Spreading Dynamics Research Articles

Assembly of a tumor microtissue by stacking normal and cancer spheroids on Kenzan using a bio-3D printer to monitor dynamic cancer cell invasion in the microtissue

In the present study, a tumor microtissue was assembled by precisely stacking normal and cancer cell spheroids on Kenzan (microneedle array) using a spheroid stacking type bio-3D printer. This is the first study to non-invasively observe the dynamic behavior of GFP-tagged cancer cell invasion in the microtissue assembled by a spheroid stacking type bio-3D printer. First, the cancer cell spheroid was prepared using 10 % cancer cells (MCF-7 expressing GFP) and 90 % normal cells (70 % HNDF and 20 % HUVEC). The normal cell spheroid was prepared using 100 % normal cells (80 % HNDF and 20 % HUVEC). The tumor microtissue was then assembled on Kenzan by placing 1 cancer cell spheroid in the center position of the microtissue and 8 normal cell spheroids around it. 9 spheroids stacked on Kenzan were fused into 1 tumor microtissue after 24 hours of culture. The green fluorescence derived from cancer cells spread from the central position to the entire area of the tumor microtissue. The spread dynamics of cancer cell-derived GFP fluorescence can be used as a simple measure to evaluate cancer cell migration/invasion and response to anticancer drugs.

Subinhibitory concentrations of antibiotics affect development and parameters of Helicobacter pylori biofilm.

Helicobacter pylori causes chronic gastric diseases in nearly 50% of people around the world. It is suggested that biofilm formation has a pronounced effect on the dynamic resistance spread and recurrence of these infections. To mimic the scenario of therapeutic ineffectiveness, we investigated the impact of sub-minimal inhibitory concentrations (sub-MICs) of antibiotics on the development and parameters of biofilms produced by clinical H. pylori strains. We observed that constant exposure of planktonic forms to metronidazole or levofloxacin stimulated the speed of autoaggregation and the amount of extracellular matrix, resulting in increased dimensions of the developed biofilms. Contrary to this, continuous exposure to clarithromycin negatively affected a number of biofilm-related reactions and led to the biofilm-weakening effect. Through assessing the membrane fatty acid profiles of antibiotic-exposed cells, we confirmed that metronidazole and levofloxacin induced a biofilm-like phenotype, while clarithromycin kept bacteria in a planktonic form. Our results suggest that sub-MICs of antibiotics affect the biochemical and biophysical properties of the developing biofilm of H. pylori strains and may impact the effectiveness of antibiotic treatment.

TRANSMISSION AND CONTROL DYNAMICS OF ROTAVIRUS DIARRHEA MODEL WITH DOUBLE DOSE VACCINATION

This study introduces a six-compartmental mathematical model (S, , , E, I, R) to examine the impact of administering a double dose vaccine on the dynamic spread of diarrhea within a community. The mathematical analysis shows the existence of equilibrium points for both disease-free and endemic states in the model. The basic reproduction number was determined using the Next Generation Matrix. Analysis has shown that the basic reproduction number which indicates the disease-free equilibrium point is locally asymptotically stable. Also, using a suitable Lyapunov functional for the model system expressed in state variables and parameters defining the dynamic characteristics of spread and control strategies of the rotavirus diarrhea to obtain the global stability of disease-free equilibrium point over time. A numerical simulation was carried out by Wolfram Mathematica to show the effect of a second-dose vaccine. The inclusion of a double-dose vaccine has been found to have a significant effect on completely eliminating the outbreak of diarrhea. This is evidenced by the local and global stability results, which indicate that effective measures have been taken to prevent the reintroduction or transmission of the disease, and if there may be a risk of outbreaks or reemergence of the disease, very little continuous monitoring and intervention strategies are required to maintain control as this should be taken seriously by medical practitioners or policy health makers.

Orthohantavirus diversity in Central-East Argentina: Insights from complete genomic sequencing on phylogenetics, Geographic patterns and transmission scenarios.

