Dynamics in Nanocrystalline Li2S‐LiI – on the Influence of Local Disorder on Short‐Range Hopping and Long‐Range Ion Transport

The enormous interest in developing powerful Li‐based batteries leads to a boost in materials research. Though Li–sulfur batteries offer very high energy densities, the nature of Li‐ion dynamics in the final discharge product has not been fully understood yet. While nanocrystalline shows enhanced ion dynamics compared to its coarse‐grained counterpart, the interaction of with another binary such as LiI seems to be rather unexplored. Herein, an equimolar mixture of and LiI is treated in a high‐energy ball mill, and both the overall and local structural changes are studied by X‐ray powder diffraction and nuclear magnetic resonance (NMR), respectively . Besides the formation of amorphous regions, evidences are found for the generation of anion‐mixed sites that give rise to facile Li exchange on the 2D exchange NMR timescale. Compared to a coarse‐grained reference sample, the overall (bulk) ionic conductivity of nanocrystalline ‐LiI increases by two orders of magnitude. Besides the anion‐mixing effect, this increase benefits from nanosize effects that include the formation of defect‐rich interfacial regions. NMR relaxation measurements fully support this result and reveal heterogeneous dynamics with lower activation energies for both the localized hopping processes and long‐range ion transport in nm‐sized ‐LiI.

Electrical Resistivity Changes During Heating Experiments Unravel Heterogeneous Thermal‐Hydrological‐Mechanical Processes in Salt Formations

AbstractRock salt is considered a suitable medium for the permanent disposal of heat‐generating radioactive waste due to its isolation properties. However, excavation damage and heating induce complex and heterogeneous thermal‐hydrological‐mechanical (THM) processes across different zones. Quantifying this heterogeneity is crucial for accurate long‐term performance assessment models, but traditional methods lack the necessary resolution. This study employs 4D electrical resistivity tomography (ERT) monitoring during controlled heating experiments in a salt formation to unravel the spatiotemporal dynamics of THM processes. Advanced time‐lapse inversion and clustering analysis quantify subsurface properties and map the heterogeneity of THM dynamics. The ERT results can estimate subsurface properties and delineate the damaged and intact zones, enabling appropriate parameterization and representation of processes for long‐term modeling. This approach may be used in further improving the predictive models and ensuring the safe long‐term disposal of radioactive waste in rock salt.

Unusual dynamics of tetrahedral liquids caused by the competition between dynamic heterogeneity and structural heterogeneity.

Tetrahedral liquids exhibit intriguing thermodynamic and transport properties because of the various ways tetrahedra can be packed and connected. Recently, an unusual temperature dependence of the stretching exponent β in a model tetrahedral liquid ZnCl2 from Tm + 85K to Tm + 35K has been reported using neutron-spin echo spectroscopy. This discovery stands in sharp contrast to other glass-forming liquids. In this study, we conducted neural network force field driven molecular dynamic simulations of ZnCl2. We found a non-monotonic temperature dependence of β from liquid to supercooled liquid temperatures. Further structural decomposition and dynamic analysis suggest that this unusual dynamic behavior is a result of the competition between the decrease in the diversity of tetrahedra motifs (structural heterogeneity) and the increase in glassy dynamic heterogeneity. This result may contribute to new understandings of the structural relaxation of other network liquids.