Hantavirus Pulmonary Syndrome (HPS), characterized by its high fatality rate, poses a significant public health concern in Argentina due to the increasing evidence of person-to-person transmission of Andes virus. Several orthohantaviruses were described in the country, but their phylogenetic relationships were inferred from partial genomic sequences. The objectives of this work were to assess the viral diversity of the most prevalent orthohantaviruses associated with HPS cases in the Central-East (CE) region of Argentina, elucidate the geographic patterns of distribution of each variant and reconstruct comprehensive phylogenetic relationships utilizing complete genomic sequencing. To accomplish this, a detailed analysis was conducted of the geographic distribution of reported cases within the most impacted province of the region. A representative sample of cases was then selected to generate a geographic map illustrating the distribution of viral variants. Complete viral genomes were obtained from HPS cases reported in the region, including some from epidemiologically linked cases. The phylogenetic analysis based on complete genomes defined two separate clades in Argentina: Andes virus in the Southwestern region and Andes-like viruses in other parts of the country. In the CE region, Buenos Aires virus and Lechiguanas virus clearly segregate in two subclades. Complete genomes were useful to distinguish person-to-person transmission from environmental co-exposure to rodent population. This study enhances the understanding of the genetic diversity, geographical spread, and transmission dynamics of orthohantaviruses in Central Argentina and prompt to consider the inclusion of Buenos Aires virus and Lechiguanas virus in the species Orthohantavirus andesense, as named viruses.

Impact of a compound droplet on a solid surface: The effect of the shell on the core

The dynamic behavior of compound droplets impacting a solid surface was studied via experiments over κ (defined as the ratio of the compound droplet shell thickness h to the diameter D0 of compound droplet) ranging from 0 to 0.34, We ranging from 25 to 325 and Re ranging from 165.3 to 3405.2. The spreading diameter ratio, the maximum spreading dynamic contact angle and spreading speed of the core were investigated. Four modalities of the core of compound droplets were observed on the solid surface, including a) core rebound, b) no rebound, c) core splitting rebound, d) core splitting. The results revealed that the thickness of the shell, We, and the viscosity of the shell have a significant effect on the rebound and spreading processes of the core of the compound droplet. The high viscosity oil shell is conducive to its spreading. As the thickness of the oil shell increases, its cushioning effect on the water core also increases. In addition,κ=0.02254We0.503,κ=-0.336e-We121.056+0.319 and κ=0.06086e-We121.056+0.07716e-We121.70598+0.01595 were used to divide the modal boundary of the compound droplet core. Further analysis reveals the correlation between We, Re, βm and.κ,12+Weβm=8+31-cos22.78+84.57κβm3+0.955We1.05Reβm6.5.

Dynamic Market Making with Asymmetric Information and Market Power

Abstract We study the dynamics of trading volume and bid-ask spread using a multiperiod trading model with oligopolistic market makers. Traders smooth out their trading even though they are not strategic, and thus trading persists after the arrival of information or liquidity shocks. Traders act quickly on their private information while postponing hedging trades until later periods. The market power of market makers enables them to widen bid-ask spreads when trading incentives are heightened. Consequently, both trading volume and bid-ask spread may exhibit U-shaped patterns. Our model calibration aligns with the empirical intraday patterns observed in bid-ask spreads and trading volumes. (JEL D53, D61, D82, G12, G14, G18)

Molecular Detection of Carbapenemases in Acinetobacter baumannii Strains of Portugal and Association With Sequence Types, Capsular Types, and Virulence

Carbapenem-resistant Acinetobacter baumannii (CRAB) is an important nosocomial pathogen. The capsular type (K-type) is considered a major virulence factor, contributing to the evasion of host defenses. The global spread and dissemination dynamics between K-types, sequence types (ST), antibiotic resistance genes, and virulence factors remain largely unknown in Portugal. A collection of 96 CRAB clinical samples collected between 2005 and 2019 in the northern region of Portugal were tested for antimicrobial susceptibility profile and screened by polymerase chain reaction for resistance genetic determinants. A subset of 26 representative isolates was subjected to whole-genome sequencing to assess K types, ST types, and genomic relatedness. The pathogenicity of distinct K-types was also tested using Galleria mellonella model. For the 96 CRAB isolates analyzed, high antimicrobial resistance (>90%) was observed to the carbapenems, fluoroquinolones, and miscellaneous agents. Greater antimicrobial susceptibility (∼30%-57%) was observed for aminoglycosides, particularly tobramycin, and amikacin. Genotypically, 75 strains (78.5%) carried blaOXA-23-like, 18 strains (18.8%) carried blaIMP-like, and 11 strains (14.9%) carried blaOXA-40-like carbapenem resistance genes, respectively. Associations between OXA and ST/capsular locus (KL) types were observed over the years (eg, OXA-40-like/ST46Past/KL120 and OXA-23-like/ST2Past/KL2). ST2Past of clonal complex II was present in most strains, a dominant drug-resistant lineage in the United States and Europe. KL7 was also the most prevalent KL-type (38.5%), followed by KL2 (34.6%), KL120 (23.1%), and KL9 (3.8%). Virulence assessment for different K-types in a Galleria mellonella model revealed a significantly increased virulence for KL120 when compared with KL7, KL9, and KL2. There are specific CRAB serotypes circulating in Portugal, accounting by the low diversity of acquired carbapenemase genes (OXA-23-like and OXA-40-like), ST types (ST2 and ST46) and KL types (KL2, KL7, KL9, and KL120) identified. The high prevalent of ST2, especially when associated with KL2 and blaOXA-23-like, suggest that antibiotic resistance has been driven by clonal expansion of clonal complex II. Such findings provide useful information on the diversity of multidrug-resistant bacterium that might be relevant for antibacterial interventions.

Modelling study on pedestrian evacuation dynamics considering exit selection behaviour under flood disaster

Flood spreading in metro stations is a dangerous hazard that frequently causes casualties and property losses. However, pedestrian evacuation under flood spreading scenarios has not been fully investigated. To fill this gap,we propose an extend Floor-Field model incorporating flood spreading and exit selection behaviour of individuals. In the model, the dynamic flood spreading process on metro platforms is expressed by using a simulation software named Mike21. The optimal exit selected by pedestrians in each step is decided on three factors, that is pedestrian density around the exit, pedestrian distance to the exit, and water depth at the exit. Meanwhile, the movement speed of pedestrain also changes with the water depth at each time step. Based on this, the transition probability to neighbor cell including static field, dynamic field, height field, and water flow field is calculated. This results in a flood evacuation model considering the pedestrian's behaviour when choosing an exit. The effects of flooding, pedestrian density, different exit selection behaviours, water flow field, and inlet flow on evacuation were thoroughly analysed. The analysis demonstrates that the likelihood of flooding significantly impacts the evacuation of pedestrians from the subway station; the more flooding is taken into account, the more influential the impact. In addition, the effect of inlet flow on evacuation is also noteworthy; considering exit selection behaviour can significantly increase the effectiveness of evacuation. The study's findings can be used to develop evacuation plans for flooded metro stations.

Theory of wetting dynamics with surface binding

Abstract Biomolecules, such as proteins and nucleic acids, can phase separate in the cytoplasm of cells to form biomolecular condensates. Such condensates are often liquid-like droplets that can wet biological surfaces such as membranes. Many molecules that participate in phase separation can also reversibly bind to membrane surfaces. When a droplet wets a surface, molecules can diffuse inside and outside of the droplet or in the bound state on the surface. How the interplay between surface binding, diffusion in surface and bulk affects the wetting kinetics is not well understood. Here, we derive the governing equations using non-equilibrium thermodynamics by relating the thermodynamic fluxes and forces at the surface coupled to the bulk. We study the spreading dynamics in the presence of surface binding and find that binding speeds up wetting by nucleating a droplet inside the surface. Our results suggest that the wetting dynamics of droplets can be regulated by two-dimensional surface droplets in the surface-bound layer through changing the binding affinity to the surfaces. These findings are relevant both to engineering life-like systems with condensates and vesicles, and biomolecular condensates in living cells.

Analysis and Simulation of Misinformation Spread in Social Networks: A Hybrid Stochastic-Deterministic Approach with NEAB Model

This paper examined and simulated the dynamics of misinformation spread within social networks using the NEAB model [32]. In this model, (N) represents non-believers, (E) denotes individuals exposed to the information but undecided, (A) refers to those who accept the information and may propagate it, and (B) are the believers. Similar to epidemiological models like SEIR (Susceptible-Exposed-Infected-Recovered), the NEAB model adapts to study the spread of various types of information and behaviors within a population [20]. By combining elements of network theory [28] and epidemiology, the model investigates how behaviors and network structures influence information transmission. Our simulations, particularly when applied to real-world scenarios like misinformation spread during events such as COVID-19 or natural disasters, highlight key factors influencing dissemination [7]. Rates of exposure to misinformation, the transition of individuals from exposed to active spreaders, and the rate of recovery all play crucial roles in shaping how misinformation spreads [33]. Misinformation propagates more easily when exposure rates are high, while higher recovery rates help limit its spread. Sensitivity analysis shows that variations in (β) and (δ) significantly impact the spread, emphasizing the importance of targeted interventions during these critical stages [22]. The objective of this study is to evaluate strategies for reducing the effects of misinformation on public discourse and health outcomes while offering insights into the key factors that drive its dissemination based on model simulations.

Single-cell virology: On-chip, quantitative characterization of the dynamics of virus spread from one single cell to another.

Virus spread at the single-cell level is largely uncharacterized. We have designed and constructed a microfluidic device in which each nanowell contained a single, infected cell (donor) and a single, uninfected cell (recipient). Using a GFP-expressing poliovirus as our model, we observed both lytic and non-lytic spread. Donor cells supporting lytic spread established infection earlier than those supporting non-lytic spread. However, non-lytic spread established infections in recipient cells substantially faster than lytic spread and yielded higher rates of genome replication. While lytic spread was sensitive to the presence of capsid entry/uncoating inhibitors, non-lytic spread was not. Consistent with emerging models for non-lytic spread of enteroviruses using autophagy, reduction of LC3 levels in cells impaired non-lytic spread and elevated the fraction of virus in donor cells spreading lytically. The ability to distinguish lytic and non-lytic spread unambiguously will enable discovery of viral and host factors and host pathways used for non-lytic spread of enteroviruses and other viruses as well.

Better preparedness for invasive crop pests in changing climate: Assessing the risk of western corn rootworm (Coleoptera: Chrysomelidae) colonization in global maize growing regions and future spread dynamics

AbstractThe establishment and spread of alien species in new areas pose a potential threat to global food security. Diabrotica virgifera virgifera LeConte is an invasive maize pest originally from Mexico, causing substantial economic damage to maize production across extensive areas of the United States and Europe. However, it has not yet invaded Asia or other regions. We used the Ensemble Model and Cellular Automaton to analyze the establishment and spread risk of this pest. The pest has not explored novel climates during past invasions, and the climatic ecological niche it occupied in Europe constitutes only a fraction of that in North America, indicating that the species still possesses the potential to spread further in Europe in the future. Currently, approximately 34% of global maize‐growing areas are at risk, with 25.5% facing a high establishment risk. By 2060, a significant northward spread is projected to occur in North America and Europe, while only a sporadic spread is expected in South America, Asia, Africa, or Oceania. Therefore, the adaptation of transnational management strategies may be necessary to prevent and control the risk of introduction and spread of this important maize pest into new areas of global maize production.

Dilute Polymer Droplets Show Generalized Wetting Dynamics via an Average Viscosity.

Despite the prevalence of non-Newtonian fluids in various practical applications, comprehensive dynamic wetting models are lacking. Existing models often oversimplify complex rheological behavior, limiting our ability to predict wetting dynamics. This work introduces and experimentally validates a generalized model for the dynamic wetting of non-Newtonian shear-thinning fluids (dilute polymer solutions) on solid substrates. We experimentally analyzed 12 different shear-thinning fluids using both a power-law model and Carreau-Yasuda model. The data clearly show that the dynamic contact angle can be generalized using an average viscosity to capture rheological changes during droplet spreading. The average viscosity was defined using the fluid's constitutive model over shear rates relevant to the spreading process. Using a small droplet approximation, we propose and validate a semianalytical spreading model to predict the basal radius of non-Newtonian droplets. The model agrees well with the experimental data. Additionally, the average viscosity was used to define a spreading time scale, which is capable of collapsing the spreading of different non-Newtonian fluids onto a master spreading curve. This work offers significant potential for predicting the dynamic shape and spreading of non-Newtonian fluids with complex rheologies in a range of applications and industrial processes.

Spreading of droplet impact on ribbed superhydrophobic surfaces with varying structure height

Hypothesis:Quantifying droplet spreading characteristics on ribbed superhydrophobic surfaces is challenging due to the complex fluid dynamics, limiting the practical applications. Droplet spreading dynamics are significantly influenced by the diameter ratio (rib diameter to droplet diameter) and height ratio (structure height to rib diameter) during impact. Experiment:Ribbed superhydrophobic surfaces with diameter ratios (0.18 to 0.75) and height ratios (0.125 to 0.5) underwent impact experiments with droplets at varied Weber numbers. Through simulations and analysis, we summarized the patterns of the maximum ribwise spreading coefficient, elucidated the droplet spreading mechanism on ribbed superhydrophobic surfaces. Findings:The findings revealed asymmetry in impact dynamics on ribbed superhydrophobic surfaces in the ribwise and radial directions. The maximum ribwise spreading coefficient initially decreases, followed by increase with increasing diameter ratio, decreasing in a slowing down trend with increasing height ratio. These observations indicated that maximum ribwise spreading coefficient can be minimize with critical ratios. Comparatively, the maximum spreading coefficient at critical height ratios is 72.7% to 92.3% of that on flat surfaces. To precisely forecast maximum ribwise spreading coefficient, two models are introduced for diameter ratios below and above critical range when height ratios below the critical range.

Genotyping of oral Candida albicans and Candida tropicalis strains in patients with orofacial clefts undergoing surgical rehabilitation by MALDI-TOF MS: Case-series study

Patients with orofacial clefts are more likely to develop oral fungal diseases due to anatomo-physiological changes and surgical rehabilitation treatment. This case-series study evaluated the genetic diversity and dynamics of oral colonization and spread of C. albicans and C. tropicalis in four patients with orofacial clefts, from the time of hospital admission, perioperative and outpatient follow-up, with specialized physician. Candida biotypes previously identified by CHROMagar Candida and PCR methods were studied by MALDI-TOF MS assays and clustering analyses. Possible correlations with pathogenicity characteristics were observed, including production of hydrolytic exoenzymes and the antifungal sensitivity profiles. Amphotericin B-sensitive and fluconazole-resistant (low frequency) C. tropicalis and C. albicans, including clinically compatible MIC of nystatin, were found in the oral cavity of these patients. Clusters of isolates revealed phenomena of (i) elimination in the operative phase, (ii) maintenance or (iii) acquisition of oral C. tropicalis in the perioperative period and specialized outpatient and medical follow-up. For C. albicans, these phenomena included (i) elimination in the operative phase, (ii) acquisition in the operative phase and propagation from the hospital environment, and (iii) maintenance during hospitalization and operative phase. Amphotericin B and nystatin were shown to be effective in cases of clinical treatment and/or prophylaxis, especially considering the pre-existence of fluconazole-resistant strains. This study confirmed the phenomena of septic maintenance, septic neocolonization and septic elimination involving the opportunistic pathogens. MALDI-TOF MS associated with clustering analysis may assist the monitoring of clinical isolates or groups of epidemiologically important microbial strains in the hospital setting.

Peer Review of “A Framework for Modeling, Analyzing, and Decision-Making in Disease Spread Dynamics and Medicine/Vaccine Distribution (Preprint)”

Peer Review of “A Framework for Modeling, Analyzing, and Decision-Making in Disease Spread Dynamics and Medicine/Vaccine Distribution (Preprint)”

The role of mobility in epidemics near criticality

Abstract The general epidemic process (GEP), also known as susceptible-infected-recovered model, provides a minimal model of how an epidemic spreads within a population of susceptible individuals who acquire permanent immunization upon recovery. This model exhibits a second-order absorbing state phase transition, commonly studied assuming immobile healthy individuals. We investigate the impact of mobility on the scaling properties of disease spreading near the extinction threshold by introducing two generalizations of GEP, where the mobility of susceptible and recovered individuals is examined independently. In both cases, including mobility violates GEP’s rapidity reversal symmetry and alters the number of absorbing states. The critical dynamics of the models are analyzed through a perturbative renormalization group (RG) approach and large-scale stochastic simulations using a Gillespie algorithm. The RG analysis predicts both models to belong to the same novel universality class describing the critical dynamics of epidemic spreading when the infected individuals interact with a diffusive species and gain immunization upon recovery. At the associated RG fixed point, the immobile species decouples from the dynamics of the infected species, dominated by the coupling with the diffusive species. Numerical simulations in two dimensions affirm our RG results by identifying the same set of critical exponents for both models. Violation of the rapidity reversal symmetry is confirmed by breaking the associated hyperscaling relation. Our study underscores the significance of mobility in shaping population spreading dynamics near the extinction threshold.

Insight into Mocha Diffusion Occurring during Ethanol Droplet Spreading on Acrylic Paint.

Mocha diffusion, a significant interfacial phenomenon in pottery painting, remains insufficiently understood in the documented literature regarding its dynamics. This study experimentally investigates Mocha patterns by quantitatively dripping ethanol droplets onto an acrylic paint surface. Results indicate that the spreading radius increases with the ethanol mass fraction, while the fractal period decreases. The fractal dimension of all Mocha patterns approximates 1.4087. Marangoni flow, generated by the volatilization of ethanol, is crucial for the growth and fractal formation of the "dendrites" in this spreading. The scaling analysis is used to interpret the spreading dynamics. This work encourages the interface science community to develop a comprehensive theory for the dynamics of Mocha diffusion and highlights the potential of this intriguing decorative technique.

Utilizing fractional derivatives and sensitivity analysis in a random framework: a model-based approach to the investigation of random dynamics of malware spread

In this study, an ordinary-deterministic equation system modeling the spread dynamics of malware under mutation is analyzed with fractional derivatives and random variables. The original model is transformed into a system of fractional-random differential equations (FRDEs) using Caputo fractional derivatives. Normally distributed random variables are defined for the parameters of the original system that are related to the mutations and infections of the nodes in the network. The resulting system of FRDEs is simulated using the predictor-corrector method based fde12 algorithm and the forward fractional Euler method (ffEm) for various values of the model components such as the standard deviations, orders of derivation, and repetition numbers. Additionally, the sensitivity analysis of the original model is investigated in relation to the random nature of the components and the basic reproduction number (R0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$R_{0}$\\end{document}) to underline the correspondence of random dynamics and sensitivity indices. Both the normalized forward sensitivity indices (NFSI) and the standard deviation of R0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$R_{0}$\\end{document} with random components give matching results for analyzing the changes in the spread rate. Theoretical results are backed by the simulation outputs on the numerical characteristics of the fractional-random model for the expected number of infections and mutations, expected timing of the removal of mutations from the network, and measurement of the variability in the results such as the coefficients of variation. Comparison of the results from the original model and the fractional-random model shows that the fractional-random analysis provides a more generalized perspective while facilitating a versatile investigation with ease and can be used on different models as well.

Long-term trend prediction of pandemic combining the compartmental and deep learning models

Predicting the spread trends of a pandemic is crucial, but long-term prediction remains challenging due to complex relationships among disease spread stages and preventive policies. To address this issue, we propose a novel approach that utilizes data augmentation techniques, compartmental model features, and disease preventive policies. We also use a breakpoint detection method to divide the disease spread into distinct stages and weight these stages using a self-attention mechanism to account for variations in virus transmission capabilities. Finally, we introduce a long-term spread trend prediction model for infectious diseases based on a bi-directional gated recurrent unit network. To evaluate the effectiveness of our model, we conducted experiments using public datasets, focusing on the prediction of COVID-19 cases in four countries over a period of 210 days. Experiments shown that the Adjust-R2 index of our model exceeds 0.9914, outperforming existing models. Furthermore, our model reduces the mean absolute error by 0.85–4.52% compared to other models. Our combined approach of using both the compartmental and deep learning models provides valuable insights into the dynamics of disease spread.